Financial Sustainability of Pension Systems: Empirical Evidence from Central and Eastern European Countries (Financial and Monetary Policy Studies, 52) 3030744531, 9783030744533

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Financial and Monetary Policy Studies 52

Stefania Amalia Jimon Florin Cornel Dumiter Nicolae Baltes

Financial Sustainability of Pension Systems Empirical Evidence from Central and Eastern European Countries

Financial and Monetary Policy Studies Volume 52

The book series ‘Financial and Monetary Policy Studies’ features the latest research in financial and monetary economics. Books published in this series are primarily monographs and edited volumes that present new research results, both theoretical and empirical, on a clearly defined topic. All books are published in print and digital formats and disseminated globally.

More information about this series at http://www.springer.com/series/5982

Stefania Amalia Jimon • Florin Cornel Dumiter • Nicolae Baltes

Financial Sustainability of Pension Systems Empirical Evidence from Central and Eastern European Countries

Stefania Amalia Jimon Faculty of Economics, Computer Science and Engineering Vasile Goldis Western University of Arad Arad, Romania

Florin Cornel Dumiter Faculty of Economics, Computer Science and Engineering Vasile Goldis Western University of Arad Arad, Romania

Nicolae Baltes Faculty of Economic Sciences Lucian Blaga University of Sibiu Sibiu, Romania

ISSN 0921-8580 ISSN 2197-1889 (electronic) Financial and Monetary Policy Studies ISBN 978-3-030-74453-3 ISBN 978-3-030-74454-0 (eBook) https://doi.org/10.1007/978-3-030-74454-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

“The monograph named Financial Sustainability of Pension Systems. Empirical Evidence from Central and Eastern European Countries represents a practical and empirical guide which should be required for both students and academics worldwide, but also for practitioners, governments, ministries, and their staff, as well as for their legislators, especially in the former communist countries in Central and Eastern Europe affected by the global transformation of pension systems and for medical, social, and financial reshaping of the entire financial system. Nice scientific study, made in crucial times for our world.” —Assoc. Prof. Miroslav Škoda, Ph.D., Vice-Rector for International Relations and Accreditation, DTI University, Slovakia “Dear colleagues, I am writing about the book Financial Sustainability of Pension Systems. Empirical Evidence from Central and Eastern European Countries; you hopefully publish soon. The book deals with a very important topic, worth learning and analyzing. The topic is even more important for Romania where employment rate of older people is among the lowest in Europe, and as we know pension system and employment rate are in very close connection. I strongly support the publication of such a book.” —Éva Berde, Ph.D., Professor of Economics, Head of the Centre for Demography and Economics Research, Department of Economics, Corvinus University of Budapest, Hungary “Authors have investigated one of the most important issues in current society. We should pay more attention to the financial sustainability of the pension system, especially in times affected by the pandemic crises

that would influence public for a few upcoming decades. Furthermore, this publication compares the situation among particular economies well known for their multilateral cooperation in Central and Eastern European region.” —Ing. Tomas Heryan, Ph.D., Department of Finance and Accounting, Silesian University, School of Business Administration, Karvina, Czech Republic

For Paula, Otilia, Adriana, Paul, and Samuel. Stefania Amalia Jimon. For Alina, Letiția, and Marina. Florin Cornel Dumiter For Dorin and Aurelia. Nicolae Baltes

Preface

In the context of the intensification of population movement and migration, one issue to be taken into account is the situation of people working in several countries and accumulating pension rights in the form of pensions in all these countries. In such cases, the issue of the transferability of these rights and the method of payment of benefits arises. The topic addresses the issue of sustainability of PAYG-type public pension systems in five CEE countries, namely the Czech Republic, Hungary, Poland, Slovakia, and Romania. This book captures aspects intensely debated in the domestic and international economic literature, as well as in demographic, social, and legal studies. This book is a complex research on the structure of pension systems and the main factors influencing the financial sustainability of public PAYG pension systems implemented in CEE countries. The issue addressed, in the current demographic context, has aroused anxiety, concern, and strong debate in the public, political, and academic environment. The issue of the sustainability of public pension systems has become the focus of both international and governmental bodies, as well as a considerable number of specialists in the field of public finance, social protection, macroeconomics, and law, as well as empirical research in academia, confirming the complex and multi-, inter-, and transdisciplinary character of the approached topic. The approached topic highlights multiple facets and divergent aspects such as social economy versus capitalist economy, globalization versus glocalization, population aging versus birth and fertility, emigration versus immigration, early retirement versus prolongation versus professional activity, restrictive eligibility criteria versus the right to the financial protection of the elderly population, the sustainability of public pension systems versus the adequacy of benefits provided, public pension systems versus private pension funds, and taxation of salary incomes versus subsidization of state social insurance budgets. Therefore, the approached topic has many aspects, inter- and transdisciplinary, and due to the complexity of the topic, it is necessary to have a multisectoral approach that brings together insurance and medical system, tax system, financial sector, education system, and labor sector, as ix

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Preface

the discussion is focused on a large number of people, a large volume of resources is being used, and the stake is the well-being and financial security of the citizens. With a similar history, the adoption of the democratic system, and accession and integration into the European Union, the national pension systems of the CEE countries have undergone numerous regulations in order to be coordinated and harmonized with other member states’ systems, but especially to strengthen their sustainability. The aim of the book is the study of the financial implications of the new sociodemographic conditions on pension systems implemented by CEE countries and the identification of methods to strengthen the financial sustainability of public PAYG pension systems, directly influenced by demographic change and the effects of globalization. The authors believe that the sustainability of pension systems remains a topical issue, CEE being still in the process of adapting national pension systems to social, economic, and demographic reality and requiring in this process a multidisciplinary and integrated approach from a socioeconomic point of view. Chapter 1 presents the introductory aspects of the book with a special focus on the scope, research methodology, main objectives, and the research hypotheses. Chapters 2 and 3 present the major implication of pension systems starting with their chronological developments and by presenting the three dimensions of pension systems: social, economic, and medical. Chapters 4–10 analyze and assess the empirical evidence of pension systems under the three directions: socio, economic, and medical characteristics; macroeconomic effects; and financial sustainability. Chapters 5 and 6 tackle the sensible problems of private pension funds and the personal savings and investments in the financial market. Chapter 7 highlights the sine qua non condition for the fulfillment of the social role of pension systems. Chapter 9 measures the soundness of the financial sustainability of pension systems. Finally, Chap. 11 draws the final considerations and remarks regarding the future path with a special focus on the need for a reorganization of pension systems worldwide. Arad, Romania Arad, Romania Sibiu, Romania

Stefania Amalia Jimon Florin Cornel Dumiter Nicolae Baltes

Acknowledgments

This book presents an economic, financial, social, econometric framework for providing a guide to good practice in the field of social protection and pension systems, providing viable solutions for business, government, central, and local authorities. The book also seeks to substantiate the pension systems by defining and consolidating some personal views on the organization and functioning of pension systems in CEE countries, as well as on the main factors influencing and determining their financial sustainability. The results obtained from econometric modeling form the basis of macroeconomic policy recommendations on strengthening the sustainability of public pension systems in a framework that promotes the sustainable economic growth of the whole economy and can be a starting point for future reforms by CEE countries, especially of Romania in terms of social policy. We would like to thank the Finance Doctoral School of Lucian Blaga University of Sibiu for interesting suggestions and debates regarding the subject enriched in this book. Insightful comments and recommendations were also provided by our colleagues from the Department of Economic and Technical Department, Faculty of Economics, Computer Sciences and Engineering of the Vasile Goldiș Western University of Arad. Special thanks go to the Information Regional Account Manager Titi Jalbă for the implication and support in the book title proposal, evaluation process, and acceptance. We are indebted and grateful to our colleague Laura Rebeca Stiegelbauer from the Faculty of Socio Humanity Sciences of the Vasile Goldiș Western University of Arad for the English-language translation supervision of the book.

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Acknowledgments

We would like to thank the entire Springer team for their professionalism, implication, and dedication to our book project, especially Parthiban Gujilan Kannan and Rocio Torregrosa for supervision and quality assessment of the entire publishing process. Stefania Amalia Jimon Florin Cornel Dumiter Nicolae Baltes

Translator’s Note

A generous basic state pension is the least a civilized society should offer those who have worked hard and saved through their whole lives. —George Osborne, Speech to the Conservative Party Conference, The Guardian, October 4, 2010.

I am very glad and happy that I could contribute to the process of translation and adjustment of this special book together with my colleagues, Florin, Ștefania, and Nicolae. The finance domain, lato sensu, and pension systems, stricto sensu, have always been cutting-edge research domains in which the main theoretical and empirical trends are very carefully debated and tackled worldwide. The terminology approached in this book has encountered three important directions. First, it encompasses the technica verba of finance and the specific technical skills of language which a finance specialist must encounter. Second, the multi-inter-transdisciplinary approach was tackled within several important connected domains such as social sciences, technical sciences, medical sciences, law, and psychology. Third, the econometrical techniques used are complex and reveal certain important statistical tools and instruments in the modern financial research agenda. These imply another type of significant terminology used in an accurate and descriptive way. I truly hope that the English translation I supervised in the early draft received from my colleagues would be successfully rated by experts, specialists, students, and practitioners worldwide. Furthermore, I am confident that the translation of this research will help them to decipher the complex features of pension systems, the quid pro qou financial determinants, and the financial sustainability of these aspects in a changing world and in a time of great institutional shifts. Finally, as stated before, the book is addressed to a wide range of audience starting with young researchers who are eager to discover important features of pension systems, especially in the Central and Eastern European Countries, but also

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for more experienced ones who want to evaluate and assess their retirement process with a technical touch of up-to-date information and advised directions in this complex field. “Vasile Goldiș” Western University of Arad Arad, Romania 10 March 2021 Laura Rebeca Stiegelbauer

Contents

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

2

Overview of Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Emergence and Development of Pension Systems Worldwide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Social Protection and Pension Systems in the European Union . 2.3 Pension Systems in Central and Eastern European States . . . . . 2.3.1 Social Protection and the Pension System in the Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Social Protection and the Pension System in Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Social Protection and the Pension System in Poland . . 2.3.4 Social Protection and the Pension System in Slovakia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.5 Social Protection and the Pension System in Romania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.

7

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7 14 20

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20

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24 28

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31

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35 44 45 46

Socioeconomic and Medical Approaches upon Pensions Systems . . . 3.1 National Culture and Civilization as Factors of Influence of Social Protection Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 The Cultural System and Social Protection of the Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 The Influence of Sociopolitical Organization and the System of Government in Forming the Specific Framework of Social Protection . . . . . . . . . . . . . . . . . 3.1.3 The Role of Education in Substantiating Contemporary Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53

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53 54

56 59

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3.2

Influence of Demographic Changes on the Labor Market and Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Aspects Regarding the Sociomedical Characteristics of Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

5

6

7

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69 73 73 74

Modeling the Impact of Socioeconomic and Medical Characteristics on Public Pension Systems in Central and Eastern European Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 General Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Research Methodology and Data Used . . . . . . . . . . . . . . . . . . . 4.3 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Model I: The Economic Impact of Pension Systems . . . 4.3.2 Model II: The Social Impact of Pension Systems . . . . . 4.3.3 Model III: The Medical Impact of Pension Systems . . . 4.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . . 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

77 77 80 83 83 87 92 95 98 98

Private Pension Funds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Mandatory Private Pension Funds . . . . . . . . . . . . . . . . . . . . . 5.2 Voluntary Private Pension Funds . . . . . . . . . . . . . . . . . . . . . . 5.3 Investment Policy of Private Pension Funds in Central and Eastern European Countries . . . . . . . . . . . . . . . . . . . . . . . 5.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . 5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Annex: Specific Aspects Regarding the Administration of Private Pension Funds in Romania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 101 . 103 . 110

Personal Savings and Investments in the Financial Market . . . . . . 6.1 Financial Literacy and the Importance of Financial Inclusion in Central and Eastern European Countries . . . . . . . . . . . . . . . . . 6.2 Personal Savings Through the Banking System . . . . . . . . . . . . 6.3 Personal Investments in the Stock Market . . . . . . . . . . . . . . . . 6.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . 6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 125

. 115 . 118 . 119 . 119 . 122

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125 126 129 130 131 131

The Importance and Role of Social Policy in Maintaining Macroeconomic Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 7.1 The Risk of Poverty and Severe Material Disadvantages Among the Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 7.2 Benefits of Public Pension Systems and the Welfare of the Elderly Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

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7.3 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . . 139 7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 8

9

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11

Modeling the Macroeconomic Effects of Pension Systems . . . . . . . . 8.1 General Aspects Regarding the Macroeconomic Effects of the Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Research Methodology and Data Used . . . . . . . . . . . . . . . . . . . 8.3 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Model I: Macroeconomic Effects of Pension Systems—Ex Ante Provision of Income Through the Social Protection System, Including Pensions . . . . . . . . 8.3.2 Model II: Macroeconomic Effects of Pension Systems—Ex Post allocation of Social Benefits Through the Pension System . . . . . . . . . . . . . . . . . . . . 8.3.3 Model III: Macroeconomic Effects of Pension Systems from an Investment Perspective . . . . . . . . . . . . . . . . . . 8.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . . 8.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Financial Sustainability of Public Pension System . . . . . . . . . . . . . 9.1 Fiscal Policy: Implications from the Perspective of the National and European Fiscal Area . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Social Contributions and Tax Compliance . . . . . . . . . . . . . . . 9.3 State Social Insurance Budget . . . . . . . . . . . . . . . . . . . . . . . . 9.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . 9.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

143 143 145 148

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154 159 166 166 167

. 169 . . . . . .

Econometric Study on the Financial Sustainability of Public Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 General Aspects Regarding the Sustainability of Public Pension Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Research Methodology and Data Used . . . . . . . . . . . . . . . . . . . 10.3 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.1 Model I: Sustainability of Pension Systems in CEE Countries Through SSIB Revenues . . . . . . . . . . . . . . . 10.3.2 Model II: Sustainability of Pension Systems in CEE Countries Through SSIB Pension Expenditures . . . . . . 10.4 Conclusions and Personal Contributions . . . . . . . . . . . . . . . . . . 10.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

169 174 180 187 187 187 191 191 193 197 197 208 217 220 220

Conclusions and Final Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . 223

List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

List of Figures

Fig. 2.1

Fig. 2.2

Fig. 2.3

Fig. 2.4

Fig. 2.5

Fig. 3.1

Evolution of the rates of compulsory social contributions in the Czech Republic in the period 2001–2017. Source: Author’s processing based on OECD reports “Taxing wages” (https://www. oecd-ilibrary.org/taxation/taxing-wages_20725124) and “Benefits and Wages” (http://www.oecd.org/els/shock/benefits-and-wagescountry-specific-information.htm) for the Czech Republic . . . . . . . . Evolution of the rates of compulsory social contributions in Hungary in the period 1999–2018. Source: Author processing based on OECD “Taxing Wages” reports (https://www.oecdilibrary.org/taxation/taxing-wages_20725124) . . . . . . . . . . . . . . . . . . . . . Thresholds used for computation of the old-age pension in Hungary. Source: Author’s work based on the OECD report “Pensions at a Glance 2013: OECD and G20 Indicators” (https://read.oecd-ilibrary.org/finance-and-investment/pensionsat-a-glance-2013_pension_glance-2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evolution of the rates of compulsory social contributions in Poland in the period 2000–2018. Source: Author’s processing based on OECD “Taxing wages” reports (https://www.oecdilibrary.org/taxation/taxing-wages_20725124) . . . . . . . . . . . . . . . . . . . . . Evolution of the rates of compulsory social contributions for normal working conditions in Slovakia between 2000 and 2018. Source: Author’s processing based on OECD “Taxing wages” reports (https://www.oecd-ilibrary.org/taxation/taxingwages_20725124) (For the years 2001, 2002, and 2003, the OECD reports show the total share of social contributions paid by the employer, not specifying the percentage targeted at the pension system.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The educational level of the population in CEE countries, period 1950–1990. Source: Author’s processing based on data published by Barro-Lee (http://www.barrolee.com/) . .. . .. . .. . .. . .. . .. . .. . .. . ..

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Fig. 3.2

Fig. 3.3

Fig. 3.4

Fig. 3.5

Fig. 3.6

Fig. 3.7

Fig. 3.8

Fig. 3.9

Fig. 3.10

Fig. 3.11

Fig. 3.12

Fig. 3.13

List of Figures

Population in CEE countries according to educational level in the period 1998–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Average population, natural growth, and total population change in CEE countries in the period 1960–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa. eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Population structure according to age group and the average age of population in CEE countries, period 1960–2018. Source: Author’s processing based on data published by Eurostat (https:// ec.europa.eu/eurostat/data/database) . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . Population migration in CEE countries during 2008–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . Applications for asylum and citizenship in CEE countries in the period 2008–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Labor market structure by age group, activity rate, and unemployment rate in CEE countries in the period 1998–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . Duration of working life in CEE countries, period 2000–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . Minimum annual income, average annual income, taxes and social contributions in CEE countries in the period 2008–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . Birth rate, mortality, and fertility rate in CEE countries between 1990 and 2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Distribution of mortality by cause in CEE countries during 1999–2006. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . Accidents at work in CEE countries during the period 2008–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . Life expectancy in CEE countries in the period 2007–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . .

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List of Figures

Fig. 5.1

Fig. 5.2

Fig. 5.3

Fig. 6.1

Fig. 6.2

Fig. 6.3

Fig. 6.4

Fig. 7.1

Fig. 7.2

Fig. 7.3

Fig. 7.4

Fig. 7.5

Contribution rate to privately managed pension funds in Romania. Source: Author processing based on Law 411/2004, of the Laws of the state social insurance budget from 2008 to 2019 . . . . . . . . . . . Market share of voluntary pension funds and the number of participants in Romania. Source: Author’s processing based on data published by ASF (https://asfromania.ro/) . . .. . . .. . . .. . . .. . . .. . Assets, the structure of investments, and the real rate of return of private pension funds in CEE countries in the period 2008–2018. Source: Author’s synthesis based on the OECD publication “Pensions Markets in Focus (2019)” (http://www.oecd.org/ pensions/private-pensions/pensionmarketsinfocus.htm) . . . . . . . . . . . Use of bank accounts in CEE countries, 2017. Source: Author’s processing based on data published by the WB (https://databank. worldbank.org/reports.aspx?source¼world-developmentindicators) . .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . The degree of saving in CEE countries in 2017. Source: Author’s processing based on data published by the WB (https://databank. worldbank.org/reports.aspx?source¼world-developmentindicators) . .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . Interest rate for bank deposits in CEE countries, period 2008–2018. Source: Author’s processing based on data published by the ECB (https://www.ecb.europa.eu/stats/ financial_markets_and_interest_rates/html/index.en.html) . . . . . . . . The evolution of the main stock market indices in CEE countries in the period 2009–2019. Source: Author’s processing based on data published by PSE, BSE, GPW, BVB, and BSSE . . . . . . . . . . . . . Risk of poverty in CEE countries, 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa. eu/eurostat/data/database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Severe material disadvantages of the population in CEE countries in the period 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Median equivalized net income, replacement rate, and median relative income ratio of the population in CEE countries in the period 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Income inequality in CEE countries, 2007–2018. Source: Author’s processing based on data published by Eurostat (https:// ec.europa.eu/eurostat/data/database) . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . Evolution of GDP/inhabitant and general government expenditures with social protection in CEE countries, period 2002–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database) . . . . . . . . . .

xxi

109

113

117

127

128

128

130

134

135

136

137

138

xxii

Fig. 7.6

Fig. 7.7

Fig. 9.1

Fig. 9.2

Fig. 9.3

Fig. 9.4

Fig. 9.5

Fig. 9.6

Fig. 9.7

Fig. 9.8

Fig. 9.9

List of Figures

Life expectancy and healthy life expectancy at the age of 65 in CEE countries, 2007–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Happiness index in CEE countries, 2014–2018. Source: Author’s processing based on data published by https://worldhappiness. report/ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evolution of social contribution rates in CEE countries, period 2008–2019. Source: Author’s processing based on data published by the OECD (https://stats.oecd.org) and the tax legislation in force in Romania, 2008–2019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evolution of annualized wage income and wage income taxation rate in CEE countries between 2008 and 2019. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/database . . . . . . . . . . . . . . . . . . . . . . . . . . The share of taxes on salary income in total taxation. Source: Author’s processing based on data published by the European Commission’s Directorate-General for Taxation and Customs Union (https://ec.europa.eu/taxation_customs/business/ economic-analysis-taxation/data-taxation_en) . . . . . . . . . . . . . . . . . . . . . . Perception of the quality of political governance in CEE countries, period 1996–2018. Source: Author’s processing based on data published by the WB, available at https://info.worldbank.org/ governance/wgi/ . . . . .. . . . . . . .. . . . . . .. . . . . . . .. . . . . . . .. . . . . . .. . . . . . . .. . . . Evolution of BASS revenues and expenditures in CEE countries in the period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/ eurostat/data/database . . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . . . .. . . SSIB revenue structure in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/database . . . . . . . . . . . . Source of SSIB revenue in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/database . . . . . . . . . . . . Structure of SSIB expenditures in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/ database . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . Structure of pension expenditure in CEE countries in the period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/ database . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . .

139

140

174

176

177

179

181

181

183

184

185

List of Figures

Fig. 9.10

Fig. 10.1 Fig. 10.2

Fig. 10.3

Fig. 10.4

Fig. 10.5

Level of budget deficit/surplus and public debt in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/ data/database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Residuals analysis of model I. Source: Author’s processing using EViews 10 Academic Edition software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Residuals analysis of model I in the case of the Czech Republic. Source: Author’s processing using EViews 10 Academic Edition software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Model I residuals analysis in the case of Hungary. Source: Author’s processing using EViews 10 Academic Edition software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis of model I residuals in the case of Romania. Source: Author’s processing using EViews 10 Academic Edition software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Residuals analysis of model I in the case of Slovakia. Source: Author’s processing using EViews 10 Academic Edition software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xxiii

186 200

203

205

208

210

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 2.7

Table 2.8 Table 2.9 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8 Table 4.9 Table 4.10 Table 4.11

Sociological premises for the formation of social protection systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Classical typologies of social protection systems . . . . . . . . . . . . . . . Parametric changes in the reform of the public pension system in the Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reform of the Hungarian public pension system . . . . . . . . . . . . . . . Regulation of the public pension system in Poland . . . .. . . .. . .. . Regulation of the public pension system in Slovakia . .. . .. .. . .. Eligibility criteria for accessing the benefits of the public pension system, according to Law no. 263/2010, with subsequent modifications and updates . . . . . . . . . . . . . . . . . . . . . . . . . . . Benefits of the pension system according to Law no. 127/2019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Algorithm used to calculate pensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of model I variables . .. . . . . .. . . . . . .. . . . . .. . . Econometric test results—economic impact—ordinary least squares (OLS) . . . . . . . .. . . . . . . . . .. . . . . . . . . .. . . . . . . . . .. . . . . . . . . .. . . . . . Econometric test results—economic impact—correlation matrix . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fixed effects test results—redundant fixed effects . . . . . . . . . . . . . . Econometric test results—economic impact—OLS with cross-section fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Econometric test results—economic impact—OLS correlation matrix—cross-section fixed effects .. . .. . .. . .. . .. . . .. . .. . .. . .. . . .. Descriptive analysis of model II variables . . . . . . . . . . . . . . . . . . . . . . . Econometric test results—social impact—OLS . . . . . . . . . . . . . . . . . Results of econometric tests—social impact—correlation matrix of the OLS model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Test results—redundant fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . Econometric test results—social impact—OLS cross-section and period-fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10 14 21 26 29 34

39 41 43 84 85 85 86 87 88 88 89 90 90 91 xxv

xxvi

Table 4.12

Table 4.13 Table 4.14 Table 4.15 Table 4.16 Table 4.17 Table 4.18 Table 4.19

Table 4.20 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 6.1 Table 8.1 Table 8.2 Table 8.3 Table 8.4

Table 8.5

Table 8.6 Table 8.7

Table 8.8

Table 8.9

List of Tables

Econometric test results—social impact—OLS model correlation matrix with cross-section and period fixed effects . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . Hausman test for random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of the variables of model III . . . . . . . . . . . . . . Econometric test results—medical impact—OLS . . . . . . . . . . . . . . Results of econometric tests—medical impact—correlation matrix of the OLS model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Test results—redundant fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . Econometric results—medical impact—OLS cross-section and period-fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—medical impact—correlation matrix of OLS model with cross-section and period-fixed effects . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . Hausman test for random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Private pension funds implemented in CEE countries . . . . . . . . . . Mandatory private pension funds in Slovakia . . . . . . . . . . . . . . . . . . . Mandatory private pension funds in Romania . . . . . . . . . . . . . . . . . . Voluntary pension funds in Romania . . . . . . . . . . . . . . . . . . . . . . . . . . . . The main Community provisions on the structure of private pension fund investments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tax regime applied to contributions to private pension funds and private pensions in CEE countries . . . . . . . . . . . . . . . . . . . . . . . . . . Investment funds from CEE countries, fourth quarter 2019 . . . Descriptive analysis of model I variables . .. . . . . .. . . . . . .. . . . . .. . . Econometric test results—macroeconomic impact (ex ante allocation of pension benefits)—standard pooled IV-2SLS . . . . Results of econometric tests—macroeconomic impact (ex ante allocation of pension system benefits)—correlation matrix . . . . Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—pooled IV-2SLS—crosssection and period fixed effects . .. . . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . Results of econometric tests—macroeconomic impact (ex ante allocation of pension system benefits)—pooled IV-2SLS correlation matrix—cross-section and period fixed effects . . . . . Hausman test for random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—pooled IV-2SLS—crosssection fixed effects and period random effects . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—correlation matrix of the Pooled IV-2SLS model—cross-section fixed effects and period random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of model II variables . . . . . . . . . . . . . . . . . . . . . . .

92 92 93 94 94 95 96

97 97 103 105 107 112 116 118 130 148 149 149

150

151 151

152

153 154

List of Tables

Table 8.10 Table 8.11

Table 8.12

Table 8.13

Table 8.14 Table 8.15

Table 8.16

Table 8.17 Table 8.18 Table 8.19

Table 8.20

Table 8.21

Table 8.22 Table 8.23

Table 8.24

Table 9.1 Table 9.2 Table 10.1 Table 10.2

xxvii

Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS standard . . . . Econometric test results—macroeconomic impact (ex post allocation of pension benefits)—correlation matrix of the standard Pooled IV-2SLS model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS with crosssection and period fixed effects . .. . . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS correlation matrix with fixed transverse and temporal effects . . . . . . . . . . . . . . Hausman test for random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS with crosssection fixed effects and period random effects . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—correlation matrix of the Pooled IV-2SLS model with cross-section fixed effects and period random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of model III variables . . . . . . . . . . . . . . . . . . . . . . Econometric test results—macroeconomic impact— investment perspective—pooled IV-2SLS standard . . . . . . . . . . . . Econometric test results—macroeconomic impact— investment perspective—standard pooled IV-2SLS model correlation matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Econometric test results—macroeconomic impact— investment perspective—pooled IV-2SLS with cross-section and period fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—macroeconomic impact— investment perspective—correlation matrix of the Pooled IV-2SLS model with cross-section and period fixed effects . . . Hausman test for random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Econometric test results—macroeconomic impact— investment perspective—pooled IV-2SLS with cross-section fixed effects and period random effects . . . . .. . . . . . . . .. . . . . . . .. . . . Results of econometric tests—macroeconomic impact— investment perspective—correlation matrix of the Pooled IV-2SLS model with cross-section fixed effects and period random effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bilateral treaties on social security in CEE states . . . . . . . . . . . . . . . Factors influencing tax compliance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of model I variables . .. . . . . .. . . . . . .. . . . . .. . . Econometric test results—sustainability of public pension systems in terms of SSIB revenues—GMM method . . . . . . . . . . .

155

155

156

157 157

158

159 160 161

161

162

163 163

164

165 172 178 198 199

xxviii

Table 10.3 Table 10.4

Table 10.5 Table 10.6

Table 10.7 Table 10.8

Table 10.9 Table 10.10

Table 10.11 Table 10.12 Table 10.13 Table 10.14

Table 10.15 Table 10.16

Table 10.17 Table 10.18 Table 10.19 Table 10.20

List of Tables

Descriptive analysis of model I variables in case of Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—sustainability of public pension systems in terms of SSIB revenues in the Czech Republic—GMM method . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . Descriptive analysis of model I variables in case of Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—sustainability of public pension systems in terms of SSIB revenues in Hungary—GMM method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive analysis of model I variables in case of Romania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—sustainability of public pension systems in terms of BASS revenues in Romania—GMM method . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . . .. . . . . .. . . Descriptive analysis of model I variables in the case of Slovakia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—sustainability of public pension systems in terms of BASS revenues in Slovakia—GMM method . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . . .. . . . . .. . . Descriptive analysis of model II variables . . . . . . . . . . . . . . . . . . . . . . . Stationary of the variables of the model II . . . . . . . . . . . . . . . . . . . . . . Testing the optimal number of lags for model II .. . .. .. . .. . .. . .. Results of econometric tests—sustainability of public pension systems in terms of SSIB pension expenditures—VAR method . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . . .. . . . . .. . . VAR Granger causality/block exogeneity Wald test on model II predictors—Eq. (10.2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of econometric tests—sustainability of public pension systems in terms of BASS pension expenditures—Eq. (10.2)— VAR method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wald test for the causality of coefficients . . . . . . . . . . . . . . . . . . . . . . . Portmanteau autocorrelation test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LM autocorrelation test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis of the residue distribution of Model II . . . . . . . . . . . . . . . .

201

202 204

205 206

207 209

210 211 212 213

214 216

216 217 217 218 219

Chapter 1

Introduction

The development and economic growth of a country can be achieved only through the population, which through the knowledge, skills, and competencies possessed represents the innovative and creative value-added capital of the society, lato sensu and economy, stricto sensu. However, in recent years, the European Union (EU) has been facing significant changes in the demographics and population structure of the Member States. Data published by Eurostat show that the average age in the European Community (EC) is 43 with an aging population, which is due both to increased life expectancy and to reduce the birth rate by reducing the number of births, reducing the rate of fertility, and increase in the average age of birth of the first child. In 2018, the birth rate of EU countries recorded an average value of 9.5%, and the fertility rate was only 1.55 children born per woman, given that the replacement rate of the population requires at least one fertility rate of 2.1. However, the total population of the EU continued to grow in 2018 based on population migration. Within the EU, the free movement gives Member States citizens multiple opportunities in terms of professional activity and educational training, so the main areas of emigration are the following: Romania, Poland, Portugal, and Italy, while Germany, Spain, France, and Italy are EU countries with the largest influx of immigrants. Also, a share of 4.9% of the population of EU countries is represented by immigrants from nonmember countries, and the average age of the migrant population is 29 years. On the other hand, the EU population over the age of 65 also increased by about 2.6% in the last 10 years, with the highest rate in Italy and Greece. As a result, the dependency rate of the elderly population reached 30.5% in 2018. In other words, a person over the age of 65 is supported by three people active in the labor market. Eurostat projections, on the future trend of the population, predict a reduction in the number of the population by 2100, the population structure being subject to aging with an increase in the number of people over 80 years, while the share of the active population in the market employment will decline, with an increase in the percentage

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_1

1

2

1 Introduction

of people over 65. Under these conditions, the rate of socially and financially dependent older people is expected to double by 2100. The topicality of the approached topic is supported by the fact that the free movement of people, goods, services, and capital entails important changes, both in the sociodemographic structure of the countries and in the economic-financial point of view. Against the background of labor migration, corroborated with the aging trend of the population, a topic of particular importance is the financial sustainability of public pay-as-you-go (PAYG) pension systems. These demographic conditions have a major impact on the economy and the sustainability of economic growth. From a macroeconomic point of view, an aging population means a reduction in productivity, a slowdown in the growth of the gross domestic product, a reduction in savings and investment. Regarding the labor market, the effects of the new demographic conditions are materializing in the increase of the participation rate of the population over 50 years of age and of women. In this regard, it is necessary to ensure accessibility to the labor market, support the development of the entrepreneurial and business environment, create jobs suitable for the vocational training of the population, facilitate access to employment, including the elderly or those with a low degree of a physical disability that allows them to carry out certain professional activities. In terms of influence on financial markets, the aging trend reduces the level of savings and generates changes in investment policy and portfolio structure, with the tendency to invest in fixed income financial assets that provide security at a minimum degree of risk. The current demographic changes also have a significant impact on public finances, the main consequences being the increase in spending on benefits provided to the elderly through public pension systems and spending on health services. The demographic structure is of colossal importance in maintaining the sustainability of PAYG-funded public pension systems funded by contributions, given that once the majority of the working-age population becomes taxpayers, the pension system is correlated with the age structure of the population. The difficulties arise in the context in which the number of elderly people receiving the pension system, as well as the period in which they receive benefits, increases, while the active population on the labor market and the targeted contributions to the public pension system decrease and determine the decrease of social insurance budget revenues. The importance of the approached topic lies in the fact that the gap between the number of taxpayers and the number of beneficiaries leads to the increase of public expenditures and the increase of budgetary pressure. According to Eurostat data, the share of pension expenditure in GDP is expected to increase by 2060, and amid the economic crisis of 2007, which led to a budget deficit and external borrowing, the solvency of the entire financial system is exacerbated. Increasing the legal retirement age and the contribution period, as measures to attract income and reduce social security budget expenditures seem to be ideal solutions, but it must be taken into account that life expectancy is influenced by the socioeconomic, financial, and occupational status of the individual, and people with a modest financial status, as well as employees in areas of activity that present

1 Introduction

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increased risks of accidents and more dangerous and demanding working conditions may have a significantly reduced life expectancy. In addition, not all people want to work until they are old or experience reluctance from employers and reduced accessibility to the labor market. The multi-pillar structure of pension systems aimed to export budgetary pressure from the public pension system, but at the same time to ensure an adequate replacement rate and maintain the standard of living. However, in the case of pension schemes connected to the stock market by pension funds invested in financial assets, the amount of the pension relates to the return on investment. The slowdown in economic growth, low-risk portfolios, and moderate returns generate a low profit, materialized in the insufficiency of the necessary financial resources. Financial education, financial planning, and the adoption of private saving measures are possible solutions to supplement the public pension and obtain the necessary resources. Another relevant aspect that supports the importance of the issue addressed and, which takes into consideration the performance of public pension systems, is the adequacy of the income provided. At an EU level, the estimated average poverty rate for people over the age of 65 before social redistributions, including pensions, is over 87%. This percentage is reduced to 19.2% after the redistributions through the pension system, which reveals the dependence of the elderly on the pension system as the main source of income, a situation that suggests the need to adjust the income of pensioners. In this regard, the protection of low-income employees and short contribution periods must be considered. The motivation for choosing the approach starts from the fact that EU pension systems face the problem of solvency and sustainability in the context of demographic transition. In the field of research, we consider it imperative to reorganize the pension system, especially in the countries of Central and Eastern Europe (CEE). One may ask why CEE? Because these countries have a common past, manifested by the experience of communism in its most severe form, because many of the conditions of emerging economies in these countries that are in the process of catching up with developed countries, “follow” similar steps, and because this area of Europe needs cohesion in pension systems. At the level of Romania, a fundamental revision of the pension system is imperative, considering the new economic, financial, legal, social, behavioral, psychological, and human context. Certainly, the old system is an antiquated one, which is not at all effective and is not harmonized with the new context of economic and social life, given the comprehensive approach to the individual and public and private finances. Given this purpose and the complexity of the issue addressed, the authors set operational objectives of the book. Thus, the first objective is to approach this topic from a historical-anthropological perspective in order to have a clear and comprehensible image of the organization and functioning of contemporary pension systems in CEE countries. The second objective aims to identify the factors that have determined the configuration of the current pension systems implemented by CEE countries and

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the impact that the demographic structure, labor market characteristics, and medical status of the population have on them. The third objective is to study the effects of the multi-pillar structure supported by the WB and the ILO on the development of the financial sector, providing a macroeconomic perspective on the configuration of pension systems in CEE countries. The fourth objective of the research focuses on the budget of public pension systems in CEE countries and the determinants of the budget balance, aiming at the one hand at the formation of budget revenues by taxing salary revenues and subsidies received, and on the other hand by the level of expenses with social benefits. The book started from the following hypotheses: • Hypothesis 1.1. The reorganization, restructuring, and consolidation of public pension and social protection systems in CEE were achieved due to the need to adapt to the new economic, legal, social, demographic conditions established at the EU level. With a common history, marked by the experience of a paternalistic system of government, the CEE countries with the transition to democracy and the capitalist economy were faced with new socioeconomic conditions that imposed the need for new reforms in the social field. With EU accession and integration, they have had to transpose Community directives and regulations into national law, in order to ensure convergence and harmonization with the Member States regarding the observance of Community freedoms and the right to social protection within the EU. • Hypothesis 1.2. A level of convergence of the public pension systems of CEE countries can lead to the construction of an efficient functioning mechanism by creating an “optimal pension area” across the region. The Treaty on the Functioning of the EU, the Charter of Fundamental Rights, and the Social Charter emphasize the observance of the right to social protection of all EU citizens, regardless of their nationality or residence or their current domicile. As a result, CEE countries need to regulate the functioning of public pension systems in a Community context, facilitating the transferability and portability of social benefit rights in the other Member States. • Hypothesis 1.3. The strengthening of the social protection framework and pension systems at the level of CEE countries can only be achieved based on the country-specific social, financial, and economic structure. Although the right to social protection of the population is universally recognized, each state, on the basis of sovereignty and autonomy, regulates the organization and functioning of social protection systems and pension systems according to the cultural characteristics of a society, economic development, and national social level.

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• Hypothesis 1.4. What is the impact of social, economic, and medical characteristics on the structure and organization of pension systems from a managerial perspective?! The main variables with which public PAYG systems operate are: population structure, birth rate, employment rate, life expectancy, mortality rate, dependency rate of the elderly population, labor taxation rate and fiscal pressure, fiscal compliance, adequacy of benefits, intergenerational equity, macroeconomic stability. Thus, the structure of pension systems in CEE countries is dependent on the socioeconomic framework in which they operate, being conditioned by current socioeconomic conditions and their dynamics. • Hypothesis 1.5. Can private pension funds constitute economically, financially, and socially viable alternatives to the reform of pension systems under the auspices of ensuring macroeconomic stability in CEE?! Private pension funds aim to increase resources through investments in financial assets, as a result of which their return is conditioned by the investment structure and the level of development of financial markets, as well as by the stability of macroeconomic policies. • Hypothesis 1.6. Is the financial sustainability of pension systems in CEE strengthened in terms of creating a “fiscal space” at an EU level, increasing the voluntary compliance of taxpayers, and ensuring a viable and sustainable state social insurance budget?! The financial sustainability of pension systems is defined by the balance between the income from social contributions of the state social insurance budget and the expenditure on benefits provided to beneficiaries. As a result, numerous studies have highlighted the positive effect of reducing the tax burden on taxpayer compliance and budgetary consolidation.

Chapter 2

Overview of Pension Systems

Understanding the configuration of social protection and pension systems can be achieved only from a sociohistorical perspective upon the framework in which these emerged and developed. In this chapter will be presented the image of the organization and operation of the contemporary pension systems in CEE countries, focusing on the Romanian case. Therefore, the chapter identifies the typologies of pension systems internationally recognized and presents the principles that govern them. The chapter also envisages the delimitation of the legislative framework governing social security and the protection of the elderly at the national, community, and international levels, discussing as well the legislative harmonization. The final part of the chapter aims to describe the national pension systems implemented in five CEE countries, which have “gone through” the experience of communism, are in the process of catching-up with developed countries, and “follow” similar steps toward the coordination with the current social, economic, cultural, and demographic context.

2.1

The Emergence and Development of Pension Systems Worldwide

Social protection systems and national pension systems have developed in a clearly territorially defined framework. The configuration and organization of the functioning were established by the state leadership, depending on the specifics of the government system during their implementation (Perotti & Schwienbacher, 2009), being configured according to the national political, economic, and sociocultural context. Pension systems, together with social assistance services, are part of the social protection and security system, enshrined at the international level by adopting the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_2

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Universal Declaration of Human Rights (United Nations, 1948). Through it are upheld equality and human dignity, highlighting the right to social protection and the role of the state in protecting its citizens. Therefore, due to the regulatory and income redistribution role, the state, through its institutions, has the capacity to organize and manage the social protection system. ILO defines the social protection system as a form of insurance for individuals through which are respected the basic rights, such as the right to health care, the right to the financial security of children, elderly, but also of people who, due to disabilities or pathologies, are unable to earn income (ILO, 2012). The purpose of social protection systems is to reduce social and economic vulnerability among marginalized and poorly materialized groups (Sabates-Wheeler & Devereux, 2008). From a juridical point of view, social security is the set of mandatory rules on the financial and material insurance of persons, subjects of law, enriched in a legal employment relationship, against the risk of accidents, illness, and old age, as well as their descendants (Ghimpu et al., 1998). The pension system is a part of social protection system that regards the situation of the elderly, who due to old age are unable to carry out professional activities, through which should obtain the necessary resources to meet the basic needs and therefore present a high risk of poverty and severe material deprivation (Begum & Wesumperuma, 2012). The main objectives of a pension system are to reduce poverty (Lannoo et al., 2014), to ensure an adequate financial flow for a decent living, and to maintain the level of consumption during retirement, especially in conditions of financial instability (Littlewood, 2014). Through the benefits provided and financial transfers, the state has a direct influence in reducing the uncertainty of income and decreasing the risk of poverty among the elderly. At the EU level, in countries such as Belgium, the Czech Republic, Denmark, Germany, the Netherlands, Finland, and Sweden, the poverty rate of the older population before the social distribution exceeds 90%. Following the allocation of pension, the percentage is significantly reduced, with values below 15% in Austria, Slovakia, Norway, Luxembourg, France, Greece, and Hungary. These evolutions are suggestive and express the dependence of older people on the income provided by national pension systems (Fiszbein et al., 2016). First forms of social protection date back to Antiquity. The first mentions regarding a social protection system are found in Egypt, where there was a mutual aid fund financed by stone carvers, through which, in case of social risks, financial and material aid was granted to members (Hudea, 2017). Hammurabi Code is the most well-known and important document attesting to the existence of laws on justice. From the prologue of the Code, it can be noticed that the purpose of Hammurabi, through the 282 laws, is justice, the destruction of criminals, and ensuring the welfare of the people (The Code of Hammurabi—King translation). Nagarajan (2009) studies the Hammurabi Code from an economic perspective and highlights the concern of this Syrian leader for the right to property, civil law, financial law, the right to protect workers, slaves, and other vulnerable people. Spiegel and Springer (1997) consider this code the forerunner of ethics and deontology in the field of medical services.

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On Dacia territory, before the Roman conquest, a series of social norms were established by which the young population had to ensure the satisfaction of the needs of the elderly. The social protection of the vulnerable categories was carried out by the community, emphasizing the distributing role of the family (Bocancea & Neamțu, 1999). In the Roman Empire, the social protection of the urban plebs, the poorest social stratum in Rome, was achieved through the free distribution of food. Also, Caius Iulius Caesar, as consul, managed to regulate the granting to the poor civilians with at least three children, as well as to the veterans of the military campaigns, the property right over some lands (Bârzu et al., 2004). Although these measures initially had a political purpose, we cannot ignore the positive effects of reducing poverty and protecting the right to private property. Although the first sources of the creation of social protection systems are found in Ancient times, the provision of social protection was more pronounced after the implementation of the Elizabethan Act for the Relief of the Poor in England and Wales. The law has innovative elements but does not present a very well-defined organizational framework (Charlesworth, 2010). The normative act established the obligation of parishes to provide support to the poor and the elderly. Initially, the activities carried out through the parishes were simple acts of charity carried out with the help of the parishioners, but later, it became the responsibility of the church to take care of these disadvantaged categories. The development of modern social protection systems took place during the industrial revolution. The main premises that formed the basis for the formation of social protection systems have their origin in the criticisms of the capitalist economic system, respectively, promoting social inequalities and poverty. Kaufmann (2012) studied the foundations of European social systems and identified the sociological premises that formed the basis of setting up the social protection systems. Table 2.1 summarizes the sociological ideas that formed the basis for the implementation of social policies. At the time, from the point of view of political economy theory, Adam Smith developed the concept of the exchange economy, which has the capacity to selfregulate (Smith & Cannan, 2003). This theory was contested by Keynes (1936), who argued that in order to achieve economic equilibrium and sustain economic growth, the intervention of the state is needed. However, Marshall (1963) points out that the human rights and psychological structure of citizens constitute a basis for developing social inequalities and poverty, the state having the responsibility to avoid this situation. On the other hand, Marx (1867) criticizes the concepts of classical political economy and reformulates its principles, supporting the idea that the state must create the necessary conditions for economic development. Analyzing these theories, Gough (1979) concludes that state intervention, through social policy, must be correlated with its socioeconomic interests. The development of social protection systems had a clear direction: respect for the social rights of the population in order to maintain the development and economic growth of countries. Abramovitz (1956) draws attention to the quality of the population in determining the country’s economic growth, and Mincer (1958)

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Table 2.1 Sociological premises for the formation of social protection systems Promoter Lorenz von Stein Adolph Wagner Hugo Sinzheimer Eduard Heimann Hans Achinger Friedrich List Alva and Gunnar Myrdal Thomas H. Marshall Jean Charles Léonard Simonde (Simonde de Sismondi) John Stuart Mill

Sustained concept Necessity of social order, given the tensions found between state, civil society, and family The state, using social policies, should protect the interest of disadvantaged citizens Activity on labor market and social protection have a legal framework Need of social policies given the capitalist economy and social inequality Social policies should comprise social protection of workers State leads the direction of economic activities and human capital development Social policies are related to demographic trends, therefore policies aimed to protect family have a great importance Social rights are the foundation of social inclusion The state is responsible for ensuring the fair redistribution of national welfare The state should promote equal opportunities for citizens and decrease the economic burden of disadvantaged population

Source: Author’s synthesis based on the publication “European Foundations of the Welfare State” by Franz-Xaver Kaufmann (2012)

presents the role of skills and experience in obtaining economic benefits. Schultz (1961) argues that the health status of the population is an essential factor for the economic development of a country. In this regard, Ginsburg (1979) presents the main directions of state action: education, medical services, poverty reduction, social security, and social assistance services. The end of the nineteenth century brought the first remarkable regulations in the field of social protection. Germany was the first state to adopt social policies regarding the social protection of the population. Chancellor Otto von Bismarck proposed three normative acts aiming at the regulation of health insurance and work insurance, as well as the implementation of a pension system (Doring, 1997). The social protection system was mainly intended for industrial workers, who earned modest incomes and were susceptible to accidents at work and disabilities. The pension system proposed by Bismarck operated based on the principle of contributivity and solidarity among workers and supposes the collection of social contributions from workers and the redistribution of funds once the eligibility criteria of age and contribution period are met. The benefits mainly included the old-age pension and the invalidity pension. Over time, the pension system proposed by Bismarck has expanded to other categories of workers and has been taken over by other European countries. The middle of the twentieth century brings a new perspective on social protection systems, William Henry Beveridge suggesting financial assistance to all citizens in delicate situations, and thus a social security system with national coverage (Hills

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et al., 1994). The funds of the pension system are formed by redistributing the resources of the general state budget and not based on contributions, the beneficiaries being only those citizens who meet certain eligibility conditions related to age, income, or assets. Countries as the United Kingdom, Denmark, Sweden, Ireland, and Cyprus have implemented the system proposed by Beveridge but additionally was established a contributory pension scheme. An innovative stage in the evolution of pension systems was marked by the American economist Milton Friedman. The author fought the idea of social redistribution through public social protection systems and promoted personal responsibility for procuring the financial resources needed in old age (Friedman, 1912). Thus, the author developed a new concept regarding pension systems that provided for pension funds to be invested in the stock market, in order to multiply the necessary resources. José Piñera successfully implemented this system in Chile, which led to the spread of the system worldwide. At the end of the twentieth century, given the economic and demographic context, World Bank is promoting a five-pillar structure for national pension systems, consisting of five elements (Holzmann et al., 2008): 1. A noncontributory component to ensure the financial security of all elderly people, called the Pillar “Zero” (P0) 2. A contributory component based on the social contributions paid by the insured population during the professional activity, called the “First Pillar” (P1) 3. A component consisting of mandatory privately managed pension funds, called “Second Pillar” (P2) 4. A component representing voluntary private pension funds, called the “Third Pillar” (P3) 5. A nonfinancial component comprised social assistance services, called the “Fourth Pillar” (P4) Noncontributory pension schemes, based on the social protection principles promoted by Beveridge, aim to protect people “who do not participate in the labor market covered by the social protection systems, who do not participate regularly enough to receive benefits, or whose earn a very modest income that allows a very small amount of pension” (Schwarz, 2006b, pp. 8). As a result, the state provides financial assistance to these people based on eligibility criteria related to residence, age, and income level, the financing being made from the general tax revenues of the state budget. The implementation of P0 in Mexico has had a positive impact on terms of income redistribution and poverty reduction among the elderly, although the amount of pension is modest (Aguila et al., 2017). The financial redistributions made through P0 reduce the level of depression and create the feeling of security and protection (Galiani et al., 2016), thus having positive effects on the mental health of the elderly and at the same time improving their well-being (Salinas-Rodriguez et al., 2014). Contributory pension schemes, depending on the method of financing, come in two forms: pay-as-you-go (PAYG) pension systems and pension funds (Schwarz, 2006a). From this perspective, P1 usually consists of PAYG public pension

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schemes, based on the social protection principles promoted by Bismarck. The operation of P1 is based on mandatory pecuniary levies from persons employed on the labor market, as social contributions applied to gross income, being paid by the employee and the employer. Specific to PAYG pension systems is the redistribution between generations, which means that the resources obtained from social contributions and other tax payments directed to the social insurance budget are used for the payment of current pensions, the state guaranteeing the provision of benefits to taxpayers once the eligibility criteria mainly related to the minimum contribution period and the standard retirement age are met. As a result, the success of PAYG pension schemes is contingent by maintaining the balance between the expenditure generated by current provisions and the income obtained from social contributions paid by the employed population. Pension funds, a concept developed by Milton Friedman, on the other hand, use the income from social security contributions for investments in financial markets in order to obtain additional income. To reduce the pressure of the public pension system and to ensure an adequate replacement rate during retirement, at the recommendation of WB, different countries have implemented a mandatory private pension system. P2 is, in fact, a hybrid form of financial insurance for the elderly formed by combining some features of the public pension system with aspects specific to privately managed pension funds (Sender, 2012). Voluntary pension schemes are an alternative for investing personal savings and a manner to receive additional income during retirement. P2 and P3 financing is based on the participants’ contribution, but the management of financial resources is made by private companies specialized in financial investments, through nominal accounts that reflect the contribution history of each participant and the performance of the investment. The distribution of benefits in the case of contributory pension schemes can be achieved either through the defined benefit mechanism (DB) or using a defined contribution mechanism (DC) (Schwarz, 2006a, 2006b). The difference between the two mechanisms lies in the reporting basis used to calculate the value of the benefits. In the case of DB, the computation formulas consider the level of income achieved during the contribution period, while the DC mechanism reflects the amount of capital accumulated in the pension fund through the contributions paid. Most commonly, PAYG pension systems use DB mechanisms to distribute pensions, and private pension funds use DC calculation formulas. In addition to these two traditional mechanisms, in recent decades, variants have been developed that combine features of the DB and DC systems, the most representative forms being the system based on pension points and notional accounts (Holzmann & Palmer, 2006). In the case of systems using pension points, these points are correlated with the level of income for which the payment of social contributions is made, and when meeting the eligibility criteria, the cumulative score and the number of benefits which will be determined according to the value of a pension point are determined. Notional accounts (NDC) are a form of the DC mechanism, which highlights contributions to the nominal pension fund and performance (notional profitability set by the government), but resources are used for

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current benefits, like the PAYG pension system. When the eligibility criteria are met, the cumulation of contributions and the notional capitalization are redistributed to the beneficiaries as annuities, the rate of annuities being correlated with life expectancy (World Bank, Pension Reform Primer, Notional accounts—Notional defined contribution plans as a pension reform strategy). It is noted that the current pension systems implemented by democratic states are generally based on the principle of contributivity, which conditions social transfers and access to benefits by fulfilling the eligibility criteria (Dodlova et al., 2017), and as a result, national pension systems based on the principle of contributivity does not reduce the risk of poverty among all citizens. In addition to the financial component of pension systems aiming at the redistribution of income and reducing financial insecurity among the elderly, a fourth nonfinancial pillar is currently being considered. The nonfinancial component aims to support the elderly, through social assistance programs that provide informal support, but also specific services needed for the elderly (Holzmann et al., 2008). The contemporary configuration of social protection systems can be seen as a bridge between the past and future, continuing to adapt to new national social, demographic, economic, and political conditions. Social protection systems, regardless of their type, aim to provide protection against social risks to all persons, regardless of age, citizenship, religion, or ethnicity. Pension systems, part of social protection systems, aim to provide financial protection to the elderly, those suffering from accidents or illness, and as a result, cannot carry out professional activities. Worldwide, the configuration of social protection systems and national pension systems is very diverse, the proportion of each pillar proposed by the WB, within the national pension system being different, according to the social policy promoted by each country. However, similarities can be identified in the organization of pension systems, depending on the geographical area and the country’s system of government. In North America, pension systems consist mainly of private funds, respectively, occupational pension funds, the role of the state in income redistribution being relatively small. In the countries of Central and Latin America, the public pension system is a PAYG type, but socioeconomic conditions have required its complete reform. In this regard, most states have decided to privatize pension funds and have defined a noncontributory component, with the primary role to reduce poverty among the elderly population. In Asia, pension systems are mainly based on the public component, but some states also regulated the participation in privately managed pension funds, their funding being relatively limited. A similar situation is encountered in the countries of the Middle East. Regarding the pension systems in African countries, there is a differentiation in their structure, in accordance with the principles established during the formation of the colonies (Egger et al., 2017). As a result, it is noted that in countries that were colonies of Great Britain, pension systems were implemented based mainly on the public component, having regulated the noncontributory pillar. In the case of former French colonies, the pension systems are the PAYG type. Some countries have also regulated participation in privately managed pension funds. The Australian pension system has a multi-pillar

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structure consisting of a public pension system, which also includes a noncontributory component, as well as privately managed pension funds.

2.2

Social Protection and Pension Systems in the European Union

In Europe, a diversity of forms of pension systems can be noted. At the EU level, national pension systems have a multi-pillar structure, each state developing its own pension system, adapted to the economic, social, demographic, and political context. Esping-Andersen analyzes social protection systems, in terms of connections between family structure, state and organization of the market, identifying three main forms of organization of social protection systems, namely: liberal system, conservative – corporative system, and social – democratic system (EspingAndersen, 1990). The typologies identified by Esping-Andersen are not found in pure form in contemporary society, but there is a tendency for countries to “follow” the principles of a certain type of social protection system. The main characteristics, as well as the European countries representative of each typology, are presented in Table 2.2. Sapir (2006) distinguishes four categories of social protection systems, according to the geographical area. The author presents four European models of social protection, namely: the Anglo-Saxon model, characterized by individual responsibility and social assistance of last resort; the Nordic model, with universal benefits based on the principle of equity and equality; the continental model, based on the contribution of people employed in the labor market; and the Mediterranean model,

Table 2.2 Classical typologies of social protection systems Typology of the social protection system Liberal

Conservative – corporative

Social – democratic

Socioeconomic characteristics – Individual responsibility – Independence – Free markets – State intervention is minimal – Social solidarity – The redistributive role of the state – Occupational social protection systems – Equality and social equity – Participation and mutual responsibility of citizens – Universality of benefits based on citizenship

Representative states Great Britain, Ireland

France, Belgium, Germany, Italy, Austria

Sweden, Norway, Denmark

Source: Synthesis of the author based on the publication “The Three Worlds of Welfare Capitalism” by Esping-Andersen (1990)

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similar to the continental model, but which shows a strong segmentation and conditioning in accessing the provisions. Flores (2014) discusses the concept of a social protection system in transition. According to the author, this type of system is characteristic in CEE countries, which experienced the “socialist legacy” and try to recalibrate with the new socioeconomic and cultural conditions (Cook, 2010). Inglot (2008) appreciates this type of social protection system as being in process of “construction,” while Adăscăliței (2012) considers it inconclusive. The debate on the existence of this typology was researched by Orosz (2019), who, using hierarchical cluster analysis showed that there is a distinction between social protection systems in CEE countries and traditional social protection systems of Europe. Thus, at the European level, five main categories of pension systems can be identified, namely: the Nordic pension system, the Anglo-Saxon pension system, the continental pension system, the Mediterranean pension system, and the transitional pension system. The discrepancy between Western countries, a symbol of multiculturalism, with economic systems based on free markets, liberal and democratic governments, and CEE countries, part of the former Soviet bloc, with socialist influences and a tendency toward conservative typology, in which state intervention is desired to maintain the order and functioning of the state (van Kersbergen & Kremer, 2008). In the context of highly diversified pension systems at the Community level, the need for coordination of these is identified, in order to respect citizens’ rights to social protection in the context of Community freedoms. The basic principles of the EU are the free movement of persons and capital within the Member States (Directive 2004/38/EC), as well as equality and nondiscrimination of persons based on residence (Directive 2000/43/EC). Article 293 of the Treaty on European Union (TEU) lays down the protection of persons and the protection of their rights in all Member States. However, the responsibility for organizing and implementing social protection systems lies with each state, the role of the EU being to assemble policies that promote convergence, harmonization, and cohesion between the Member States. Free movement into the EU gives great freedom to carry out professional activities. In the case of persons performing professional activities on the territory of several states, for different periods of time, appears participation in multiple pension systems. The EU Charter of Fundamental Rights emphasizes, in Article 34, the right of all people to social security and dignity; and the provisions of the European Social Charter establish the obligation of the Member States to organize a system that provides social security, reduces the risk of poverty and social exclusion, and provides social and medical assistance to the population, including immigrants. Moreover, in Article 23, the Social Charter stipulates the obligation of states to ensure social protection for the elderly population, by providing the necessary financial resources, medical services, and shelter to people in difficult situations, including institutionalization in gerontological and geriatric centers. At the Community level, Regulation no. 883/2004 and Regulation no. 987/2009 for the implementation of Regulation 883/2004 of the European Commission are the

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most relevant regulations on ensuring the social protection of persons resident in a Member State, but who are or have been under the legislation of one or more States. The purpose of the provisions established by these Community acts is to coordinate the legislation regarding the benefits of national social protection systems in the Member States.1 These provisions aim to delimitate the jurisdiction of each State2 and to ensure that the rights acquired in one-Member State are maintained,3 as well as to guarantee the export of the benefits to another Member State.4 In specialized literature and in practice, three forms for the computation of the amount of the pension can be identified, namely: the method of integration, which takes into account the cumulative contribution period; the direct method, according to which the number of benefits is determined according to the national regulations of each country; and the pro-rata method, which involves determining the amount of the pension correlated with the contribution to each national pension system (Hirose et al., 2011). According to the two above-mentioned European Commission Regulations, at the EU level, the pro-rata method is used to determine benefits. The amount of the pension in the case of contributions at multiple national pension

1 Art. 3, Para. (1) of Regulation (EC) No. 883/2004 establishes as an object of the mentioned regulation “sickness benefits; assimilated maternity and paternity benefits; invalidity benefits; old-age benefits; survivor benefits; benefits for work accidents and occupational diseases; death benefits; unemployment benefits; early retirement benefits; family benefits.” 2 According to Art. 11, Para. (1) and Para. (2), lit. (e) of Regulation (EC) No. 883/2004, persons resident in a Member State located in the territory of another Member State shall be subject to the “legislation of a single Member State,” namely “the legislation of the Member State of residence, without prejudice to other provisions of this Regulation guaranteeing him/her benefits under the legislation of one or more other Member States.” The defining element for establishing the residence of a person, according to Art. 11 of Regulation no. 987/2009 is: “the center of interests of the person concerned, based on an overall assessment of all available information relating to relevant facts, which may include, as appropriate: (a) the duration and continuity of presence on the territory of the Member States concerned; (b) the person’s situation, including: (i) the nature and the specific characteristics of any activity pursued, in particular the place where such activity is habitually pursued, the stability of the activity, and the duration of any work contract; (ii) his family status and family ties; (iii) the exercise of any non-remunerated activity; (iv) in the case of students, the source of their income; (v) his housing situation, in particular how permanent it is; (vi) the Member State in which the person is deemed to reside for taxation purposes.” 3 Art. 6 of Regulation (EC) No. 883/2004 provides: “the competent institution of a Member State whose legislation makes: the acquisition, retention, duration or recovery of the right to benefits, the coverage by legislation, or the access to or the exemption from compulsory, optional continued or voluntary insurance, conditional upon the completion of periods of insurance, employment, selfemployment or residence shall, to the extent necessary, take into account periods of insurance, employment, self-employment or residence completed under the legislation of any other Member State as though they were periods completed under the legislation which it applies.” 4 According to Art. 7 of Regulation (EC) No. 883/2004 “cash benefits payable under the legislation of one or more Member States or under this Regulation shall not be subject to any reduction, amendment, suspension, withdrawal or confiscation on account of the fact that the beneficiary or the members of his/her family reside in a Member State other than that in which the institution responsible for providing benefits is situated.”

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17

schemes shall be established in terms of the legislation of each Member State5 and may not be less than the minimum benefit laid down by law.6 To access the benefits of pension schemes from the EU Member States, the applicant must make and submit an application for a pension,7 together with the supporting documents specified in the legislation. Based on the documentation, each competent institution shall analyze the applicant’s situation, calculate the number of benefits and notify the other institutions involved, as well as the applicant of the pension decision.8 According to the European Commission’s Report on the coordination of social protection systems, about 4.5% of the number of pensioners in the Member States reside in the territory of another Member State. The implementation of these regulations at the EU level has led to the transfer of over 20.7 billion € as pensions between EU States (De Wispelaere et al., 2020).

Art. 50, Para. (1) of Regulation (EC) No. 883/2004 establishes “All the competent institutions shall determine entitlement to benefit, under all the legislations of the Member States to which the person concerned has been subject, when a request for an award has been submitted, unless the person concerned expressly requests deferment of the award of old-age benefits under the legislation of one or more Member States,” but according to Para. (2) “the person concerned does not satisfy, or no longer satisfies, the conditions laid down by all the legislations of the Member States to which he/she has been subject, the institutions applying legislation the conditions of which have been satisfied shall not take into account, when performing the calculation in accordance with Article 52 (1) (a) or (b), the periods completed under the legislations the conditions of which have not been satisfied, or are no longer satisfied, where this gives rise to a lower amount of benefit.” Once the eligibility criteria established by law are met, according to Para. (4), the benefits will be recalculated. Also, Art. 10 of the same Regulation highlights that “this Regulation shall neither confer nor maintain the right to several benefits of the same kind for one and the same period of compulsory insurance.” 6 Art. 58, Para. (2) of Regulation (EC) No. 883/2004 establish that “the competent institution of that Member State shall pay him/her throughout the period of his/her residence in its territory a supplement equal to the difference between the total of the benefits due under this chapter and the amount of the minimum benefit.” 7 Art. 45, Para. (1) of Regulation (EC) No. 987/2009 states that “the claimant shall submit a claim to the institution of the Member State, whose legislation was applicable at the time when the incapacity for work occurred followed by invalidity or the aggravation of such invalidity, or to the institution of the place of residence, which shall forward the claim to the first institution,” respectively the claimant of other benefits “shall submit a claim to the institution of his place of residence or to the institution of the last Member State whose legislation was applicable. If the person concerned was not, at any time, subject to the legislation applied by the institution of the place of residence, that institution shall forward the claim to the institution of the last Member State whose legislation was applicable.” 8 According to Art. 47, Para. (6) of Regulation (EC) No. 987/2009, “Each institution in question shall calculate the amount of benefits in accordance with Article 52 of the basic Regulation and shall notify the contact institution and the other institutions concerned of its decision, of the amount of benefits due and of any information required for the purposes of Articles 53–55 of the basic Regulation,” and the first part of Para. (1) of Art. 48 establish that “Each institution shall notify the claimant of the decision it has taken in accordance with the applicable legislation. Each decision shall specify the remedies and periods allowed for appeals.” 5

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Regarding the status of migrants from the non-EU Member States, it is governed by international conventions signed. The EU has the widest network of bilateral and multilateral treaties and agreements regarding the social protection of its own citizens, as well as nonresidents, and thus, is considered to be the most advanced form of regional integration, cooperation, and cohesion (Deacon, 2012). In this regard, the accent is put on bilateral and multilateral social security treaties (Alvarez Cortes, 2001). These are the main instrument for ensuring social protection and equal rights for nonresidents in a partner state (Tamagno, 2008). The agreements on social protection aim to regulate the benefits provided by national social protection systems as health care, unemployment benefits, maternity allowances, work accidents, as well as benefits provided by pension systems, in accordance with ILO recommendations. Besides the delimitation of the applicable legislation, international social security treaties set out the eligibility criteria for accessing the benefits in case of participation in multiple national pension schemes and the manner in which the amount of the pension is determined. The signing of international conventions also regulates the transfer of benefits provided by a pension system abroad, as well as the exchange of information between contracting states. Simultaneously, these facilitate the mobility of people, competitiveness, cooperation, and exchange of information at the international level. At the regional level, the social protection of migrant people can be regulated by multilateral social security treaties. These international agreements establish the principles of social protection, through the consensus of several states, on the free movement of persons and the recognition of social protection rights. Moreover, multilateral treaties stimulate cohesion and regional socioeconomic development, this being the reason for which states that are part of regional socioeconomic cooperation bodies have concluded such multilateral treaties. Such treaties are the conventions signed by the Member States of CARICOM,9 OISS,10 and GCC,11 9

The CARICOM Community consists of 15 Member States (Antigua and Barbuda, Bahamas, Barbados, Belize, Dominica, Grenada, Guyana, Haiti, Jamaica, Montserrat, Saint Lucia, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago) and 5 associated states (Anguilla, Bermuda, British Virgin Islands, Cayman Islands, Turks and Caicos Islands). The Convention on Social Security was signed in 1996 with the aim of harmonizing social protection legislation in the CARICOM Member States. Persons contributing to multiple pension systems are subject to the legislation of the signatory states, when fulfilling the eligibility criteria, they benefit of provisions depending on the contributiveness of each state. More information at: https://www.ilo. org/dyn/migpractice/docs/93/Info.pdf. 10 The Ibero-American Multilateral Convention on Social Security is the latest multilateral agreement on social security, signed by 13 Latin American states (Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Paraguay, Peru, the Dominican Republic, Uruguay, and Venezuela) and two European countries (Spain and Portugal). Citizens of signatory states who contribute to two or more pension schemes within the signatory states, upon fulfillment of the eligibility conditions will benefit from the pro-rata method for the contributory period to each pension scheme. Available online at: https://oiss.org/convenio-multilateral/. 11 The Gulf Cooperation Council (composed of representatives of Saudi Arabia, Bahrain, the United Arab Emirates, Kuwait, Oman, and Qatar) has implemented the Unified Law on Extending Insurance Protection for Citizens of Signatory States which states that social protection is provided

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CIPRES.12 A more complex form of multilateral treaties is encountered within the EU, whose regulations are implemented at the level of all Member States. States may also implement some unilateral measures to avoid disputes over the jurisdiction on social security rights of nonresidents. A unilateral measure is to extend the benefits of social protection systems beyond the borders of the country in case of citizens who decide to migrate. This unilateral measure is applied by states such as Jordan, the Philippines, and Pakistan, which take the responsibility to ensure the social protection of their citizens, regardless of the geographical area in which they are located.13 National sovereignty implies the freedom of a state to implement its own social protection system, to establish the principles of operation, to define its composition, to identify the beneficiaries and to impose the eligibility criteria for accessing benefits, to specify the benefits granted and to decide the form of providing them. Globalization and free movement of people at the international level have led to the inadequacy of the principle of territoriality in the field of social protection for people, which are in a migration process, their right to social protection being constrained, and the access to benefits limited. Thus, it can appear a violation of human rights, as well as contradictions between the regulations of national legislation regarding the jurisdiction over the rights to collect social security contributions and the obligations to redistribute income to beneficiaries. International agreements on social security are based on the principle of reciprocity and equal treatment applied to residents of other partner State, in the national territory of the other contracting States. This implies a uniform application in terms of social security rights, the maintenance of acquired rights, and the guarantee of export of benefits abroad. This form of coordination of national social protection systems has positive effects on international cooperation and macro-regional cohesion.

by the State of residence. More information at: https://www.social-protection.org/gimi/gess/ ShowWiki.action?wiki.wikiId¼953. 12 Inter-African Conference on Social Security, consisting of 15 French-speaking African countries (Benin, Burkina Faso, Cameroon, Congo, Ivory Coast, Gabon, Guinea, Madagascar, Mali, Nigeria, Democratic Republic of Congo, Senegal, Chad, Togo, Republic of Central African Republic, Comoros) has established that persons contributing to multiple pension systems are subject to the legislation of several signatory states, when fulfilling the eligibility criteria to benefit from provisions based on the contribution made in each state, through the pro rata temporis system. Available online at: http://www.lacipres.org/IMG/pdf/Convention_Multilaterale_de_Securite_ Sociale.pdf. 13 More information at: https://www.social-protection.org/gimi/gess/ShowWiki.action?wiki. wikiId¼935.

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2 Overview of Pension Systems

Pension Systems in Central and Eastern European States

In CEE, social protection systems, including pension systems, were founded in the socialist period based on the principles enhanced by Chancellor Otto von Bismarck. The public pension systems were of the PAYG type, being financed by the contributions of active people on the labor market. The demographic situation is characterized by: high fertility rates, low share of the elderly in the total population, low unemployment rates, substantial budget revenues and the relatively small number of beneficiaries ensured the success of this form of organization of pension systems. The eligibility criteria for accessing benefits were relatively easy to accomplish, and the increased degree of contributions and low expenditures with benefits allowed to provide considerable pensions to insured persons. The abolition of the socialist system of government, the transition to a market economy, and later the accession and integration in the EU have brought many changes within CEE countries. The adaptation to the new socioeconomic and demographic conditions requires, also the reform of national pension systems (Poteraj et al., 2017). Although these countries have a relatively similar historical background and face the same demographic challenges, there is a different approach regarding the regulations adopted to maintain the sustainability of national pension systems (Balteș & Jimon, 2018).

2.3.1

Social Protection and the Pension System in the Czech Republic

The social protection system of the Czech Republic includes the following categories of benefits: pensions (old-age, disability, survivors, sickness), unemployment benefits, family benefits, social assistance and social services, benefits for work accidents and occupational diseases, and medical services (MISSOC database). The first regulation regarding social protection in the Czech Republic dates from 1887 and aimed at the protection of employees against accidents at work. In 1888 are regulated the medical insurance for illness and for the maternity period, and in 1945 was established the family benefits. Unemployment benefits were introduced only in 1991 (Social Security Administration, 2018). The organization and functioning of the social protection system were based on the principles of German Chancellor Otto von Bismarck, namely, social solidarity and contributivity. The pension scheme was financed based on the contributions paid by the employee and employer, and the benefits were distributed after meeting the eligibility criteria, which in the case of the old-age pension referred to the standard retirement age. Thus, in 1924, the standard retirement age was 65 years, being reduced to 60 years for men and 55 years for women in 1956. In 1964, the standard

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Table 2.3 Parametric changes in the reform of the public pension system in the Czech Republic Year 2002

2004

2006

2008

2012

2017 2018

Stipulations The standard retirement age for men is 63, and for women, depending on the number of children born, it is between 59 and 63 years The full contribution period is 25 years, and the minimum period of contribution is 15 years Early retirement is possible in case of a full contribution period with a penalty of 3.6%/ year, and the postponement of retirement will determine an increase with 6%/year of the pension amount, being possible the cumulation of the pension with salary income Standard retirement age is increased to 65 for men and will be between 62 and 65 for women, depending on the number of children born. The period of raising children up to the age of 4 is assimilated into the noncontributory periods considered in the calculation of benefits The minimum contribution period will be increased to 20 years, and the complete period of contribution will be 35 years Early retirement is possible only after reaching the age of 60, if the full contribution period is met, with a penalty of 3.6%/year, respectively 6%/year starting with 2010 The unemployment period is considered a noncontributory period assimilated into the contribution period, but only in a percentage of 80% From 2010, persons who decide to continue their professional activity after reaching the standard retirement age have the possibility to request either the full provision of the pension with a bonus of 0.4%/year, or the provision of ½ of the pension amount with a bonus of 3%/year The standard retirement age will be increased for each cohort by 2 months for men and up to 6 months starting with 2019, for women, without an upper limit The penalty for early retirement differs depending on the period until reaching the standard retirement age as follows: up to 360 days, the penalty is 3.6%/year; between 361 days and 720 days, the penalty will be 4.8%/year, and the period over 721 days will have a penalty of 6%/year The standard retirement age will be 65 years, canceling the increase provided in the previous legislation Retirees with a minimum age of 85 will receive a bonus of 1000 Czech crowns

Source: Author’s synthesis based on OECD reports “Pensions at a Glance” (https://www.oecdilibrary.org/finance-and-investment/oecd-pensions-at-a-glance_19991363)

retirement age for women was set between the ages of 53 and 57, depending on the number of children born (Poteraj, 2008). The abolition of the socialist government system led to the reform of the pension system. The first measures aimed to cancel the privileges of political party activists, reducing discrimination, adjusting the level of benefits, and strengthening the financial sustainability of the public pension system. The reform considered both the parameters and structure of the system. The main parametric reforms carried out for this purpose are summarized in Table 2.3. Regarding the structure of the national pension system, in addition to the PAYG public pension system with DB, the contribution to the voluntary private pension funds was regulated (OECD, 2007a– 2019a). The financing of the social protection system and public pension system is made, based on the social contributions paid to the Social Insurance Budget. Social

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Employee 2017 2015 2013 2011 2009 2007 2005 2003 2001 0.0%

2.0%

Health insurance

4.0%

6.0%

Sickness insurance

8.0% Pension system

10.0%

12.0%

14.0%

Unemployment insurance

Employer 2017 2015 2013 2011 2009 2007 2005 2003 2001 0.0%

5.0%

Health insurance

10.0%

15.0%

Sickness insurance

20.0%

25.0%

Pension system

30.0%

35.0%

40.0%

Unemployment insurance

Fig. 2.1 Evolution of the rates of compulsory social contributions in the Czech Republic in the period 2001–2017. Source: Author’s processing based on OECD reports “Taxing wages” (https:// www.oecd-ilibrary.org/taxation/taxing-wages_20725124) and “Benefits and Wages” (http://www. oecd.org/els/shock/benefits-and-wages-country-specific-information.htm) for the Czech Republic

contributions are borne by both the employee and the employer, the amount being determined by applying a percentage to the gross income. The evolution of the social contribution quotas is summarized in Fig. 2.1. The significant percentage of contributions directed to the pension system can be noted, as well as the increased degree of contribution of the employers. Upon reaching the standard retirement age, under the conditions of fulfilling the minimum contribution period, the taxpayer has the right to receive the old-age

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23

pension. The redistribution of pension by the public pension system of the Czech Republic is conducted using two components for determining the amount, namely: a basic component in a fixed amount and a component correlated with the level of income obtained during the activity period, using progressive replacement rates (OECD, 2015a). The fixed component of the pension had an amount of 1310 crowns in 2002, increasing to 2700 crowns in 2018 and representing 10% of the average value of national wage. As for the variable component, it represents 1.5% of the value of income earned by the taxpayer in each contributory year. The personal calculation basis is determined according to the monthly income threshold, which is established annually. Thus, in 2018, there are three income thresholds: the first threshold is up to 13,191 crowns, the second is between 13,192 and 119,916 crowns, and the third is over 119,916 crowns. The revenues included in the first threshold of income are taken 100% as a basis for calculation, the revenues from the second income threshold are taken in a percentage of 26%, and the revenues included in the third threshold are not considered a basis for calculation (Social Security Administration, 2018). The total amount of the pension starting with 2019 is indexed annually with the increase in the consumer price index of households formed by the pensioners or of all the households (OECD, 2019a). The early retirement pension can be accessed under conditions established by the legislation in force, the amount of pension being established using the same methodology as in the case of the old-age pension, but related penalties are applied. The access of invalidity pension is conditioned by the contribution period existing at the date in which the disability happened, depending on the person’s age. Thus, people up to the age of 20 must have a contribution period of up to 1 year; for persons aged between 20 and 21, the minimum contribution period must be 1 year; persons aged between 22 and 23 must have contributed to the social security system for at least 2 years; for people in the age group 24–25 years the minimum contribution period is 3 years, and people aged 26 and 27 must have a minimum of 4 years of contribution. In the case of persons aged between 28 and 38 years, at the date of occurrence of disability the contributory period must be at least 5 years of the last decade, and in the case of persons in the age group 39–64 years they must have either 5 years of contribution for the last 10 years, or 10 years of contribution from the last 20 years (Social Security Administration, 2018). The number of benefits is determined according to the degree of disability, established in proportion to the reduction of work capacity. In the case of the first degree of disability, the work capacity is diminished by 35–49%, and the benefit contains the fixed component and 0.50% of the personal computation base. The second degree of disability implies a decrease of working capacity between 50 and 69%, the variable component used for calculating the pension being 0.75% of the value of the calculation base. The third degree of disability has a reduction of over 70% of work capacity, and the calculation of the benefit has a variable component of 1.5% of the calculation base of the beneficiary. Once the eligibility criteria for accessing the old-age pension have been met, the beneficiary of the invalidity pension will be recalculated the amount of the benefit and will be transferred to the category of old-age pensioners (Social Security Administration, 2018).

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The survivor’s pension is granted to the surviving spouse or children of the deceased, who was a beneficiary or was entitled to receive the old-age pension, or if the death occurred as a result of an occupational disease or a work accident. The acquirement of the benefits by the orphan is conditioned by the contribution period. Thus, the deceased must meet at least half of the contribution period required for the disability pension, or in the case of persons under the age of 38 the contributory period must be at least 1 year for the last 10 years or 2 years from the last 20 years. The surviving spouse can access the survivor’s pension 4 years before the standard retirement age for men or if he or she suffers from a third-degree disability or is caring for a dependent or disabled child. Granting the survivor’s pension ceases with the remarriage of the surviving spouse, and in case of the children who once reached the age of 26 (Social Security Administration, 2018). The survivor’s pension in the case of children is composed of the fixed component and 40% of the value of the old-age pension or the invalidity pension to which the deceased was entitled. Orphans of both parents are entitled to a survivor’s pension for each parent. In the case of the surviving spouse, the survivor’s pension consists of the fixed base and 50% of the amount of the old-age or invalidity pension to which the deceased was entitled. If the surviving spouse is also the beneficiary of its own old-age pension or invalidity pension, the pension with the highest amount and ½ of the amount of the other pension to which he or she is legally entitled will be provided (Social Security Administration, 2018). An additional form of income in old age is offered by private pension funds. In the Czech Republic, only personal private pension funds are regulated, as pension plans based on individual accounts and investment strategies adapted to the participant’s risk profile. The participation rate of the population to a voluntary pension fund reached 64% of the employed population in 2018. Regarding the investment return, it can be noted that in 2018 the return was positive, although it had a low value (0.4%). The investment structure consists mainly of low-risk financial securities, namely government bonds and bank deposits, which guarantee a fixed income (OECD, 2019b).

2.3.2

Social Protection and the Pension System in Hungary

Hungary’s social protection system consists of five areas, namely: the pension system, medical services, unemployment benefits, family benefits, and social assistance services. The foundation of this social protection system has its origins in the Bismarckian principles applied during the Habsburg Empire. The first legislative source referring to social protection is mentioned in 1890 and considered accidents at work, and in 1891 being recorded as the first legislative reference on the pension system and health insurance (Social Security Administration, 2018). The organization of the pension system was based on the principles of the PAYG typology with DB mechanism, the amount of the benefit being established according to the level of income achieved in the most prosperous 3 years of the last five before

2.3 Pension Systems in Central and Eastern European States

25

accessing the benefits. Initially, the standard retirement age was set at 65 for both sexes, later being reduced to 60 for men and 55 for women. In 1936, the agricultural pension system was regulated, being abolished with the collectivization of 1961, a new unitary pension system starting to operate in 1975 (Poteraj, 2008). The implementation of the democratic system of government has led to several reforms to strengthen the sustainability of the public pension system. Hungary was the first country from the former communist bloc to regulate private pension funds, implementing P3 in 1993 (Allott et al., 2010). In 1997, the decision was taken to implement mandatory privately managed pension funds. These operated based on the forwarding of a percentage, initially of 6% and to be increased to 8%, from the social contributions paid to the public pension system. At the same time, the share of social contributions paid to the public system will be reduced up to 22% by 2000. The conditions required for the authorization and operation of a private pension fund included the existence of a reserve fund of 100 million forints and a minimum number of 2000 participants, who at the time the benefit payments started, had to have at least 25,000 participants. Participation in this pillar was mandatory for all employees up to 42 years and voluntary for others (Allott et al., 2010). At the end of 2010, the number of participants in privately managed pension funds reached 3.1 million people, representing 70% of the workforce. Between 01.11.2010 and 31.12.2011, the distribution to mandatory privately managed pension funds was suspended, and their participants had the option to transfer their assets either to the public pension system or to private funds (OECD, 2013a). In addition to this restructuration, a series of measures regarding the public pension system was taken, being summarized in Table 2.4. The public pension system provides old-age pensions and survivors’ pensions. The social protection system and the pension system of Hungary are financed based on the contribution of insured persons. The amount of social contributions is determined by applying a percentage rate to the gross income earned by the taxpayer. The evolution of the contribution rates is highlighted in Fig. 2.2. In Hungary, the financing of the social protection system is mainly based on the contribution of employers, although in the last 21 years the share of compulsory social contributions paid by employers has decreased by 17.2%. The contribution of employees to the pension system and to the health insurance fund increased during this period by 3%, respectively by 4%. The distribution of the benefits provided by the public pension system is made under the conditions of fulfilling the eligibility criteria specified above. The determination of the old-age pension is made based on the computation of a redistribution rate related to the base of the income for which contributions were paid. In 2002, the coefficient for calculating the pension was 1.65%, the amount being adjusted with ½ of the increase in the consumer price index and with ½ of the value of wages. Starting with 2008, the basis for calculating the pension is the gross value of income, less the social contributions paid by the employee, and starting with 2010, the value of pensions will be indexed to the evolution of GDP. Until 2009, all pensioners benefited from the “thirteenth pension,” a benefit that was canceled starting with 2010. Since 2012, computation of pensions is made in

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Table 2.4 Reform of the Hungarian public pension system Year 2002 2004

2006

2008

2012

Legislative provisions Standard retirement age will gradually increase to 62 for both sexes. The full contribution period is 20 years, and the minimum period is 15 years Early retirement is possible for taxpayers who have a contribution period of 38 years and the age of 60, in the case of men and 57 years, in the case of women. Under the conditions of a contribution period of 33 years, the partial early retirement pension can be accessed. With the increase in the standard retirement age, the age required to access early retirement will increase, which in 2013 will be possible at 60 years old, for both sexes. The penalty for early retirement is 1.2%/year The continuation of professional activity after reaching the standard retirement age is rewarded with 6%/year Prenatal leave, childcare leave, and the period for which unemployment benefits are granted are noncontributory periods assimilated to the contribution period The penalty in case of early retirement is 3.6% for a period of 1 year, to which is added 0.4% for each additional month The standard retirement age will increase to 65 for both sexes by 2022 Early retirement will be possible at most 2 years before reaching the standard retirement age and under a contribution period of 37 years Early retirement is canceled, excepting the population employed in places with dangerous working conditions (e.g., miners, army personnel)

Source: Author’s synthesis based on OECD reports “Pensions at a Glance” (https://www.oecdilibrary.org/finance-and-investment/oecd-pensions-at-a-glance_19991363) 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Sickness insurance

Pension system

Unemployment insurance

Social insurance borne by the employer

Fig. 2.2 Evolution of the rates of compulsory social contributions in Hungary in the period 1999–2018. Source: Author processing based on OECD “Taxing Wages” reports (https://www. oecd-ilibrary.org/taxation/taxing-wages_20725124)

thresholds, depending on the contributory period, according to Fig. 2.3. The basis of calculation is the gross income less social contributions paid by the employee. Since 2014, the calculation basis is the net income. The amount of the pension is adjusted

2.3 Pension Systems in Central and Eastern European States

27 Pension calculation coefficient

Over 40 years 37-40 years 26-36 years 11-25 years 10 years

+2% +1,5% +1% +2% 33%

Contributory period

Fig. 2.3 Thresholds used for computation of the old-age pension in Hungary. Source: Author’s work based on the OECD report “Pensions at a Glance 2013: OECD and G20 Indicators” (https:// read.oecd-ilibrary.org/finance-and-investment/pensions-at-a-glance-2013_pension_glance-2013)

with the evolution of the consumer price index. The minimum pension is 28,500 forints (OECD, 2007a–2019a). The survivor’s pension is granted to the descendants of the deceased, who was a beneficiary or was entitled to be a beneficiary of the old-age pension at the time of death. Beneficiaries of the survivor’s pension may be the following: the surviving spouse, including the divorced one, the partner who has lived with the deceased for the last 10 years or 1 year, if they had a child, children to the age of 16 years or 25 years if they are students, siblings, grandchildren, parents, or grandparents at least 65 years of age or if they are suffering from a disability, adoptive parents if the deceased has been in their care for at least 10 years (Social Security Administration, 2018). The survivor’s pension granted to the surviving spouse is 60% of the deceased person’s old-age pension or 30% of its value, if the surviving spouse is the beneficiary of his or her old-age pension or invalidity pension. In the case of children, an amount equal to 30% of the deceased’s old-age pension shall be distributed for each child, at least 24,500 forints or an amount of 60% of its value if the surviving parent suffers from a disability. In the case of children orphaned by both parents, the survivor’s pension represents 60% of the maximum old-age pension of the parents. The parents or grandparents receiving the survivor’s pension acquire an amount of 60% of the deceased’s old-age pension, respectively 30% if they receive their own old-age pension or invalidity pension (Social Security Administration, 2018). In addition, a temporary pension may be granted to the surviving spouse who has not met the conditions for a permanent survivor’s pension or is caring for the deceased’s child aged 1 year and 6 months or suffering from a disability or chronic illness. The amount of the pension is 60% of the value of the old-age pension of the deceased person. The temporary pension is granted for 1 year, but if the spouse takes care of a child under 1 year and 6 months, the period is extended by another 6 months. Also, if the applicant for a temporary pension takes care of a child suffering from a disability or a chronic illness, the benefit is granted for a period of 3 years. The temporary pension can be converted into a permanent benefit if the surviving spouse reaches the standard retirement age, has a reduced work capacity, cares for a child up to 16 or 25 years old, in the case of student children, or if he or

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she cares for a child with disabilities or chronic diseases (Social Security Administration, 2018). The invalidity pension is granted for the reduction of the working capacity by at least 40% of the insured persons for at least 3 years of the last 5 years or at least 7 years of the last 10 years (Social Security Administration, 2018). Depending on the ability to recover, two types of benefits can be provided, namely: invalidity pension and recovery allowance, both provided through the health insurance system (MISSOC database). The invalidity pension is granted to persons with major illnesses and requires permanent personal assistance, as well as to those whose recovery is possible but not recommended. The value of the pension represents 30%, up to 70% of the average income obtained in the last 6 months before the occurrence of the disability, depending on the degree of disability. The recovery allowance has an amount between 35 and 45% of the average income obtained in the last 6 months before the occurrence of the disability. The minimum pension established for 2018 is 28,500 forints (Social Security Administration, 2018). The participation rate of the population in private pension funds decreased once the P2 was nationalized, in the case of voluntary pension funds, this rate being about 18.7% of the population aged between 15 and 65 years (OECD, 2019b). The level of assets of voluntary pension funds is 5.3% of GDP, and the return in 2018 was negative (–1.7%) (OECD, 2019a).

2.3.3

Social Protection and the Pension System in Poland

The first mentions regarding the existence of some forms of social protection on the territory of Poland are found in 1866, having as beneficiaries soldiers and civil servants, and in 1891 is mentioned the implementation of the German pension system for old age and disability in the annexed territories by the Kingdom of Prussia. In 1927, the first comprehensive regulation on social protection of workers appeared, which included provisions on the old-age pension. After 1990, the increased share of beneficiaries, the large number of benefits, and the shortage of employees led to the need to adopt measures to maintain the financial sustainability of the pension system (Poteraj, 2008). In 1998, the restructuration of the national pension system in a multi-pillar form was decided. Thus, since 1999 in Poland, the pension system consisted of the PAYG public pension scheme with NDC mechanism, mandatory privately managed pension funds, and voluntary pension funds. In 2019, a new occupational pension scheme was regulated with DC mechanism. Employers will have the responsibility and obligation to provide an occupational pension fund to their employees (OECD, 2019a). The financial pressure found in the public pension system has led to a series of regulations on the parameters of the system. The main changes made to the Polish public pension system are summarized in Table 2.5.

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Table 2.5 Regulation of the public pension system in Poland Year 2002

2006 2009

2012 2014 2017 2019

Legislative provisions Standard retirement age is 65 for men and 60 for women The minimum contribution period is 25 years for men and 20 years for women Early retirement is possible for employees in areas with special working conditions Pension income can be cumulated with wages Periods in which unemployment or maternity benefits are collected, for which social contributions are paid, are included in the taxpayer’s contribution period Bridging pensions are regulated for taxpayers in areas with special working conditions and allow their early retirement up to 5 years before the standard retirement age. People who do not meet the conditions to access the bridging pension, but have 15 years of work in special conditions will be compensated when accessing the old-age pension The standard retirement age will increase from 2013 to 67 years for both sexes The minimum contribution period is 25 years for both sexes The standard retirement age is reduced to 60 for women and 65 for men Women who have given birth and raised at least 4 children benefit from the minimum pension, without any other criteria

Source: Author’s synthesis based on OECD reports “Pensions at a Glance” (https://www.oecdilibrary.org/finance-and-investment/oecd-pensions-at-a-glance_19991363)

The financing of the public pension system is based on social contributions, determined by applying proportional quotas on gross income. Both employees and employers are subject to taxation. The evolution of social contribution rates is presented in Fig. 2.4. Poland has a policy regarding financing the public pension system, which divides compulsory social contributions into approximately equal shares between employer and employee. However, the total social contributions borne by the employer have a higher share compared to the total contributions applied to employees. The distribution of the benefits of the public pension system has been carried out since 1999, using the notional accounts procedure. As a result, the social contributions paid will credit the individual notional account of the taxpayer. The notional interest rate is the percentage value of the increase in wage income, but it cannot be below the level of consumer prices. The calculation of the old-age pension involves the ratio between the accumulated notional capital and the life expectancy at retirement age. The amount of the pension is indexed annually with the evolution of the consumer price index (OECD, 2015a). The invalidity pension and the survivor’s pension follow the methodology for calculating the benefits under the legislation used before the old-age pension uses notional accounts (Hirose, 2011). The invalidity pension is granted to the taxpayer who has a total or partial incapacity for work with a full contribution period or with at least 5 years of contributory in the last 10 years. The noncontributory periods assimilated into the contribution period must not exceed one-third of the contributory period. For physical incapacity and total dependence is granted medical assistance. The amount of benefit is determined according to the formula 2.1 (Social Security Administration, 2018):

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Employee 2018 2016 2014 2012 2010 2008 2006 2004 2002 2000 0.0%

2.0%

4.0%

6.0%

Pension system

8.0%

10.0%

12.0%

Sickness insurance

14.0%

16.0%

18.0%

20.0%

Health/maternity insurance

Employer 2018 2016 2014 2012 2010 2008 2006 2004 2002 2000 0.0%

5.0% Pension system

10.0%

15.0%

Sickness insurance

20.0%

25.0%

Other social security

Fig. 2.4 Evolution of the rates of compulsory social contributions in Poland in the period 2000–2018. Source: Author’s processing based on OECD “Taxing wages” reports (https://www. oecd-ilibrary.org/taxation/taxing-wages_20725124)

Pi ¼ 24%  Bc þ 1:3%  pc þ 0:7%  pnc þ 0:7%  V  spc

ð2:1Þ

where: Pi represents the value of the invalidity pension; Bc is the calculation basis, respectively the average level of income considered for the payment of social contributions; pc represents the contribution period; pnc stands for the noncontributory periods assimilated into the contribution period; V represents the insured income, respectively the value of the incomes from 10 consecutive years from the last 20 contributory years or the value of the incomes for 20 years from the

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whole contributory period; spc is the potential contribution period, respectively, the number of years required by the applicant for the invalidity pension to complete the full contribution period until the age of 60. The partial invalidity pension represents 75% of the value of the total invalidity pension. The survivor’s pension is provided if the deceased was a beneficiary of the pension system or was entitled to receive benefits of the scheme, to a surviving spouse aged at least 50 years, without the capacity to work, who is caring for a child aged up to 16 years, respectively 18 years if he is a student or a child with disabilities, the divorced spouse who is entitled to alimony, children of the deceased taxpayer up to the age of 16, respectively 25 years in the case of children attending college and without age limit for children with a disability; dependent parents of the deceased. The amount of the survivor’s pension is determined as a percentage of the amount of the old-age pension or invalidity pension, depending on the number of beneficiaries, as follows: for one beneficiary the percentage of distributions is 85%, for two beneficiaries the percentage is 90%, and for three or more survivors the percentage is 95% (Social Security Administration, 2018). Income from the distribution of the invalidity pension or survivor’s pension is indexed annually with the increase in the consumer price index and by at least 20% of the average salary income per economy (Social Security Administration, 2018). In Poland, the minimum pension is regulated, its value in March 2018 being 1,029.80 zlotys (Social Security Administration, 2018). P2 operated based on the distribution of a percentage of 7.3% of gross income, participation being mandatory for all employees up to the age of 30 years. The low yield and decrease of the revenues of the public pension system due to the allocation of a part of the social contributions to P2 determined the reconsideration of this pension scheme. In 2014, it was decided to nationalize the funds, the participants having the opportunity to participate in voluntary pension funds (OECD, 2019b). P3 includes personal pension funds, investment funds, and collective life insurances (Poteraj, 2008). The degree of participation in a voluntary pension scheme increased reaching 66% of the population aged between 15 and 65, and in the case of occupational pension funds, the percentage is 1.8%. The assets of P3 represent 8.5% of GDP, but the return in 2018 was negative (11.1%) (OECD, 2019b). The occupational pension funds will be implemented starting with July 2019 by large companies, and later by medium and small companies, involving approximately 11.5 million employees. The financing comes from the contributions paid by both employees and employers, the minimum quotas being set at 2% of the gross income in the case of employees, respectively 1.5% in the case of employers (OECD, 2019b).

2.3.4

Social Protection and the Pension System in Slovakia

Social security regulations in Slovakia date from 1887 to 1888 and aimed the protection against work accidents, health insurance, and old-age pension. In 1945,

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family allowances were introduced, and in 1965 were regulated maternity allowances (Poteraj, 2008). According to MISSOC, the social protection system provides seven types of benefits, namely: old-age, invalidity and survivors’ pensions, benefits for accidents at work and occupational diseases, sickness and maternity benefits, unemployment benefits, social assistance services, family allowances, and medical services (MISSOC database). The transition to a market economy was a crucial moment in redefining social protection. After 1989, the pension system was reorganized into a multi-pillar structure consisting of three components: the public pension system, mandatory privately managed pension funds, and voluntary pension funds. The mandatory privately managed pension funds have been operational since 2005. Their financing involved the allocation of a percentage of the social contributions paid to the public pension system by the employer. Participation is compulsory for all persons employed from January 2005 and optional for persons previously employed (OECD, 2007a). Each participant must choose the structure of the investment portfolio. Depending on the composition of the financial titles found in the portfolio, there are three types of funds: low-risk conservative pension funds, consisting mainly of financial securities and monetary instruments; slightly higher risk-balanced pension funds consisting of up to 50% of shares or other derivatives; and high-risk expansive pension funds with up to 80% of the portfolio structure consisting of shares or other derivative instruments. One year after the implementation of P2 number of participants was 1.1 million (Poteraj, 2008). Both P1 and P2 have as a source of funding the social contributions paid by employees and employers. In Fig. 2.5 is highlighted the evolution of quotas of the mandatory social contributions in the period 2001–2018. The contribution rate of the employer is higher, and the largest share being directed to the pension system and health insurances. Employers’ contribution to the public pension system has decreased with the implementation of P2. Starting with 2012, the policy regarding the social contributions allocated to P2 changed and only 4% of them were distributed to private funds. This measure was applied until 2017, when it was decided to increase the share of contributions paid to P2 by 0.25%/year, decreasing with the same share the contributions paid to P1, so that by 2024 the share of contributions of P2 will reach 6%. In addition to the structural reform and changes in the rates of social contributions, the public pension system has undergone several parametric regulations, summarized in Table 2.6. Once the eligibility criteria are met, the taxpayer is entitled to receive benefits from the pension system. The amount of the old-age pension is determined using a formula based on pension points, which reflects the amount of income earned during the contributory period and expresses the ratio between individual income and average income per economy. If the score obtained is less than 1, an increase coefficient between 16 and 22% will be applied, and if the score exceeds 1.25, a coefficient of between 60 and 84% will be applied for the reduction of the score. These operations are the “element of solidarity.”

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Employee 16% 14% 12% 10% 8% 6% 4% 2% 0% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Health insurance

Sickness insurance

Pension system

Disability insurance

Unemployment

Employer 40% 35% 30% 25% 20% 15% 10% 5% 0% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Health insurance Sickness insurance Pension system Unemployment Other social contribuons

Social insurance

Second Pillar

Fig. 2.5 Evolution of the rates of compulsory social contributions for normal working conditions in Slovakia between 2000 and 2018. Source: Author’s processing based on OECD “Taxing wages” reports (https://www.oecd-ilibrary.org/taxation/taxing-wages_20725124) (For the years 2001, 2002, and 2003, the OECD reports show the total share of social contributions paid by the employer, not specifying the percentage targeted at the pension system.)

The formula for calculating the amount of pension is the following (OECD, 2015a): P ¼ Pctmed  Sc  V pct

ð2:2Þ

where: P represents the amount of the pension; Pctmed is the average score achieved in the contributory period; Sc represents the contribution period; Vpct is the value of a pension point. The value of the pension point is indexed annually with the increase in the average income, and the value of the pension with the increase in the consumer price index in the case of pensioners (OECD, 2015a).

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Table 2.6 Regulation of the public pension system in Slovakia Year 2002

2004

2006 2008

2017 2019

Legislative changes regarding the parameters of the public pension system The determination of the number of benefits is made based on a system of pension points The standard retirement age is increased to 62 for both sexes by 2014 The minimum contribution period is 10 years Early retirement is possible at any age, if the minimum contribution period is reached. The penalty applied is 6%/year Continuation of professional activity after fulfilling the eligibility criteria for accessing the pension benefits is rewarded with a bonus of 6%/year. The number of points achieved until retirement is considered for the recalculation of benefits in a percentage of ½ Noncontributory periods for raising children are assimilated into the contribution period The minimum contribution period is increased to 15 years Early retirement can be required with a maximum of 2 years before reaching the standard retirement age, and the penalty applied being 6.5%/year The bonus granted for continuing the professional activity after fulfilling the necessary criteria for accessing the benefits is 6.5%/year Starting with 2017, the standard retirement age is indexed with the increase in life expectancy at retirement age The standard retirement age is increased to 64 years, without further increases

Source: Author’s synthesis based on OECD reports “Pensions at a Glance” (https://www.oecdilibrary.org/finance-and-investment/oecd-pensions-at-a-glance_19991363)

The early retirement pension is determined by reducing the value of the old-age pension with the penalty established by law. The invalidity pension is granted for the reduction of working capacity by at least 70% under the conditions of the existence of a minimum contribution period depending on the age at which the disability occurs. Thus, the taxpayer aged between 21 and 24 years requires at least 1 year of contributions, and the one in the age group 25–28 years must have a contribution period of 2 years. People between the ages of 29 and 34 need five years of contributions to be eligible for a disability pension, those in the 35–40 age group need at least 8 years of contributions, and those aged between 41 and 45 years need a 10-year contribution period, while people over 56 will need a minimum contributory period of 15 years. A partial invalidity pension is also granted for a reduction in working capacity of between 40 and 70%. The pension amount is determined by the same formula used for the computation of old-age pension. The survivor’s pension is provided in the conditions in which the deceased was a beneficiary or has the right to receive benefits from the public pension system. The beneficiaries of the survivor’s pension can be: the surviving spouse, children up to 16 years old, respectively 26 years old if they attend a college. The surviving spouse benefits from 60% of the value of the deceased taxpayer’s pension and is granted for 1 year. If the surviving spouse suffers from a disability that reduces his or her work capacity by 70% or if he or she is caring for a dependent child or has raised at least three, or two children and has reached the age of 52 or has reached the standard age retirement, survivor’s pension is granted for life. In the case of children, the

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35

survivor’s pension is 40% of the value of the deceased taxpayer’s pension (Social Security Administration, 2018). Regarding the accession of the benefits of privately managed pension funds, the taxpayer may open the pension account once the eligibility conditions for receiving the old-age pension have been met. The pension consists of the asset held in the account, and its monetization can be achieved either by granting a lifetime annuity, by a single payment, or by scheduled withdrawals. If the participant in the pension fund dies before opening the account, the account asset is inherited by the legal successors.

2.3.5

Social Protection and the Pension System in Romania

From a historical point of view, in Romania, the first forms of social protection date back to the 1800s, having the form of the “mercy box” and the “fraternal box” (Hudea, 2017). Through them, the craftspersons gave each other support in case of financial difficulties. Due to the socioeconomic evolution during the industrial revolution, this form of social protection developed in self-help associations for industrial workers. The first reform regarding the social protection system in Wallachia and Moldova was carried out at the beginning of the twentieth century, by adopting the Law for the organization of crafts, credit and workers’ insurances. It establishes the obligation to contribute to the maternity, accidents, sickness and disability, old age and death insurance fund of all employees and employers, as well as the state. Under a minimum contribution period of 23 years and a minimum age of 65, taxpayers were entitled to receive a financial allowance to ensure decent living in old age.14 In the Romanian regions being under the rule of the Austro-Hungarian Empire, the social protection system was organized in a similar way, according to the principles of Otto von Bismarck. The territorial and political redefinition achieved through the Union of Romanian Principalities in 1918 was a key moment for the organization of the national social protection system. Thus, in 1933 it was realized the unification of the social insurance systems of all Romanian provinces (Law no. 55/1933). The system was based on the principle of contributivity and the principle of solidarity between generations. Employees and employers contribute 3% of the amount of gross salary to the social insurance system, the role of the state being to guarantee and subsidize the system, in case of a financial deficit. The territorial pension houses had the

14

According to Art. 169 of the Law on the organization of crafts, credit and workers’ insurances (Neniţescu Law), “all insured persons who will prove that they have reached the age of 65 are entitled to the old-age pension,” and according to Art. 175 “cannot obtain the old-age pension, if he or she has not contributed in total for at least 1200 weeks.”

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2 Overview of Pension Systems

function of collecting income from social contributions and distributing benefits, as pensions and other financial aids. The change in the government system of Romania in 1947 also determined the reorganization of the social protection system. Based on the PAYG principles, the public pension system was financed by contributions of socialist units and by the state (Law 27/1966). The new regulations provided some advantages to certain categories of taxpayers, namely: employees whose activity was carried out in harmful working conditions, with a predisposition to physical or mental overload, accidents or illnesses; women with at least three children; aeronautical workers and artists affiliated to cultural institutions. They benefited from favorable eligibility criteria in accessing the benefits of the social protection system, by granting seniority bonuses or by reducing the standard retirement age.15 The categories of benefits provided by the public pension system included the old-age pension, the invalidity pension, and the survivor’s pension. The eligibility criteria for accessing them were represented by the contribution period and the standard retirement age. The minimum contribution period was 10 years, and the full contribution period was differentiated according to gender: 20 years for women and 25 years for men. The standard retirement age was 57 for women and 62 for men. For calculating the number of benefits granted by the pension system, percentage quotas were established according to the income thresholds obtained during the activity period, with values between 60 and 95%. These percentages were applied to the level of income for which social contributions were paid in a period of 5 consecutive years in the last 10 years of professional activity.16 Starting with 1967, an additional contribution of 2% of the gross salary paid by employees was established for the creation of an additional pension fund aiming to ensure adequate incomes for pensioners and to maintain the standard of living at a level comparable to that of the period of professional activity. This fund was initially deposited at National Bank, and later at the Savings and Consignment House, so that it was interest-bearing. The distribution of the supplementary pension was also made by applying a percentage on the value of the gross salary used in the calculation of the pension, varying between 5 and 16%, depending on the period for which the contributions were paid.17 In 1977, new regulations were adopted regarding the pension system, through which social protection was extended on the members of agricultural production cooperatives, as well as on farmers with their own households (Law no. 3/1977). The full contribution period is increased to 25 years for women and 30 years for men and is introduced the possibility of early retirement in case of completing the full contribution period, at the age of 55 for women and 60 years for men.18

15

According to Art. 7, 8, 9, 10, 11, 12 of Law 27/1966. According to Art. 13 and Art. 14 of Law no. 27/1966. 17 According to the provisions of Law no. 27/1966, Title II: Supplementary pension. 18 According to Art. 8 of Law no. 3/1977. 16

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The demographic situation at that time was characterized by high fertility rates, a low share of the elderly in the total population, and low unemployment rates. As a result, there is a high contribution rate to the social protection system and substantial budget revenues, given the relatively small number of beneficiaries. All these conditions have ensured the success of this form of organizing the public pension system. The transition to a market economy has brought new regulations regarding the organization and functioning of the social protection system in Romania. The main legislative changes applied to the pension system aimed at the redefinition of working groups and the rights related to each group, granting new benefits, increasing contribution quotas and establishing penalties for unfulfillment of social obligations, regulation of early retirement, implementation of a new social protection system for farmers, the integration in the state social insurance system the social insurance of writers, composers, musicologists, filmmakers and members of the Union of Visual Artists, as well as the social insurance of religious cults and craft cooperation. Also, to diminish the inflationary effects, increases, compensations, and indexations of the benefits provided by the public pension system were operated. Regarding the structure of the national pension system, the multi-pillar structure proposed by the WB was implemented, the organization and functioning of private pension funds and their administrators being regulated. In 2000, Law no. 19/2000 was adopted, which established the National House of Pensions and other Social Insurance Rights with its county structures having the role of coordinator of the public social insurance system. The operating principles of the pension system and other social insurance were contributivity, solidarity, equality, obligation, uniqueness, autonomy, and redistribution.19 The amount of contributions was determined in proportion to the level of income obtained. The contribution rates were established annually by the Law on the State Social Insurance Budget. The law established a reserve fund from the income obtained from contributions, in order to finance the expenses of the pension system if necessary.20 Law no. 19/2000 established an increase of the full contribution period to 30 years for women, respectively 35 years for men, and the minimum contribution period to 15 years. The standard retirement age has also been raised to 60 years for women and 65 years for men. The law also modified the method of determination of the number of benefits, using a system based on the accumulated score during the period of professional activity. For each month in which contributions were paid to State Social Insurance Budget, a monthly score is determined, calculated as the ratio between the income considered base for calculating the contribution and value of the average gross monthly salary at the national level. The average of the monthly scores was the annual score, and for the calculation of the score from the activity period, the sum of the annual scores was divided into the full contribution period. By

19

Art. 2 of Law no. 19/2000. Art. 13, Para. (2) of Law 19/2000 provides for the withdrawal of an amount of “up to 3% for the establishment of a reserve fund.”

20

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multiplying this score by the value of a pension point, the amount of pension was established.21 In the case of taxpayers contributing to the supplementary pension fund, the contribution period was also considered in determining the score. Due to this new pension calculation procedure, all pensions have been recalculated and updated.22 In 2004, the second pillar of the national pension system was legislated, by adopting Law no. 411/2004 regarding the mandatory privately managed pension funds. The law established the redirection of a part of social contributions paid to the public social insurance system to the money market and the capital market. The contribution rate was 2% of the income considered as the basis for calculation, and will gradually increase to 6%.23 At the time of law enforcement, participation was mandatory for taxpayers up to the age of 35 and voluntary for those up to the age of 45.24 As these funds were managed by private investment companies, each participant in P2 had a nominal account showing all the contributions paid and their value in fund units. The fund units reflected the value of the assets in the monetary and financial assets portfolio, and at the date of retirement the beneficiary was entitled to receive a private pension. Furthermore, in 2004, Law no. 249 was adopted regarding occupational pensions, which establishes the right of employers and/or unions or employees’ representatives to set up occupational pension funds, based on the principle of contributivity and invested in the money and capital market. Employee participation was optional. The minimum contribution period was 5 years, and once the eligibility conditions for accessing the public pension were met, the participants could also benefit from the occupational pension.25 Subsequently, the law was repealed by Law no. 204/2006 on voluntary pensions regulating the third pillar of the pension system. At the end of 2010, the Parliament issued Law no. 263/2010 regarding the unitary public pension system, a normative act that incorporates in the public pension system the social insurances of the personnel in the field of national defense, public order, and national security, of the diplomatic and consular personnel, and also of the farmers. More restrictive eligibility conditions for access to disability and early retirement pensions have been regulated, and the standard retirement age for women has been increased to 63 years. In Table 2.7 are synthesized the main eligibility conditions for accessing the benefits provided by the public pension system in Romania, according to Law no. 263/2010. 21

The methodology for calculating pensions is established in Chapter IV, Section 6 of Law 19/2000. According to Art. 81 of Law 19/2000. 23 According to Art.43 of Law no. 411/2004. 24 Art. 30 of Law no. 411/2004. 25 Art. 70 (2) of Law no. 249/2004 stipulates that “the right to an occupational pension is opened, at the participant’s request, with the fulfillment of the following cumulative conditions: a) the retirement age provided in Law no. 19/2000 on the public pension system and other social insurance rights, with subsequent amendments and completions; b) if at least 60 monthly contributions have been paid; c) the personal asset is at least equal to the amount necessary to obtain the minimum occupational pension provided by the rules of the Commission.” 22

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Table 2.7 Eligibility criteria for accessing the benefits of the public pension system, according to Law no. 263/2010, with subsequent modifications and updates Pension category Old-age pension Early retirement Partial early retirement Disability pension

Survivors pension

Eligibility criteria Standard retirement age Minimum contribution period Up to 5 years before reaching the standard retirement age At least 8 years over the full contribution period Up to 5 years before reaching the standard retirement age To have completed the full contribution period or at most 8 years above the full contribution period Medical expertise of work capacity attesting the reduction of work capacity by at least ½ of the normal value, following the professional activity or work accidents The existence of a minimum contribution period established by the legislation in force in case of accidents and pathologies occurred for reasons other than occupational Participation at regular medical examinations The deceased supporter was a pensioner or future beneficiary of the pension system In case of children: up to 16 years or under the conditions of continuing their studies throughout this period, maximum until the age of 26 or during the entire period of disability In case of the surviving spouse: after the standard retirement age, throughout the life if the marriage lasted at least 15 years, and for at least 10 years of marriage, with a reduction of 0.5%/month until reaching the duration of 15 years, or throughout life if the marriage has lasted at least one year and he or she is in the first or second degree of invalidity

Source: Law no. 263/2010, with subsequent modifications and updates

Through all the changes in legislation, has been pursued to maintain the financial sustainability of public pension system and to provide adequate benefits to pensioners, by reducing the risk of poverty and ensuring a decent living for elderly. However, there were inequities between the categories of beneficiaries, but also between genders. This determined in 2018 the proposal of a new law regarding public pension system by which the inequities found shall be decreased, a normative act that was adopted in 2019 and will enter into force in September 2021.26 Law no. 127/2019 regarding the public pension system has a new principle of operation, namely the principle of availability. According to this principle, in case of the unfulfillment of the minimum contribution period, the beneficiaries can choose to renounce the pension and access the social allowance provided by the legislation in force in the field of social assistance.

Law no. 127/2019 in Art. 182, Para. (1) “This law enters into force on September 1, 2021, except for: a) art. 86 para. (2) lit. a), which enters into force on September 1, 2019; b) art. 86 para. (2) lit. b), which enters into force on 01.09.2020; c) art. 139, art. 145, art. 148 para. (2), art. 157 para. (2) and (5) and art. 183 para. (1), which enters into force 3 days from the date of publication of this law in the Official Gazette of Romania, Part I.” 26

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The new law redefines the categories of benefits and includes new eligibility criteria for accessing the benefits of the public pension system. The minimum contribution period, the full contribution period, and the standard retirement age remain unchanged but are set some noncontributory periods that will be assimilated as contribution periods.27 The criteria for accessing the benefits of the public pension system in Romania are summarized in Table 2.8. Law no. 127/2019 regulates the social insurance contract, concluded between a person and the National House of Public Pensions (CNPP), having as object the supplementation of the contribution period. This contract has a maximum period of 5 years28 and can only be concluded if there is a contribution period of at least 10 years. The insured monthly income will be the basis for calculating the benefits, the amount being at least equal to the average gross wage earnings. Respect for the right to social protection is achieved in a Community and international context, the new pension law regulating the accession of benefits in case of nonresidents. The provision of benefits by the public pension system is conditioned by the semestrial transmission by the nonresident person of a life certificate, authenticated by legal authority of the state of residence.29 The fulfillment of the eligibility criteria for accessing the benefits of the public pension system must be notified to CNPP within 30 days, in the case of residents and in 12 months in case of nonresidents, through a retirement application and the documents certifying the fulfillment of the eligibility criteria.30 Within 10 days from the date of submission of the documentation, CNPP will issue and communicate the decision to the applicant, who can benefit from a single type of pension. The issued decisions can be contested at the competent court, within 45 days from the communication. Law no. 127/2019 stipulates the obligation of the beneficiaries to present all the documents necessary to establish the rights to the provisions of the pension system, as well as the obligation to notify any change that influences the criteria for obtaining benefits or their amount, within 15 days from the occurrence. Companies that have the right to certify the data necessary to establish/modify the social rights of a beneficiary must provide the requested documents within 30 days of receiving the request. Failure of the beneficiary and company to provide the 27

According to Art. 14 of Law no. 127/2019, under the conditions of fulfilling the minimum contribution period, the periods in which the insured attended and graduated the courses of a higher education institution (bachelor, master, PhD), completed the military service, was on leave for temporary incapacity for work or for raising a child, was the beneficiary of the unemployment benefit or disability pension, as well as the periods provided in Decree-Law no. 118/1990 will be included in the contribution period. 28 Art. 6, para. (3) of Law no. 127/2019 stipulates that the social insurance contract is concluded for “maximum 5 years prior to the month of concluding the contract, in which the person has not completed a contribution period in the public pension system”. 29 According to art. 102 of Law no. 127/2019. 30 In Art. 95, Para. (3), Law no. 127/2019 stipulates that in the situation where “the application is registered in excess of the term provided in art. 94 para. (3) [respectively 30 days from the date of fulfillment of the conditions] the rights are granted starting with the date of registration of the application.”

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Table 2.8 Benefits of the pension system according to Law no. 127/2019 Type of benefit Pensions

Old-age pension

Early retirement

Disability pension

Survivors pension

Legislative changes The full contribution period includes the assimilated periods and is 35 years The standard retirement age is reduced for people who: – Have realized contribution periods in jobs with particular/special working conditions – Have realized contribution periods in disability conditions – Women who have given birth/adopted at least 3 children and raised them up to the age of 16, respectively 13 years in the case of adopted children and meet the minimum contribution period – The inhabitants of the administrative-territorial units who have lived and/or worked for at least 30 years in industrial areas with residual pollution or across 8 km around them – Fulfilling the minimum contribution period, including the assimilated periods – Maximum 5 years before reaching the standard retirement age Upon reaching the standard retirement age, the penalties will be removed and the amount of the pension will be recalculated Are eligible persons who: – Do not meet the conditions for accessing the old-age pension – Have diminished work capacity due to work accidents, occupational diseases, other illnesses and accidents or due to participation in the 1989 Revolution The specialist doctor of the National Institute of Medical Expertise and Work Capacity Recovery (INEMRC) will issue within 45 days the medical decision regarding the work capacity Persons classified in the first degree of disability benefit from an attendant allowance, financed by the State Budget, in the amount of 50% of the minimum gross salary of the month for which the payment is made Upon reaching the standard retirement age, it will be recalculated the amount of pension by including the assimilated periods The surviving spouse will also receive a survivor’s pension in the following situations: – The death of the supporting spouse occurred because of a work accident or occupational diseases, regardless of age and duration of marriage – Cares for children under 7 years of age – Does not earn income or their amount is less than (continued)

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2 Overview of Pension Systems

Table 2.8 (continued) Type of benefit

Legislative changes

Minimum pension

Other social security benefits

Monthly allowance for the surviving spouse

Spa treatment

Death aid

the average gross earnings, for a period of 6 months from the date of death of the supporting spouse Is financed by the State Budget and is granted to beneficiaries domiciled in Romania, depending on the contribution period: – 10-year contribution period—40% of the minimum gross salary of the country – For each contribution year, 1% is added, up to a maximum percentage of 75% of the minimum gross salary of the country The minimum pension for beneficiaries of the survivor’s pension is 35% of the minimum gross national wage guaranteed in payment for each survivor Is granted under the conditions in which the surviving spouse, beneficiary of an old-age pension: – Completed the contribution period – Meets the standard retirement age – He or she did not remarry – The marriage lasted at least 10 years Monthly allowance ¼ 25 %  the amount of the deceased supporter’s pension, maximum 80% of the minimum gross salary of the country. The monthly allowance for the surviving spouse is financed from the State Budget The spouse of the insured/pensioner, who does not benefit from benefits of the public pension system, can benefit from spa treatment tickets with full payment of their value Is granted within 3 days of the request and in cases where the deceased: – Has been insured in public pension system for at least 3 months – Had the employment relationship interrupted by leave – He or she was not insured/beneficiary of the public pension system, but the request for aid comes from a family member who at the date of death is insured/ pensioner of the public pension system The amount of death benefit may not be less than the average gross wage

Source: Law no. 127/2019 on the public pension system

requested documents is a contravention and is sanctioned according to the legislation in force. The calculation of the number of benefits is performed using a system of pension points, the calculation algorithm being presented in Table 2.9. The distribution of

2.3 Pension Systems in Central and Eastern European States

43

Table 2.9 Algorithm used to calculate pensions Pension amount ¼ Total number of points  value of one reference point

ðinsured monthly incomeÞ 1:Monthly score ¼ earnings average gross earnings The monthly score is reduced if the insured is a taxpayer of a privately managed pension fund with the value of the ratio: social contribution rate due to the

public pension system  contribution rate to the privitally administered pension fund social contribution rate due to the

Assimilated periods

Potential internship granted to beneficiaries of invalidity pensions

public pension system 2. Annual score ¼ ∑ Monthly score achieved in 1 year 3. Total number of points ¼ ∑ Annual score + number of points corresponding to the potential stage + number of points corresponding to the assimilated periods point 4: Value of the reference point ¼ value of pension 25 Value of the pension point¼ 75 RON (on 09.07.2019) ¼ 1265 RON (on 01.09.2019) ¼ 1775 RON (on 01.09.2020) ¼ 1875 RON (on 01.09.2021) The value of the reference point will be indexed annually starting with 2022 with an average annual inflation rate and 50% of the real increase of the average gross earnings, according to the publications of the National Institute of Statistics (INS) – In the case of invalidity pension ¼ the gross amount – Periods of higher education ¼ 0.25 points – Period of military service ¼ 0.25 points – Periods in which unemployment benefits were received and the periods of leave for temporary incapacity for work ¼ the amount of the allowance – The period of parental leave ¼ 0.25 points – For the first degree of disability ¼ 0.50 points – For the second degree of disability ¼ 0.35 points – For the third degree of disability ¼ 0.15 points

Source: Law no. 127/2019 regarding the public pension system

pensions is made either at home or in the bank account of the beneficiary, in which case the transfer of the pension will be notified at their home. If, for 3 consecutive months, the beneficiary cannot be contacted to receive the pension or notification, payments will be suspended from the following month. The application of Law no. 127/2019 will determine the recalculation of all pensions in payment, by including assimilated periods, and in case of differences

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2 Overview of Pension Systems

in the amount, it will be distributed to the most advantageous amount for the pensioner or the minimum pension. Authors believe that these legislative changes will have a positive impact on the beneficiaries of the Romanian public pension system, especially due to the high level of income inequalities (Balteș & Jimon, 2019). The activity of CNPP is organized by the Board of Directors of CNPP, consisting of 19 members. At the level of territorial structures, the law establishes the number of personnel necessary to ensure the functioning of the CNPP.31 A new change regarding the structure of the national pension system in Romania was adopted in 2020. Law no. 1/2020 considers the regulation of the organization of occupational pension funds and the activity of the administrators of these funds. Occupational pension funds will operate based on the contribution of employees and/or employers, depending on the provisions of the pension fund prospectus. The pension distribution is made once the standard retirement age is reached, in accordance with the legislation on the payment of private pensions (Law no. 1/2020).

2.4

Conclusions and Personal Contributions

The contemporary configuration of social protection and pension systems can be seen as a bridge between the past and the future, which continues to adapt to the sociocultural values of the population, in the context of multiculturalism. In this chapter, we aimed to present the principles that constitute the basis of the formation of national pension systems, the evolution of the structural organization, highlighting the benefits offered and the conditions for accessing them in five CEE countries, including Romania. The foundation of the formation of social protection and pension systems is the right of the population to social protection, in the context of income inequality, which will lead to poverty. Regardless of the form of organization, structure, and the proportion of each pillar, pension systems have the role of reducing the risk of poverty of the elderly by financial redistributions made by the state and ensuring a decent and dignified life in old age. The Czech Republic, Hungary, Poland, Slovakia, and Romania have “experienced” centralized governments, but in recent decades have implemented numerous regulations on reforming the national pension system. The reforms have emerged on a similar socioeconomic background in all five countries, characterized by an increase in the number of beneficiaries of the pension scheme and the period for which benefits are granted, given the existence of categories of taxpayers who benefit from “privileged” eligibility criteria.

Art. 126, Para. (3) of Law no. 127/2019 stipulates that the number of CNPP employees “cannot be less than the number corresponding to the ratio of one employee to 2,000 insured persons and beneficiaries of social insurance benefits.”

31

2.5 Summary

45

The most significant change to the pension systems in CEE countries was the adoption of the multi-pillar structure proposed by WB. However, in practice it is noted that the decision to outsource budgetary pressure from the public pension system by implementing privately managed pension funds is not a solution for all countries, in the Czech Republic this pillar has not been implemented and Hungary and Poland have decided to nationalize P2. In addition to this structural change, several parametric regulations have been adopted in order to maintain the sustainability of public pension systems and provide adequate benefits. However, the contributory pension schemes implemented in CEE suppose the existence of eligibility criteria, which require reaching the minimum contribution period and the standard retirement age and thus limit the accessibility of financial benefits to all citizens. The situation is similar in the case of privately managed pension funds, but there is also the investment risk. From a legislative point of view, the legal framework of the right to social protection is adapted to the right to free movement. The EU Member States have national pension systems that ensure the protection of the elderly, but European regulations on the coordination of pension systems and the transfer of benefits are applied unanimously. The coordination of social protection systems, cooperation and the exchange of information at the international level increase their usefulness and role in ensuring the social protection of people in the process of migration in the context in which globalization and market liberalization facilitate migration. This chapter provides a historical perspective on the development of social protection systems and the evolution of pension systems in CEE, presents the benefits and eligibility criteria, as well the community legislation and the national pension systems. The conclusion that can be drawn from this chapter emphasis that there is no universally valid formula for strengthening the sustainability of national pension systems, the efficiency and effectiveness of a national pension system being given by its adequacy to the existing conditions within that country. The reform of the social protection system must be carried out from a multidisciplinary perspective, having an integrated approach, and correlated with fiscal regulations, labor market, education system, capital market, etc., promoting sustainable economic growth of the entire national economy.

2.5

Summary

This chapter provided a sociohistorical perspective on the framework in which contemporary pension systems in CEE countries have emerged and developed. The first part of the chapter identifies the main typologies of social protection systems and the principles that govern them. The second part envisages the delimitation of the legislative framework governing social security and the protection of the elderly at the national, Community, and international levels, as well as legislative harmonization. The last part of the chapter highlights the organization and

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2 Overview of Pension Systems

functioning of contemporary pension systems in CEE countries, focusing on Romania in particular. The Czech Republic, Hungary, Poland, Slovakia, and Romania have “experienced” centralized leadership and descending structures of paternalistic socialist systems, but in recent decades have adopted numerous regulations on the reform of national social protection systems and public pension systems. Reforms have emerged on a similar socioeconomic background in all five CEE countries, characterized by declining populations, declining employment rates, increasing the number of beneficiaries of the pension system, increasing life expectancy, and at the same time the benefit period, as well as the lack of fairness and equality in accessing benefits.

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e x p i r e s ¼1 5 8 1 6 3 2 9 6 5 & i d ¼i d & a c c n a m e ¼g u e s t & checksum¼3D08AD05CC50394B86DE30EBF9A0403E OECD. (2015b). Taxing wages 2015. OECD. Available online at: https://www.oecd-ilibrary.org/ taxation/taxing-wages-2015_tax_wages-2015-en OECD. (2016). Taxing wages 2016. OECD. Available online at: https://www.oecd-ilibrary.org/ taxation/taxing-wages-2016_tax_wages-2016-en OECD. (2017a). Pensions at a glance 2017: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/social-issues-migration-health/pensions-at-a-glance-2017_ pension_glance-2017-en OECD. (2017b). Taxing wages 2017. OECD. Available online at: https://www.oecd-ilibrary.org/ taxation/taxing-wages-2017_tax_wages-2017-en OECD. (2018). Taxing wages 2018. OECD. Available online at: https://www.oecd-ilibrary.org/ taxation/taxing-wages-2018_tax_wages-2018-en OECD. (2019a). Pensions at a glance 2019: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/docserver/b6d3dcfc-en.pdf?expires¼1581632950&id¼id& accname¼guest&checksum¼3254AED642ED3C02D7A89DCE43F26559 OECD. (2019b). Pension markets in focus. OECD. Available online at: https://www.oecd.org/ finance/private-pensions/pensionmarketsinfocus.htm OECD. (2019c). Taxing wages 2019. OECD. Available online at: https://www.oecd-ilibrary.org/ taxation/taxing-wages-2019_tax_wages-2019-en Orosz, A. (2019). The emergence of East Central Europe in a welfare regime typology. Border Crossing, 9(2), 97–112. Perotti, E., & Schwienbacher, A. (2009). The political origin of pension funding. Journal of Finance Intermediation, 18, 384–404. Poteraj, J. (2008). Pension systems in 27 EU countries. MPRA Paper No. 31053. The Association of Polish Scientists of Lithuania, Vilnius. Available online at: https://mpra.ub.uni-muenchen.de/ 31053/. Poteraj, J., Meijdam, L., Ponds, E., & Westerhout, E. (2017). Aging-driven pension reform. Journal of Population Economics, 30, 953–976. Regulation (EC) no. 883/2004 of the European Parliament and of the Council of 29 April 2004 on the coordination of social security systems. Official Journal of the European Communities L 166, 30.04.2004. Available online at: https://eur-lex.europa.eu/legal-content/RO/TXT/HTML/? uri¼CELEX:02004R0883-20140101&from¼RO. Regulation (EC) no. 987/2009 of the European Parliament and of the Council of 16 September 2009 laying down the procedure for implementing Regulation (EC) No. 883/2004 on the coordination of social security systems. Official Journal of the European Communities L 284, 30.10.2009. Available online at: https://eur-lex.europa.eu/legal-content/RO/TXT/PDF/? uri¼CELEX:32009R0987&from¼PL. Sabates-Wheeler, R., & Devereux, S. (2008). Transformative social protection: The currency of social justice. In A. Barrientos & D. Hulme (Eds.), Social protection for the poor and poorest. Risk, needs and rights. Palgrave Macmillan. Salinas-Rodriguez, A., Torres-Pereda, M. D. P., Manrique-Espinoza, B., Moreno-Tamayo, K., & Tellez-Rojo Solis, M. M. (2014). Impact of the non-contributory social pension program 70 y mas on older adults’ mental well-being. PLoS One, 9(11), 1–11. Sapir, A. (2006). Globalisation and the reform of European social models. Journal of Common Market Studies, 44(2), 369–390. Schultz, T. W. (1961). Investment in human capital. American Economic Review, 51, 1–17. Schwarz, A. (2006a). Pension system reforms. In A. Coudouel & S. Paternostro (Eds.), Analyzing the distributional impact of reforms, a practitioner’s guide to pension, health, labor markets, public sector downsizing, taxation, decentralization, and macroeconomic modeling (Vol. 2). The International Bank for Reconstruction and Development/The World Bank. Schwarz, A. (2006b). Pension system reforms (SP Discussion Paper, no. 0608). Social Protection & Labor, World Bank.

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Sender, S. (2012). Shifting towards hybrid pension systems: A european perspective. EDHEC-Risk Institute. Smith, A., & Cannan, E. (2003). The wealth of nations. Bantam Classic. Social Security Administration. (2018). Social security programs throughout the world: Europe 2018. SSA Publication No. 13-11801. Available online at: https://www.ssa.gov/policy/docs/ progdesc/ssptw/2018-2019/europe/index.html. Spiegel, A. D., & Springer, C. R. (1997). Babylonian medicine, managed care and codex of Hammurabi, circa 1700 B.C. Journal of Community Health, 22(1), 69–89. Tamagno, E. (2008). Strengthening social protection for ASEAN migrant workers through social security agreements. International Labour Office. Treaty on European Union (Consolidated Version). Official Journal of the European Communities C 326/13, 26.10.2012. Available online at: https://eur-lex.europa.eu/resource.html? uri¼cellar:2bf140bf-a3f8-4ab2-b506-fd71826e6da6.0023.02/DOC_1&format¼PDF United Nations. (1948). Universal declaration of human rights, UN Document No. A/810. Available online at: https://www.un.org/en/universal-declaration-human-rights/. van Kersbergen, K., & Kremer, M. (2008). Conservatism and the welfare state: Intervening to preserve. In W. van Oorschot, M. Opielka, & B. Pfau-Effinger (Eds.), Culture and welfare state values and social policy in comparative perspective. Edward Elgar. World Bank. Pension reform primer. Notional accounts—Notional defined contribution plans as a pension reform strategy. Available online at: http://documents.albankaldawli.org/curated/ar/ 524371468322154992/pdf/333820ENGLISH0PRPNoteNotionalAccts.pdf.

Chapter 3

Socioeconomic and Medical Approaches upon Pensions Systems

The social protection of citizens was an essential issue for all countries, regardless of the form of government, sociocultural characteristics, and economic system. In this chapter, we aim to identify the factors, which determined the configuration of the current pension systems implemented in the five CEE countries. The chapter points out the historical-anthropological framework and the sociocultural and political factors that determined the establishment of social protection systems, as well as their impact on the contemporary pension mechanisms implemented by five CEE countries. Also, it presents the evolution of the demographic situation in CEE countries and the influence of the demographic transition, with a special focus on the impact of the aging process and migration on the labor market and pension systems. At the end of the chapter are revealed some features regarding the health status of the population of CEE countries.

3.1

National Culture and Civilization as Factors of Influence of Social Protection Systems

Social protection systems and national pension systems have developed within a territorially delimited framework, being configured in accordance with the specifics of the government system, the economic and sociocultural framework (Aggarwal & Goodell, 2013). In contemporary society, the characteristics of a state are influenced by globalization and migration. Migrants carry their own national identity, values, and cultural ideology; therefore, the current society is governed by multiculturalism, ethnic and religious diversity. Bauman (2011) sees in today’s society a cultural pluralism, and tolerance for different social identities as a socioeconomic force. From this perspective, we consider that the national cultural identity is a determining factor for the formation and organization of contemporary social protection and pension systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_3

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3.1.1

3 Socioeconomic and Medical Approaches upon Pensions Systems

The Cultural System and Social Protection of the Elderly

Current empirical studies in sociology aim at the individual–society relationship in terms of factors that influence the social behavior of individuals. There are two main reasons that explain and support the contribution to social protection systems, respectively, to the pension system implemented within a state. First, we notice the existence of social and biometric risks such as unemployment, various diseases, aging, and accidents, which cause a feeling of helplessness and insecurity, and the role of social protection systems is precisely to insure against these risks. Second, there is a need for financial security. The role of the redistribution of social protection systems and especially of pension systems allows the provision of the financial flow necessary to meet personal needs. Glaeser (2016) analyzes the involvement in society, starting from the writings of the Greeks and Jews, continuing with modern philosophical ideas, and emphasizes two main motivations of the action of the individual in society. On one hand, individuality, by pursuing the satisfaction of their own interests and desires, as well as respect for their own rights, and on the other hand, the community, which integrates the individual into a group and community, its objectives being correlated with the objective of the community he or she is belonging, through solidarity with the group (Glaeser, 2016). By extrapolation of this idea, we note the presence of these concepts in contemporary social protection systems. Contribution to pension funds, whether compulsory or voluntary, expresses the interest in benefiting from the provisions of pension schemes. The contribution for a minimum period established by law or by contract offers the right to benefit from the provisions related to it, a right which is not prescribed and cannot be assigned. Also, within the PAYG-type pension systems, we find social solidarity as a fundamental principle of their functioning. Sociological studies conducted by Bellah et al. (1985), Inglehart (1997), and Hunter (1992) highlight the role of capitalism in promoting human rights, by forming political, professional, and educational points of view that support the free expression of the individual. On the other hand, Sayer (2011) notes that the inequality in exchange markets is a form of coercion of the human individual, and Côté et al. (2015) believe that the perception of a high level of inequity will reduce the generosity and motivation of taxpayers to comply with the taxation policy applied. Also, the contribution of citizens and the support of social policy promoted by a state are influenced by the perception of the quality of political leadership. The study by Rothstein et al. (2012) highlights a significant direct correlation between the quality of government and trust in social protection promoted by a state. According to Powell (2000), trust in a system is actually an investment of hope in the benefits offered, through faith in that system. The literature presents three basic concepts regarding the perception of society, namely: a model of loyalty and common welfare promoted in ancient Greek society; a universal community with an ideal that transcends the individual specific to

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religious communities; the conception of the Enlightenment who considered society to be in fact a contract for the individual good (Irwin, 2016). If we relate these notions to the social protection system, we could say that the Greek conception supports the noncontributory system and the provision of support to all citizens; the religious vision brings into question social solidarity; the Enlightenment approach promotes the partnership for ensuring welfare, a partnership that can be achieved with the state through the public pension system or with insurance companies, through private pension funds. Today’s society is based on civic activity and social solidarity, which aims at the common good. Social action is seen as a model of thinking and involvement in the community agreed by all members of that human community (Neamţu & Stan, 2005), and solidarity, in the context of social protection appears as a form of care to accomplish the needs of others, based on social relationships developed in the community. Values such as friendship, empathy, compassion, altruism, and charity determine the desire for sacrifice and active participation in helping others. Trust and solidarity have been positively correlated with economic prosperity (Fukuyama, 1996), a sine qua non condition for ensuring social welfare. Sociological and philosophical studies conducted by Weber (1930), Durkheim (1976), Manow (2002), van Kersbergen and Kremer (2008) have focused on the influence of religion in society, as well as in the formation and development of social protection systems. From a historical point of view, religion has played a key role in society, by being involved in meeting social needs, especially the needs for education and welfare of citizens, when the state did not have the necessary resources to meet these needs. Religion and morality are considered essential factors in the formation of human values and the development of social solidarity. It is noted that religious individuals (homo religiosus) are much more open in terms of charity (Brooks, 2006); on the other hand, they also have a higher level of racial prejudice (Johnson et al., 2012), they are more likely to have anxiety and tend to be conservative and authoritarian (Carney et al., 2008). Consistent with these observations, Tezcan (2007) refers to Islamism and the influence of Islamic religious culture in Muslim societies, concluding that religion is a resource by which governments ensure social order, based on authoritarian structures. At the European level, Esmer (2013) shows the existence of similar values of Muslim and Christian communities. Herbert (2000) discusses the role of religion in national society and culture, emphasizing the impact that religion has had on social integration and in promoting the process of democratization of CEE countries. The author identifies four forms by which religion has contributed positively to the democratic transition, namely: the opposition for socialist domination and the promoted ideology; relationships and connections, both domestic and international, between members of religious denominations; the provision of symbolic resources, respectively, the collective memory regarding the persecutions of the communist system, used to undermine the ideology imposed by the state; and the role of theological intellectuals, who promote human rights and freedom (Herbert, 2000).

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Burchardt (2017) analyzes the impact of religion on contemporary society from three perspectives, namely, promoting consumer behavior, promoting prosperity, success, well-being, and entrepreneurship, and as an expression of transnational freedom and mobility. From this perspective, the encouragement of population migration to countries that offer major benefits both financially and socio-culturally can be observed.

3.1.2

The Influence of Sociopolitical Organization and the System of Government in Forming the Specific Framework of Social Protection

The sociopolitical organization and the government system of a state are considered essential aspects for understanding the organization and functioning of the social protection system, as the state, through its structures and institutions, has the responsibility to regulate, implement, and control social policies meant to respect the right to social protection of their own citizens. Boadway and Keen (2000) support the effectiveness of the state in ensuring citizens against social risks due to fiscal autonomy and the role of income redistribution. The hypothesis that the present situation is a response to past circumstances, conditions, and experiences is developed by Bafoil (2009) who analyzes CEE countries from the perspective of inheritance from predecessors, suggesting that the recognition of sovereignty and freedom are determinants of the current system of government. The Czech Republic, Hungary, Poland, Slovakia, and Romania, historically, have gone through different forms of government. During the great empires, the AustroHungarian Empire in central Europe, the Ottoman Empire in the southeast, and the Tsarist Empire in the northeast of the continent imposed their domination over the territories of these countries. Dependence on the imperial leadership and administration was characterized by social conflicts over ethnic, linguistic, and sometimes religious unity, as well as by the desire for national sovereignty and independence. On the other hand, this period also had some advantages. From the point of view of the right to social protection, in Central European territories close to the influence of social principles promoted by Chancellor Otto von Bismarck, the implementation of social protection systems was made much faster. World War II left many victims and poverty behind, and the communist system of government in the CEE countries promised to eliminate the three major shortcomings in post-war society, namely, lack of housing, lack of food, and lack of jobs. For this, the state had to exercise tight control, both in public and in the private life of citizens, promoting an authoritarian leadership style, in which the citizen was not involved in sociopolitical life. The values and mindset promoted by the new political leadership formed a typology of the citizen, called “Homo Sovieticus,” characterized by total dependence on the state (Zaslavsky, 1994). Contrary to this point of view,

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Ferge (2008) argues that the so-called “dependent” character of the CEE population has its origins in feudal society, due to the strong social stratification according to social class and gender, a situation found all over Europe, and socialism has resolved these differences by eliminating private property. Judt (2008) presents the socialist system of government as a hostile takeover and a “cultural colonization,” so that “each [state] was to undergo economic reforms, adopt 5-year plans, become a police state and be led by a communist party fully subordinated to the dictatorship of Moscow communism” (Judt, 2008, pp. 163). The socialist ideology of welfare was based on the principle of equality, according to which redistributions were made “according to the needs of each individual,” keeping a minimum gap between minimum and maximum income. This policy has increased inequity in terms of educational level and social status, but also in terms of the active population in labor force and those who were beneficiaries of pension systems. A permanent concern of the socialist leadership was family and the repopulation of countries after the massive human losses during the war. Family policies supported the increase in birth rate, both through prohibitive measures such as banning abortions, but also by providing benefits such as housing for young families or facilities for families with more children. As a result, natural growth has seen a spectacular increase with positive effects on the labor market, based mainly on the agricultural and industrial sectors. Economic development was reflected in the pension system, by providing significant benefits, comparable to the salary level. After 1960, the first questions regarding the sustainability of the social protection system rise. The desire of socialist leaders to provide benefits to offset the inter-war and post-war crisis, as well as the desire to demonstrate the superiority of this political system in the field of social protection of citizens, has led, in conditions of increased life expectancy, to the rise of budgetary costs. As a result, in the following years, the standard retirement age was increased, as well as the rates of social contributions. The sociopolitical pressure of the nineteenth century in Europe culminated in CEE countries with the reaffirmation of national sovereignty and the abolition of the socialist system of government. However, the transition to a democratic system and market economy did not mean the instant elimination of socialist ideology, some values remaining deeply imprinted in the culture of the society. Marody (1992) notes that the socialist period reduced democratic attitudes such as entrepreneurship and individual responsibility among the population, which according to Sztompka (2000) is characterized by “cultural incompetence.” Alexander (1992) notes the existence of major conflicts between socialist ideology and the democratic system, which will be a challenge in political, social, and economic reform after 1898, respectively, the opposition between collectivism and individualism, solidarity and competitiveness, equality and meritocracy, security and risk, passivity and social commitment. Changing the governance system in CEE countries has had a major impact on national systems. As regards the social protection system, it faces a mismatch between income and benefits. The new socioeconomic conditions that emerged in

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the post-socialist society demanded an urgent reform of the social protection system, which was delayed. The effective reform began after 1995, being identified two main causes in this regard. The first cause was the inexistence of a program adapted to the existing socioeconomic conditions. The Social Democrats largely supported the redistributive role as the exclusive prerogative of the state, while the Liberal Democrats were much more open to capital markets and privatization. The external support received from IMF and WB specialists was essential for adapting the international models of organizing the social protection system to the national specifics. On the other hand, the democratic system and the market economy, based on free competition between different forms of capital, were new concepts in post-socialist countries. The cultural values implemented by the socialist system, respectively, the paternalistic system, in which the state had the role of ensuring the necessary incomes for the entire population, promoted the total dependence on the state. As a result, citizens did not express their opinion immediately and promptly, nor did they intervene to speed up the process of reforming the social protection system (Howard, 2003). The reform of the pension systems was carried out at the consensus between the Social Democrats and the Liberals following the pressure of the socioeconomic environment, but the context in which the reforms were adopted reflected the previous socialist influence. Government decentralization was a fundamental objective after 1989, but the formation of independent institutions and bodies, with the role of managing the social protection system, was considered insufficient due to the close relations between public bodies. Sztompka (2004) sees the transition from socialism to democracy as a cultural trauma due to the rapid, unexpected nature hidden in the structures of the old system and the macroeconomic impact that led to the complete change of the structures of society. Although in the short term the negative effects (inflation, unemployment, migration, poverty, criminal activity) were overwhelming, the cultural trauma of CEE countries, named “the trauma of victory,” was a positive force for national development. However, the author also draws attention to the possibility that this cultural trauma may have produced sociocultural destruction. If cultural disorientation and incompetence persist long enough, social activism is paralyzed and society is characterized by apathy, pessimism, and resignation, and in the end, all this will ruin the cultural identity and lead to the collapse of society (Sztompka, 2004). Outhwaite and Ray (2005), analyzing the process of transition of CEE countries from socialism to democracy, draw attention to the fact that the democratic system will not solve all existing problems in society, social inequalities being indeed easier to identify in the market economy. The gradual strengthening of the democratic system of government has inevitably led to the expression of the desire for “Europeanisation” through EU accession and integration. This stage can be considered as the process of national definition and formation in accordance with the community values: freedom, equality, solidarity, nondiscrimination, meritocracy, etc. The right to security and social protection is protected by the European Commission, which facilitates the coordination of

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national social protection systems and the transfer of information between the Member States to ensure the protection of all its citizens, regardless of their nationality.

3.1.3

The Role of Education in Substantiating Contemporary Pension Systems

The development of a state can be appreciated through the level of education of its population. The role of education and education system is to ensure skills, by giving knowledge and training the skills necessary for the individual to integrate socioprofessionally and culturally. On one hand, information, knowledge, and civic values are the window through which the human individual perceives the environment in which lives, being able to understand and characterize the interactions between different factors of this environment (cultural, economic, political, legislative, etc.), as well as the effects of these interactions. On the other hand, skills are the key of the professional integration of the individual on the labor market and the indispensable resource for the socioeconomic development of the country. Education and the contemporary education system are a response to the need for a specialized labor force that emerged with the industrial revolution and the fragmentation of the labor market in various sectors and activities. The demand for skilled labor, with skills specific to the sector of activity, has become the starting point for mass education of the population, followed by the expansion of secondary and tertiary education. The educational structure of the population from CEE countries, between 1950 and 1990, is characterized by a primary level of education. In 1950, the out-of-school population represented less than 5% of the population of Hungary and Slovakia, while in the Czech Republic and Poland, this category had values between 8 and 11% of the total population. Romania had the largest share of the out-of-school population in 1950, respectively 16.5% of the population. Gradually, until 1990, was a reduction in the number of out-of-school population and an increase in the population with secondary and higher education. Romania presented a slightly different situation compared to the other CEE countries, having a share of the outof-school population in 1990 of 4.4% of the total population, compared to values below 2% in all other countries included in the research (Fig. 3.1). These evolutions highlight, more precisely, the structure of the economy of this period, a centralized economy, based mainly on agricultural and industrial sectors. After 1990, the population of the five CEE countries in terms of education was largely characterized by a secondary level of education. There is noted the strengthening of tertiary level, especially due to belief that education is the most effective way to reform a country. The transition to a market economy was a shock for the population of the five European countries, and the low predictability from a fiscal, political, and legislative point of view slowed down the process of reforming the

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Fig. 3.1 The educational level of the population in CEE countries, period 1950–1990. Source: Author’s processing based on data published by Barro-Lee (http://www.barrolee.com/)

education system (Berryman, 2000). Economic uncertainty has led to the formation among the population of the concept that education, especially economic education, is a solution that guarantees integration to the labor market and earning the necessary income (Heyns, 2000), as well as guaranteeing the right to social protection. Zimmermann (2008) points out that in CEE countries, the promotion of education and participation in tertiary education is mainly influenced by financial factors. Scholarships and other facilities provided, especially to people from disadvantaged groups, have a positive impact on access to higher education. In 2018, Romania had a significant share of the population with primary education, respectively 26.3%, while the share of the population with higher education was 15.5%, compared to values over 21% in all other countries included in the research (Fig. 3.2). The socioeconomic implications of education level in CEE countries are multiple. OECD emphasizes the role of education in the sustainable socioeconomic development of a state. A higher level of education implies a higher level of skills in the field of specialization. This is reflected in higher rates of employment and reduced unemployment, as well as higher incomes, compared to people with a lower level of education. From the point of view of social protection systems, the costs associated with unemployment benefits are reduced, and the budget revenues obtained from social contributions can be increased. On the other hand, it was noted that people with higher educational levels are more involved in sociocultural life and show concerns related to maintaining health, a healthy and balanced lifestyle, personal development, and environmental protection (OECD, 2018).

3.2 Influence of Demographic Changes on the Labor Market and Pension Systems

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Fig. 3.2 Population in CEE countries according to educational level in the period 1998–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/ data/database)

3.2

Influence of Demographic Changes on the Labor Market and Pension Systems

Population represents the “force” that ensures the socioeconomic development of a state. The European Union is currently facing two significant demographic problems: an aging population and its excessive immigration to heavily industrialized Western countries. This situation puts a lot of pressure, both on the labor market in CEE countries and on the national PAYG pension systems, correlated with population structure. Social protection and pension systems have emerged as a response to the population’s need to insure against biometric risks such as aging, illness, accidents, etc., which reduce the ability to obtain financial resources necessary for a decent living. According to data published by Eurostat, CEE countries show an oscillating evolution of the demographic situation. Figure 3.3 presents the evolution of the most representative indicators for the characterization of the five countries included in research in terms of population evolution. First, the fluctuation of the population in the period 1960–2018 can be observed, except in Slovakia, where the average population records a progressive level throughout all periods. The Czech Republic also has an upward trend of the average population but has a period of decline between 1998 and 2003. In Hungary, Poland, and Romania, the average population shows a significant increase until 1982, respectively, in 1998 and 1990. By 2018, the values of this indicator will decrease, the highest value being registered in Romania (
16%), followed by

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Fig. 3.3 Average population, natural growth, and total population change in CEE countries in the period 1960–2018. Source: Author’s processing based on data published by Eurostat (https://ec. europa.eu/eurostat/data/database)

Hungary (
9%) and Poland (
2%). These developments are primarily determined by natural growth and then by net migration. Regarding natural growth, the reduction of this indicator in all five CEE countries can be seen, mainly due to the reduction of birth rate. The total population change, although follows the trend of natural growth in these five European countries, due to the influence of migration, reflects a slightly different situation, the existence of periods with significant variations in each state being noted. Thus, the minimum points of the number of population are the cumulative result of the negative natural growth and migration. From this point of view, Slovakia shows the most moderate evolution with three periods of a slight decline in 1970, 1991, and 2000–2003. At the opposite pole is Romania, where after 1990 the population decreased dramatically, the years of “intense exodus” being 1991, 2001, and 2007. The other countries also have periods in which the population decreased significantly, respectively, in Poland, 1989 in Hungary, respectively 1970, 1980, and 1990 in the Czech Republic. Eurostat forecasts suggest a significant reduction of population by 2100, especially in Romania, Slovakia, and Poland. Regarding the structure by age groups, starting from 1960 until 2018, there is an increase in the share of the population over the age of 65, while reducing the share of other age groups (Fig. 3.4). The most significant decrease in population is registered in the age group 0–14, which in 2018, compared to 1960, decreased by 12% in Slovakia and Poland, by 10% in Romania, by 7% in Hungary, and by 6% in the Czech Republic. The share of the population aged between 15 and 39 years also has a downward trend, while the population in the age group 40–64 still has a positive trend. These evolutions have led to an increase in the average age of population in these countries by 12.3 years in Poland, 11.9 years in Slovakia, 11.2 years in

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Fig. 3.4 Population structure according to age group and the average age of population in CEE countries, period 1960–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

Romania, 8.8 years in the Czech Republic, and 8.5 years in Hungary. Thus, in 2018, the average age of population exceeded 42 years in Hungary, the Czech Republic, and Romania. Bricker and Ibbitson (2009) argue that population decline is a process that will characterize all countries of the world, the main cause being economic development. The industrial revolution determined the concentration of population in urban areas where the labor market offered multiple opportunities for earning income. If in rural areas, the child was seen as “an investment” and support in the household, in the city, the child becomes “an expenditure.” Also, in urban areas, many more cultural and educational are found factors that, over time, have influenced and changed the role of women in society. The right to education, the right to work, and the right to social protection have led to reduced fertility. Pradhan (2015) shows that a higher level of women’s education leads to a reduction in the number of pregnancies and births. The decline of population represents a threat to the productivity of the labor market, but also to the sustainability of PAYG pension systems financed from social contributions paid by professionally active people. Measures for stimulating fertility failed to reach the minimum replacement rate needed to maintain the population, respectively 2.1 children/woman. As a result, a solution would be to attract a foreign population to replace the national demographic decline (Pânzaru, 2015). Immigration must be seen as an economic policy that will support economic development and labor market productivity, respectively, the balance between taxpayers and beneficiaries of pension systems. Attracting foreign human capital, accepting and including immigrants, interactions, and social cohesion, according to Heyneman (2000), can only be maintained through transparency, common values,

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Fig. 3.5 Population migration in CEE countries during 2008–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

involvement, and social participation. However, cultural and ethnic diversity is a difficult obstacle to overcome for the formation of national and community unity. The creation of European area and Community freedoms have had felt their effects on the CEE countries, which, in addition to the benefits of foreign investment, are facing the effects of globalization and labor migration to Western countries with developed economies (Ionescu, 2008). The Czech Republic, Hungary, Poland, Slovakia, and Romania present a specific situation in terms of migration (Fig. 3.5). In the last decade, Hungary and Slovakia have a positive net migration, managing to attract on average over 21,000, respectively 3000 immigrants per year. The Czech Republic recorded a negative net migration between 2010 and 2012, but on average attracted about 25,000 immigrants each year. At the opposite pole are Poland and Romania, which in the last 10 years have a negative net migration and have lost every year an average number of over 100,000 people of the national population. The areas of emigration preferred by the population of these five countries are the Community countries, the countries of North America, and Southeast Asia. However, there are fewer applications for asylum and citizenship. Compared to the number of immigrants, asylum applications hold a percentage of 53.6% in Hungary, 10% in Poland, 8% in Slovakia, 2.7% in the Czech Republic, and 0.4% in Romania (Fig. 3.6). Applications for citizenship in one of the five CEE countries have an even lower percentage, not exceeding an average of 0.3% of the number of immigrants. On average, citizenship is granted in less than 30% of applications, the largest share being held by applications made in accordance with the provisions of the Geneva Convention for Refugees. In the period 2008–2018, Romania responded favorably to the applications for citizenship made by refugees in the case of

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Fig. 3.6 Applications for asylum and citizenship in CEE countries in the period 2008–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/ data/database)

830 people, the Czech Republic for 140 people, Hungary for 115 people, Poland for 90 people, and Slovakia for only 15 people. The socioeconomic integration of immigrants is facilitated by the educational level. The employment rate for people with primary education is between 17.5 and 45.6%, increasing in the case of secondary education to values between 62.5 and 74% and in the case of higher education reaching values above 76.3%. It is noted that in the case of men, the employment rate is higher. Regarding the right to social protection, the principle of territoriality becomes inappropriate for people in the process of migration because by virtue of national sovereignty, a country is free to implement a social protection system to ensure its own citizens, and from this point of view, the host state has no social obligations toward nonresidents. The issue of ensuring the right to social protection of immigrants has been partially solutioned by the adoption of the International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families, which establishes the obligation of nondiscriminatory treatment of immigrants in one country, compared with their own citizens. The population of a country, from the perspective of the labor market, is usually classified into two broad categories, namely, the active population, consisting of the employed and unemployed population, and the inactive population. In CEE countries, since 1998, the share of the active population in the total population has increased steadily, in 2018 exceeding 67% of the total population in the case of Romania and 76% in the case of the Czech Republic. These evolutions are also reflected in the employment rate, which in the last 21 years has increased by 16% in Hungary, 8% in Poland, and 7% in the Czech Republic and Slovakia. In Romania,

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Fig. 3.7 Labor market structure by age group, activity rate, and unemployment rate in CEE countries in the period 1998–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

the employment rate gradually decreased to a minimum of 5.7% in 2005, later having an upward trend, but which failed to reach the value of 1998. The unemployment rate decreased in all five CEE countries, the largest reduction was registered in Poland (
6.1%) and Slovakia (
5.7%), in Romania the unemployment rate decreased by only 1.5%. As regards the structure of the employed population according to age, in CEE countries the largest share is held by employees aged between 25 and 54 years. A reduction in the share of employees up to the age of 24 and, at the same time, an increase in the share of employees over the age of 55 can be noted (Fig. 3.7). The distribution by gender reflects a slight predominance of male employees, representing 55% of the total employed population, and the distribution by educational level shows the preponderance of employees with secondary education (between 68 and 80% of the employed population, in 2018), the decrease of the share of employees with primary education and increasing the share of employees with higher education, especially for women, in all five CEE countries. The employed population and the structure of the labor market are the essential factors that determine the functioning of pension systems. In the case of CEE countries included in the research, the protection of the elderly is achieved through public pension systems, based on the principle of contributivity, social solidarity, and intergenerational redistribution. As a result, the characteristics of the employed population will be reflected in the public pension system, as the employed population provides, through social contributions paid to the State Social Insurance Budget (SSIB), the budget revenues necessary to provide financial support to beneficiaries. The average working period of the population in the five CEE countries increased between 2000 and 2018, for both men and women, reaching values above 36 years for men and over 30 years for women, in all five countries (Fig. 3.8). In 2018, the Czech population had the longest duration of working life, respectively 39.2 years

3.2 Influence of Demographic Changes on the Labor Market and Pension Systems

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Fig. 3.8 Duration of working life in CEE countries, period 2000–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

for men and 33.2 years for women. Compared to 2000, the largest increase was recorded in Hungary, where the average working period of men increased by 6.6 years, and of women by 6.4 years, in other countries, the duration of working life increased by 2.4 years. In Romania, a reduction in the average working period between 2000 and 2018 is noted, the indicator having a decrease of 4 years for women and 1.1 years for men. The implications of this indicator on public pension systems are reflected in the contribution periods, which, together with age, represent an eligibility criterion in accessing the benefits of pension systems. The average annual incomes obtained by employees of CEE countries included in research increased in the period 2008–2018, the highest growth being in the Czech Republic, Poland, and Hungary, and the lowest in Romania. Between 2008 and 2018, the minimum annual income registered the highest increase in Romania (+197%), followed by Slovakia (+79%), Hungary and Poland (+43%), the Czech Republic having an increase in the minimum annual income of 40% in the last 11 years. The average annual gross income also increased, the highest increase being registered in Romania (+71%), while in the other countries, the increase was between 32 and 40% (Fig. 3.9). However, in monetary expression, the income earned by Romanian employees is lower, compared to employees in other CEE countries (Fig. 3.9). The incomes obtained by the population have a major implication on public pension systems as the contributions paid to SSIB are established proportional to contribution capacity, respectively, depending on the level of income earned. Also, the contribution to voluntary pension funds is determined by the level of income obtained and the ability of the population to save. The taxes and social contributions paid by employees show different evolutions, depending on the state of residence. Income tax increased between 2008 and 2018 with 67% in the Czech Republic, 53% in Slovakia, and 35% in Poland. In Hungary, the income tax had a downward trend until 2013, after which it appreciated and reached the level held in 2008. In Romania, until 2017, a progressive increase in

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Fig. 3.9 Minimum annual income, average annual income, taxes and social contributions in CEE countries in the period 2008–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

income tax was recorded, but beginning with 2018, its value has reduced, due to tax changes, which decreased the tax rate to 10% of gross income. Regarding social contributions, these have increased in all five CEE countries. The decision to transfer the social contributions in charge of the employee starting with 2018, determined the doubling of social contributions paid by Romanian employees and their increase by 229% compared to 2008. In Hungary, the social contributions paid by the employees registered an increase of 52%, in Slovakia of 38%, in Poland of 32%, and in the Czech Republic of 20%. Compared to the average gross income, taxes and social contributions determined the increase in fiscal pressure by 9.51% in Romania, while in Slovakia and the Czech Republic the increase in fiscal pressure is about 1%, and in Hungary, it decreased by 4.8% in the last 11 years. In the current demographic context, the importance of pension systems is reflected by the social role played, namely, the reduction of financial vulnerability among the elderly population. The current and projected demographic structure of Eurostat highlights the declining population in the five CEE countries, as well as the aging trend and the increase in the number of older people who will need financial support. This situation is alarming for the financiers of pension systems based on the principle of redistribution between generations, who will have to financially support an increasing number of people. In the Czech Republic, Hungary, Poland, Slovakia, and Romania, the financial protection of the elderly is achieved mostly through PAYG public pension systems. Reducing the share of the young population active in the labor market raises the issue of gathering the necessary budgetary resources and threatens the financial sustainability of these systems (Balteș & Jimon, 2020). Goldin (2016) presents the positive aspect of an aging population, which is the accumulation of human capital with both knowledge and experience needed to

3.3 Aspects Regarding the Sociomedical Characteristics of Pension Systems

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support economic development, but the sustainable development of countries requires also innovation and finding solutions to maintain the quality of life of the population (Panța, 2019), regarding the level of income, as well as of the right to health care and social protection (Creț, 2012).

3.3

Aspects Regarding the Sociomedical Characteristics of Pension Systems

Economic development and labor market productivity are not only influenced by the abilities and skills of human capital but include both the motivation, creativity, experiences, and health of the individual (Luthans et al., 2004). As we have seen, the decline in the population of CEE countries is due to, on one hand on migration and on the other hand to the reduction in the birth rate. The number of births decreased between 1990 and 2017 by 36% in Romania, with a percentage between 25 and 28% in Hungary, Poland, and Slovakia, but in the Czech Republic, the decrease of birth rate was 12% (Fig. 3.10). One factor that has led to the reduction of the birth rate in recent decades is the legalization of abortions, which often leads to a permanent reduction of fertility (Ananat et al., 2007). In all CEE countries, the liberalization of abortions has led to a decrease in birth rate, but Hungary and Romania stand out, where the share of abortions in 2017 accounted for 30%, respectively, 28% of births. The fertility rate in these five CEE countries reached in 2017 values between 1.48 and 1.70 children/woman. The largest decreases, compared to 1990 are recorded in Poland (from 2.06 children/woman in 1990 to 1.48 children/woman in 2017) and in

Fig. 3.10 Birth rate, mortality, and fertility rate in CEE countries between 1990 and 2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/ database)

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Slovakia (from 2.09 children/woman in 1990 to 1.52 children/woman in 2017), followed by Hungary and the Czech Republic (with a decrease in the fertility rate of 0.33 children/woman, respectively 0.21 children/woman). Romania has the lowest fertility rate reduction among the five CEE countries, with 0.12 children/woman. Fertility is influenced by the age of women at birth. It can be noted an increase in the number of births after 25 years and up to 35 years, so that the average age of women at birth has increased in the last 27 years in all five countries analyzed. This indicator has the highest value in the Czech Republic (+5.2 years, the average age of women at birth of the first child being 28.2 years in 2017) and Hungary (+4.2 years, the average age of women at first birth being 28 years old in 2017). In Poland and Slovakia, in 2017, the average age at which women give birth to their first child was 27 years, and the average age of women at birth is 29.8 years, respectively 28.8 years. In Romania, the average age of women at birth increased in 2017, compared to 1990, by 2.4 years, on average the first birth of a woman is at the age of 26.5. Regarding mortality, compared to 1990, the number of deaths decreased by 13.7% in the Czech Republic, by 9.5% in Hungary and by 1.3% in Slovakia, while in Romania and Poland were registered more deaths than in 1990 with 5.7%, respectively 3.2%. The main causes that determined the morbidity and mortality of the population in CEE countries have a pathological nature (Fig. 3.11). Thus, depending on health problems, between 1999 and 2006, cardiovascular diseases caused between 40 and 60% of deaths, neoplasms between 15 and 26%, and respiratory and digestive diseases between 8 and 11% of total deaths. A share between 4 and 7% of all deaths was due to external causes, such as vehicle accidents, work accidents, falls, accidental drowning, exposure to toxic substances, self-harm, or aggression. Related to external causes of mortality, an important aspect of the labor market and social protection systems is work accidents. If, in the case of labor market, accidents at work and temporary incapacity leave result in reduced productivity, for the employed population these represent both a risk of invalidity or death and financial risk. In the CEE countries, in recent years has been a tendency to decrease accidents at work with a higher degree of severity, the periods of leave for temporary incapacity for work being largely granted for a period of 1–3 months (Fig. 3.12). Accidents that caused disability or were fatal to employees decreased in the period 2008–2017, but still hold a significant share in Romania, Slovakia, and Hungary. These cases fall within the scope of pension schemes, which have the role of ensuring the financial protection of the population, by providing benefits in the form of invalidity pension and survivor’s pension, if the surviving spouse or children meet the eligibility criteria. In the last 10 years, the number of beneficiaries of invalidity and survivors’ pensions has remained approximately constant in the Czech Republic and Slovakia, in the other three CEE countries, their number has decreased. The measures of prevention, diagnosis, and treatment, as well as policies to reduce malnutrition and poverty, have led to increased quality of life and increased life expectancy. In CEE countries included in the research, life expectancy at birth has increased in the last 11 years, having values over 70 years (Fig. 3.13). It is noted

3.3 Aspects Regarding the Sociomedical Characteristics of Pension Systems

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According to the International and Statistical Classification of Diseases and Health Problems (ICD 10): A00-B99 - Infectious and parasitic diseases

M00-M99 - Diseases of the osteo-articular system, muscles and connective tissue

C00-D48 - Tumors N00-N99 - Diseases of the genitourinary system D50-D89 - Diseases of the blood and hematopoietic organs and some disorders of the immune system

O00-O99 - Pregnancy, birth and childbirth

E00-E90 - Endocrine diseases, nutrition and metabolism

P00-P96 - Some diseases whose origin is in the perinatal period

F00-F99 - Mental and behavioral disorders

Q00-Q99 - Congenital malformations, deformities and chromosomal abnormalities

G00- H95 - Diseases of the nervous system and sensitive organs I00-I99 - Diseases of the circulatory system J00-J99 - Respiratory diseases K00-K93 - Digestive system diseases

R00-R99 - Symptoms, signs and abnormal results of clinical and laboratory investigations, not elsewhere classified V01-Y89 - External causes of morbidity and mortality (accidents, falls, drowning, aggression)

L00-L99 - Diseases of the skin and subcutaneous tissue

Fig. 3.11 Distribution of mortality by cause in CEE countries during 1999–2006. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

that in the case of women, life expectancy is 6–8 years higher than the life expectancy of men. The explanation for this evolution lies in the hormonal protection of women, but especially in the fact that they give more importance to personal care, nutrition, regular medical checkups, prevention methods, and prescribed

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Fig. 3.12 Accidents at work in CEE countries during the period 2008–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

Fig. 3.13 Life expectancy in CEE countries in the period 2007–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

treatment. However, the increase in life expectancy and the decrease in birth rate have led to the growth of the dependency rate of the elderly. The highest increases, reported to 1960, are registered in Romania (+15%), Poland (+13%), Hungary, and the Czech Republic (+12%). Life expectancy is reduced, given the period of life with health, to values between 53 and 65 years. Between 2007 and 2017, healthy life expectancy decreased in Romania by 4.2 years for women and 1.3 years for men, and in the Czech Republic and Slovakia, the indicator decreases between 0.5 and 0.9 years, while in Hungary and Poland the values increased for men by 4.5 years in Hungary, respectively, by 3 years in Poland and in case of women by 3 years in Hungary and 2 years in Poland.

3.5 Summary

73

Regarding the perception of the population of their own state of health, in the five CEE countries, it is noted that in about 50–58% of the employed population considered to be in good health, a percentage between 15 and 30% considered to be in excellent health, and between 10 and 23% of the total employed population are considered to have satisfactory health. Life expectancy is an essential indicator for the characterization of the labor market that allows the approximation of the average number of years in which a person can carry out professional activities. From the perspective of PAYG public pension schemes implemented in CEE countries, this period helps to estimate the contribution periods that provide the funds needed to provide benefits, as well as the average period for which benefits will be provided.

3.4

Conclusions and Personal Contributions

The foundation of the formation of social protection and pension systems is the right of the population to social protection, in the context of income inequality, which will lead to poverty. The respect for this right has been achieved differently, depending on the system of government and political ideology. The efforts of the CEE countries to ensure social protection of the elderly through the benefits of public pension systems have been felt by the population, which present increased well-being, both in terms of income and consumption, and as well in terms of health. The direct link between population structure and public pension systems in CEE countries represents, especially in Romania, a threat in the context of reduced birth rates, extensive migration, and increased life expectancy. The general conclusion of this chapter lies in the need for a correlation of the reforms regarding the social protection systems with the general national framework, considering the determinants of the economic, social, and medical environment, as well as their influence on the parameters of pension systems.

3.5

Summary

This chapter presents the historical-anthropological framework and defines the sociocultural and political factors that determined the configuration of social protection systems, as well as their impact on the contemporary pension mechanisms implemented by the five CEE countries included in the research. The second part of the chapter highlights the influence of demographic transition, respectively the impact of the aging process and migration on the labor market and public pension systems. The direct link between the population structure and the public pension systems in CEE countries represents, especially in Romania, a threat in the context of reduced birth rates, extensive labor migration, and increased life expectancy, given that the success of PAYG type pension systems is conditional on maintaining a

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balance between expenditure on current benefits and income from social contributions paid by the employed population.

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Chapter 4

Modeling the Impact of Socioeconomic and Medical Characteristics on Public Pension Systems in Central and Eastern European Countries

Due to the direct link between the structure of the labor market and public pension systems, some important aspects are highlighted in this chapter regarding the correlation between the level of budget expenditures with social insurance and national economic development, demographic and medical characteristics of the population. Based on other works on the field of social protection and pension systems, an empirical study was conducted following three dimensions of social protection systems, namely, economic, social, and medical features.

4.1

General Aspects

The demographic situation of CEE countries is defined, as we have seen before, by the phenomenon of the aging population, due to the reduction of birth rate and fertility rate, negative natural growth, and increased life expectancy. These aspects have determined that the structure of the labor market in 2018 be formed in the proportion of approximately 15% of people over the age of 55, and the dependency rate of the elderly population to reach up to 29%. In CEE countries, a strong link is noticed between the structure of the labor market and respect for the right to social protection of the elderly through the PAYG public pension system. The mismatches between the employed population, payers of social contributions, and the number of pensioners represent a threat to the budgetary sustainability of public pension systems. The measures suggested by the European Parliament to limit the negative effects that demographic transition has on PAYG public pension systems include raising the retirement age, limiting early retirement, increasing the employability of older people, lifelong learning, active aging, and encouraging private savings (Eatock, 2015). Even though these measures have been regulated by CEE countries, sociodemographic changes still represent a challenge for PAYG pension systems and suggest the need for more comprehensive reforms © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_4

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harmonized with the education system, the labor market, the tax system, and financial markets (Balteș et al., 2018). The connections between sociodemographic characteristics, bio-medical aspects, and public pension systems are an important topic of research conducted in the fields of social sciences, economics, and medicine. The main directions of empirical research focus on the correlations between some demographic indicators, such as fertility, life expectancy or dependency rate of the elderly population, and the parameters of pension systems. The study conducted by Fenge and Scheubel (2017) regarding the demographic transition in Germany shows that the implementation of the Bismarckian pension system has led to a reduction in the fertility rate. On the other hand, Wang (2015) argues that social protection systems and the distribution of pensions can have a positive effect on fertility, especially if there are preferential eligibility conditions for accessing benefits according to the number of births (Fenge & von Weizsäcker, 2010). To strengthen public pension systems, Dieppe and Guarda (2015) point out that for coping with demographic changes, the reform must encourage an increase in the employment rate on the labor market. Verbic and Spruk (2011) argue that raising the fertility rate and retirement age would be effective measures to reduce expenditures with public pension benefits, and Heijdra and Romp (2009) show the negative effects of early retirement and the need for strict reforms. On the other hand, studies conducted not only by Brockmann et al. (2009), but also by Hallberg et al. (2015) highlight the positive effects of early retirement on the physical and mental health of employees highly exposed to the risk of accidents and occupational diseases. The socioeconomic implications of demographic transition are studied by Kunze (2014), who shows that increasing life expectancy decreases economic growth. The effects of labor migration on pension systems were studied by Han (2013) in the case of 14 European countries, and the author’s conclusions indicate a reduction in the level of benefits and an increase in budgetary pressure, especially in the case of Bismarckian systems. Lacomba and Lagos (2010) focus on the impact of the immigrant population with a low level of skills on the labor market and on the benefits of pension systems in the host country, showing the positive effects of immigration. Di Liddo (2018) completed this study, demonstrating that in conditions of budgetary pressure and “unsustainability” only immigrants with high professional skills bring a real benefit to the economy and to the pension systems. Regarding the increasing life expectancy and aging population, Haan and Prowse (2012) demonstrate that in order to obtain adequate future benefits, the population must work longer and postpone retirement, a view also supported by Cipriani (2018). Also, the study conducted by Heller-Sahlgren (2017) on a sample of ten European countries shows the positive effect of continued professional activity on the mental health of the population, Krumins et al. (2019) identifying professional activity as a significant factor in reducing mortality. In contradictory, Staubli and Zweimüller (2013) point out that raising the retirement age in Australia has had a slight effect on the employment rate and at the same time on the social protection system as low-income employees and those with medical conditions have applied

4.1 General Aspects

79

for either early retirement or disability pension, or they became unemployed. Similar results were obtained by Engels et al. (2017) in the study regarding the German population. Also, the study conducted by Jimon et al. (2020) pointed out the existence of a significant positive correlation between working life and unemployment, suggesting that increasing the standard retirement age and the contribution period will also increase the number of unemployed people. The effects of retirement on health were also studied by Coe and Zamarro (2011), in the case of ten European countries, which highlighted the fact that retirement has positive effects on maintaining health. A similar conclusion is drawn from the study conducted by Eibich (2015), which identifies the reduction of stress, adequate rest, and physical exercise as the main factors for maintaining health. On the other hand, Shin (2012) argues that pension systems do not improve the quality of life in all circumstances, a conclusion also supported by Fitzpatrick and Moore (2018), who show that retirement can have negative effects on health, but also by Fe and Hollingsworth (2016), who draw attention to the fact that retirement favors sedentarism and social isolation, indirectly affecting the health of pensioners. Several studies investigate the influence of working conditions on the medical status of the population and on the benefits provided by social protection systems. Frequent illnesses and temporary incapacity leave are considered factors that are associated with long-term disability and mortality (Narusyte, et al., 2013), meanwhile, Falkstedt et al. (2014) demonstrating that the high level of invalidity pensions among the population with primary education in Sweden is partly due to working conditions. Sundstrup et al. (2018) demonstrate that a high level of work tasks, nonrecognition of merit, and a climate of conflict will lead to increased employee absenteeism, the prevalence of mental illness and increased expenditures with health care and disability pensions. The role of financial transfers through public pension systems in maintaining the quality of life of the elderly has been studied by authors such as Mitrut and Wolf (2011), Mentzakis and Moro (2009), Cheng et al. (2018), and Ju et al. (2017), which highlight the positive influence, satisfaction, and increase in quality of life, especially in the case of the population with a modest socioeconomic level. Empirical studies regarding the correlations between sociodemographic indicators and parameters of pension systems have an essential place in current research. However, the share of empirical studies targeting the specific situation of CEE countries is relatively small, with small-scale studies within volatile parameters and insufficiently long periods of time. The econometric study we propose starts from the premise of reducing the abovementioned deficiencies, by considering significant indicators in three dimensions: economic, social, and medical, the use of a long run time, but also some techniques for modeling by which empirical results are correctly estimated, analyzed, and interpreted.

80

4.2

4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

Research Methodology and Data Used

In order to study the influence of national economic development, demographic, socioeconomic, and medical characteristics of the population on pension systems, was set up a database, using statistics published by Eurostat, consisting of the following macroeconomic variables: (I) Indicators regarding the development of the national economy—the level of GDP per capita (GDPcap) (II) Budget expenditures with social insurance (pGExpSP) (III) Demographic indicators: total population (POPt), net migration (nMIGR), total population change (TCHPOP), natural population change (NCHPOP), and old dependency ratio (OLDDr) (IV) Labor market indicators: active population (ACT), employed population (EMP), unemployed population (UNE), and duration of working life (DWL) (V) Sociomedical indicators: total births (LBT), birth rate (LBr), fertility rate (Fr), mean age of women at birth (mnAGEcb), number of deaths (DTT), and mortality rate (DTr) According to Eurostat, GDPcap expresses the average level per person of gross value added and production taxes, less subsidies received, expressed in market prices, and pGExpSP highlights the share of social security expenditures in national GDP. POPt indicates the number of inhabitants of a country on January 1st, the difference between the number of population on this date in 2 consecutive years representing TCHPOP. nMIGR, commonly known as the difference between immigration and emigration, is calculated by Eurostat as the difference between TCHPOP and NCHPOP. NCHPOP expresses the difference between LBT and DTT in 1 year, and OLDDr represents the ratio between the number of people over the age of 65 and the population aged between 15 and 64 years. LBT shows the number of children born who showed vital signs, excluding miscarriages and intrauterine fetal death, and LBr defines the share of children born in a year on average population of that year, usually expressed in thousands of inhabitants. Fr describes the average number of children a woman could have in her lifetime, considering age-specific fertility, and mnAGEcb expresses the average age of women giving birth to children. DT expresses the inexistence of life, respectively the failure of vital functions and the inability to resuscitate after birth, DTr representing the share of deaths in the average population, usually expressed in thousands of inhabitants, over a period of 1 year. ACT includes the employed population and the unemployed population, except for the economically inactive categories: preschool children, schoolchildren, students, and pensioners. EMP is defined as people who work for at least 1 h for pay or who are on temporary leave during the reference period, and UNE shows all persons between the ages of 15 and 74 who are not employed, have sought a place of work,

4.2 Research Methodology and Data Used

81

or are ready to employ. DWL measures the number of years a person is expected to be active in the labor market. The extraction of the aforementioned macroeconomic variables from the Eurostat database was made for the period 2008–2017, due to the need to establish a period in which all the variables considered have values, in order to obtain a high statistical significance of the sample formed. The econometric tests were performed using the software package EViews 10 University Edition, and the method used is Pooled Least Squares. The pool data regression model analyzes the statistical variables in bidimensional, respectively, in a cross-section and a period section. The most well-known and used method for performing such regressions in empirical studies in economics is the Ordinary Least Squares (OLS) method. Depending on the impact of unobservable variables on the dependent variable, the OLS method can be used in three forms: without effects, with fixed effects, and with random effects, both cross-sectional and period dimensions. The standard model, without effects, implies, according to the name, the inexistence of effects, respectively, the specific factors that determine the relationship between explanatory and dependent variables. The model with fixed effects considers the existence of an individual constant specific to each country, which explains the differences in the relationship established between the variables by the variants of the free coefficient (intercept). The random-effects model assumes the existence of an independent random variable that explains the differences in the relationship established between the variables by the variances of the error of the equations. To determine which of the two effects models is most appropriate in a study, Hausman test it is used to analyze whether the errors are correlated with the regressors, with confirmation of the alternative hypothesis suggesting the use of the fixed-effects method. The regression equations used in the econometric study are the following: pGExpSPit ¼ α þ β1  GDPcapit þ β2  ACTit þ β3  ACTmit þ β4  ACTf it þ β5  EMPit þ β6  EMPmit þ β7  EMPf it þ β8  UNEit þ β9  UNEmit þ β10  UNEf it þ εit

ð4:1Þ

pGExpSPit ¼ α þ 14:51  GDPcapit þ 0:02  ACTit þ 0:09  ACTmit  12:87  ACTf it  0:10  EMPit þ 0:02  EMPmit  0:12  EMPf it  442:62  UNEit þ 0:02  UNEmit þ 1404:50  UNEf it þ εit

ð4:1aÞ

pGExpSPit ¼ α þ 268:63  GDPcapit  0:01  ACTit þ 0:001  ACTmit  6:08  ACTf it  0:01  EMPit þ 0:01  EMPmit þ 0:01  EMPf it þ 719:90  UNEit  0:01  UNEmit  775:26  UNEf it þ εit

ð4:1bÞ

4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

82

pGExpSPit ¼ α þ β1  POPtit þ β2  nMIGRit þ β3  TCHPOPit þ β4  DWLit þ β5  DWLmit þ β6  DWLf it þ εit

ð4:2Þ

pGExpSPit ¼ α þ 1653:93  POPtit  574:08  nMIGRit þ 0:01  TCHPOPit  0:01  DWLit þ 609:78  DWLmit þ 0:01  DWLf it þ εit ð4:2aÞ pGExpSPit ¼ α  796:11  POPtit  1011:51  nMIGRit  0:01  TCHPOPit  0:01  DWLit  438:39  DWLmit þ 0:01  DWLf it þ εit ð4:2bÞ pGExpSPit ¼ α þ β1  LBTit þ β2  LBrit þ β3  Frit þ β4  mnAGEcbit þ β5  DTTit þ β6  DTrit þ β7  NCHPOPit þ β8  OLDDrit þ εit ð4:3Þ pGExpSPit ¼ α þ 1:69  LBTit  0:02  LBrit  794:15  Frit þ 14, 820:38  mnAGEcbit þ 0:01  DTTit  0:08  DTrit  0:11  NCHPOPit þ 0:01  OLDDrit þ εit ð4:3aÞ pGExpSPit ¼ α þ 4:11  LBTit  0:01  LBrit þ 1603:32  Frit  8504:62  mnAGEcbit  7:79  DTTit þ 0:08  DTrit  0:14  NCHPOPit  0:01  OLDDrit þ εit where: • • • • • • • • • • • • • • • • • • • • • •

α—free coefficient pGExpSP—budget expenditures with social insurance GDPcap—GDP per capita ACT—number of active people ACTm—number of active males ACTf—number of active females EMP—number of employees EMPm—number of employees males EMPf—number of employees females UNE—number of unemployed UNEm—number of unemployed males UNEf—number of unemployed females POPt—total population nMIGR—net migration TCHPOP—total population change DWL—duration of working life DWLm—duration of working life of males DWLf—duration of working life of females LBT—number of births LBr—birth rate Fr—fertility rate mnAGEcb—mean age of women at birth

ð4:3bÞ

4.3 Empirical Results

• • • • •

83

DTT—number of deceased persons DTr—death rate NCHPOP—natural change of population OLDDr—old dependency ratio εit—regression error

4.3 4.3.1

Empirical Results Model I: The Economic Impact of Pension Systems

Model I aims to test the economic impact of pension systems and uses the regression equation (4.1) presented above. The descriptive analysis of the variables used in this model is presented in Table 4.1. The Jarque–Bera (JB) test shows a normal distribution of the number of active persons and males, the number of employees, both males and females, and the number of males unemployed, for the threshold of 5%. Since all other variables exceed this threshold, according to the JB test we consider that their distribution is not normal. As regards the asymmetry, it can be noted that the number of active people, the number of active women, the number of unemployed people, and the number of unemployed women have a negative asymmetry (Skewness < 0), and the other variables have a positive asymmetry (Skewness > 0). The kurtosis shows a leptokurtic distribution for the number of employed persons and the number of unemployed persons, both males and females (Kurtosis > 3), the other variables having a platykurtic distribution. In the case of variables whose distribution is leptokurtic, the probability to have extreme values is higher, compared to a normal distribution, while the probability of extreme values in the case of variables with a platykurtic distribution is lower. The results of the first equation were firstly performed using a standard Pooled Least Squares method (Table 4.2). It is noted that the regression model is marginally significant (R-squared ¼ 0.90 and Adjusted R-squared ¼ 0.87) and, from the perspective of the significance of the coefficients, it is a valid model (Prob Fstatistic ¼ 0.00). Expenditures on social insurance are positively correlated with GDP/capita, the number of active people, the number of active males, the number of employed males, and the number of males and females unemployed. Social security expenditures are negatively correlated with the number of female workers, the number of employees, the number of female employees, and the number of females unemployed. The results show that increasing the level of GDP/capita, the number of active people, the number of male employees, and the number of unemployed people, both males and females will increase social security expenditures, while reducing these expenditures is possible by increasing the number of active women, the number of people employed, especially women, and the number of unemployed.

EMP 3402440. 2279000. 7734000. 1180000. 2324914. 1.027603 2.556137 9.210186 0.010001 1.70E+08 2.65E+14

PGEXPSP 11,524.20 11,145.00 18,100.00 6150.000 3072.049 0.060400 2.101072 1.713882 0.424458 57,6210.0 4.62E+08

GDPCAP 2012.500 2012.500 2017.000 2008.000 2.901442 2.96E–17 1.775758 3.122436 0.209880 100,625.0 412.5000 EMPM EMPF 7031900. 4233700. 4870000. 2913000. 16,079,000 9418000. 2303000. 1481000. 4752819. 2844004. 0.936847 0.929999 2.429199 2.392123 7.992792 7.977309 0.018382 0.018525 3.52E+08 2.12E+08 1.11E+15 3.96E+14

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

Table 4.1 Descriptive analysis of model I variables ACT –20,137.16 –91.50000 82,361.00 –195,170.0 53,320.52 –1.199876 4.369242 15.90341 0.000352 –1006858. 1.39E+11 UNE 29.71200 29.65000 32.80000 26.30000 1.365858 –0.252253 3.426298 0.908866 0.634808 1485.600 91.41280

ACTM 7636200. 5203500. 17,153,000 2668000. 5166757. 0.974751 2.467496 8.508581 0.014203 3.82E+08 1.31E+15 UNEM 601,700.0 402,000.0 1793000. 155,000.0 451,322.6 1.511391 4.041237 21.29455 0.000024 30,085,000 9.98E+12 UNEF 35.31600 35.45000 38.90000 31.10000 1.854763 –0.439493 3.118262 1.638754 0.440706 1765.800 168.5672

ACTF 22.62000 23.45000 28.60000 16.80000 3.167694 –0.147320 2.046475 2.075046 0.354331 1131.000 491.6800

84 4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

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85

Table 4.2 Econometric test results—economic impact—ordinary least squares (OLS) Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:22 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient C –51,541.87 GDPCAP 14.51363 ACT 0.015298 ACTM 0.087271 ACTF –12.87371 EMP –0.097762 EMPM 0.020233 EMPF –0.115730 UNE –442.6156 UNEM 0.019796 UNEF 1404.498 Root MSE 975.0324 Mean dependent var 11,524.20 S.D. dependent var 3072.049 Akaike info criterion 17.04282 Schwarz criterion 17.46346 Hannan–Quinn criterion 17.20300 Durbin–Watson stat 0.742493

Std. error 207,511.1 105.4382 0.006929 0.348463 77.56382 0.350333 0.017418 0.352036 684.4208 0.016893 572.7021 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic)

t-Statistic –0.248381 0.137651 2.207721 0.250445 –0.165976 –0.279055 1.161592 –0.328745 –0.646701 1.171791 2.452406

Prob. 0.8051 0.8912 0.0332 0.8036 0.8690 0.7817 0.2525 0.7441 0.5216 0.2484 0.0188 0.897209 0.870852 1104.007 47,534,405 –415.0705 34.04100 0.000000

Source: Author’s processing using EViews 10 Academic Edition software

Table 4.3 Econometric test results—economic impact— correlation matrix

CZ HU PL RO SK

CZ 1 –0.0615 0.3665 –0.2073 0.2422

HU

PL

RO

SK

1 –0.0678 –0.0657 –0.7763

1 –0.2485 0.4971

1 0.0332

1

Source: Author’s processing using EViews 10 Academic Edition software

As the study takes into account the specific situation of some CEE countries, the analysis of the links between those countries is considered relevant (Table 4.3). As a result, the correlation matrix of CEE countries in the case of the first econometric model regarding the economic impact of pension systems identifies their independence, “r” coefficient having subunitary values. The Czech Republic is

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Table 4.4 Fixed effects test results—redundant fixed effects

Redundant fixed effects tests Pool: ECO Test cross-section fixed effects Effects test Statistic Cross-section F 30.561952 Cross-section Chi-square 75.123745

d.f. (4.35) 4

Prob. 0.0000 0.0000

Source: Author’s processing using EViews 10 Academic Edition software

negatively correlated with Hungary and Romania and positively correlated with Poland and Slovakia. Hungary establishes negative correlations with all four other countries, and Poland and Romania have a positive correlation with Slovakia. The first model testing by the standard OLS method started from the premise of a single free constant for all five CEE countries and for the whole period analyzed, without taking into account the specific effects that could exist at the level of each country or period. As a result, it was also considered appropriate to employ the OLS model with effects. To determine the need for OLS modeling with fixed effects, the Redundant Fixed Effects test was performed (Table 4.4). The probabilities of the F test and Chi-square test reveal the acceptance of individual cross-section effects in tests. The test results by Pooled Least Squares method with cross-section fixed effects highlight a significant degree of the regression model (R-squared ¼ 0.98 and Adjusted R-squared ¼ 0.97) and, from the perspective of the significance of coefficients, it is a valid model (Prob F-statistic ¼ 0.00) (Table 4.5). The individual effects specific to CEE countries influence the correlations between variables. Thus, there is a positive correlation between social security expenditures and the level of GDP/capita, the number of active males, the number of employed males and females, and the number of unemployed. At the same time, there is a negative correlation between social security expenditures and the number of active persons, the number of active females, the number of employees, and the number of unemployed males and females. These results suggest that social security expenditures will increase with the increase in GDP/capita, the number of active males, the number of male and female employees, and the number of unemployed. On the other hand, social security expenditures can be reduced by increasing the number of active people, the number of active females, the number of employed people, the number of unemployed males and females. The correlation matrix between CEE countries reveals their independence, the “r” coefficient having subunitary values (Table 4.6). Romania is positively correlated with all four CEE countries. The Czech Republic negatively correlates only with Poland, Hungary is negatively correlated only with Slovakia, and Poland is negatively correlated only with the Czech Republic, being established positive correlations with all other CEE countries.

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87

Table 4.5 Econometric test results—economic impact—OLS with cross-section fixed effects Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:25 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient Std. error t-Statistic C –530241.2 266193.3 –1.991941 GDPCAP 268.6322 134.8660 1.991846 ACT –0.000770 0.005755 –0.133755 ACTM 0.006275 0.180841 0.034698 ACTF –6.083111 168.7048 –0.036058 EMP –0.014068 0.181396 –0.077556 EMPM 0.000623 0.012051 0.051662 EMPF 0.000940 0.180754 0.005198 UNE 719.9023 553.3584 1.300969 UNEM –0.001910 0.012009 –0.159073 UNEF –775.2569 397.0924 –1.952334 Fixed effects (cross) CZ—C 6462.206 HU—C 2603.338 PL—C –8903.536 RO—C –7306.045 SK—C 7144.037 Effects specification Cross-section fixed (dummy variables) Root MSE 460.0031 R-squared Mean dependent var 11,524.20 Adjusted R-squared S.D. dependent var 3072.049 S.E. of regression Akaike info criterion 15.70034 Sum squared resid Schwarz criterion 16.27395 Log likelihood Hannan–Quinn criterion 15.91878 F-statistic Durbin–Watson stat 1.334057 Prob(F-statistic)

Prob. 0.0542 0.0542 0.8944 0.9725 0.9714 0.9386 0.9591 0.9959 0.2018 0.8745 0.0589

0.977121 0.967969 549.8089 10,580,142 –377.5086 106.7699 0.000000

Source: Author’s processing using EViews 10 Academic Edition software

4.3.2

Model II: The Social Impact of Pension Systems

Model II envisages testing the social impact of pension systems and uses the regression equation (4.2) presented in the part dedicated to research methodology. The descriptive analysis of the variables used in the model reveals, through the JB test, for the 5% significance threshold, a normal distribution of the following

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4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

Table 4.6 Econometric test results—economic impact— OLS correlation matrix— cross-section fixed effects

CZ HU PL RO SK

_CZ 1 0.8375 0.0557 0.8324 0.1005

_HU

_PL

_RO

_SK

1 0.1291 0.8617 0.19032

1 0.0956 0.1119

1 0.2141

1

Source: Author’s processing using EViews 10 Academic Edition software Table 4.7 Descriptive analysis of model II variables Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev. Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

PGEXPSP POPT NMIGR 11,524.20 28.83000 11.19000 11,145.00 28.90000 10.35000 18,100.00 30.00000 13.50000 6150.000 26.70000 9.500000 3072.049 0.903338 1.445507 0.060400 –0.845793 0.391143 2.101072 2.804587 1.324391 1.713882 6.040940 7.124242 0.424458 0.048778 0.028379 576,210.0 1441.500 559.5000 4.62E+08 39.98500 102.3850 DWL DWLM 3125300. 32.58200 2109000. 32.60000 7237000. 35.90000 1018000. 28.70000 2129741. 1.597918 0.976025 –0.432871 2.494083 3.311385 8.471777 1.763482 0.014467 0.414061 1.56E+08 1629.100 2.22E+14 125.1138

TCHPOP –14,244.90 –1088.500 35,100.00 60,447.00 26,986.46 –0.191173 1.893454 2.855486 0.239850 –712,245.0 3.57E+10 DWLF 3906700. 2769500. 8842000. 1278000. 2624644. 0.903439 2.375064 7.615319 0.022200 1.95E+08 3.38E+14

Source: Author’s processing using EViews 10 Academic Edition software

descriptive variables: total population, net migration, duration of working life, and working life of women. Regarding asymmetry, the Skewness coefficient shows negative values for the total population, total population change, and duration of working life of men, all other variables having a positive asymmetry. The Kurtosis coefficient shows a leptokurtic distribution only for the variable duration of working life of women, all other variables have values below 3 of the indicator, which means their platykurtic distribution and a low probability of having extreme values (Table 4.7).

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Table 4.8 Econometric test results—social impact—OLS Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:40 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient C –47,877.27 POPT 1653.931 NMIGR –574.0767 TCHPOP 0.009176 DWL –0.000825 DWLM 609.7697 DWLF 0.000252 Root MSE 702.9075 Mean dependent var 11,524.20 S.D. dependent var 3072.049 Akaike info criterion 16.22833 Schwarz criterion 16.49601 Hannan–Quinn criterion 16.33026 Durbin–Watson stat 0.980907

Std. error t-Statistic 4912.897 –9.745220 176.2569 9.383639 195.8101 –2.931803 0.010489 0.874798 0.001478 –0.558421 106.8026 5.709314 0.001199 0.210383 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob (F-statistic)

Prob. 0.0000 0.0000 0.0054 0.3865 0.5795 0.0000 0.8344 0.946579 0.939125 757.9646 24,703,945 –398.7082 126.9872 0.000000

Source: Author’s processing using EViews 10 Academic Edition software

The result of testing the regression equation for model II was initially performed by the standard Pooled Least Squares method (Table 4.8). The regression model is significant (R-squared ¼ 0.95 and Adjusted R-squared ¼ 0.94) and from the perspective of the significance of the regression coefficients, the model is valid (Prob F-statistic ¼ 0.00). Model II tests show a positive correlation between social security expenditures and total population, population change, and the duration of work of males and females, but a negative correlation between social security expenditure, net migration, and duration of working life. These results show that with the increase in population and working period, for both men and women, social insurance expenditure will also increase, while increasing migration will lead to a reduction in social insurance expenditures. The correlation matrix of CEE countries in case of an econometric model regarding the social impact of pension systems identifies subunitary values of “r” coefficient, which means the independence of the variables. The Czech Republic, Poland, and Romania are positively correlated with all four other CEE countries, the only negative correlation being established between Hungary and Slovakia (Table 4.9).

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Table 4.9 Results of econometric tests—social impact— correlation matrix of the OLS model

CZ HU PL RO SK

_CZ 1 0.5506 0.4975 0.6793 0.3847

_HU

_PL

_RO

_SK

1 0.1724 0.45181 –0.3179

1 0.5846 0.7763

1 0.4654

1

Source: Author’s processing using EViews 10 Academic Edition software Table 4.10 Test results—redundant fixed effects Redundant fixed effects tests Pool: ECO Test cross-section and period fixed effects Effects test Cross-section F Cross-section Chi-square Period F Period Chi-square Cross-section/period F Cross-section/period Chi-square

Statistic 15.097029 55.145771 19.109338 95.349565 18.278402 109.418389

d.f. (4.30) 4 (9.30) 9 (13.30) 13

Prob. 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

Source: Author’s processing using EViews 10 Academic Edition software

Model II tested by the standard OLS method does not take into account specific effects of country or period effects, so it was considered, given the purpose of the research, the extension of tests by applying OLS methods with effects. The Redundant Fixed Effects test highlighted that the effects are not redundant and it is accepted to test the individual effects, both cross-section and temporal (Table 4.10). The second regression model tested by Pooled Least Squares method with fixed cross-section and period effects is very significant in terms of the values of Rsquared (0.99) and Adjusted R-squared (0.99) and is validated by the F test (Prob F-statistic ¼ 0.00) (Table 4.11). The influence of individual effects on the model is reflected in the change of the correlation of variables so that it can be noticed the existence of a negative correlation between social security expenditures and total population, net migration, population change, and duration of working life of men. Social security expenditures are positively correlated with women’s working life, which means that with the increase in the period in which women work, social security expenditures will also increase. The increase in population, migration, total population change, and duration of working life will lead to a reduction of social security expenditures. Regarding the correlation matrix of CEE countries in the case of the econometric model with cross-section and period-fixed effects is noted their independence and subunitary values of the coefficient “r”. Czech Republic correlates positively with Hungary and negatively with the other three CEE countries, Hungary has a positive correlation with Romania, and with Poland and Slovakia it is negatively correlated.

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91

Table 4.11 Econometric test results—social impact—OLS cross-section and period-fixed effects Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:41 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient C 49,053.91 POPT –796.1134 NMIGR –1011.513 TCHPOP –0.004549 DWL –0.004421 DWLM –438.3875 DWLF 0.006342 Fixed effects (cross) CZ—C 7628.967 HU—C 6141.639 PL—C –14,991.86 RO—C –6832.625 SK—C 8053.884 Fixed effects (period) 2008—C –1544.113 2009—C –2202.202 2010—C –1185.126 2011—C –693.5781 2012—C –366.0275 2013—C –164.7505 2014—C 102.7518 2015—C 1330.307 2016—C 1599.944 2017—C 3122.794 Effects specification Cross-section fixed (dummy variables) Period fixed (dummy variables) Root MSE 235.3424 Mean dependent var 11,524.20 S.D. dependent var 3072.049 Akaike info criterion 14.55996 Schwarz criterion 15.32477 Hannan–Quinn criterion 14.85120 Durbin–Watson stat 1.405704

Std. error 15,587.31 578.4321 488.0235 0.006502 0.001208 132.0817 0.001665

t-Statistic 3.147041 –1.376330 –2.072673 –0.699593 –3.658559 –3.319063 3.808313

R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob (F-statistic)

Source: Author’s processing using EViews 10 Academic Edition software

Prob. 0.0037 0.1789 0.0469 0.4896 0.0010 0.0024 0.0006

0.994012 0.990219 303.8257 2769302. –343.9990 262.0843 0.000000

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4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

Table 4.12 Econometric test results—social impact—OLS model correlation matrix with cross-section and period fixed effects

CZ HU PL RO SK

_CZ 1 0.1274 –0.8512 –0.2112 –0.6099

_HU

_PL

_RO

_SK

1 –0.1743 0.0503 –0.7156

1 –0.1879 0.6168

1 –0.3019

1

Source: Author’s processing using EViews 10 Academic Edition software Table 4.13 Hausman test for random effects

Correlated random effects—Hausman test Pool: ECO Test period random effects Test summary Chi-sq. statistic Chi-sq. d.f. Period random 45.479774 6

Prob. 0.0000

Source: Author’s processing using EViews 10 Academic Edition software

A positive correlation is established between Poland and Slovakia, these two countries were negatively correlated with all three other CEE countries (Table 4.12). Given that the cross-section variables are CEE countries, it is expected that there will be fixed effects, related to the national specifics. However, we aimed to extend the empirical study to random effects as well. According to the Hausman test for random effects, there is a correlation between temporal random effects and predictors, therefore it is recommended to use the OLS model with fixed effects (Table 4.13).

4.3.3

Model III: The Medical Impact of Pension Systems

The third model studies the medical impact of pension systems, using the regression equation (4.3) specified in the research methodology. Following the descriptive analysis of variables, it can be noticed the normal distribution of the number of births, fertility rate, the number of deaths, and dependency rate of the elderly population, for all other variables the probability of the JB test exceeds 5%, which shows that their distribution is not normal. Regarding the asymmetry, the fertility rate and the old dependency ratio show negative values of the Skewness coefficient, in the case of the other variables the indicator has positive values. The Kurtosis coefficient reflects the leptokurtic distribution of the number of births and dependency rate of the elderly population and the platykurtic distribution for the other variables (Table 4.14). The first tests were performed by the standard Pooled Least Squares method (Table 4.15). The results show that the model is significant (R-squared ¼ 0.96 and Adjusted R-squared ¼ 0.95) and viable (Prob F-statistic ¼ 0.00).

4.3 Empirical Results

93

Table 4.14 Descriptive analysis of the variables of model III Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev. Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

LBT 2.59E+10 1.74E+10 7.68E+10 8.31E+09 1.93E+10 1.479189 3.575850 18.92416 0.000078 1.30E+12 1.83E+22 DTT 8142298. 5160295. 18,429,700 2613688. 5698568. 0.949612 2.419302 8.217205 0.016431 4.07E+08 1.59E+15

LBR 172,034.2 111,713.5 417,589.0 54,823.00 121,833.4 0.987911 2.507352 8.638705 0.013308 8601708. 7.27E+11 DTR 96,445.38 63,693.50 207,671.0 26,499.00 64,188.93 0.615163 1.880605 5.764055 0.056021 4822269. 2.02E+11

FR 10.26000 10.30000 11.50000 8.800000 0.657453 –0.192907 2.506916 0.816632 0.664769 513.0000 21.18000 NCHPOP 89,833.68 64,884.50 195,181.0 24,847.00 56,915.68 0.595715 1.960987 5.206366 0.074038 4491684. 1.59E+11

MNAGECB 1.454800 1.450000 1.710000 1.230000 0.118032 0.330126 2.430524 1.583823 0.452978 72.74000 0.682648 OLDDR –5892.260 3046.500 67,739.00 –163,868.0 36,074.58 –2.205675 9.910760 140.0388 0.000000 –294,613.0 6.38E+10

Source: Author’s processing using EViews 10 Academic Edition software

The results show the direct and positive correlation between social insurance expenditures and the number of births, the average age of women at birth, the number of deceased persons, and the old dependency ratio, as well as the negative correlation between social security expenditures and birth rate, fertility, mortality rate and natural growth of population. Explicitly, these results mean that the increase in the number of births, the average age of women at birth, the number of deaths, and the dependency rate of the elderly population will lead to an increase in social security expenditure. On the other hand, increasing the birth rate, fertility, and mortality rates, as well as the natural growth of the population will lead to a reduction of social security expenditures. The correlation matrix of countries reflects subunitary values and their independence (Table 4.16). Czech Republic is negatively correlated with Slovakia and positively correlated with the other three CEE countries. Hungary is negatively correlated only with Romania and Slovakia, and Poland is positively correlated with all four other CEE countries. Romania is negatively correlated with Hungary and positively with the other four CEE countries. Slovakia is negatively correlated

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Table 4.15 Econometric test results—medical impact—OLS Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:48 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient C 1320.307 LBT 1.69E-07 LBR –0.022799 FR –794.1541 MNAGECB 14,820.38 DTT 0.001702 DTR –0.075042 NCHPOP –0.113937 OLDDR 0.007827 Root MSE 646.0320 Mean dependent var 11,524.20 S.D. dependent var 3072.049 Akaike info criterion 16.13958 Schwarz criterion 16.48374 Hannan–Quinn criterion 16.27063 Durbin–Watson stat 1.707726

Std. error t-Statistic 3120.525 0.423104 3.46E-08 4.874177 0.016649 –1.369418 386.8397 –2.052928 1532.830 9.668639 0.000450 3.779762 0.074072 –1.013102 0.068552 –1.662058 0.005082 1.540361 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob (F-statistic)

Prob. 0.6744 0.0000 0.1783 0.0465 0.0000 0.0005 0.3170 0.1041 0.1312 0.954874 0.946069 713.4229 20,867,864 –394.4894 108.4462 0.000000

Source: Author’s processing using EViews 10 Academic Edition software Table 4.16 Results of econometric tests—medical impact—correlation matrix of the OLS model

CZ HU PL RO SK

_CZ 1 0.3965 0.2649 0.1470 –0.1771

_HU

_PL

_RO

_SK

1 0.1957 –0.0159 –0.1539

1 0.2648 0.3257

1 0.6810

1

Source: Author’s processing using EViews 10 Academic Edition software

with the Czech Republic and Hungary and positively correlated with Poland and Romania. The standard OLS method assumes the absence of individual effects, specific to CEE countries and periods. Thus, it was considered appropriate to extend the study by the OLS method with effects. The Redundant Fixed Effects test showed that the cross-section and period effects are not redundant, therefore the OLS method with fixed effects can be applied (Table 4.17).

4.4 Conclusions and Personal Contributions

95

Table 4.17 Test results—redundant fixed effects Redundant fixed effects tests Pool: ECO Test cross-section and period fixed effects Effects test Cross-section F Cross-section Chi-square Period F Period Chi-square Cross-section/period F Cross-section/period Chi-square

Statistic 22.327013 71.629944 8.241215 64.722136 11.897669 93.773753

d.f. (4.28) 4 (9.28) 9 (13.28) 13

Prob. 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

Source: Author’s processing using EViews 10 Academic Edition software

The third regression model was tested by Pooled Least Squares method with fixed effects, both cross-section and period (Table 4.18). Following these tests, it is noticed that the model is significant (R-squared ¼ 0.99 and Adjusted Rsquared ¼ 0.99) and valid (Prob F-statistic ¼ 0.00). The influence of the effects on predictors determines that social security expenditures to be positively correlated with the number of births, fertility rate, and mortality rate, but to have a negative correlation with the birth rate, the average age of women at birth, the number of deaths, natural change of population and old dependency ratio. These results suggest that by increasing the number of births, fertility and mortality rates, and by lowering birth rates, the average age of women at birth, the number of deaths, the natural growth of population, and the dependency rate of the elderly population, will increase the social security expenditures. As regards the links between CEE countries, according to the correlation matrix and subunitary values of “r,” these are independent. It is noted the positive correlation between the Czech Republic and Hungary and the negative correlation of both countries with the other three CEE countries. Poland is positively correlated with Slovakia, with both countries establishing a negative correlation with the other three countries. Romania correlates negatively with all four CEE countries (Table 4.19). The empirical study can be extended by the OLS model with random effects. The results of the Hausman test for random effects show the existence of a correlation between temporal random effects and predictors, therefore the recommended model for testing is the one with fixed effects (Table 4.20).

4.4

Conclusions and Personal Contributions

The empirical results obtained from the econometric tests performed in this chapter are more relevant when using the OLS method with fixed effects, as the characteristic aspects of the five CEE countries are also captured.

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Table 4.18 Econometric results—medical impact—OLS cross-section and period-fixed effects Dependent variable: PGEXPSP Method: Pooled least squares Date: 02/25/20; Time: 12:50 Sample: 2008 2017 Included observations: 10 Cross-sections included: 5 Total pool (balanced) observations: 50 Variable Coefficient Std. error t-Statistic C 14,054.26 11,639.70 1.207442 LBT 4.11E-08 3.17E-08 1.296746 LBR –0.012694 0.011542 –1.099824 FR 1603.326 691.8803 2.317346 MNAGECB –8504.627 4129.365 –2.059548 DTT –7.79E-05 0.001271 –0.061279 DTR 0.083460 0.059610 1.400107 NCHPOP –0.143894 0.055713 –2.582798 OLDDR –0.003502 0.003226 –1.085625 Fixed effects (cross) _CZ—C 1525.251 _HU—C –1649.812 _PL—C 4656.640 _RO—C –893.7374 _SK—C –3638.341 Fixed effects (period) 2008—C –1681.368 2009—C –2392.264 2010—C –1615.976 2011—C –943.4182 2012—C –341.1292 2013—C 33.29344 2014—C 345.1767 2015—C 1544.324 2016—C 1764.977 2017—C 3286.383 Effects specification Cross-section fixed (dummy variables) Period fixed (dummy variables) Root MSE 252.9297 R-squared Mean dependent var 11,524.20 Adjusted R-squared S.D. dependent var 3072.049 S.E. of regression Akaike info criterion 14.78410 Sum squared resid Schwarz criterion 15.62539 Log likelihood Hannan–Quinn criterion 15.10447 F-statistic Durbin–Watson stat 1.313712 Prob (F-statistic) Source: Author’s processing using EViews 10 Academic Edition software

Prob. 0.2374 0.2053 0.2808 0.0280 0.0488 0.9516 0.1725 0.0153 0.2869

0.993083 0.987895 337.9915 3198671. –347.6025 191.4287 0.000000

4.4 Conclusions and Personal Contributions Table 4.19 Results of econometric tests—medical impact—correlation matrix of OLS model with cross-section and period-fixed effects

CZ HU PL RO SK

_CZ 1 0.0075 –0.5810 –0.2376 –0.7731

97 _HU

_PL

_RO

_SK

1 –0.0176 –0.0696 –0.3405

1 –0.3042 0.26328

1 –0.0550

1

Source: Author’s processing using EViews 10 Academic Edition software Table 4.20 Hausman test for random effects

Correlated random effects—Hausman test Pool: ECO Test period random effects Test summary Chi-sq. statistic Chi-sq. d.f. Period random 73.953483 8

Prob. 0.0000

Source: Author’s processing using EViews 10 Academic Edition software

Strengthening budgetary sustainability by reducing social security spending can be achieved by increasing the activity and employment rate, especially of women. In this respect, social policy must be linked to labor market regulations, where it is necessary to stimulate the entrepreneurial environment by providing subsidies, a favorable tax and fiscal policy, and the necessary infrastructure for the development of SMEs. At the same time, the development of professional activities in legal, taxed forms should be encouraged. Regarding the increase in the activity level in case of females, it must be taken into account the social role that women fulfill in birth and the raising of children, a solution in this sense being the development of part-time jobs, but also the regulation of home working. Econometric tests also highlighted the role of unemployment in reducing social security expenditures. The explanation lies in limiting access to all the benefits of the social protection system only for the period in which the unemployment benefit is received, subsequently the person benefiting only from the minimum benefits. From the perspective of the pension system, the incomes from unemployment benefits are lower than the income realized during the activity period, an aspect that will determine the decrease in the number of social contributions. However, a policy that favors unemployment does not bring economic benefits and is unsustainable in the long run. In order to reduce social security expenditure, increasing population and reducing migration play a key role. Increasing the population means adopting policies that stimulate young people to start families and achieve at least the minimum replacement rate. Attracting people from abroad requires the existence of a socioeconomic framework that allows their integration, and on the other hand, the exodus of the active population must be limited. All these are closely related to the national competitiveness and socioeconomic attractiveness of the country. At the same time, the expenditures with social protection can be reduced by increasing the

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4 Modeling the Impact of Socioeconomic and Medical Characteristics on Public. . .

duration of the working life of the population, so that longevity could be beneficial. In this regard, the accessibility of people over the age of 45 on the labor market should be facilitated by tax deductions, and the continuation of activity after the standard retirement age should be permitted according to the person’s health, as temporary and part-time contracts. Finally, reducing social security spending is possible by increasing the birth rate, reducing mortality, and consolidating a positive natural growth. Increasing the birth rate means primarily rising the fertility rate through sex education, planning, and family counseling programs to reduce the rate of abortions. In the aftermath, financial and social incentives, such as parental leave and allowances, access to extended daycare, and kindergarten services play an important role.

4.5

Summary

In this chapter, an empirical study was conducted on the impact of socioeconomic and medical characteristics on public pension systems implemented by CEE countries by highlighting the correlations between public spending on social protection of the population and the most relevant demographic and labor market indicators, and also the medical status of the population. Empirical studies confirm the correlations between expenditures for social protection of the population and economic development of the country, labor market activity and duration of professional activity, population number and change, and the dependency rate of the elderly population in the five CEE countries. The empirical results reflect the fact that strengthening the financial sustainability of public pension systems in CEE countries requires a higher level of activity and employment in the labor market. Even if the empirical results reflect a reduction in long-term social protection spending as unemployment rises, this does not bring economic benefits and is unsustainable.

References Balteș, N., Dumiter, F., David, D., & Jimon, Ș. (2018). Trends regarding the evolution of the Romanian pension system. Studia Universitatis “Vasile Goldis” Economics Series, 28(1), 1–16. Brockmann, H., Muller, R., & Helmert, U. (2009). Time to retire—Time to die? A prospective cohort study of the effects of early retirement on long-term survival. Social Science & Medicine, 69, 160–164. Cheng, L., Liu, H., Zhang, Y., & Zhao, Z. (2018). The health implications of social pensions: Evidence from China’s new rural pension scheme. Journal of Comparative Economics, 46, 53–77. Cipriani, G. P. (2018). Aging, retirement, and pay-as-you-go pensions. Macroeconomic Dynamics, 22, 1173–1183. Coe, N. B., & Zamarro, G. (2011). Retirement effects on health in Europe. Journal of Health Economics, 30, 77–86.

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Dieppe, A., & Guarda, P. (Eds.). (2015). Occasional paper series: Public debt, population ageing and medium-term growth, Occasional Paper No 165. European Central Bank. Di Liddo, G. (2018). Immigration and PAYG pension systems in the presence of increasing life expectancy. Economics Letters, 162, 56–61. Eatock D. (2015). European Union pension systems Adequate and sustainable? European Parliamentary Research Service. Eibich, P. (2015). Understanding the effect of retirement on health: Mechanisms and heterogeneity. Journal of Health Economics, 43, 1–12. Engels, B., Geyer, J., & Haan, P. (2017). Pension incentives and early retirement. Labour Economics, 47, 216–231. Falkstedt, D., Backhans, M., Lundin, A., Allebeck, P., & Hemmingsson, T. (2014). Do working conditions explain the increased risks of disability pension among men and women with low education? A follow-up of Swedish cohorts. Scandinavian Journal of Work, Environment and Health, 50(5), 483–492. Fe, E., & Hollingsworth, B. (2016). Short- and long-run estimates of the local effects of retirement on health. Journal of the Royal Statistical Society, A, 179(4), 1051–1067. Fenge, R., & Scheubel, B. (2017). Pensions and fertility: Back to the roots Bismarck’s Pension Scheme and the first demographic transition. Journal of Population Economics, 93–139. Fenge, R., & von Weizsäcker, J. (2010). Mixing Bismarck and child pension systems: An optimum taxation approach. Journal of Population Economics, 23, 805–823. Fitzpatrick, M. D., & Moore, T. J. (2018). The mortality effects of retirement: Evidence from Social Security eligibility at age 62. Journal of Public Economics, 157, 121–137. Haan, P., & Prowse, V. (2012). Longevity, life-cycle behavior and pension reform. MPRA Paper No. 39282. Available online at: https://mpra.ub.uni-muenchen.de/39282/. Hallberg, D., Johansson, P., & Josephson, M. (2015). Is an early retirement offer good for your health? Quasi-experimental evidence from the army. Journal of Health Economics, 44, 274–285. Han, K. J. (2013). Saving public pensions: Labor migration effects on pension systems in European countries. The Social Science Journal, 50, 152–161. Heijdra, B. J., & Romp, W. E. (2009). Retirement, pensions, and ageing. Journal of Public Economics, 93, 586–604. Heller-Sahlgren, G. (2017). Retirement blues. Journal of Health Economics, 54, 66–78. Jimon, Ș. A., Balteș, N., & Dumiter, F. (2020). Empirical approaches upon pension systems in central and eastern European countries. Triangle assessment: Free movement of people, labor market and population health features. Studia Universitatis “Vasile Goldis” Economics Series, 30(1), 1–21. Ju, Y. J., Han, K. T., Lee, H. J., Lee, J. E., Choi, J. W., Hyun, I. S., & Park, E. C. (2017). Quality of life and national pension receipt after retirement among older adults. Geriatrics and Gerontology International, 17, 1205–1213. Krumins, J., Berzins, A., Dahs, A., & Ponomarjova, D. (2019). Healthy and active pre-retirement and retirement ages: Elderly inequality in Latvia. In: 11th International scientific conference “New challenges of economic and business development—2019: Incentives for sustainable economic growth” proceedings (pp. 463–475). Kunze, L. (2014). Life expectancy and economic growth. Journal of Macroeconomics, 39, 54–65. Lacomba, J. A., & Lagos, F. (2010). Immigration and pension benefits in the host country. Economica, 77, 283–295. Mentzakis, E., & Moro, M. (2009). The poor, the rich and the happy: Exploring the link between income and subjective well-being. The Journal of Socio-Economics, 38, 147–158. Mitrut, A., & Wolf, F. C. (2011). Do private and public transfers received affect life satisfaction? Evidence from Romania. Journal of Economic Psychology, 32, 969–979. Narusyte, J., Ropponen, A., Alexanderson, K., & Svedberg, P. (2013). The role of familial factors in the associations between sickness absence and disability pension or mortality. European Journal of Public Health, 24(1), 106–110.

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Shin, I. (2012). The effect of pension on the optimized life expectancy and lifetime utility level. MPRA Paper No. 41374. Available online at: http://mpra.ub.uni-muenchen.de/41374/. Staubli, S., & Zweimüller, J. (2013). Does raising the early retirement age increase employment of older workers? Journal of Public Economics, 108, 17–32. Sundstrup, E., Hansen, A. E., Mortensen, E. L., Poulsen, O. M., Clausen, T., Rugulies, R., Møller, A., & Andersen, L. L. (2018). Retrospectively assessed psychosocial working conditions as predictors of prospectively assessed sickness absence and disability pension among older workers. BMC Public Health, 18, 149–160. Verbic, M., & Spruk, R. (2011). Aging population and public pensions: Theory and evidence. MPRA Paper No. 38914. Available online at: https://mpra.ub.uni-muenchen.de/38914/. Wang, L. (2015). Fertility and unemployment in a social security system. Economics Letters, 133, 19–23.

Chapter 5

Private Pension Funds

The sociodemographic situation in CEE, characterized by the reduction of birth rate and increased share of elderly, draws attention to national social protection systems and in particular to public pension systems. The direct link between the labor market and public pension systems, based on the principle of social solidarity between generations, runs the risk of diminishing budgetary resources obtained from social contributions, while spending on benefits will increase, due to a higher number of beneficiaries, as well as due to the increase in life expectancy, which will determine that the period for which the benefits will be provided will be longer. The solution proposed by WB for maintaining the sustainability of the public pension system is to diversify funding sources and encourage individual savings. The transition to a democratic system, accession and integration in the EU of countries that were part of the former communist bloc led to the reconfiguration of pension systems to reflect the new socioeconomic and demographic conditions from CEE countries (Bonenkamp et al., 2017). The Directive of the Council of Europe no. 49/1998 refers to the right to social protection of persons pursuing professional activities in the territory of the Member States, concerning taxpayers of a supplementary pension scheme or an occupational pension scheme. The provisions of the Directive ensure equality in accessing the benefits provided by them, in case of nonresidents, as well as the transfer of these rights to another EU Member State.1 Directive no. 50/2014 strengthens the right to Art. 4 of Directive no. 49/1998 provides that “Member States shall take the necessary measures to ensure the preservation of vested pension rights for members of a supplementary pension scheme in respect of whom contributions are no longer being made to that scheme as a consequence of their moving from one Member State to another, to the same extent as for members in respect of whom contributions are no longer being made but who remain within the same Member State. This Article shall also apply to other persons holding entitlement under the rules of the supplementary pension scheme in question,” and Art. 5 states that “Member States shall ensure that, in respect of members of supplementary pension schemes, as well as others holding entitlement under such schemes, supplementary pension schemes make payment in other Member States, net of any taxes and transaction charges, which may be applicable, of all benefits due under such schemes.” 1

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_5

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social protection of EU citizens and regulates the minimum requirements for the organization and functioning of supplementary pension schemes implemented by the Member States.2 Supplementary pensions have been developed as a complementary form of the public pension system, with the main role of increasing the incomes of beneficiaries and maintaining living standards and consumption during retirement. Additional forms of pensions refer to occupational pensions, defined as “pension scheme established in conformity with national legislation and practice such as a group insurance contract or pay-as-you-go scheme agreed by one or more branches or sectors, funded scheme or pension promise backed by book reserves, or any collective or other comparable arrangement intended to provide a supplementary pension for employed or self-employed persons” (Art. 3b) of Council Directive 98/49/EC). In the EU, supplementary pension schemes are mainly present in the northwestern states of the continent, while in countries of the central, eastern, and southern parts of the continent, they have very low coverage. Among the causes that determine the underdevelopment of supplementary pension schemes are the preference for nonfinancial instruments, the low profitability of financial markets, the modest level of income disposable to population, the insufficiency of social partners (European Commission-Directorate-General for Employment, Social Affairs and Inclusion, 2018). CEE countries have transposed Community provisions into national law and regulated and implemented private pension funds, following the Argentine multipillar model (Bonoli & Palier, 2007). Private pension funds are, from a legal point of view, contracts whose explicit object is the provision of financial resources after retirement, complementary or which replaces public pension schemes. They can be found as occupational pension funds, conditioned by the existence of an employment contract, or as individual pension funds, often called personal pension funds, which offer the possibility to anyone to join a private pension fund. Occupational pension schemes are usually organized by employers or trade unions. Depending on the obligation to join and contribute to private pension funds, can be identified mandatory private pension funds, imposed by national legislation, and voluntary pension funds, in which participation is voluntary (Impavido, 2013). The presence of these types of private pension funds in CEE countries is summarized in Table 5.1.

According to Art. 5, Para. (2) of Directive no. 50/2014 “Member States shall, with regard to the nature of the pension scheme rules and practice, adopt the measures necessary to ensure that outgoing workers’ and their survivors’ dormant pension rights or their values are treated in line with the value of the rights of active scheme members or the development of pension benefits currently in payment, or are treated in other ways which are considered as fair.” 2

5.1 Mandatory Private Pension Funds

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Table 5.1 Private pension funds implemented in CEE countries

Czech Republic Hungary Poland Romania Slovakia

Mandatory private pension funds No

Occupational pension funds No

Optional individual pension funds Yes

Revoked in 2011 Revoked in 2014 Yes Yes

Yes Yes No No

Yes Yes Yes Yes

Source: Author’s synthesis based on the OECD publication “Pensions Markets in Focus (2019)” (http://www.oecd.org/pensions/private-pensions/pensionmarketsinfocus.htm)

5.1

Mandatory Private Pension Funds

Mandatory private pension funds, respectively P2 proposed by WB, aim to reduce the financial pressure within the public pension system and ensure an adequate replacement rate of income, so that the living standard of beneficiaries to be maintained at a similar level to the one had in the period of professional activity. This pillar is, in fact, a hybrid form of financial insurance for the elderly, formed by combining some features of the public pension system with aspects specific to privately managed pension funds. Thus, this pillar is compulsory and is based on the principle of contributivity, but the management of financial resources is performed in nominal accounts that reflect the contribution history of each participant. In CEE countries, Hungary and Poland were the first to regulate the organization, operation, and administration of privately managed pension funds. In Hungary, P2 was regulated in 1997 and was addressed to all employees up to the age of 47. The financing was based on the distribution of 6% of participant’s gross income, a percentage that should have increased to 8.5% by 2003. Szikra (2018) points out that with the maturity of P2 pension funds, the positive effects on the capital market and on the labor market have been modest, and moreover, the costs of privatization have increased the public system deficit, but pension fund yields have been below expectations. As a result, in 2011, the nationalization of the pension funds of P2 was decided. A similar path is encountered in the case of P2 pension funds implemented in Poland. In this country, the formation and operation of P2 were regulated in 1998. P2 funding was based on the distribution of 7.3% of the gross income of taxpayers, participation being mandatory for all employees up to 30 years. In 2014, it was decided to close the mandatory private pension funds, the motivation being the low profitability and the growing deficit of the public pension system budget (OECD, 2019b). Drahokoupil and Domonkos (2012) point out that the cancelation of some reforms in CEE was a specific reaction to “socialist legacy,” financial circumstances of the 2007 economic crisis, and new economic policy guidelines that do not support

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the indebtedness of future generations. However, Slovakia and Romania maintained the functioning of P2, although they reduced the percentage of contributions. In Slovakia, the implementation of P2 has been carried out since 2005, and participation was mandatory for all newly hired people. P2 financing was based on participants’ contribution, the share of contributions being 9% of salary income and other income assimilated into salaries. On the background of the socioeconomic situation resulting from the financial crisis, starting with 2012 this percentage decreased by 5%, and starting with 2017 the contributivity gradually increased by 0.25%, reaching 6% in 2024 (OECD, 2007, 2019a). At the beginning of 2018, the number of participants of pension funds of P2 reached 1,425,843 people.3 There are 17 mandatory private pension funds in Slovakia, managed by five management companies. The main features of pension funds operating in Slovakia are summarized in Table 5.2. Each pension fund management company holds two types of funds, namely: guaranteed pension funds, consisting mainly of bonds and deposits, and unguaranteed pension funds, with an investment portfolio consisting of different financial instruments: shares, stock indices, or mixed portfolios. The risk associated with guaranteed pension funds is minimal. Usually, joining a privately managed pension fund is done through personal option, depending on personal risk profile, determined based on a questionnaire, managed by the Association of Pension Management Companies (ADSS). The supervision of administrators’ activity regarding private pension funds is performed by the National Bank of Slovakia. The distribution of benefits is made as an old-age pension, including an early retirement pension, conditioned on reaching the standard retirement age provided in the public pension system. In case of the death of a participant related to a P2 pension fund, the accumulated assets are distributed to the descendants.4 Romania regulated P2 in 2004 and the effective implementation occurred on July 1, 2006. Law no. 411/2004 regulates the organization and functioning of P2, as well as the activity of the administrators of private pension funds in Romania, aspects summarized in Annex. In Romania are seven privately managed pension funds with moderate and highrisk profiles, the main characteristics of them and of the administrators are summarized in Table 5.3. The entry into force of the law imposed the obligation of participation to P2 for all taxpayers up to 35 years and voluntary participation for persons aged between 35 and 45 years.5 Joining a privately managed pension fund is done either by 3

According to the International Organization for the Supervision of Pensions. Available online at: http://www.iopsweb.org/researchbycountry/. 4 According to the Association of Pension Management Companies (ADSS). Available online at: https://www.adss.sk/asociacia-dss. 5 Art. 30 of Law no. 411/2004 establishes the obligation to contribute to privately managed pension funds of all persons who earn income from salaries and similar payments and are insured in public pension system, except for persons “who carry out activities in the construction sector and who fall

11,949,810.48

Československá obchodná banka, a.s.

Slovenská sporiteľňa, a.s.

Poštová banka, a. s.

NN Životná poisťovňa, a.s.

Dôchodková správcovská spoločnosť Poštovej banky d.s.s., a.s.

NN dôchodková správcovská spoločnosť, a.s.

10,023,200

47,924,980

UniCredit Bank Czech Republic and Slovakia, a.s.

AXA životní pojišťovna a.s.

AXA d.s.s., a.s.

Capital (euro) 37,177,280

Depository Tatra banka, a.s.

Main shareholder Allianz - Slovenská poisťovňa, a.s.

Management company Allianz - Slovenská dôchodková správcovská spoločnosť, a.s.

Table 5.2 Mandatory private pension funds in Slovakia

Index global Solid

Index euro

Harmónia

Dynamika

Stabilita

Prosperita

Perspektíva

Indexový

Dlhopisový

Akciový

Progres

Pension fund Garant

(continued)

Type of pension fund Guaranteed— bonds Unguaranteed— shares Unguaranteed— shares Guaranteed— bonds Unguaranteed— index Unguaranteed— index Unguaranteed— shares Guaranteed— bonds Unguaranteed— shares Unguaranteed— mixt Unguaranteed— index Unguaranteed— index Guaranteed— bonds

5.1 Mandatory Private Pension Funds 105

Main shareholder 1. VUB a.s. 2. GENERALI poisťovňa, a.s.

Depository UniCredit Bank Czech Republic and Slovakia, a.s.

Capital (euro) 10,090,976

Profit

Mix

Klasik

Pension fund Index

Type of pension fund Unguaranteed— index Guaranteed— bonds Unguaranteed— mixt Unguaranteed— shares

Source: Author processing based on data published by the National Bank of Slovakia (https://subjekty.nbs.sk/?aa¼select_sector&bb¼5&cc¼&qq¼)

Management company VÚB Generali dôchodková správcovská spoločnosť, a.s.

Table 5.2 (continued)

106 5 Private Pension Funds

5.1 Mandatory Private Pension Funds

107

Table 5.3 Mandatory private pension funds in Romania Mandatory private pension fund Aripi

Private pension fund management company

AZT viitorul tău BCR

AllianzŢiriac Pensii Private BCR Pensii

BRD

BRD

Metropolitan life

Metropolitan Life

NN

NN Pensii

Vital

AEGON Pensii

Name Generali

Shareholders 1. Generali CEE Holding B. V. 2. Generali Romania Asigurare - Reasigurare S.A. 1. Allianz - Ţiriac Asigurări S.A. 2. Tiriac Holdings Limited 1. Banca Comercială Română S.A. 2. Zbîrcea Gabriel 1. Sogecap 2. BRD - Groupe Société Générale S.A. 1. Metlife EU Holding Company Limited 2. Metlife Services Spolka z Ograniczona Odpowiedzialnoscia 1. NN Continental Europe Holdings B.V. 2. NN Asigurări de Viaţă S. A. 1. AEGON Poland/Romania Holding B.V. 2. AEGON Czech Republic Holding B.V.

Depository BRD - Groupe Societe Generale S.A.

Capital (lei) 67,000,000

BRD - Groupe Societe Generale S.A. BRD - Groupe Societe Generale S.A. Banca Comercială Română S.A. Unicredit Bank S.A.

32,375,000

88,471,840

35,970,000

94,561,700

BRD - Groupe Societe Generale S.A.

206,100,000

BRD - Groupe Societe Generale S.A.

72,000,000

Source: Author processing based on data published by ASF (https://asfromania.ro/)

personal option or by automatic distribution, if the taxpayer does not express his choice.6 Joining a privately managed pension fund is done once is signed the accession contract, which specifies the rights and obligations of parties, as well as risks and their distribution. Thus, is opened an individual account, which highlights the contributions paid, the value of fund units, and the net assets. However, a

under the conditions provided in art. 60 point 5 of Law no. 227/2015, in the period January 1, 2019 – December 31, 2028 inclusive.” 6 According to Art. 33, Para. (1) of Law no. 411/2004, “the person who did not join a pension fund within 4 months from the date on which he or she is obliged by law is randomly assigned to a pension fund by the evidence institution,” and according to Para. (4) of the same article of Law no. 411/2004 “each administrator shall inform, in writing, within 30 days of notification, the participants who have been randomly assigned to the fund under its administration by the evidence institution regarding the name of the privately managed pension fund and of its administrator.”

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5 Private Pension Funds

participant has the right to transfer to another pension fund, after prior notification of the transfer to the initial fund administrator.7 Since the implementation of P2, four pension funds have been written off by the decision to deregister the management companies. Thus, BCR privately managed pension fund absorbed Omniforte, Prima Pensie, and OTP funds; Metropolitan Life was formed from AIG and VIVA funds, and Vital absorbed EUREKO pension fund, which in turn incorporated BANCPOST and KD pension funds. Subsequently, the ING pension fund changed its name to NN. The withdrawal of contributions is made by redirecting a share of social contributions paid to the public social insurance system to the money market and capital market. Croitoru (2015) mentions that, in the short term, the funds mobilized toward this pillar have a negative impact on the financial sustainability of the public pension system, but in the long term it ensures an adequate level of pensioners’ incomes. From this perspective, the decision to privatize the pension system must be correlated with the national socioeconomic and political context. Law no. 411/2004 provided the redistribution of a share of 2% of the total contribution paid by an insured to the public pension system to a privately managed pension fund, following that each year the share will be increased by 0.5% up to the maximum value of 6%.8 This provision was not strictly respected, being observed a slight gap, which since 2016 increased (Fig. 5.1). The decision to reduce the contribution rate to privately managed pension funds to 3.75% in 2018 and maintaining it in 2019 is due to the low returns obtained from these funds. Also, one reason that supported this decision was the deficit registered by the State Social Insurance Budget, but also the low confidence of citizens in P2. The participation of the population in privately managed pension funds increased by approximately 2,930,500 people between December 2008 and December 2019. The distribution of participants by age group reveals a reduction in the share of participants under the age of 35 by 22% compared to December 2008. This statistic reflects the demographic situation of Romania, as well as the reduction of the number of young employees on the labor market. Regarding the distribution of participants by sex, a minor difference can be noticed between the number of females and males, in favor of the latter. Contribution to a privately managed pension fund confers the right to benefit from a private pension, once the eligibility conditions for accessing the old-age

Art. 39 of Law no. 411/2004 stipulates that “if a participant wishes to join another pension fund, he or she is obliged to notify the administrator of the pension fund from which he or she is transferring in writing, with 30 days before the effective accession to the new pension fund, and send him a copy of the new act of accession,” and “the quality of participant in the old pension fund ceases on the date of the transfer of funds, and the quality of participant in the new pension fund begins at the same time.” 8 Art. 43 of Law no. 411/2004 states that “the calculation base, the withholding and the terms of payment of the contribution to pension fund are the same as those established for the social insurance contribution,” and “the share of contribution to the pension fund is 2% of the calculation base. Starting with January 1st, 2018, the contribution rate to the pension fund is 3.75%.” 7

5.1 Mandatory Private Pension Funds

109

Fig. 5.1 Contribution rate to privately managed pension funds in Romania. Source: Author processing based on Law 411/2004, of the Laws of the state social insurance budget from 2008 to 2019

pension within the public pension system are met.9 The redistribution of the pension is made based on an actuarial calculation, depending on net assets available in the individual account of participants, but its value may not be less than the total value of the contributions paid.10 This provision does not apply if the beneficiary of the private pension suffers from a permanent disability, the value of the net asset is reduced, as well as if the beneficiary is not a participant in the privately managed pension fund, but is the legal heir of the net asset.11 The Supervisory Commission of the Private Pension System (CSSPP) establishes the rules for the redistribution of the minimum private pension. The payment of entitlements may be made in a single

According to Art. 135 of Law no. 411/2004 “the participant is entitled to a private pension from the date of fulfilling the retirement conditions for the old-age pension in public system.” 10 Article 135, Para. (2) of Law no. 411/2004 stipulates that “the total amount due for the private pension may not be lower than the value of the contributions paid, less the transfer penalties and legal fees.” 11 According to Art. 136, the personal net asset is distributed “within 30 days from the proof of being” in one of the following categories: “a) beneficiaries who do not have the quality of participant; b) persons retired from disability for diseases that no longer allow the resumption of activity, defined by the provisions of Law no. 19/2000, with further modifications and updates, and whose personal net assets at the date of withdrawal are too small to receive a private pension; c) persons whose personal net assets at the date of withdrawal are too small to be able to receive a private pension.” These people will receive a single payment or installments for a maximum time of 5 years, upon request. 9

110

5 Private Pension Funds

installment or in installments for a maximum period of 5 years,12 in country or abroad.13

5.2

Voluntary Private Pension Funds

Voluntary private pension schemes, respectively, P3 promoted by WB, are an alternative for investing personal savings and a way to supplement income during retirement. It is also a solution for the financial security of people who do not meet the eligibility criteria for accessing the benefits provided by the public pension system, as well as if the amount of benefits is very modest. Voluntary private pension funds have been more successful than mandatory private pension funds and occupational pension funds in CEE countries. In all five CEE countries included in the research, voluntary pension funds are organized and managed by financial investment companies. With the authorization of the pension fund administration by the competent national body, the financial investment company may open personal accounts to highlight the contribution and the evolution of the participant’s assets, and by fulfillment of retirement conditions specified in legislation and accession contract, the optional pension will be distributed. The first regulations regarding the organization of voluntary private pension funds (related to the countries included in the research) appeared in Hungary and the Czech Republic. In Hungary, voluntary pension funds have been operational since 1994, and at the time of their implementation, participants benefited from multiple tax reductions and deductions (Simonovits, 1999). Optional pension funds in Hungary comprise both voluntary pension funds and pension savings accounts and insurances provided by financial investment companies.14 According to the Report on Insurance, Funds and Capital Market Risks published by the National Bank, at the end of 2018, there were 37 institutions in Hungary that manage voluntary pension funds, with a number of 1,134,000 participants and assets worth 1.403 billion of forints (Hergár, 2019).

12 Norm no. 27/2017, Art. 6, Para. (5) and Para. (8) state that payments “shall be calculated based on the last unitary net asset value, calculated and reported by administrator and depositary for the business day preceding the day on which the transfer is made.” Available online at: https:// asfromania.ro/legislatie/legislatie-sectoriala/legislatie-pensii/legislatie-secundara-pensii/normepensii. 13 According to Art. 35, Para. (4) of Law no. 411/2004 “the participant’s rights may be transferred to other countries in which he or she has his domicile or residence, under the conditions regulated by the international agreements and conventions to which Romania is a party, in the currency of those countries or in another currency agreed.” 14 Hungarian Ministry for National Economy Central Administration of National Pension Insurance, Country Fiche on Pension Hungary. Available online at: https://ec.europa.eu/info/sites/info/files/ economy-finance/final_country_fiche_hu.pdf.

5.2 Voluntary Private Pension Funds

111

In the Czech Republic, supplementary pension funds have been operating since 1994 and are addressed to the resident population earning income using retirement insurance contracts. At the date of implementation of P3, 44 pension funds were authorized (Hlaváč, 2011), and based on this, in 2013 the voluntary pension funds were regulated as a pillar of the national pension system. At the end of 2019, there were a number of 28 optional private pension funds, ran by eight companies that managed 4,441,429 participants and assets worth 487.1 billion crowns. According to the 2013 legislation, the minimum contribution of a participant is 100 crowns, the state granting a contribution, depending on the amount of the participant up to 230 crowns.15 Poland regulated the organization and operation of voluntary pension funds in 1997 and by the end of 2019, ten voluntary pension fund management companies had been authorized.16 The number of active participants reached 15,890,284 people, and the total number of personal accounts managed is approximately 16,209,063. The net assets of voluntary pension funds are 157.33 billion zlotys, with an average unit value of 41.74 zlotys/fund unit.17 Slovakia regulated the organization and operation of voluntary pension funds in 2003. In addition to individual accession of an optional pension fund, management companies also proposed the possibility of employer contribution. From implementation to the end of 2017, the 17 active voluntary private pension funds accumulated 757,000 participants and a net asset of 1.92 billion euros.18 In Romania, voluntary pension funds were regulated by Law no. 204/2006. The main specific aspects regarding the organization and administration of voluntary pension funds have been summarized in Annex. Since the implementation of P3, five pension funds have been written off by the decision to deregister the companies that manage these funds, so that currently operate only ten voluntary pension funds. The main characteristics of them and of the management companies are presented in Table 5.4. Joining a voluntary pension fund is optional and it is done based on an accession contract between the company that manages the voluntary pension fund and the participant.19 Contributions directed to a voluntary pension fund may amount to a

15

According to the Association of Pension Societies of the Czech Republic. Available online at: https://www.apfcr.cz/. 16 According to the Polish Ministry of Finance. 17 According to data published by the Polish Financial Supervisory Authority. Available online at: https://www.knf.gov.pl/en/REPORTS_AND_ANALYSIS/Pension_system/Monthly_data_pen sion_funds_market. 18 IOPS, Country Profile: Slovak Republic, (2018), Available online at: http://www.iopsweb.org/ resources/SlovakRepublic-IOPSWebsite-Country-Profile.pdf. 19 According to Art. 74, Para. (2) of Law no. 204/2006 “joining a voluntary pension fund is an individual option,” the participant being informed about all the information “on the conditions of the voluntary pension scheme, especially regarding the rights and obligations of the parties involved in voluntary pension scheme, financial, technical and other risks, as well as the nature and distribution of these risks.”

112

5 Private Pension Funds

Table 5.4 Voluntary pension funds in Romania Management company Voluntary pension fund AEGON ESENȚIAL

Name Aegon Pensii Societate de Administrare a Fondurilor de Pensii Facultative S.A.

AZT MODERATO AZT VIVACE

Allianz-Ţiriac Pensii Private Societate de Administrare a Fondurilor de Pensii Facultative S.A.

BCR PLUS

BCR Pensii Societate de Administrare a Fondurilor de Pensii Facultative S.A.

BRD MEDIO

BRD Societate de Administrare a Fondurilor de Pensii Facultative S.A.

NN ACTIV NN OPTIM

NN Asigurări de Viaţă S.A.

PENSIA MEA

Certinvest Pensii Societate de Administrare a Fondurilor de Pensii Facultative S.A.

RAIFFEISEN ACUMULARE

S.A.I. Raiffeisen Asset Management S.A.

STABIL

Generali Societate de Administrare a Fondurilor de Pensii Facultative S.A.

Shareholders 1. Aegon Poland/ Romania Holding B.V. 2. Egon Czech Republic Holding B.V. 1. Allianz - Ţiriac Asigurări S.A 2. Tiriac Holdings Limited 1. Banca Comercială Română S.A. 2. Zbîrcea Gabriel 1. SOGECAP 2. BRD - Groupe Societe Generale S.A. 1. NN Continental Europe Holdings B.V. 2. NationaleNederlanden Intertrust B.V. 1. S.A.I. Certinvest S.A. 2. Carmen Voicu 3. TeodorMarian Alecu 4. Andrei Alecu 5. Arthur Mușetescu 1. Raiffeisen Bank S.A. 2. FeliciaVictoria Popovici 1. Generali CEE Holding B.V. 2. Generali Romania Asigurare Reasigurare S.A.

Capital (lei) 72,000,000

32,375,000

88,471,840

35,970,000

120,491,626

Depository BRD Groupe Societe Generale S. A. BRD Groupe Societe Generale S. A. BRD Groupe Societe Generale S. A. Banca Comercială Română S. A. BRD Groupe Societe Generale S. A.

7,230,766

BRD Groupe Societe Generale S. A.

10,656,000

BRD Groupe Societe Generale S. A. BRD Groupe Societe Generale S. A.

67,000,000

Source: Author’s processing based on data published by ASF (https://asfromania.ro/)

5.2 Voluntary Private Pension Funds

113

Fig. 5.2 Market share of voluntary pension funds and the number of participants in Romania. Source: Author’s processing based on data published by ASF (https://asfromania.ro/)

maximum of 15% of the salary income earned by the participant and may be made either by withholding or by subsequent payment by the employee. The participant of an optional pension fund shall have the right to increase, within the limit specified above, to suspend and cancel the contribution to a voluntary pension fund, if he or she notifies the other contracting parties.20 There is also the possibility of transfer to another voluntary pension fund,21 the participant retaining the right to an optional pension. The number of participants in voluntary pension funds in Romania in December 2019 was 486,580 people. The largest number of participants is registered by NN OPTIM and BCR PLUS pension funds, which also have the largest market share. Initially, the largest share was held by people aged between 30 and 44 years, but gradually it decreased so that in December 2019 participants over the age of 45 had a share of 53% of the total number of participants, and people under the age of 30 accounted for only 6.3% of the total number of participants (Fig. 5.2). This distribution reflects the demographic changes in Romania but draws attention to the fact that young adults have difficulties in saving and participating in an optional pension fund. The distribution of participants in voluntary pension funds by gender reflects a slight increase in the share of females, which can be explained by the desire to compensate for the noncontributory periods at the public pension

20

According to the provisions of Art. 76 of Law no. 204/2006. Article 71, Para. (2) stipulates the following: “the participant [who] has joined a new voluntary pension fund, may: a) transfer his personal assets from the previous voluntary pension funds to a new fund; b) to keep the quality of participant in all voluntary pension funds, following to accumulate them at the moment of opening the pension right.” 21

114

5 Private Pension Funds

system. The assets held in a personal account are distributed to the beneficiary as an optional pension, after formulating a request to open the account, together with the eligibility criteria regarding age, minimum contribution period, and level of personal assets.22 In addition to mandatory and voluntary private pension funds, a supplementary form of individual financial protection during retirement is represented by occupational pension funds. These pension schemes are organized by employers in order to provide financial benefits to employees as occupational pensions. In Western European countries, these types of pensions play a key role in ensuring the protection of the elderly. However, occupational pension funds are less developed in the five research countries. Only Poland and Romania have regulated the formation, organization, and administration of occupational pension funds. The recent regulation of occupational pension funds in Poland provides modest statistical data on the evolution of funds in terms of participants, financial assets, and rates of return, meanwhile, in Romania, such information does not exist yet. In Poland, occupational pension funds will be implemented in four stages. In the first stage, employers with at least 250 employees will establish participation in an occupational pension fund until July 2019. Subsequently, until July 2020, in stages 2 and 3, employers with at least 50 employees, respectively, at least 20 employees will join occupational pension funds. The last stage will take place until January 2021 and will integrate the other categories of economic entities. The financing of an occupational pension fund is made from the employee’s contributions (minimum 2% and a maximum 4% of the gross income), the employer’s contributions (minimum 1.5% and maximum 2.5% of the gross income), and from the transfers made by the state (upon accession 250 zlotys and subsequently 240 zlotys/year) (Chłoń-Domińczak, 2019). The employer has the obligation to choose a financial institution that will prepare the investment prospectus and manage the occupational pension fund.23 Each financial institution that manages occupational pension funds must establish investment prospects specific to the risk profile and age of the participant, as a result, each administrator has established eight types of occupational pension funds. According to the statement of the Polish Ministry of Finance, in September 2019, the number of members of occupational pension funds reached 376,000 participants, and the level of assets of 1.8 billion zlotys.24 Romania regulated the organization of occupational pension funds at the beginning of 2020 by Law no. 1/2020. Occupational pension funds are optionally Article 93, Para. (2) of Law no. 204/2006 stipulates that “the right to a voluntary pension is opened, at participant’s request, with the fulfillment of the following cumulative conditions: a) the participant has reached the age of 60; b) at least 90 monthly contributions have been paid; c) the personal asset is at least equal to the amount necessary to obtain the minimum voluntary pension provided by the rules adopted by the Commission.” 23 According to data published by Pracownicze Plany Kapitałowe. Available online at: https://www. mojeppk.pl/ 24 According to: https://www.gov.pl/web/finance/pension-funds. 22

5.3 Investment Policy of Private Pension Funds in Central and Eastern European. . .

115

organized by companies authorized to manage private pension funds,25 their operation being carried out according to the prospectus of the pension scheme. All employees who earn a salary or other incomes assimilated into salaries can participate in an occupational pension fund,26 by signing an individual act of accession,27 if there is a contract for the administration of a pension fund signed by the employer.28 The contribution to the occupational pension funds is made according to the prospectus of an occupational pension scheme,29 being limited to a maximum of 33% of the participant’s salary.30 The specific aspects regarding the organization and administration of occupational pension funds in Romania are summarized in Annex. Participation in an occupational pension fund confers the right to benefit from an occupational pension, based on personal assets, once the conditions set out in the prospectus of the pension scheme are met. Thus, in Poland, a participant can decide to open a personal account at the age of at least 60, and in Romania, the conditions for opening a personal account are specified in the prospectus of the pension scheme.

5.3

Investment Policy of Private Pension Funds in Central and Eastern European Countries

Community regulations support the investment of private pension funds in a prudent manner, which protects the interests of participants and ensures the long-term profitability of pension funds. As a result, the investment portfolio must be sufficiently diversified, both in terms of financial instruments and in terms of issuers of financial securities, to avoid dependence on a particular asset or issuer and to reduce exposure at investment risk. Investments must be made predominantly in regulated markets, and investment in derivatives only to reduce investment risk and for the efficient management of the security portfolio. The main Community provisions

25

According to Art. 4, Para. (2) of Law no. 1/2020. According to Art. 79, Para. (1) of Law no. 1/2020. 27 According to Art. 80, Para. (1) and Para. (2) of Law no. 1/2020 “the individual act of joining a fund is signed by the future participant and by the fund manager.” 28 Article 59, Para. (1) of Law no.1/2020 stipulates that “the management contract is concluded by the employer with a management company authorized by the A.S.F.” 29 Law no. 1/2020 provides in Art. 80, Para. (4) that “the contribution may be divided between employee and employer according to the provisions established by the scheme and individual act of accession,” and according to Art. 80, Para. (2), “in case that employee chooses to contribute to a fund, his contribution is established by the individual act of accession,” respectively in Art. 81 para. (1) “the employer’s contributions to a fund are established by the occupational pension scheme.” 30 According to Art. 85, Para. (3) of Law no.1/2020 “a maximum contribution of a participant may be one third of his monthly gross salary or others incomes assimilated to them without exceeding, together with other withholdings he or she would have, half of the net monthly salary, respectively of assimilated incomes.” 26

116

5 Private Pension Funds

Table 5.5 The main Community provisions on the structure of private pension fund investments UCITS authorized – Securities or money market instruments— maximum 10% of assets – Securities or money market instruments issued by the same entity—maximum 5% of assets (maximum 25% for certain bonds) – Derivative financial instruments—maximum 10% of assets – Participation securities of collective investment undertakings (UCITS)—maximum 10% of assets (states may set a percentage of maximum 20%) – Participation titles of other collective investment undertakings (other than UCITS)—30% of assets

IORP authorized – Investments in enterprise—maximum 5% of the entire portfolio (maximum 10% in case of investments made in instruments issued by bodies belonging to the same group) – Shares, securities, marketable securities assimilated into shares, corporate bonds— minimum 35%—maximum 70% – Assets denominated in currencies other than those in which their liabilities are expressed— maximum 30%

Source: EC Directive no. 65/2009 and EC Directive no. 2341/2016

regarding the investment policy are governed by Directive no. 65/2009 and Directive no. 2341/2016 and are summarized in Table 5.5. In subsidiary, EU Member States have transposed these provisions into national law. According to OECD Report on Private Pension Fund Market (2019), the number of participants in private pension funds implemented in CEE countries related to population aged 15–64 years increased between 2008 and 2018, with a coverage rate of over 67% in Poland, 64.1% in the Czech Republic, 57% in Romania, 39.7% in Slovakia, and only 18.7% in Hungary. The share of private pension fund assets in CEE countries in GDP has increased in the last 11 years, except for Hungary and Poland, where the elimination of P2 led to a reduction in the level of private pension fund assets by 10.8%, respectively 9.1%, compared to the level registered in the year prior to nationalization (Fig. 5.3). The highest increase was recorded in Slovakia, followed by Romania. Thus, in 2018, the assets of private pension funds had the highest values in Poland (US$47,987 million) and Czech Republic (US$21,754 million), followed by Romania (US $12,176 million) and Slovakia (US$12,038 million). Regarding the investment structure of pension funds in CEE countries, it is noted the investment portfolios are formed predominantly by government securities, except for Poland where, since 2014, over 80% of pension fund assets are represented by equities. A significant proportion is held by investments in shares in the case of Romanian pension funds (since 2014, approximately 20% of total assets) and in deposits in the case of Slovakia (over 10% of total assets). The real rate of return on private pension funds had a fluctuating evolution between 2008 and 2018, but which in the growth periods does not exceed 15%. It is noted that in all five CEE countries, in 2018, the real rate of return is negative, with values between 2 and 1.8% in Slovakia, the Czech Republic, and Romania, the lowest value of the indicator being 11.1% in Poland (Fig. 5.3).

5.3 Investment Policy of Private Pension Funds in Central and Eastern European. . .

117

Fig. 5.3 Assets, the structure of investments, and the real rate of return of private pension funds in CEE countries in the period 2008–2018. Source: Author’s synthesis based on the OECD publication “Pensions Markets in Focus (2019)” (http://www.oecd.org/pensions/private-pensions/ pensionmarketsinfocus.htm)

From a taxation point of view, private pension funds can be subject to taxation at the following times: when the contributions are collected; the time of obtaining a return on investment; the moment of opening the personal account and distributing the pension.31 It is usually preferred to tax pensions, both to encourage participation in a private pension fund and to reduce the fiscal impact of demographic decline. The fiscal regime of contributions directed to private pension funds, as well as the redistribution of funds at the opening of the personal accounts is specific to each state (Table 5.6). The multi-pillar structure proposed by WB and the privatization of pension systems represent a way to increase the financial protection of the elderly, but it should be noted that privately managed pension funds are not an accepted and viable solution for all countries, Hungary and Poland nationalizing Pillar II of pension funds. Carp (2018) argues that the nationalization of privately managed pension funds only to finance the public pension system is an inadequate solution, which will not ensure its long-term sustainability. However, it should not be overlooked that, in the case of the privatization of pension schemes, benefits are influenced by the return on investment. With low economic growth and moderate returns on financial assets, the financial resources needed to distribute pensions may be insufficient. From this

31

According to ASF. Available online at: https://asfromania.ro/consumatori/pensii-private/ deductibilitate-pilon-iii/98-root-ro/protectia-consumatorilor/sistem-pensii-private/1782-analizaprivind-regimul-tax-applied-voluntary-pensions.

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5 Private Pension Funds

Table 5.6 Tax regime applied to contributions to private pension funds and private pensions in CEE countries Contributions paid to private pension funds Private pension Exempt

Employee Contributions over 12,000 zlotys/year are deductible up to the limit of 24,000 zlotys Deductible, 17.7% income for personal tax related to the account employer’s contribution

Employer Deductible, up to 50,000 zlotys/year – Deductible for profit tax – 23.01% health contributions

Exempt

Poland

Deductible

Exempt

Romania

P2—Deductible P3—Deductible up to 400 euro/ year

Deductible up to 7% of employee’s salary P2—Deductible for profit tax

Slovakia

P2—Deductible P3—Deductible up to 180 euro 4% health contributions

Czech Republic Hungary

P2—Deductible for profit tax P3—Deductible for profit tax up to 6% of employee’s salary 10% health contributions

– Deductible up to 2.000 lei – 10% of taxable income Exempt

Income from the distribution of net assetsa 15%

– 15% income tax – 19.5% health contributions 19%

Exempt

19%b

Source: Author’s synthesis based on the OECD publication “Financial Incentives and Retirement Savings (2018)” (https://www.oecd.org/finance/financial-incentives-retirement-savings.htm) a Opening a personal account and distributing the net assets before fulfilling the conditions for accessing the private pension b Only the return on personal assets is taxed

perspective, Rivera-Rozo et al. (2018) consider that states wishing to reduce income uncertainty will eighth for public pension systems in which the main component is the PAYG pension scheme, limiting private pension funds and the investment risk associated with them.

5.4

Conclusions and Personal Contributions

The restructuring of national pension systems through the implementation of private pension funds has allowed the outsourcing of a part of the demographic pressure felt by public systems. However, the increase in public system expenditure, the growth

Annex: Specific Aspects Regarding the Administration of Private Pension. . .

119

of social contribution pressure, and the negative rates of return of private funds have led to a minimization of the attractiveness of private pension funds in CEE countries.

5.5

Summary

This chapter offers a socioeconomic perspective to pension systems, given the recommendation of international bodies to diversify the financial sources of the elderly population, on the one hand by joining private pension funds, and on the other hand by personal savings using various tools offered by the banking and stock market. The responsibility of the population to ensure the necessary income after retirement consists of an opportunity for the development of financial markets, but the lack of financial education and poor knowledge of financial concepts poses a major risk that the investments made will not produce the expected return. From this perspective, public pension systems eliminate this risk but instead present the risk of demographics and redistribution between generations.

Annex: Specific Aspects Regarding the Administration of Private Pension Funds in Romania Regulated aspect Pension fund management company

– Administrator can be:

– Subscribed and paid-in capital

– Minimum number of participants – Responsibilities in the administration of pension funds

Mandatory private Occupational pension Voluntary pension pension funds funds funds – Requires authorization to set up and authorization to manage privately administered pension funds issued by CSSPP – Must be registered at the Trade Register in the form of S.A. having as object of activity the administration of pension funds – The company hav– Pension companies ing as object of activ- – Investment management companies ity the administration – Insurance companies of pension funds – Authorized to administer pension funds 4,000,000 euros, 1,500,000 euros, equivalent in lei equivalent in lei * exceeding the value of 200,000,000 euros of net assets requires the increase of capital by 0.2%/1,000,000 euros 50,000 persons 100 persons – Keeping records of participants’ accounts – Investing the assets of pension fund – Managing day-to-day operations of the fund – Calculation of value of fund units – Calculation of net assets – Determining profitability rates – Provision of services – Designates the depositary (continued)

120

Regulated aspect

– Management fee

The role of the depositary

The Supervisory Commission of the Private Pension System orders the withdrawal of the authorization for the administration of private pension funds in the following situations:

5 Private Pension Funds Mandatory private pension funds

Occupational pension funds

Voluntary pension funds

– Maintaining links with third-party bodies and institutions – Promotion and marketing – Preparation and publication of audited annual financial statements – Elaboration and publication of annual report on the activity carried out – Managing, keeping, and archiving the documents regarding the fund, their employers, contributions, participants, and heirs – Other activities provided for in the regulations of the A.S.F – Maximum 0.5% of – Maximum 0.2% of – Maximum 5% of contributions paid fund’s net assets contributions paid – A percentage – The collection of a – Maximum 0.2% of between 0.02 and fixed amount borne by the total net assets of 0.07% of total net the employer voluntary pension assets of the privately fund, established by managed pension the prospectus of the fund, depending on voluntary pension the inflation rate scheme – Maintains and updates the records relating to the movable assets of the pension fund – Determines and daily informs the administrator of the pension fund and A.S.F. about the value of the pension fund’s assets – Calculates and reports the value of the assets corresponding to the technical provision – Provides A.S.F. information on all aspects of storage and custody activity carried out – Ensures that transactions involving the assets of a fund is paid within the usual time limits – Ensures that the income obtained from the investment of the fund’s assets is used in accordance with the applicable legal provisions – Reducing the mini– Violation of the – The administrator has not started the mum number of parprovisions for the operations for which ticipants pension scheme prohe was authorized, – The rate of return is spectus within 2 years from lower than the mini– Violation of legal mum value of the provisions and CSSPP the receipt of the authorization or has return of all pension rules not exercised for more funds for 1 year – Lack of documents than 2 years his – Violation of the requested by CSSPP administration activity legal provisions and – Reducing the mini– Division/merger of norms of the CSSPP mum number of parthe administrator or of the pension ticipants – The rate of return is – The administrator is scheme prospectus in default of payment – The administrator lower than the mini– The administrator has not started the mum value of the no longer meets the operations for which return of all pension operating conditions he was authorized, funds for 1 year – The administrator within 1 year from – Division/merger of does not ensure proper the receipt of the the administrator defense of the interauthorization, or has ests of the participants not exercised his and beneficiaries administration (continued)

Annex: Specific Aspects Regarding the Administration of Private Pension. . .

Regulated aspect

Mandatory private pension funds

Occupational pension funds

121

Voluntary pension funds

– The administrator has not established sufficient technical provisions for the entire activity or does not have sufficient assets to cover the technical provisions

Special supervision

Special administration

activity for more than 6 months – Division/merger of the administrator – The administrator is unable to pay or no longer meets the operating conditions – The administrator does not ensure proper defense of the interests of the participants and of the beneficiaries – The administrator has not established sufficient technical provisions for the entire activity or does not have sufficient assets to cover the technical provisions – Applies in case of – The purpose is to apply additional measures deficiencies found by to limit the risks and ensure the recovery of the CSSPP that do not voluntary pension fund, in order to protect the require special admin- interests of participants and beneficiaries istration – The tasks of the Special Supervisory Board: – The special supervi- – Analyzes the financial situation of the fund sion commission has and of the manager and presents the the role to assist the A.S.F. periodic reports on this activity of the admin- – Monitors the manner in which the adminisistrator of the pension trator applies the measures to remedy the defifund ciencies found in the control documents drawn – The purpose is to up by the control bodies of the A.S.F limit the risks, to – Follows the realization of the plan for ensure the recovery of remedying the deficiencies or for financial the pension fund and recovery of the fund, proposed by the adminto protect the interests istrator of the participants – Suspends or cancels the acts of administrator, contrary to the prudential regulations or which determine the deterioration of the financial situation of the fund – Proposes A.S.F. the application of sanctions in case the administrator does not comply with the measures ordered by the Special Supervisory Board – Other duties established by the A.S.F – Is applied in case of withdrawal/suspension of the authorization to manage the pension fund for a maximum of 1 year – The role is to protect the participants and reduce the losses of the (continued)

122

Regulated aspect

Technical provisions and guarantees

5 Private Pension Funds Mandatory private pension funds

Occupational pension funds

Voluntary pension funds

pension fund’s assets by transferring the assets to another pension fund – Participants are required to join another pension fund, and if they do not choose a pension fund, they will be automatically allocated by CSSPP – The calculation is performed annually and is certified by an actuary expert based on the norms established by CSSPP – The volume must be correlated with the obligations provided in the pension scheme prospectus General principles: (a) The minimum level of technical provisions is calculated using a prudent actuarial assessment, considering all commitments for the payment of benefits and contributions, as shown in the prospectus of the private pension scheme of fund (b) The maximum interest rates used are chosen prudently and are determined taking into account the return on investment and/or the yields on high quality or government bonds (c) The biometric tables used for the calculation of technical provisions are based on prudent principles, depending on the main characteristics of the group of participants and of the private pension schemes

Source: Law no. 411/2004, Law no. 204/2006, and Law no. 1/2020, with subsequent amendments and completions

References Bonenkamp, J., Meijdam, L., Ponds, E., & Westerhout, E. (2017). Aging-driven pension reform. Journal of Population Economics, 30, 953–976. Bonoli, G., & Palier, B. (2007). When past reforms open new opportunities: Comparing old-age insurance reforms in Bismarckian welfare systems. Social Policy & Administration, 41, 555–573. Carp, A. (2018). Scenarii privind evoluţia sistemului de pensii private din România. Romanian Statistical Review – Supplement, 4, 186–195. Chłoń-Domińczak, A. (2019). New occupational pension savings scheme in Poland, ESPN Flash Report 2019/01. European Social Policy Network (ESPN). Council Directive 98/49/EC of 29 June 1998 on safeguarding the supplementary pension rights of employed and self-employed persons moving within the Community. Official Journal of the European Communities L 209/46. Available online at https://eur-lex.europa.eu/search.html? DTN¼0050&DTA¼2014&qid¼1586241630532&DB_TYPE_OF_ACT¼directive&DTS_ DOM¼ALL&excConsLeg¼true&typeOfActStatus¼DIRECTIVE&ALLS. Croitoru, E. (2015). Pension system reform in Romania: A dynamic analysis of the demographic influence. In 7th International conference on globalization and higher education in economics and business administration, GEBA, Procedia Economics and Finance (vol. 20, pp. 140–146). Directive 2009/65/EC of the European Parliament and of the Council of 13 July 2009 on the coordination of laws, regulations and administrative provisions relating to undertakings for collective investment in transferable securities (UCITS). Official Journal of the European Union L 302/32. Available online at https://eur-lex.europa.eu/legal-content/en/TXT/? uri¼CELEX:32009L0065.

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Directive 2014/50/EU of the European Parliament and of the Council of 16 April 2014 on minimum requirements for enhancing worker mobility between Member States by improving the acquisition and preservation of supplementary pension rights. Official Journal of the European Union L 128/1. Available online at: https://eur-lex.europa.eu/search.html?DTN¼0049&DTA¼1998& q i d ¼1 5 8 6 2 4 0 8 9 8 1 3 4 & D B _ T Y P E _ O F _ A C T ¼d i r e c t i v e & D T S _ D O M ¼A L L & excConsLeg¼true&typeOfActStatus¼DIROMOMIT&IT. Directive (EU) 2016/2341 of the European Parliament and of the Council of 14 December 2016 on the activities and supervision of institutions for occupational retirement provision (IORP). Official Journal of the European Union L 354/37. Available online at: https://eur-lex.europa. eu/legal-content/en/TXT/?uri¼CELEX:32016L2341. Drahokoupil, J., & Domonkos, S. (2012). Averting the funding–gap crisis: East European pension reforms after 2008. Global Social Policy, 12(3), 283–299. European Commission-Directorate-General for Employment, Social Affairs and Inclusion. (2018). The 2018 Pension Adequacy Report: Current and future income adequacy in old age in the EU (vol. I). Publications Office of the European Union. Hergár, E. (Ed.) (2019). Insurance, funds and capital market risk report. Magyar Nemzeti Bank. Available online at https://www.mnb.hu/en/publications/reports/insurance-funds-and-capitalmarket-risk-report. Hlaváč, J. (2011). Financial performance of the Czech private pension scheme: Its current position and the comparison with other CEE countries (IES Working Paper 9/2011). IES FSV, Charles University. Impavido, G. (2013). Pension funds. In G. Caprio et al. (Eds.), Handbook of key global financial markets, institutions and infrastructure. Elsevier. Legea nr. 1/2020 privind pensiile ocupaţionale, publicată în Monitorul Oficial nr. 10 din 8 ianuarie 2020 (Law no. 1/2020 on occupational pensions, published in the Official Gazette no. 10 of January 8, 2020). Available online at: https://static.anaf.ro/static/10/Anaf/legislatie/L_1_2020. pdf. Legea nr. 204/2006 privind pensiile facultative, publicată în Monitorul Oficial nr. 470 din 31.05.2006, cu completările și moficările ulterioare (Law no. 204/2006 on voluntary pensions, published in the Official Gazette. no. 470 of 31.05.2006, with the subsequent completions and modifications). Available online at: https://asfromania.ro/csspp/uploads/files/legea-204-din2006-privind-pensiile-facultative_gd8t.pdf. Legea nr. 411/2004 privind fondurile de pensii administrate privat, publicată în Monitorul Oficial nr. 1033 din 09.11.2004, cu completările și modificările ulterioare (Law no. 411/2004 on privately managed pension funds, published in the Official Gazette no. 1033 of 09.11.2004, with the subsequent completions and modifications). Available online at: http://legislatie.just.ro/ Public/DetaliiDocument/83682. Norma ASF nr. 27/2017 privind utilizarea activului personal net al participantului la un fond de pensii administrat privat, publicată în M. Of. nr. 976 din 08.12.2017 (ASF norm no. 27/2017 on the use of the net personal assets of the participant in a privately managed pension fund, published in the Official Gazette. no. 976 from 08.12.2017.). Available online at: https:// asfromania.ro/legislatie/legislatie-sectoriala/legislatie-pensii/legislatie-secundara-pensii/normepensii. OECD. (2007). Pensions at a glance 2007: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/docserver/pension_glance-2007-en.pdf?expires¼1581633008& id¼id&accname¼guest&checksum¼9E550BF1E09A3644DE3E1C3DCB0E8CAE OECD. (2009). Pensions at a glance 2009: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/finance-and-investment/pensions-at-a-glance-2009_pension_ glance-2009-en OECD. (2011). Pensions at a glance 2011: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/finance-and-investment/pensions-at-a-glance-2011_pension_ glance-2011-en

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OECD. (2013). Pensions at a glance 2013: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/docserver/pension_glance-2013-en.pdf?expires¼1581632974& id¼id&accname¼guest&checksum¼9CC4E2F8E2F3AA89B6CDE3E18F3D5631 OECD. (2015). Pensions at a glance 2015: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/docserver/pension_glance-2015-en.pdf?expires¼1581632965& id¼id&accname¼guest&checksum¼3D08AD05CC50394B86DE30EBF9A0403E OECD. (2017). Pensions at a glance 2017: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/social-issues-migration-health/pensions-at-a-glance-2017_pen sion_glance-2017-en OECD. (2018). Financial incentives and retirement savings. OECD. Available online at: https:// www.oecd.org/finance/financial-incentives-retirement-savings.htm OECD. (2019a). Pensions at a glance 2019: OECD and G20 indicators. OECD. Available online at: https://www.oecd-ilibrary.org/docserver/b6d3dcfc-en.pdf?expires¼1581632950&id¼id& accname¼guest&checksum¼3254AED642ED3C02D7A89DCE43F26559 OECD. (2019b). Pension markets in focus. OECD. Available online at: https://www.oecd.org/ finance/private-pensions/pensionmarketsinfocus.htm Rivera-Rozo, J. A., Garcia-Huitron, M. E., Steebeek, O. W., & van der Lecq, S. G. (2018). National culture and the configuration of public pensions. Journal of Comparative Economics, 16(2), 457–479. Simonovits, A. (1999). The new Hungarian pension system and its problems (KTK/IE Discussion Papers 1999/1). Institute of Economics, Hungarian Academy of Sciences. Szikra, D. (2018). Reversing privatization and re-nationalizing pensions in Hungary (ESS – Working Paper No. 66). Social Protection Department, International Labour Office.

Chapter 6

Personal Savings and Investments in the Financial Market

After 1998, CEE countries underwent an extensive reform process toward compliance with the new political, economic, and sociodemographic conditions. Reduced birth rate, increased life expectancy, and migration are challenges for PAYG public pension systems, which are directly dependent on the labor market and funding based on social security contributions paid by all earners and other wage earners. This chapter aims to give a socioeconomic perspective regarding personal saving, through various instruments offered by the banking and capital market, to supplement the financial resources of the elderly during retirement.

6.1

Financial Literacy and the Importance of Financial Inclusion in Central and Eastern European Countries

The last decades marked the decreasing role of the state in ensuring the financial protection of the population during retirement and the transfer of responsibility for the individual during the period of activity which should be concerned with setting up the necessary funds for retirement. This feature has raised concerns about the degree of individual involvement in investment and administrative costs, as well as investment performance (Grech, 2014). The degree of savings for financial security after retirement is determined by the ability to understand financial concepts. Financial literacy is defined by OECD as “a combination of awareness, knowledge, understanding, attitudes and behavior, necessary to make sound financial decisions that lead to individual financial well-being” (OECD/INFE, 2012, pp.2). In the report on measuring the financial literacy of the population in the G20 countries, OECD shows that most of the population does not have basic financial knowledge, the percentage being higher for women (OECD, 2017). This report draws attention to the need to strengthen financial education,

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_6

125

126

6 Personal Savings and Investments in the Financial Market

which has positive effects on the financial behavior of the population (Kaiser & Menkhoff, 2017). Financial education and the ability to understand and operate with financial concepts materialize in reducing financial uncertainty and the development of financial markets. It has been found that an increased level of financial education reduces the over-indebtedness of the population (Gerardi et al., 2013), stimulates investment in the stock market (Almenberg & Dreber, 2015), diversifies saving (Hastings et al., 2011), and increases the capacity of the population to cope with unexpected expenses (Hasler et al., 2018). Lusardi and Mitchell (2014) show that people with a high level of financial literacy tend to save for retirement, the fact that reduces the risk of poverty and supports economic growth (Majid et al., 2019). The financial inclusion of the population can be achieved by exposure to financial and banking products and services. Marin and Schwabe (2019) argue that policies that facilitate banking competitiveness have a positive effect on financial inclusion and literacy, due to the development of products accessible to the population. However, the lack of financial knowledge and improper or erroneous use of financial and banking information increases the risks to which the population is exposed (Klapper & Lusardi, 2019). The report on financial stability published by the National Bank of Romania (BNR) shows that Romania is among the last EU countries in terms of financial inclusion of population, the value of the financial inclusion index being only 0.16. Regarding the banking products and services used by populating CEE states, in 2017, it is noted that Romania has the lowest share of the usage of bank accounts and online banking services, regardless of the age group of the population (Fig. 6.1). The low financial inclusion in Romania can be attributed to several factors, the most important being: the modest level of income of the population, poor financial education, limited accessibility of population living in rural areas to financial and banking products and services, and low confidence in the banking system, but also in the stock market (BNR, 2019).

6.2

Personal Savings Through the Banking System

The WB supports the diversification of the sources regarding the income of the elderly population in order to maintain a decent standard of living, and the responsibility for ensuring the necessary income in old age is divided between state and individuals. Scharfstein (2018) studies how the typology of pension system influences the financial system and demonstrates a negative relationship between the replacement rates provided by PAYG public pension systems and market capitalization and that PAYG pension systems are correlated with lower values of mortgage loans contracted by individuals, but also with the predominant financing of the business environment from the banking sector. In addition to privately managed pension funds, a form of securing additional income is by savings, using financial and banking products, such as deposits and

6.2 Personal Savings Through the Banking System

127

Fig. 6.1 Use of bank accounts in CEE countries, 2017. Source: Author’s processing based on data published by the WB (https://databank.worldbank.org/reports.aspx?source¼world-developmentindicators)

investment funds. Savings, through financial and banking institutions, are most used by the population of the Czech Republic and Slovakia, which in a proportion between 35% (Czech Republic) and 65% (Slovakia) use banking products for savings. Lower values of savings through financial and banking institutions are recorded by Hungary and Poland (between 17%, respectively 40% of the population). Saving, through the banking system, is not a preferred option of the Romanian population, which saves using banking products in a proportion not exceeding 15%, in the case of all age groups (Fig. 6.2). According to data published by the WB, in 2017, the share of the Romanian population under the age of 35 who save for retirement is 6%, a percentage similar to that found in Poland and Hungary. The saving rate increases in the case of the 35–59 age group to values of 53–54% in the Czech Republic and Slovakia, but the values remain modest in Romania (15%). The share of the population with savings for retirement, in Romania, reaches the highest values in the case of the population over 60 years old (37%). Bank deposits are an individual form of saving, being preferred by some categories of people due to high liquidity and low investment risk. Deposits provide a high degree of security but have low rates of return. According to data published by the ECB, the level of bank deposits of the population of CEE countries in the national

128

6 Personal Savings and Investments in the Financial Market

Fig. 6.2 The degree of saving in CEE countries in 2017. Source: Author’s processing based on data published by the WB (https://databank.worldbank.org/reports.aspx?source¼world-develop ment-indicators)

Fig. 6.3 Interest rate for bank deposits in CEE countries, period 2008–2018. Source: Author’s processing based on data published by the ECB (https://www.ecb.europa.eu/stats/financial_ markets_and_interest_rates/html/index.en.html)

currency decreased between 2008 and 2018 by 76% in Hungary, 67% in the Czech Republic and 27% in Poland, and in Romania and Slovakia increased by 59% and 39%, respectively. Interest rates on deposits decreased, in 2019 with values between 0.02 and 3.32% (Fig. 6.3).

6.3 Personal Investments in the Stock Market

6.3

129

Personal Investments in the Stock Market

Reduced interest rates on bank deposits are a reason to look for alternative sources of savings, with higher returns. The financial system, through investment management companies, offers the possibility of investing savings in investment funds or directly in financial instruments traded on the stock market. The modern theory on investment portfolios supports their optimization according to the profitability/investment risk ratio, although from the point of view of practitioners, this theory has shortcomings (Turcaș et al. 2019). The risk to which investors are exposed for the case of investing in investment funds is reflected in the financial instruments contained in an investment portfolio. Thus, the lowest exposure is in the case of monetary funds, and the highest in the case of equity funds. Turcaș et al. (2016) propose the selection of financial assets according to the existence of statistical correlations between the profitability of financial instruments and the diversification of assets should focus on the protectionist effect and not on risk reduction, portfolio monitoring through methods of technical analysis. The main indicators regarding the development of investment funds in CEE countries included in the research are summarized in Table 6.1. Both private pension and investment funds have a direct link with the stock market. With the transition to a market economy in CEE countries, stock markets registered a strong capitalization and development, an aspect reflected by both the level of capitalization and by the evolution of stock indices, thus becoming attractive for foreign investors (Fig. 6.4). In the Czech Republic, the market capitalization is 19.562 billion crowns, and the evolution of the index of prices of most liquid companies traded on the Prague Stock Exchange—PX over the last 11 years reflects a slight depreciation.1 In Poland, the market capitalization is over 818 billion zlotys, but between 2009 and 2019 the market trend is downward, the value of the stock market index WIG20, which highlights the evolution of the 20 most liquid companies traded on the Warsaw Stock Exchange, decreased by 10%.2 In Hungary, the market capitalization is 6.634 billion forints, and the upward evolution of the main stock market index–BUX, which doubled in value between 2009 and 2019, suggests consolidating the stock market and interest of investors to trading in financial instruments.3 A similar situation is encountered in Romania, where the market capitalization in 2019 is over 180 billion lei, and the BET index registered an increase of 113%, compared to 2009.4 The positive results registered by the stock market in Romania and Hungary determined the promotion to the stage of emerging markets by the international agency FTSE Russell. A more modest increase is noticed in Slovakia, where the SAX index in the last 11 years registered 1

Prague Stock Exchange, https://www.pse.cz/en. Warsaw Stock Exchange, https://gpwbenchmark.pl/en-home. 3 Budapest Stock Exchange, https://www.bse.hu/. 4 Bucharest Stock Exchange, http://www.bvb.ro/. 2

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6 Personal Savings and Investments in the Financial Market

Table 6.1 Investment funds from CEE countries, fourth quarter 2019

Czech Republic Hungary Poland Romania Slovakia

Number of funds Shares Bonds Mixt 34 44 79

Monetary 1

Real estate 7

Net assets (million euros) 14,626.4

104 225 27 11

12 – – –

49 17 – 9

19,557.2 62,957.1 9629.2 7413.8

73 197 17 25

108 271 30 49

Source: Author’s processing based on data published by EFAMA (https://www.efama.org/ statistics/SitePages/Statistics.aspx)

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

PX

1,117.

1,224.

911.10

1,038.

989.04

946.71

956.33

921.61

1,078.

986.56

1,115.

BUX

21,227

21,327

16,974

18,173

18,564

16,634

23,920

32,003

39,377

39,138

46,082

WIG20 2,388.

2,744.

2,144.

2,582.

2,400.

2,315.

1,859.

1,947.

2,461.

2,276.

2,150.

BET

4,690.

5,268.

4,336.

5,149.

6,493.

7,083.

7,004.

7,085.

7,753.

7,383.

9,977.

SAX

266.97

230.38

215.45

192.21

197.76

222.32

292.35

318.57

325.62

332.37

351.14

Fig. 6.4 The evolution of the main stock market indices in CEE countries in the period 2009–2019. Source: Author’s processing based on data published by PSE, BSE, GPW, BVB, and BSSE

an increase of only 32%, and the stock market capitalization in 2019 decreased by 42.3% compared to 2018.5

6.4

Conclusions and Personal Contributions

The main conclusion of this chapter reflects the fact that in the current demographic and socioeconomic context, personal saving is an essential condition for maintaining well-being during retirement. Increasing the responsibility of the population in ensuring the necessary resources in old age is an opportunity to develop the capital market and stimulate competitiveness in the financial and banking sector, as well as 5 Bratislava Stock Exchange, Factbook 2019. Available online at: http://www.bsse.sk/bcpben/ Statistics/Year/tabid/171/language/en-US/Default.aspx.

References

131

to reduce the risk of poverty. At the same time, it must be ensured an adequate financial flow to the active population, to favor personal savings. It is also necessary to increase the level of financial knowledge of the population, a sine qua non condition in the rational use of financial products.

6.5

Summary

This chapter gives a socioeconomic perspective to pension systems, given the recommendation of international bodies to diversify the financial sources of the elderly population, on the one hand by joining private pension funds, and on the other hand by personal savings using various tools offered by the banking and stock market. The responsibility of the population to ensure the necessary income after retirement is an opportunity for developing financial markets, but the lack of financial education and poor knowledge of financial concepts poses a major risk that the investments made will not produce the expected return. From this perspective, public pension systems eliminate this risk but instead present the risk of demographics and redistribution between generations.

References Almenberg, J., & Dreber, A. (2015). Gender, stock market participation and financial literacy. Economics Letters, 137, 140–142. BNR. (2019). Raport asupra stabilității financiare 2/2019. Banca Națională a României. Available online at: https://www.bnr.ro/PublicationDocuments.aspx?icid¼19966. Gerardi, K., Goette, L., & Meier, S. (2013). Numerical ability predicts mortgage default. Proceedings of the National Academy of Sciences, 110, 11267–11271. Grech, A. G. (2014). Pension policy design: The core issues. MPRA Paper No. 53662. Available online at: http://mpra.ub.uni-muenchen.de/53662/. Hasler, A., Lusardi, A., & Oggero, N. (2018). Financial fragility in the US: Evidence and implications (GFLEC Working Paper 2018-1). Hastings, J., Mitchell, O. S., & Chyn, E. (2011). Fees, framing, and financial literacy in the choice of pension manager. In O. S. Mitchell & A. Lusardi (Eds.), Financial literacy: Implications for retirement security and the financial market place. Oxford University Press. Kaiser, T., & Menkhoff, L. (2017). Does financial education impact financial behaviour, and if so, when? (DIW Berlin discussion paper). Available online at: https://www.diw.de/documents/ publikationen/73/diw_01.c.529454.de/dp1562.pdf. Klapper, L., & Lusardi, A. (2019). Financial literacy and financial resilience: Evidence from around the world. Financial Management, 1–26. Available online at: https://doi.org/10.1111/fima. 12283. Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, American Economic Association, 52(1), 5–44. Majid, M.S.A.M., Dewi, S., Aliasuddin, Kassim, SH. (2019). Does financial development reduce poverty? Empirical evidence from Indonesia. Journal of Knowledge Economy, 10, 1019–1036. Marin, A. G., & Schwabe, R. (2019). Bank competition and financial inclusion: Evidence from Mexico. Review of Industrial Organization, 55, 257–285.

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OECD. (2017). G20/OECD INFE report on adult financial literacy in G20 countries. OECD. Available online at: https://www.oecd.org/finance/g20-oecd-infe-report-adult-financialliteracy-in-g20-countries.htm. OECD/INFE. (2012). High-level principles on national strategies for financial education. OECD. Available online at: https://www.oecd.org/daf/fin/financial-education/OECD-INFE-PrinciplesNational-Strategies-Financial-Education.pdf. Scharfstein, D. (2018). Pension policy and the financial system. The Journal of Finance, LXXIII(4), 1463–1512. Turcaș, F., Dumiter, F., Braica, A., Brezeanu, P., & Opreț, A. (2016). Using technical analysis for portfolio selection and post-investment analysis. Economic Computation and Economic Cybernetics Studies and Research, 50(1), 197–214. Turcaș, F., Dumiter, F., Brezeanu, P., Farcas, P., & Coroiu, S. (2019). Practical aspects of portfolio selection and optimisation on the capital market. Economic Research—Ekonomska Istraživanja, 30(1), 14–30.

Chapter 7

The Importance and Role of Social Policy in Maintaining Macroeconomic Stability

Pension systems have the role of reducing the financial risk associated with the loss of the ability to carry out professional activities for income, a risk that determines poverty and is associated with severe material deprivation. The objective of this chapter is to emphasize the role of social policy in society and in macroeconomic policies in order to maintain socioeconomic stability and promote sustainable economic growth.

7.1

The Risk of Poverty and Severe Material Disadvantages Among the Population

Poverty is said to be the “mother of all evil.” From an economic point of view, poverty is the result of income inequality, which in CEE countries has increased together with social development and economic growth (Neagu et al., 2016). Lewis (1959) describes poverty as a cultural subsystem perpetuated from generation to generation, in which the population fails to overcome financial and material constraints, so they accept this burden and includes it in their value system. Mojan (2011) opposes the “culture of poverty” theory, arguing that poverty represents, mutadis mutandis, a political problem based on sociocultural dysfunctions, due to changing human values and ethics that exist at the level of a state. Social transfers have a direct impact in reducing the rate of poverty and social exclusion risk of the population (Arza, 2015). It is noted that before social transfers, the risk of poverty threatens up to 30% of the population under the age of 65 in the Czech Republic and Slovakia and up to 45% of the population of Hungary, Poland, and Romania. These percentages are reduced after social distributions to values between 8.5 and 14% in the Czech Republic and Slovakia, 13.4 and 18.8% in Hungary and Poland, Romania registering the highest rates of poverty risk between 22.2 and 27%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_7

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Fig. 7.1 Risk of poverty in CEE countries, 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

The risk of poverty before social transfers, in the case of people over the age of 65, in all five CEE countries is between 80 and 90%. This percentage is reduced after the distribution of the benefits granted by the pension systems by up to 83%, reaching values below 18% in the period 2007–2018. Romania is an exception, where in the last 12 years the risk of poverty after the distribution of pensions among the elderly population has decreased by 8.6%, in 2018 having the highest value, compared to the other four CEE countries, of 24.7%. After social transfers, the at-risk-of-poverty rate decreases even more, registering in 2018 percentages below 10% in Hungary and Slovakia, between 14 and 16% in the Czech Republic and Poland, Romania having the highest share of poverty risk of 22.8% (Fig. 7.1). The European Commission, through the Social Protection Committee, supports cooperation between member countries and promotes social policies to reduce poverty and social exclusion of vulnerable groups. To have a broader picture of material deprivation regarding the population of Member States, it was developed a specific indicator: material deprivation rate. The purpose of this indicator is to provide a clear picture of the financial inability of the population to purchase things and services considered necessary for a decent living, namely payment of current utilities, rents and bank rates, maintaining an adequate temperature in house, capacity to bear some unforeseen expenses, regular protein consumption, going on vacation/trips at least once a year and borne entirely from one’s own funds, purchasing a TV, a telephone, a washing machine, and a car. If a person does not have the necessary financial resources to acquire four of the above elements, he or she is considered to have a severe state of material deprivation. Figure 7.2 shows that CEE countries have seen reductions in the severe material deprivation rate of population, especially Romania and Poland. It is noted that the rate of material deprivation, as well as the risk of poverty, is higher for women, except for Poland and Romania, where since 2010 severe material deprivation before the age of 65 is higher for men. Contrary to the risk of poverty, the rate of severe material disadvantages is higher for the population under the age of 65, suggesting

7.2 Benefits of Public Pension Systems and the Welfare of the Elderly Population

135

Fig. 7.2 Severe material disadvantages of the population in CEE countries in the period 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa. eu/eurostat/data/database)

that the employed population has encountered difficulties in purchasing goods and services that are considered necessary for a decent living. At the same time, this situation expresses the fact that the benefits granted by pension systems have an adequate level and manage to provide the beneficiaries with the necessary financial resources.

7.2

Benefits of Public Pension Systems and the Welfare of the Elderly Population

Public pension schemes in CEE countries provide four types of pensions, namely: old-age pension, early retirement pension, invalidity pension, and survivor pension. The role of these redistributions is not only to reduce poverty and material deprivation, as shown above, but also to ensure incomes like those obtained during the period of professional activity in order to maintain the standard of living, ex ante, retirement. To this mean, each of the five countries has set a minimum level of benefits that public pension systems must provide (European Commission Directorate-General for Employment, Social Affairs and Inclusion, Social Protection Committee, 2018). The level of income provided by the pension systems during the retirement period reflects the generosity and respect given to the human being (Shahid, 2014). The OECD has created an indicator entitled equivalized net income to be able to compare the income of the population under equal conditions. In the case of the five CEE countries, the median equivalized net income has increased in the last 12 years, but shows significant differences, depending on the age group, being strongly

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The Importance and Role of Social Policy in Maintaining Macroeconomic. . .

Fig. 7.3 Median equivalized net income, replacement rate, and median relative income ratio of the population in CEE countries in the period 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

influenced by the distributions made by national pension systems, especially after the age of 65 (Fig. 7.3). The incomes of the population of CEE countries increased significantly between 2007 and 2018. It can be noted that the median equivalized net income before social transfers in the case of people aged between 16 and 64 recorded important increases especially in Romania (+121%) and Poland (+103%). However, the median equivalized net income realized in Romania in 2018 does not reach 3000 euros, compared to incomes realized in the Czech Republic and Slovakia that exceed 6500 euros or in Hungary and Poland, which are over 4000 euros. After the distribution of pensions, the median equivalized net income records an increase between 5 and 30%. In the case of the population aged 65 and over, it is noted that pension income is practically the only income that this category of the population has (Balteș & Jimon, 2018). After the distribution of pensions, the median equivalized net income reaches values between 3300 and 7000 euros, except in Romania, where this indicator does not exceed 2600 euros. Thus, the incomes of the population over the age of 65 are comparable to those of the population up to the age of 65, in Hungary the median equivalized net income having even higher values in the case of the elderly. This evidence is also supported by the relative median income ratio, an indicator that shows the ratio between equivalized net income before and after the age of 65, and whose values are between 74 and 105%. The capacity of pension systems to provide the needed income to beneficiaries can be assessed by the replacement rate of income obtained during the period of

7.2 Benefits of Public Pension Systems and the Welfare of the Elderly Population

137

Fig. 7.4 Income inequality in CEE countries, 2007–2018. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

activity on the labor market. In recent years, in the five CEE countries, this indicator has values around 60%, except the Czech Republic, where the replacement rate is around 50%. According to WB, these values suggest that pension systems manage to provide adequate income to beneficiaries and to reduce the financial risk associated with the loss of working capacity. Income inequality is most often expressed by the Gini coefficient, an index that shows the dispersion of income distribution compared to an equal distribution. In the case of CEE countries included in the research, the Gini coefficient registers values between 47 and 55 in Hungary, Poland, and Romania, and between 37 and 45 in the Czech Republic and Slovakia, respectively. After the distribution of pensions, these values are reduced by 4–5 points. The measure of inequality is given by the income inequality index, calculated by the ratio between the incomes of the population found in quartile 5 and quartile 1 of income. In the five CEE countries, the income inequality index is reduced after the age of 65 to between 2.1 and 3.5. In Romania, the income inequality index has decreased in the last 12 years, but has higher values than the other four CEE countries, in 2018 a beneficiary with income from quartile 5 earning 4.5 times more than one with income from quartile 1 (Fig. 7.4). The pension systems of CEE countries included in the research manage to provide adequate income to beneficiaries and to fulfill the role of reducing the risk of poverty and ensuring a decent living, but the income inequality existing, especially in Romania can be a threat to the beneficiaries whose incomes are included in quartile 1, if the benefits provided will have a slower growth rate than the incomes found in quartile 5. Certainly, the income available to a person does not automatically reflect the level of individual consumption, consumption being rather the expression of giving up a

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The Importance and Role of Social Policy in Maintaining Macroeconomic. . .

Fig. 7.5 Evolution of GDP/inhabitant and general government expenditures with social protection in CEE countries, period 2002–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa.eu/eurostat/data/database)

part of the income available to meet a need, depending on personal preferences (Ilmonen, 2001). Given that a human being is an individual subject to permanent transformations, including physical, social, and cognitive, his needs are specific to each stage of human development. As a result, consumer behavior changes, being correlated with physiological age and social status (Wakabayashi & Hewings, 2007), but also with technical and technological innovation and national socioeconomic development. The well-being of the population is associated with the income possessed and the ability to meet the needs, being directly influenced by the economic development of a country (Jimon et al., 2019). It is noted that the CEE countries included in this research are in a period of economic growth, in terms of increasing the value of GDP per capita and rising level of population income (Fig. 7.5). These factors also influence the capacity of government structures to redistribute benefits through social protection systems, respectively, through the public pension system. It should be noted that between 2002 and 2017, budget expenditures on social protection accounted for 10–13% of the national GDP of the Czech Republic and Romania, and had values between 15 and 19% of GDP in Poland, Hungary, and Slovakia. Pension systems, from the perspective of beneficiaries, provide the income needed to maintain the level of consumption and meet the specific needs. However, in addition to the financial dimension, well-being is also defined by physical health (Gilhooly et al., 2005). Life expectancy at the age of 65 has increased in the last 11 years, especially in the case of women. However, the number of healthy life years does not exceed 15, being noted the increase in the healthy life period in Hungary and its reduction in Romania, starting with 2009. A share of 36–53% of the population over the age of 65 considers having levels of satisfactory health;

7.3 Conclusions and Personal Contributions

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Fig. 7.6 Life expectancy and healthy life expectancy at the age of 65 in CEE countries, 2007–2017. Source: Author’s processing based on data published by Eurostat (https://ec.europa. eu/eurostat/data/database)

meanwhile, the share of people who consider having unsatisfactory health has decreased (Fig. 7.6). However, well-being is a subjective aspect, positively correlated with satisfaction, self-esteem, control over one’s life, but negatively influenced by depressive disorder and domination by others (López-Torres Hidalgo et al., 2010). Minkov (2013) points out that the citizens of CEE countries who have experienced the socialist government system and the transition to the democratic political system perceive a low level of well-being and control in their own lives, explained by the hard work and authority imposed by the socialist system of government. According to publications regarding the evolution of the happiness index (Helliwell et al., 2015, 2016, 2017, 2018, 2019), the population of the five CEE countries included in the research reported an increase in the happiness index, the highest being in Hungary (+20%) and Romania (+18%). This suggests an improvement in living conditions and satisfaction that citizens feel about the socioeconomic development of the country (Fig. 7.7).

7.3

Conclusions and Personal Contributions

Ensuring a decent standard of living for the population can only be achieved by ensuring an adequate financial flow, which must be adjusted to the level of inflation, so as to maintain the purchasing power of the population. The income level of the population must also be coordinated with the at-risk-of-poverty rate, to prevent the phenomenon of population impoverishment. At the same time, social policies must aim to reduce the share of the population with severe material deprivations, through

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The Importance and Role of Social Policy in Maintaining Macroeconomic. . .

Fig. 7.7 Happiness index in CEE countries, 2014–2018. Source: Author’s processing based on data published by https://worldhappiness.report/

deductions and tax exemptions for people earning below the poverty line, social assistance services (shelter, food, health services), increasing education, and encouraging carrying out professional activities, as well as by establishing the value of the minimum benefits granted to pensioners at least equal to the poverty threshold.

7.4

Summary

This chapter emphasizes the role of social policy in society and in macroeconomic policies to maintain socioeconomic stability and foster sustainable economic growth. At the macroeconomic level, pension systems are fulfilling their purpose only if they manage to provide an adequate financial flow to ensure a decent standard of living among the population. The well-being of the population is associated with the income and ability to meet needs, being directly influenced by the economic development of a country. Social transfers made through pension systems have a direct impact on reducing the risk rate of poverty and social exclusion of the population as in the case of people over the age of 65, it is noted that pension income is practically the only income this category of the population disposes of.

References Arza, C. (2015). Discussion paper—The gender dimensions of pension systems: Policies and constraints for the protection of older women. UN Women flagship report Progress of the World’s Women.

References

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Balteș, N., & Jimon, Ș. A. (2018). Pension system in reducing poverty risk in Romania. Revista Economică, 70(3), 8–21. European Commission - Directorate-General for Employment, Social Affairs and Inclusion, Social Protection Committee. (2018). The 2018 Pension Adequacy Report: current and future income adequacy in old age in the EU (Vol. I). European Union. Gilhooly, M., Gilhooly, K., & Bowling, A. (2005). Quality of life: Meaning and measurement. In A. Walker (Ed.), Understanding quality of life in old age. Open University Press. Helliwell, J. F., Layard, R., & Sachs, J. (Eds.). (2015). World happiness report 2015. Sustainable Development Solutions Network. Available online at: https://worldhappiness.report/ed/2015/ Helliwell, J., Layard, R., & Sachs, J. (2016). World happiness report 2016, update (Vol. I). Sustainable Development Solutions Network. Available online at: https://worldhappiness. report/ed/2016/ Helliwell, J., Layard, R., & Sachs, J. (2017). World happiness report 2017. Sustainable Development Solutions Network. Available online at: https://worldhappiness.report/ed/2017/ Helliwell, J., Layard, R., & Sachs, J. (2018). World happiness report 2018. Sustainable Development Solutions Network. Available online at: https://worldhappiness.report/ed/2018/ Helliwell, J., Layard, R., & Sachs, J. (2019). World happiness report 2019. Sustainable Development Solutions Network. Available online at: https://worldhappiness.report/ed/2019/ Ilmonen, K. (2001). A social and economic theory of consumption. Palgrave Macmillan. Jimon, Ș. A., Balteș, N., & Muntean, N. (2019). Social protection of older people and the structure of consumption expenditure in countries of Central and Eastern Europe. Revista Economică, 71 (2), 103–117. Lewis, O. (1959). Five families: Mexican Case studies in the culture of poverty. Mentor Books. López-Torres Hidalgo, J., Navarro Bravo, B., Párraga Martínez, I., Pretel, F. A., Latorre Postigo, J. M., & Rabadán, F. E. (2010). Psychological well-being, assessment tools and related factors. In I. E. Wells (Ed.), Psychological well-being. Nova. Minkov, M. (2013). Cross-cultural analysis: the science and art of comparing the world’s modern societies and their cultures. SAGE. Mojan, B. (2011). Development, poverty of culture, and social policy. Palgrave Macmillan. Neagu, O., Dumiter, F., & Braica, A. (2016). Inequality, economic growth and trade openness: A case study for Central and Eastern European Countries (ECE). Amfiteatru Economic, 18(43), 557–574. Shahid, A. (2014). Ageing with dignity: Old-age pension schemes from the perspective of the right to social security under ICESCR. Human Rights Review, 15, 455–471. Wakabayashi, M., & Hewings, G. J. D. (2007). Life-cycle changes in consumption behavior: Age-specific and regional variations. Journal of Regional Science, 47(2), 315–337.

Chapter 8

Modeling the Macroeconomic Effects of Pension Systems

This chapter aims to achieve a socioeconomic perspective on the financial resources of the elderly population, considering the recommendation of international bodies as OECD, WB, EC to diversify financial resources, on one hand by joining private pension funds and, on the other hand by increasing the degree of personal saving. The objective of this chapter pursued the econometric study of the macroeconomic effects of pension systems, in terms of the close correlation between several specific indicators oriented toward macroeconomic stability, the development of the financial sector, and the structure of national pension systems in CEE countries.

8.1

General Aspects Regarding the Macroeconomic Effects of the Pension Systems

Pension systems are the main tool for ensuring the financial protection of the elderly population. Although public systems face budget deficits and international bodies such as the OECD, the WB and the European Commission support the diversification of financial resources through access to private pension funds and personal savings. Wang et al. (2016) show that extensive reforms to PAYG public pension system and the transition to private pension funds in developing countries did not have the expected results due to the lack of adequacy of reforms related to the national socioeconomic context. However, personal savings are essential for ensuring financial protection and well-being during retirement, the most appropriate method, according to Kurtbegu (2018), is a personal investment. Marcinkiewicz (2018) points out that the savings decision is essential in order to determine the level of savings, depending on the income obtained. Apouey (2018) shows that the degree of savings is higher in the case of people who expect to be long-lived or predict the appearance of pathologies or disability. On the other hand, Metzger (2018) studied personal savings in Germany and demonstrated the positive © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_8

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correlation between savings accounts and the civil status of the population, suggesting the existence of a “herd behavior” on savings, determined by the savings tendency of the life partner. This behavior was also observed by Gerrans et al. (2018) who found that decisions about savings are influenced by the peer environment, especially by colleagues and friends of the same kind. The study by Rey-Ares et al. (2018) concludes that the personal saving decision is positively correlated with age, income and well-being, educational level, job security, medical status, and long-term personal plans. Similar results were obtained by Gallo et al. (2018) in the study regarding the participation of the Italian population in private pension plans, confirming the hypothesis that the degree of participation is positively correlated with financial education, age, and income level. Dushi et al. (2017) found that income level is the main factor, which determines savings and participation in a voluntary pension scheme, and consequently the low-income US population has a low participation rate in voluntary pension schemes. However, Berk et al. (2013) point out that in CEE countries, the level of personal savings for retirement must be determined according to the asset allocation strategy and should be less influenced by income level. Supplementary pension schemes have been developed in order to increase the income of beneficiaries and to ensure well-being during retirement. However, the connection between pension funds and the capital market increases the exposure of the population to investment risk related to the return of financial instruments on the capital market (Gustafson, 2017). The savings made for retirement target a long period of time, Zeng et al. (2018) suggesting three main factors that determine the optimal investment of pension funds, namely: aversion to ambiguity, investments in derivatives, and the level of income and related contributions. On the other hand, Sievanen et al. (2013) show that responsible investment of pension funds is correlated with the legal foundations of a country, ownership of funds, and variables that define the size of the fund. Boubaker et al. (2017) point out that monetary shocks increase the share of pension fund investments in equities, and Alda (2017) notes the positive influence of equity investments on the development of the capital market. Thomas et al. (2014) establish a negative correlation between equity investments and capital market volatility in OECD countries. However, the impact of pension reform and the implementation of private pension funds on economic growth has been relatively small, especially in countries where the distribution of financial assets of the pension fund is mainly in bonds and government securities (Altiparmakov & Nedeljkovic, 2016). Been et al. (2017) note that the expansion of private pension funds is associated with increasing income inequality and poverty risk in OECD countries. Maku et al. (2020) highlight the effectiveness of monetary policies on the exchange rate and bank interest rates in reducing the risk of poverty in Nigeria. Nkeki (2018) establishes the existence of correlations between inflation, interest rate, income security, and investment strategy, by revealing that the increase in income determines the expansion of the risk associated with the investment portfolio and vice versa.

8.2 Research Methodology and Data Used

8.2

145

Research Methodology and Data Used

The empirical study on the macroeconomic effects of pension systems required the construction of a database, including indicators characteristic of the well-being and living conditions of the population, as well as financial and banking indicators. Thus, statistical data published by Eurostat, OECD, IMF, and ECB were used to compile the database, the macroeconomic variables considered relevant for the empirical study were the following: (I) Indicators for assessing the level of population income—median equivalized net income (mdENI); median equivalized net income before social transfers (including pensions)—mdENIbP; median equivalized net income before social transfers (excluding pensions)—mdENIaP (II) Indicators for assessing the level of population poverty—at risk of poverty rate (pARPr); severe material deprivation (psMD) (III) Indicators of price stability—inflation rate (pINFacp) (IV) Financial and banking indicators—interest rate for bank deposits (INTr2); the share of investment of private pension funds in shares (EQ); the share of investment of private pension funds in government securities (BB); the share of investment of private pension funds in cash and deposits (CD); the share of investment of private pension funds in other financial securities (OTH) Equivalized income is an indicator developed by the OECD for the comparability of household income and represents the net disposable income of each household, in cases in which all its members are equal. mdENI represents the median income of a household after tax and other tax payments, available for consumption and savings expressed on an equal footing with members of the household. Eurostat presents this indicator according to the allocations of the social protection system and the distribution of pensions. Thus, mdENIbP expresses the median equivalized net income before the provision of income through the social protection system, including pensions, and mdENIaP expresses the median equivalized net income after the granting of pensions. pARPr highlights the percentage of the population whose income, after the allocations of the social protection system, is below the limit considered the threshold for the risk of poverty, respectively, below 60% of the median equivalized income after the provision of social benefits. psMD shows the share of the population that does not have the necessary financial resources to purchase the things and services considered necessary for a decent living. The IMF presents pINFacp as representing the average percentage change in the prices of goods and services consumed by households compared to the previous year. The ECB provides data on the interest rate of household deposits expressed as a percentage for each period. For the empirical study, it was considered relevant to use the interest rate of new or renegotiated contracts for bank deposits for an average period between 1 year and 2 years.

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The OECD presents the development and evolution of private pension funds at the international level. Among the aspects pursued, an investment strategy is also remarked, respectively, the share of investments in different categories of financial assets. The reports published by the OECD highlight the evolution of private pension fund investments in four categories, namely: equities (EQ), government securities (BB), bank deposits (CD), and other financial securities (OTH). The extraction of these macroeconomic variables from the Eurostat, OECD, IMF, and ECB databases was carried out for the period 2008–2018, while, for the mentioned variables, there were values for all five CEE countries included in the research. The time period was adjusted automatically by the econometric program EViews 10 University Edition, so that the sample formed to be as significant and statistically relevant as possible, and finally, the time section was set for the interval 2009–2018. Econometric tests were performed using the EViews 10 University Edition software package, using pool data regression models, which allow the bi-dimensional analysis of variables, both in the period and in the cross-section section. The method used for econometric testing is Pooled Instrumental Variables (IV)—Two-stage Least Squares (2SLS). Instrumental variables define variables that influence the dependent variable through effects only on the independent variable and not on unobservable variables (regression errors). The 2SLS method aims to determine and replace independent variables related to the residuals of the equation, called endogenous variables, with their values estimated by a regression equation with the instrumental variables, to eliminate the endogeneity of the independent variables. Like the OLS method, the 2SLS method allows the realization of standard regressions—without effects, with fixed effects, and with random effects, both period and cross section. The regression equations used in the econometric study are the following: mdENIbPit ¼ α þ β1  pINFacpit þ β2  psMDit þ β3  pARPRit þ εit

ð8:1Þ

mdENIbPit ¼ α þ 31:94  pINFacpit  125:54  psMDit  148:50  pARPRit þ εit

ð8:1aÞ

mdENIbPit ¼ α þ 85:69  pINFacpit  0:86  psMDit þ 60:09  pARPRit þ εit

ð8:1bÞ

mdENIbPit ¼ α þ 83:50  pINFacpit  44:31  psMDit þ 79:80  pARPRit þ εit

ð8:1cÞ

mdENIaPit ¼ α þ β1  pINFacpit þ β2  psMDit þ β3  pARPRit þ εit

ð8:2Þ

mdENIaPit ¼ α þ 3:12  pINFacpit  126:05  psMDit  168:58  pARPRit þ εit

ð8:2aÞ

8.2 Research Methodology and Data Used

147

mdENIaPit ¼ α þ 80:44  pINFacpit  3:59  psMDit þ 22:91  pARPRit þ εit

ð8:2bÞ

mdENIaPit ¼ α þ 71:27  pINFacpit  46:17  psMDit þ 45:53  pARPRit þ εit

ð8:2cÞ

INTr2it ¼ α þ β1  mdENIit þ β2  pINFacpit þ β3  psMDit þ β4  EQit þ β5  BBit þ β6  CDit þ β7  OTHit þ εit ð8:3Þ INTr2it ¼ α þ 0:01  mdENIit þ 0:50  pINFacpit þ 0:40  psMDit þ 0:07  EQit þ 0:05  BBit þ 0:05  CDit þ 0:26  OTHit þ εit

ð8:3aÞ

INTr2it ¼ α þ 0:01  mdENIit þ 0:43  pINFacpit þ 0:22  psMDit  0:09  EQit  0:13  BBit  0:14  CDit  0:47  OTHit þ εit

ð8:3bÞ

INTr2it ¼ α  0:01  mdENIit þ 0:58  pINFacpit þ 0:35  psMDit þ 0:01  EQit  0:03  BBit  0:08  CDit  0:20  OTHit þ εit

ð8:3cÞ

where: • α—free coefficient • mdENIbP—median equivalized net income before social transfers (including pensions) • pINFacp—inflation rate • psMD—severe material deprivation • pARPR—at risk of poverty rate • mdENIaP—median equivalized net income before social transfers (excluding pensions) • INTr2—interest rate for bank deposits • mdENI—median equivalized net income • EQ—the share of investment of private pension funds in shares • BB—the share of private pension funds investment in government securities • CD—the share of private pension funds’ investment in bank deposits • OTH—the share of investment of private pension funds in other financial securities • εit—regression error

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8.3 8.3.1

8 Modeling the Macroeconomic Effects of Pension Systems

Empirical Results Model I: Macroeconomic Effects of Pension Systems— Ex Ante Provision of Income Through the Social Protection System, Including Pensions

The first model tests the macroeconomic impact of pension systems based on the first regression equation presented above. Following the descriptive analysis of the variables used in the model, it can be noticed that the model variables have an abnormal distribution, according to the JB test for a significance threshold of 5% and positive asymmetry (Skewness > 0), as well as platykurtic vaulting (Kurtosis < 3), with a low probability for the existence of extreme values (Table 8.1). Tests of the first equation were performed using the standard Pooled IV-2SLS method (Table 8.2), considering that independent variables are instrumental variables due to the close relationship between income level, inflation, severe material deprivation, and risk of poverty. The obtained results reveal that the model is marginally significant given the value of the coefficient of determination (Rsquared ¼ 0.91) and the adjusted coefficient of determination (Adjusted Rsquared ¼ 0.91). The model is validated by the significance of the coefficients (Prob F-statistic ¼ 0). The level of the median equivalized net income of the population prior to the allocation of pensions is positively correlated with the inflation rate and negatively with the rate of severe material deprivation and the risk of poverty. In other words, the incomes of the population will expand in accordance with the increase in the inflation level and by reducing the severe material deprivation, as well as the risk of poverty. Table 8.1 Descriptive analysis of model I variables Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

MDENIBP 3798.309 3646.000 7654.000 1197.000 1707.218 0.083639 2.057562 2.099559 0.350015 208907.0 1.57E+08

PINFACP 2.360400 1.975000 7.846000 –1.555000 2.195067 0.379292 2.351185 2.283440 0.319269 129.8220 260.1893

PSMD 14.65273 11.80000 32.70000 2.800000 8.656615 0.641209 2.169718 5.348669 0.068953 805.9000 4046.597

Source: Author’s processing using EViews 10 Academic Edition software

PARPR 15.13455 14.10000 25.40000 8.600000 4.966414 0.662780 2.343818 5.013437 0.081535 832.4000 1331.924

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149

Table 8.2 Econometric test results—macroeconomic impact (ex ante allocation of pension benefits)—standard pooled IV-2SLS Dependent variable: MDENIBP? Method: pooled IV/two-stage least squares Date: 03/17/20; Time: 13:02 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Variable Coefficient Std. error t-Statistic C 7874.415 270.8363 29.07445 PINFACP 31.94317 61.23817 0.521622 PSMD –125.5363 15.45955 –8.120309 PARPR –148.4958 23.29024 –6.375882 Root MSE 504.4763 R-squared Mean dependent var 3878.060 Adjusted R-squared S.D. dependent var 1731.974 S.E. of regression Sum squared resid 12,724,819 F-statistic Durbin–Watson stat 0.412181 Prob(F-statistic) Second-stage SSR 12,447,377 Instrument rank

Prob. 0.0000 0.6044 0.0000 0.0000 0.913429 0.907783 525.9529 165.7328 0.000000 20

Source: Author’s processing using EViews 10 Academic Edition software Table 8.3 Results of econometric tests—macroeconomic impact (ex ante allocation of pension system benefits)— correlation matrix

CZ HU PL RO SK

CZ 1 0.53 0.75 0.08 0.73

HU

PL

RO

SK

1 0.74 0.18 0.18

1 0.18 0.70

1 0.271

1

Source: Author’s processing using EViews 10 Academic Edition software

At the level of CEE countries, the first econometric model on the macroeconomic impact of pension systems reveals their independence through subunit values of the “r” coefficient (Table 8.3). The Czech Republic is negatively correlated with Hungary and Poland and positively correlated with Romania and Slovakia. Positive correlations are established between Hungary and Poland, and there are negative correlations between Hungary and Romania, respectively, Slovakia. Poland is also negatively correlated with all five CEE countries and Romania and Slovakia are negatively correlated with Hungary and Poland (Table 8.3). To highlight the country-specific characteristics of each CEE, as well as each period, the regression equation of the first model was also tested by the Pooled IV-2SLS method with fixed effects (Table 8.4).

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Table 8.4 Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—pooled IV-2SLS—cross-section and period fixed effects Dependent variable: MDENIBP? Method: Pooled IV/two-stage least squares Date: 03/17/20; Time: 13:07 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Variable Coefficient Std. error t-Statistic C 2803.676 744.3925 3.766395 PINFACP 85.68910 41.30400 2.074596 PSMD 0.862915 15.75532 0.054770 PARPR 60.09404 48.86971 1.229679 Fixed effects (cross) CZ—C 2694.196 HU—C 981.0634 PL—C 150.9437 RO—C 3013.863 SK—C 1451.675 Fixed effects (period) 2009—C 326.1263 2010—C 529.0061 2011—C 483.5604 2012—C 233.6621 2013—C 151.1764 2014—C 6.090874 2015—C 120.3454 2016—C 311.2674 2017—C 446.8830 2018—C 838.9446 Effects specification Cross-section fixed (dummy variables) Period fixed (dummy variables) Root MSE 150.2463 R-squared Mean dependent var 3878.060 Adjusted R-squared S.D. dependent var 1731.974 S.E. of regression Sum squared resid 1128697. F-statistic Durbin–Watson stat 1.317882 Prob (F-statistic) Second-stage SSR 1183630. Instrument rank Source: Author’s processing using EViews 10 Academic Edition software

Prob. 0.0006 0.0459 0.9567 0.2275

0.992321 0.988598 184.9404 254.0652 0.000000 29

8.3 Empirical Results Table 8.5 Results of econometric tests—macroeconomic impact (ex ante allocation of pension system benefits)— pooled IV-2SLS correlation matrix—cross-section and period fixed effects

151

CZ HU PL RO SK

CZ 1 0.37 0.19 0.58 0.61

HU

PL

RO

SK

1 0.09 0.51 0.30

1 0.37 0.34

1 0.23

1

Source: Author’s processing using EViews 10 Academic Edition software Table 8.6 Hausman test for random effects

Correlated random effects—Hausman test Pool: MACROECONOMIC Test period random effects Test summary Chi-sq. statistic Chi-sq. d.f. Period random 0.000000 3

Prob. 1.0000

Source: Author’s processing using EViews 10 Academic Edition software

The test result by the Pooled IV-2SLS method with cross-section and period-fixed effects highlights that the model is significant (R-squared ¼ 0.99 and Adjusted Rsquared ¼ 0.99) and valid in terms of coefficients (Prob F-statistic ¼ 0.00). Following the application of this model, a positive correlation is noted between the median equivalized net income, the level of inflation and the at-risk-of-poverty rate, and the negative correlation of the equivalized median net income and the share of the population with severe material deprivation. As a result, the income level of the population will increase if the level of inflation and the at-risk-of-poverty rate increase, as well as if the rate of severe material deprivation decreases. The correlation matrix at the level of the five CEE countries shows their independence, the coefficient “r” having subunit values (Table 8.5). Czech Republic is negatively correlated with all four other CEE countries. Hungary correlates positively with Poland and Romania but is negatively correlated with the Czech Republic and Slovakia. Poland is negatively correlated with the Czech Republic, Romania, and Slovakia, but is positively correlated with Hungary. Romania has a positive correlation with Hungary and Slovakia, and negative correlations with the Czech Republic and Poland. Slovakia is positively correlated only with Romania, having negative correlations with the other three CEE countries. The cross-section variables refer to five CEE countries, so the existence of fixed effects, related to the national specificity, was somewhat predictable. The study can be extended by studying random effects in the case of the period section. Thus, according to the Hausman test, there is no correlation between period random effects and predictors, as a result, the Pooled IV-2SLS model with period random effects can be used (Table 8.6). The tests of the first regression equation by the Pooled IV-2SLS method with cross-section fixed effects and period random effects (Table 8.7) show that the model is significant both in terms of the coefficient of determination (R-squared ¼ 0.98)

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8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.7 Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—pooled IV-2SLS—cross-section fixed effects and period random effects Dependent variable: MDENIBP? Method: Pooled IV/two-stage EGLS (period random effects) Date: 03/17/20; Time: 13:12 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic C 3133.501 726.6095 4.312496 PINFACP 83.49709 40.72310 2.050362 PSMD 44.30819 13.36619 3.314946 PARPR 79.79948 48.10485 1.658866 Fixed effects (cross) CZ—C 2423.448 HU—C 694.0101 PL—C 359.8694 RO—C 2662.023 SK—C 1292.455 Random effects (period) 2009—C 154.0251 2010—C 323.1153 2011—C 308.3551 2012—C 74.37518 2013—C 23.12287 2014—C 25.30821 2015—C 30.02527 2016—C 147.2213 2017—C 215.8484 2018—C 464.5904 Effects specification S.D. Cross-section fixed (dummy variables) Period random 157.4764 Idiosyncratic random 181.1733 Weighted statistics Root MSE 217.0292 R-squared Mean dependent var 3878.060 Adjusted R-squared S.D. dependent var 1699.050 S.E. of regression Sum squared resid 2355083. F-statistic Durbin–Watson stat 0.772885 Prob (F-statistic) Second-stage SSR 2452985. Instrument rank

Prob. 0.0001 0.0466 0.0019 0.1046

Rho 0.4304 0.5696 0.983351 0.980576 236.7982 339.9910 0.000000 20 (continued)

8.3 Empirical Results

153

Table 8.7 (continued) Dependent variable: MDENIBP? Method: Pooled IV/two-stage EGLS (period random effects) Date: 03/17/20; Time: 13:12 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic Unweighted statistics R-squared 0.961825 Mean dependent var Sum squared resid 5611278. Durbin–Watson stat

Prob. 3878.060 0.531237

Source: Author’s processing using EViews 10 Academic Edition software Table 8.8 Results of econometric tests—macroeconomic impact (ex ante allocation of pension benefits)—correlation matrix of the Pooled IV-2SLS model—cross-section fixed effects and period random effects CZ HU PL RO SK

CZ 1 0.841 0.87 0.81 0.75

HU

PL

RO

SK

1 0.93 0.65 0.82

1 0.79 0.78

1 0.62

1

Source: Author’s processing using EViews 10 Academic Edition software

and the coefficient of determination adjusted (Adjusted R-squared ¼ 0.98). Also, the model is validated from the perspective of the significance of the coefficients (Prob F-statistic ¼ 0.00). The results highlighted the period random effects of the predictors, and it is noted that, as with the Pooled IV-2SLS model with cross-section and period-fixed effects, there is a positive correlation between the level of median equivalized net income, inflation and risk of poverty, and a negative correlation between the median equivalized net income and the share of the population with severe material deprivation. However, the determination that the rate of severe material deprivation has on the equivalized median net income is much higher (β2 ¼ –44.31, Prob ¼ 0.0019). As a result, the median equivalized net income of the population increases when the level of inflation and the at-risk-of-poverty rate increase, but also when the rate of severe material deprivation decreases. Regarding the correlations established between the five CEE countries, the correlation matrix of the Pooled IV-2SLS model—cross-section fixed effects and period random effects highlights their independence through the subunit level of the

154

8 Modeling the Macroeconomic Effects of Pension Systems

coefficient “r” and the positive correlation between all five countries CEE included in the research (Table 8.8).

8.3.2

Model II: Macroeconomic Effects of Pension Systems— Ex Post allocation of Social Benefits Through the Pension System

Through the second model, we proposed extending the econometric study, considering as a dependent variable the median equivalized net income of the population after the distribution of pension benefits and keeping the same predictors. The descriptive analysis of these variables shows, through the JB test for a significance threshold of 5%, the abnormal distribution, the negative asymmetry (Skewness < 0), and the platykurtic vault (Kurtosis < 3), according to Table 8.9. The econometric testing of Eq. (8.2) was performed by the standard Pooled IV-2SLS method, and the results obtained reflect the marginal significance of the model (R-squared ¼ 0.94 and Adjusted R-squared ¼ 0.94). From the perspective of the significance regarding the coefficients, the model is valid (Prob F-statistic ¼ 0.00). Following the tests, there can be identified a positive correlation between the median equivalized net income of the population after the distribution of pension benefits and inflation, and a negative correlation with both the share of the population with severe material deprivation and the at-risk-of-poverty rate. Econometric testing has shown that the income level of the population can be increased by reducing the rate of severe material deprivation and the risk of poverty while increasing the rate of inflation (Table 8.10). The correlation matrix for the five CEE countries included in the research highlights their interdependence, coefficient “r” having subunit values. Czech Republic is positively correlated with Slovakia and negatively with all three other Table 8.9 Descriptive analysis of model II variables Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

MDENIAP 4892.655 4940.000 8558.000 1783.000 1802.951 0.201564 2.121401 2.141445 0.342761 269096.0 1.76E+08

PINFACP 2.360400 1.975000 7.846000 –1.555000 2.195067 0.379292 2.351185 2.283440 0.319269 129.8220 260.1893

PSMD 14.65273 11.80000 32.70000 2.800000 8.656615 0.641209 2.169718 5.348669 0.068953 805.9000 4046.597

Source: Author’s processing using EViews 10 Academic Edition software

PARPR 15.13455 14.10000 25.40000 8.600000 4.966414 0.662780 2.343818 5.013437 0.081535 832.4000 1331.924

8.3 Empirical Results

155

Table 8.10 Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS standard Dependent variable: MDENIAP? Method: Pooled IV/two-stage least squares Date: 03/17/20; Time: 13:18 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP? (-1) PSMD? (-1) PARPR? (-1) Variable Coefficient Std. error t-Statistic C 9363.872 233.0473 40.18014 PINFACP? 3.123550 52.69379 0.059277 PSMD? 126.0525 13.30253 9.475832 PARPR? 168.5752 20.04062 8.411675 Root MSE 434.0883 R-squared Mean dependent var 4996.580 Adjusted R-squared S.D. dependent var 1820.934 S.E. of regression Sum squared resid 9421631. F-statistic Durbin–Watson stat 0.658226 Prob (F-statistic) Second-stage SSR 9076342. Instrument rank

Prob. 0.0000 0.9530 0.0000 0.0000 0.942012 0.938230 452.5683 259.1464 0.000000 20

Source: Author’s processing using EViews 10 Academic Edition software Table 8.11 Econometric test results—macroeconomic impact (ex post allocation of pension benefits)—correlation matrix of the standard Pooled IV-2SLS model

CZ HU PL RO SK

CZ 1 0.13 0.28 0.28 0.79

HU

PL

RO

SK

1 0.60 0.27 0.05

1 0.58 0.40

1 0.11

1

Source: Author’s processing using EViews 10 Academic Edition software

CEE countries. Hungary is positively correlated with Poland, Romania, and Slovakia, but is negatively correlated with the Czech Republic. Poland has a positive correlation with Hungary and Romania and a negative correlation with the other CEE countries. Romania correlates positively with Hungary and Poland, and negatively with the Czech Republic and Slovakia, and Slovakia is positively correlated only with the Czech Republic and Hungary (Table 8.11). To highlight country-specific characteristics and periods, the Pooled IV-2SLS method with cross-section and period-fixed effects was applied (Table 8.12). The test results of the Pooled IV-2SLS model with cross-section and period-fixed effects highlight the significance of the model (R-squared ¼ 0.99 and Adjusted Rsquared ¼ 0.99), as well as its validity in terms of coefficients (Prob F-statistic ¼ 0.00). It is noted that the median equal net income of the population, after

156

8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.12 Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS with cross-section and period fixed effects Dependent variable: MDENIAP? Method: Pooled IV/two-stage least squares Date: 03/17/20; Time: 13:21 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?( -1) Variable Coefficient Std. error t-Statistic C 4536.958 793.1210 5.720386 PINFACP 80.43505 44.00779 1.827746 PSMD 3.592550 16.78668 0.214012 PARPR 22.91326 52.06876 0.440058 Fixed effects (cross) CZ—C 2347.779 HU—C 785.8370 PL—C 82.19223 RO—C 3044.530 SK—C 1400.395 Fixed effects (period) 2009—C 482.3951 2010—C 679.6299 2011—C 466.3205 2012—C 221.6548 2013—C 130.9879 2014—C 66.96275 2015—C 172.8998 2016—C 388.9493 2017—C 442.9490 2018—C 909.2274 Effects specification Cross-section fixed (dummy variables) Period fixed (dummy variables) Root MSE 160.0815 R-squared Mean dependent var 4996.580 Adjusted R-squared S.D. dependent var 1820.934 S.E. of regression Sum squared resid 1281304. F-statistic Durbin–Watson stat 1.349545 Prob (F-statistic) Second-stage SSR 1347617. Instrument rank Source: Author’s processing using EViews 10 Academic Edition software

Prob. 0.0000 0.0766 0.8319 0.6628

0.992114 0.988290 197.0467 246.6010 0.000000 29

8.3 Empirical Results Table 8.13 Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)— pooled IV-2SLS correlation matrix with fixed transverse and temporal effects

157

CZ HU PL RO SK

CZ 1 0.16 0.35 0.44 0.31

HU

PL

RO

SK

1 0.26 0.28 0.46

1 0.14 0.27

1 0.24

1

Source: Author’s processing using EViews 10 Academic Edition software Table 8.14 Hausman test for random effects

Correlated random effects—Hausman test Pool: MACROECONOMIC Test period random effects Test summary Chi-sq. statistic Chi-sq. d.f. Period random 0.000000 3

Prob. 1.0000

Source: Author’s processing using EViews 10 Academic Edition software

the distribution of pension benefits, is positively correlated with the inflation rate and the poverty risk rate, but is negatively correlated with the share of the population with severe material deprivation. Thus, the income of the population will increase by increasing the level of inflation and the risk of poverty, as well as by reducing the severe material deprivation of the population. Regarding the correlation matrix of the five CEE countries, it is noted their interdependence. Thus, Czech Republic, Poland, and Slovakia have negative correlations with each of the other four CEE countries, the only positive correlation being established between Hungary and Romania (Table 8.13). The model can be extended by studying random effects. According to the Hausman random effects test, there is no correlation between predictors and temporal random effects, and the Pooled IV-2SLS with random temporal effects can be used (Table 8.14). The results of the econometric test using the Pooled IV-2SLS method with fixed transverse effects and random temporal effects (Table 8.15) show that the model is significant (R-squared ¼ 0.98 and Adjusted R-squared ¼ 0.98) and is validated from the point of view of coefficients (Prob F-statistic ¼ 0.00). Following modeling, the correlations between the variables established by the Pooled IV-2SLS method with cross-section fixed effects and period random effects are retained, but the degree of predictor determination on the dependent variable changes, in order to increase the influence of the inflation rate and decrease the influence of material deprivation and of the risk of poverty. Regarding the correlation matrix of the five CEE countries (Table 8.16), their interdependence, the subunit value of the coefficient “r” and the establishment of positive correlations between all five CEE countries can be observed.

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8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.15 Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—pooled IV-2SLS with cross-section fixed effects and period random effects Dependent variable: MDENIAP? Method: Pooled IV/two-stage egls (period random effects) Date: 03/17/20; Time: 13:23 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic C 4824.216 774.8583 6.225933 PINFACP 71.27478 43.99149 1.620195 PSMD 46.16535 14.57404 3.167643 PARPR 45.52534 51.25441 0.888223 Fixed effects (cross) CZ—C 2098.149 HU—C 496.3439 PL—C 130.3649 RO—C 2720.502 SK—C 1249.061 Random effects (period) 2009—C 283.1341 2010—C 454.6769 2011—C 297.9637 2012—C 59.50541 2013—C 10.60747 2014—C 63.79045 2015—C 60.25891 2016—C 204.1755 2017—C 225.3470 2018—C 552.3157 Effects specification S.D. Cross-section fixed (dummy variables) Period random 187.0080 Idiosyncratic random 193.0331 Weighted statistics Root MSE 228.5688 R-squared Mean dependent var 4996.580 Adjusted R-squared S.D. dependent var 1776.818 S.E. of regression Sum squared resid 2612185. F-statistic Durbin–Watson stat 0.762532 Prob (F-statistic) Second-stage SSR 2775950. Instrument rank

Prob. 0.0000 0.1127 0.0029 0.3795

Rho 0.4842 0.5158 0.983114 0.980300 249.3890 328.3657 0.000000 20 (continued)

8.3 Empirical Results

159

Table 8.15 (continued) Dependent variable: MDENIAP? Method: Pooled IV/two-stage egls (period random effects) Date: 03/17/20; Time: 13:23 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C PINFACP?(-1) PSMD?(-1) PARPR?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic Unweighted statistics R-squared 0.954634 Mean dependent var Sum squared resid 7370876. Durbin–Watson stat

Prob. 4996.580 0.491037

Source: Author’s processing using EViews 10 Academic Edition software Table 8.16 Results of econometric tests—macroeconomic impact (ex post allocation of pension benefits)—correlation matrix of the Pooled IV-2SLS model with cross-section fixed effects and period random effects CZ HU PL RO SK

CZ 1 0.84 0.87 0.85 0.82

HU

PL

RO

SK

1 0.87 0.64 0.77

1 0.89 0.82

1 0.74

1

Source: Author’s processing using EViews 10 Academic Edition software

8.3.3

Model III: Macroeconomic Effects of Pension Systems from an Investment Perspective

The third model studies the macroeconomic effects of pension systems from an investment perspective using the standard Pooled IV-2SLS method. The descriptive analysis of the variables reveals the normal distribution of the interest rate on bank deposits; the share of investment of private pension funds in shares, government securities, bank deposits, and other financial securities, and an abnormal distribution in the case of other variables, according to the JB test for a significance threshold of 5% (Table 8.17). The variables median equivalized net income and the share of private pension fund investments in government securities show a negative asymmetry (Skewness < 0), and the other variables show a positive asymmetry. The Kurtosis coefficient shows a platykurtic distribution (Kurtosis < 3) of the interest rate on bank deposits, the share of investment of private pension funds in shares, government securities, bank deposits, and other financial securities, and leptokurtic distribution in the case of other variables (Table 8.17).

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8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.17 Descriptive analysis of model III variables Mean Median Maximum Minimum Std.Dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev. Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

INTR2 3.423636 2.640000 11.58000 0.610000 2.500888 1.354175 4.268283 20.49598 0.000035 188.3000 337.7397 EQ 16.21022 6.667801 85.23110 0.148445 23.86830 2.020685 6.068998 59.01368 0.000000 891.5622 30,763.57

MDENI 5276.764 5164.000 9088.000 1952.000 1912.882 0.245555 2.159418 2.171962 0.337570 290,222.0 1.98E+08 BB 64.78886 67.94380 88.01801 7.401099 20.21214 –1.755041 5.778284 45.92392 0.000000 3563.387 22,060.66

PINFACP 2.360400 1.975000 7.846000 1.555000 2.195067 0.379292 2.351185 2.283440 0.319269 129.8220 260.1893 CD 9.531344 7.724748 29.19348 1.628340 6.828415 1.434832 4.255399 22.48354 0.000013 524.2239 2517.872

PSMD 14.65273 11.80000 32.70000 2.800000 8.656615 0.641209 2.169718 5.348669 0.068953 805.9000 4046.597 OTH 1.653276 1.275524 6.850087 –0.280547 1.610854 1.056604 3.581586 11.00891 0.004069 90.93018 140.1219

Source: Author’s processing using EViews 10 Academic Edition software

Model III uses the standard Pooled IV-2SLS method for econometric testing of Eq. (8.3). The results reflect the existence of a reduced significance of the model (Rsquared ¼ 0.79 and Adjusted R-squared ¼ 0.52), but also its validity from the perspective of the significance of the coefficients (Prob F-statistic ¼ 0.00). The interest rate is positively correlated with all predictors, which means that the interest rate will increase by increasing the level of median equivalized net income, inflation, the share of the population with severe material deprivation, but also by increasing the share of private pension fund investments in shares, government securities, deposits and other financial instruments (Table 8.18). The correlation matrix of countries reflects their interdependence and subunit values of the coefficient “r”. The Czech Republic and Slovakia are positively correlated with each of the four CEE countries. Hungary correlates negatively with Poland, being in a positive correlation with the other countries. Poland is in a negative correlation with Hungary and Romania (Table 8.19). The empirical study on the macroeconomic impact of pension systems from an investment perspective was extended by the Pooled IV-2SLS method with fixed effects (Table 8.20). The empirical results obtained from the application of the

8.3 Empirical Results

161

Table 8.18 Econometric test results—macroeconomic impact—investment perspective—pooled IV-2SLS standard Dependent variable: INTR2? Method: Pooled IV/two-stage least squares Date: 03/17/20; Time: 13:35 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C MDENI?(-1) PINFACP?(-1) PSMD?(-1) EQ?(-1) BB? (-1) CD?(-1) OTH?(-1) Variable Coefficient Std. error t-Statistic Prob. C 14.57140 3.672823 3.967356 0.0003 MDENI 0.001020 0.000303 3.363881 0.0016 PINFACP 0.496981 0.100506 4.944802 0.0000 PSMD 0.392476 0.069241 5.668260 0.0000 EQ 0.074657 0.022114 3.376055 0.0016 BB 0.054556 0.020623 2.645416 0.0114 CD 0.048077 0.039424 1.219482 0.2295 OTH 0.259459 0.202394 1.281952 0.2069 Root MSE 1.079911 R-squared 0.787323 Mean dependent var 3.185400 Adjusted R-squared 0.751876 S.D. dependent var 2.365452 S.E. of regression 1.178279 Sum squared resid 58.31039 F-statistic 24.02661 Durbin–Watson stat 1.114118 Prob (F-statistic) 0.000000 Second-stage SSR 54.78596 Instrument rank 40 Source: Author’s processing using EViews 10 Academic Edition software Table 8.19 Econometric test results—macroeconomic impact—investment perspective—standard pooled IV-2SLS model correlation matrix

CZ HU PL RO SK

CZ 1 0.46 0.33 0.57 0.82

HU

PL

RO

SK

1 0.19 0.87 0.38

1 0.22 0.41

1 0.56

1

Source: Author’s processing using EViews 10 Academic Edition software

Pooled IV-2SLS method with cross-section and period-fixed effects show that the model is marginally significant (R-squared ¼ 0.94 and Adjusted R-squared ¼ 0.89) and valid in terms of the significance of the coefficients (Prob F-statistic ¼ 0.00). The influence of the cross-section and period-fixed effects determined that the interest rate on bank deposits to be positively correlated with the median equivalized net income of the population, the level of inflation, and the share of the population with severe material deprivation, and negatively correlated with the share of private pension fund investments in shares, government bonds, deposits, and other financial

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8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.20 Econometric test results—macroeconomic impact—investment perspective—pooled IV-2SLS with cross-section and period fixed effects Dependent variable: INTR2? Method: Pooled IV/two-stage least squares Date: 03/17/20; Time: 13:45 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C MDENI?(-1) PINFACP?(-1) PSMD?(-1) EQ?(-1) BB? (-1) CD?(-1) OTH?(-1) Variable Coefficient Std. error t-Statistic Prob. C 6.993577 10.09699 0.692640 0.4940 MDENI 0.000733 0.000784 0.934646 0.3577 PINFACP 0.434705 0.134933 3.221640 0.0031 PSMD 0.217949 0.064658 3.370818 0.0021 EQ 0.093252 0.075023 1.242977 0.2238 BB 0.127000 0.077733 1.633808 0.1131 CD 0.139186 0.062169 2.238814 0.0330 OTH 0.471135 0.245184 1.921558 0.0645 Fixed effects (cross) CZ—C 1.020878 HU—C 1.992024 PL—C 0.023491 RO—C 1.586064 SK—C 0.638409 Fixed effects (period) 2009—C 2.855692 2010—C 0.800868 2011—C 0.734658 2012—C 0.637283 2013—C 0.023931 2014—C 0.217229 2015—C 0.189962 2016—C 0.900647 2017—C 1.878593 2018—C 1.866000 Effects specification Cross-section fixed (dummy variables) Period fixed (dummy variables) Root MSE 0.593510 R-squared 0.935761 Mean dependent var 3.185400 Adjusted R-squared 0.891458 S.D. dependent var 2.365452 S.E. of regression 0.779316 Sum squared resid 17.61269 F-statistic 20.62814 Durbin–Watson stat 1.726964 Prob (F-statistic) 0.000000 Second-stage SSR 18.00653 Instrument rank 49 Source: Author’s processing using EViews 10 Academic Edition software

8.3 Empirical Results Table 8.21 Results of econometric tests—macroeconomic impact—investment perspective—correlation matrix of the Pooled IV-2SLS model with cross-section and period fixed effects

163

CZ HU PL RO SK

CZ 1 0.74 0.47 0.78 0.01

HU

PL

RO

SK

1 0.76 0.86 0.25

1 0.88 0.32

1 0.10

1

Source: Author’s processing using EViews 10 Academic Edition software Table 8.22 Hausman test for random effects

Correlated random effects—Hausman test Pool: MACROECONOMIC Test period random effects Test summary Chi-sq. statistic Chi-sq. d.f. Period random 0.000000 7

Prob. 1.0000

Source: Author’s processing using EViews 10 Academic Edition software

instruments. The model showed that the interest rate on bank deposits will increase if the level of household income, the level of inflation, and the rate of material deprivation will increase and the level of investments in pension funds will decrease. The correlation matrix of CEE countries shows their interdependence, through the subunit level of the “r” coefficient (Table 8.21). The Czech Republic correlates negatively with Hungary and Romania but is positively correlated with Poland and Slovakia. Hungary is positively correlated with Romania and negatively with all other CEE countries. Poland correlates positively only with the Czech Republic, being negatively correlated with all other CEE countries. Positive correlations are established between Romania and Hungary, and between Romania and Slovakia, as well as between Slovakia and the Czech Republic. The econometric study can be extended by analyzing random effects. According to the Hausman test on random effects, they are not correlated with period predictors, therefore the Pooled IV-2SLS method with cross-section fixed effects and period random effects can be used in econometric testing (Table 8.22). Following the application of the Pooled IV-2SLS method with cross-section fixed effects and period random effects, it is confirmed that the model is marginally significant (R-squared ¼ 0.83 and Adjusted R-squared ¼ 0.80) and valid from the perspective of the significance of the coefficients (Prob F-statistic ¼ 0.00). The test results reflect the influence of period random effects and the positive correlation between the interest rate on bank deposits and the level of inflation, the share of the population with severe material deprivation, and the share of private pension fund investments in shares (Table 8.23). The interest rate on bank deposits is negatively correlated with the median equivalized net income of the population and the share of investments of private pension funds in government securities, bank deposits, and other financial securities. It was concluded that the level of interest on bank deposits increases as inflation

164

8 Modeling the Macroeconomic Effects of Pension Systems

Table 8.23 Econometric test results—macroeconomic impact—investment perspective—pooled IV-2SLS with cross-section fixed effects and period random effects Dependent variable: INTR2? Method: Pooled IV/two-stage EGLS (period random effects) Date: 03/17/20; Time: 13:47 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C MDENI?(-1) PINFACP?(-1) PSMD?( -1) EQ?(-1) BB? (-1) CD?(-1) OTH?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic Prob. C 2.173482 7.859008 0.276559 0.7836 MDENI 0.000366 0.000470 0.779983 0.4402 PINFACP 0.582010 0.082596 7.046422 0.0000 PSMD 0.350032 0.051083 6.852203 0.0000 EQ 0.004423 0.065100 0.067934 0.9462 BB 0.034887 0.065963 0.528889 0.6000 CD 0.080488 0.050328 1.599279 0.1180 OTH 0.200358 0.199727 1.003159 0.3221 Fixed effects (cross) CZ—C 4.259648 HU—C 2.214914 PL—C 0.357472 RO—C 3.985675 SK—C 2.298412 Random effects (period) 2009—C 0.511505 2010—C 0.102301 2011—C 0.052182 2012—C 0.074970 2013—C 0.136402 2014—C 0.067203 2015—C 0.089021 2016—C 0.007269 2017—C 0.189248 2018—C 0.014512 Effects specification S.D. Rho Cross-section fixed (dummy variables) Period random 0.218349 0.0731 Idiosyncratic random 0.777428 0.9269 Weighted statistics Root MSE 0.894924 R-squared 0.829067 (continued)

8.3 Empirical Results

165

Table 8.23 (continued) Dependent variable: INTR2? Method: Pooled IV/two-stage EGLS (period random effects) Date: 03/17/20; Time: 13:47 Sample (adjusted): 2009 2018 Included observations: 10 after adjustments Cross-sections included: 5 Total pool (balanced) observations: 50 Instrument specification: @CXINST C MDENI?(-1) PINFACP?(-1) PSMD?( -1) EQ?(-1) BB? (-1) CD?(-1) OTH?(-1) Swamy and Arora estimator of component variances Variable Coefficient Std. error t-Statistic Prob. Mean dependent var 3.185400 Adjusted R-squared 0.779586 S.D. dependent var 2.186554 S.E. of regression 1.026548 Sum squared resid 40.04446 F-statistic 18.21570 Durbin–Watson stat 1.545850 Prob (F-statistic) 0.000000 Second-stage SSR 37.34597 Instrument rank 40 Unweighted statistics R-squared 0.831535 Mean dependent var 3.185400 Sum squared resid 46.18848 Durbin–Watson stat 1.548042 Source: Author’s processing using EViews 10 Academic Edition software Table 8.24 Results of econometric tests—macroeconomic impact—investment perspective—correlation matrix of the Pooled IV-2SLS model with cross-section fixed effects and period random effects CZ HU PL RO SK

CZ 1 0.62 0.12 0.51 0.33

HU

PL

RO

SK

1 0.24 0.94 0.51

1 0.40 0.26

1 0.58

1

Source: Author’s processing using EViews 10 Academic Edition software

increases, the rate of severe material deprivation and the increase in the share of investments of pension funds in assets, as well as by reducing the level of income of the population and decreasing investments of pension funds in bonds, bank deposits, and other financial instruments. The correlation matrix of the five CEE countries (Table 8.24) reflects their interdependence and subunit values of the “r” coefficient. The results of econometric tests show that the Czech Republic is positively correlated with all four other CEE countries. Hungary is negatively correlated only with Poland, being in a positive correlation with all other CEE countries. Poland positively correlates only with the Czech Republic and is negatively correlated with the other CEE countries. Romania

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8 Modeling the Macroeconomic Effects of Pension Systems

and Slovakia have negative correlations only with Poland, with the other CEE countries establishing positive correlations.

8.4

Conclusions and Personal Contributions

The empirical study regarding the macroeconomic effects of pension systems using the Pooled IV-2SLS method shows more relevant results in cases that include fixed cross-section and temporal effects, as in such models are captured the specific characteristics of the five CEE countries and each period. Econometric results have proved that the benefits provided by public pension systems and privately managed pension funds must be increased as the level of real purchasing power erodes. In this respect, monetary policies must be oriented toward maintaining consumer price stability, ensuring a macroeconomic climate favorable for investments and personal savings. The econometric study showed that the interest rate on bank deposits increases in proportion to the income of the population. Thus, the reduced existence of economic resources determines the increase in their prices, and the reduced amount of financial resources will lead to an increase in the interest rate on bank deposits. The interest rate on bank deposits is influenced by the investment strategy of private pension funds and reflects the competitiveness between savings through the banking system and private pension funds. Personal savings must be diversified by acquiring financial assets with different degrees of risk exposure. In this regard, we consider that the level of financial literacy, increasing financial inclusion, and promoting financial instruments should be improved in CEE countries. Simultaneously, personal savings should be encouraged by providing tax deductions and exemptions.

8.5

Summary

This chapter offers an econometric study of the macroeconomic effects of pension systems, in view of the existence of close correlations between specific indicators of macroeconomic stability, the development of the financial sector, and the structure of national pension systems in CEE countries. The empirical results reflect the fact that with the increase of the population’s incomes, the competitiveness of the saving instruments will also increase. Increasing the responsibility of the population to provide the necessary resources for old age is an opportunity to develop the stock market and stimulate competitiveness in the financial banking sector, as well as to reduce the risk of poverty of the elderly population in CEE countries.

References

167

References Alda, M. (2017). The relationship between pension funds and the stock market: Does the aging population of Europe affect it? International Review of Financial Analysis, 49, 83–97. Altiparmakov, N., & Nedeljkovic, M. (2016). Does pension privatization increase economic growth? Evidence from Latin America and Eastern Europe (CESIFO Working Paper no. 6074). Apouey, B. H. (2018). Preparation for old age in France: The roles of preferences and expectations. The Journal of the Economics of Ageing, 12, 15–23. Been, J., Caminada, K., Goudswaard, K., & van Vliet, O. (2017). Public/private pension mix, income inequality and poverty among the elderly in Europe: An empirical analysis using new and revised OECD data. Social Policy & Administration, 51(7), 1079–1100. Berk, A. S., Cok, M., Kosak, M., & Sambt, J. (2013). CEE transition from PAYG to private pensions: Income gaps and asset allocation. Czech Journal of Economics and Finance, 63(4), 360–381. Boubaker, S., Gounopoulos, D., Nguyen, D. K., & Paltalidis, N. (2017). Assessing the effects of unconventional monetary policy and low interest rates on pension fund risk incentives. Journal of Banking and Finance, 77, 35–52. Dushi, I., Iams, H. M., & Tamborini, C. R. (2017). Contributory retirement saving plans: Differences across earnings groups and implications for retirement security. Social Security Bulletin, 77(2), 13–24. Gallo, G., Torricelli, C., & van Soest, A. (2018). Individual heterogeneity and pension choices: Evidence from Italy. Journal of Economic Behavior and Organization, 148, 260–281. Gerrans, P., Moulang, C., Feng, J., & Strydom, M. (2018). Individual and peer effects in retirement savings investment choices. Pacific-Basin Finance Journal, 47(C), 150–165. Gustafson, M. T. (2017). The market sensitivity of retirement and defined contribution pensions: Evidence from the public sector. Journal of Public Economics, 145, 1–13. Kurtbegu, E. (2018). Replicating intergenerational longevity risk sharing in collective defined contribution pension plans using financial markets. Insurance: Mathematics and Economics, 78, 286–300. Maku, O. E., Tella, A. T., & Fagbohun, A. C. (2020). Alleviating poverty in Nigeria: Keynesian vs monetary theory of poverty. Studia Universitatis “Vasile Goldis” Arad. Economics Series, 30 (1), 103–120. Marcinkiewicz, E. (2018). Does the retirement saving motive foster higher savings? The evidence from the Polish household survey. Business and Economic Horizons, 14(1), 85–96. Metzger, C. (2018). Intra-household allocation of non-mandatory retirement savings. The Journal of the Economics of Ageing, 12, 77–87. Nkeki, C. I. (2018). Optimal pension fund management in a jump–diffusion environment: Theoretical and empirical studies. Journal of Computational and Applied Mathematics, 330, 228–252. Rey-Ares, L., Fernandez-Lopez, S., & Vivel-Bua, M. (2018). The influence of social models on retirement savings: Evidence for European countries. Social Indicators Research, 136, 247–268. Sievanen, R., Rita, H., & Scholtens, B. (2013). The drivers of responsible investment: The case of European pension funds. Journal of Business Ethics, 117, 137–151. Thomas, A., Spataro, L., & Mathew, N. (2014). Pension funds and stock market volatility: An empirical analysis of OECD countries. Journal of Financial Stability, 11, 92–103. Wang, X., Williamson, J. B., & Cansoy, M. (2016). Developing countries and systemic pension reforms: Reflections on some emerging problems. International Social Security Review, 69(2), 85–106. Zeng, Y., Li, D., Chen, Z., & Yang, Z. (2018). Ambiguity aversion and optimal derivative-based pension investment with stochastic income and volatility. Journal of Economic Dynamics & Control, 88, 70–103.

Chapter 9

Financial Sustainability of Public Pension System

The object of this chapter is the presentation of the budgetary system of public pension schemes in CEE countries, in terms of salary incomes taxation, in order to obtain the resources needed to finance social benefits, but also from the perspective of the level of benefits and the situation of budgetary balance. The first part of this chapter concerns the fiscal policy pursued by CEE countries, from the perspective of the Community fiscal framework and international tax law. Next, there are exposed specific issues related to the contributions to national social protection systems which are presented as the main factors influencing taxpayers’ compliance. The following section is dedicated to social insurance systems budgets, both in terms of levy the resources needed to finance social benefits, the structure of budget expenditures, and the level of the budget deficit.

9.1

Fiscal Policy: Implications from the Perspective of the National and European Fiscal Area

Fiscal policy is a major component of financial policy, promoted by the state and public authorities regarding the establishment and collection of taxes, fees, and social contributions to finance public spending (Chirleșan, 2008). The fiscal policy establishes the volume of financial resources necessary for the state to cover the expenses incurred, the origin of these resources, the methods of collection, the amount of taxes imposed, the tax rate, and the tax pressure. Due to fiscal sovereignty, each state has the right “to organize the fiscal system it establishes, to define the taxes that make up that system, to specify the subjects of taxation, to determine the tax base, to size the tax rates, to fix the payment terms, to grant fiscal facilities, to establish fiscal sanctions, to set up the means of appeal and the procedure for solving the fiscal disputes, etc.” (Condor, 1999, pp. 31).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_9

169

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9 Financial Sustainability of Public Pension System

At an international level, the fiscal policy defines the legal framework for the taxation of international transactions, both in terms of direct taxes and in terms of indirect taxes. The formation of the EU, while respecting the four fundamental freedoms, namely: free movement of persons, goods, services, and capital, requires the harmonization and convergence of fiscal and social legislation, a delicate issue in terms of national sovereignty, but also due to the need for unanimity regarding the legislative adaptation process (Brezeanu, 2007). As a result, the internationally accepted convention in genere limits the tax authority of a state on the collection of taxes on taxable objects in its territory, as well as the impossibility of imposing tax claims on the territory of another state (Dumiter et al., 2019). Direct taxation, from a single market perspective, does not require harmonization if the four fundamental freedoms are respected. However, from the perspective of the right to social protection, the free movement of the population presents two risks. First, social protection and pension systems are organized and operate within the territory of a country; in this sense, the application of the principle of territoriality eliminates the provision of social benefits at an international level. On the other hand, the state has the obligation to ensure the social protection of its citizens, and according to the principle of residence, the host state has no obligation toward nonresidents present on its territory. At the same time, these situations generate the incidence of multiple legislative systems that can lead to the manifestation of international double taxation. The occurrence of such events is most often eliminated by signing bilateral agreements on social protection and conventions to avoid international double taxation in the social field. Through these legislative instruments, the Contracting States establish the circumstances of taxation by either the source state or the residence state (Kirsch, 2009), the purpose is “to protect taxpayers against the abuse of legislation regarding the taxation of income and profits obtained abroad and to establish the limit of the jurisprudence of national tax authorities” (Dumiter et al., 2017, pp. 248). The bilateral nature of international treaties supposes that the contracting states have made compromises on fiscal sovereignty and the right to impose, depending on the economic and political relationship between them (Taylor, 2010). Although the fiscal sovereignty of both states is maintained, international treaties are mutual agreements that specify only the limit of the right to impose (Lefter & Chirică, 2010), being an integral part of international law, which once ratified by both contracting states, their provisions enter into force and achieves a priority in application over the national legislation. The tax system and fiscal policies implemented at the state level must be adapted to the international framework in order to ensure competitiveness in terms of taxes and duties. Through appropriate policies, the state can “positively influence the increase of mobility of capital and labor, each taxpayer being interested in having the most profitable opportunities to obtain the highest return on income before or after taxation” (Chilarez & Ene, 2014), and as a result, it is favored the socioeconomic development. However, the promotion of fiscal policies that favor the mobility of capital and labor, leads to the transfer of fiscal burdens and an economic,

9.1 Fiscal Policy: Implications from the Perspective of the National and. . .

171

financial, and social imbalance, the role of current fiscal systems being to ensure socioeconomic stability by stopping harmful fiscal competition. Regulations regarding the respect of the right to social protection are closely linked to labor market regulations, especially in the case of pension systems which involve the contributions and the mobilization of funds during the period of professional activity. In this sense, the international bilateral treaties that register the most influence of the contribution and, implicitly, condition the right to social security, are the international treaties regarding social security and the international double taxation avoidance conventions. International social security treaties are the main legal instrument by which the right to social protection of nonresidents is respected at an international level. These aim to regulate the portability of the minimum benefits provided by the social protection systems stipulated by Convention no. 102 of the ILO (1952), namely: medical care, unemployment, maternity, accidents, and pension benefits. The study made by Holzmann (2016) on the impact of concluding such treaties between EU states with nonmember partners showed that these have a positive effect on nonresidents, but only a small percentage of the migrant population make use of their provisions. Bilateral social security treaties are not as widespread as international double taxation avoidance agreements. At the level of CEE countries, the Czech Republic, Romania, and Hungary have more than ten social security treaties concluded mainly with non-EU European countries, but also with countries in Asia, Africa, and America (Table 9.1). Holzmann and Koettl (2015) argue the importance of ensuring social protection at an international level from three perspectives: from an economic point of view, the absence of obstacles to the transfer of social protection rights has a positive effect on economic development; from a social point of view, the well-being of beneficiaries is negatively influenced by the impossibility of portability of cumulated social rights; from a human point of view, the right to social security is a universal right, which must be respected regardless of the state of residence and domicile of the individual. Regarding the conventions for international double taxation avoidance, these are intended to prevent the taxpayer of one state, or in certain cases of several states, from being taxed for the same income or capital in more than one state (Dumiter et al., 2015). The situation of double taxation most often occurs at the international level when “one state claims tax authority based on the residence or nationality of the taxpayer, while another state applies the tax authority based on the origin of the income” (Barthel et al., 2010, pp. 367). Worldwide, there are more than 3000 conventions to avoid international double taxation, which establish the competence of each state to tax the income of nonresidents (Kirsch, 2009). However, according to the United Nations Conference on Trade and Development, there are only seven agreements to avoid double international taxation in case of contributions to social protection systems. Among the CEE states, Poland concluded such an agreement in 2006 with Macedonia, and Czech Republic signed a treaty in 2007 to avoid double taxation of social security contributions with the USA (Dumiter, 2020).

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9 Financial Sustainability of Public Pension System

Table 9.1 Bilateral treaties on social security in CEE states Country Czech Republic

Hungary

Poland

Number of partner countries 17

10

7

Romania

14

Slovakia

7

Partner countries: Europe Albania Croatia Macedonia Montenegro Moldova Russia Serbia Switzerland Ukraine Bosnia and Herzegovina Croatia Montenegro Russia Switzerland Ukraine Macedonia Serbia Albania Macedonia Moldova Montenegro Russia Serbia Ukraine Croatia Russia Switzerland Ukraine

Asia India Japan Turkey

Africa Israel

America Canada Chile USA

Oceania Australia

India

–

Canada USA

Australia

Korea

Israel

Australia

Korea Turkey

Algeria Libya Morocco

Canada USA Canada Peru

–

Israel

Canada

Australia

–

Source: Author’s processing after the publication “Migrant access to social protection under Bilateral Labor Agreements: A review of 120 countries and nine bilateral arrangements” by van Panhuys et al. (2017)

CEE countries have concluded multiple international double taxation treaties, most often aimed to avoid double taxation of income, including pension income and capital. To avoid international double taxation, the Czech Republic grants, in accordance with the concluded treaties, an exemption or a credit for taxes paid abroad, and if a convention for the avoidance of international double taxation does not apply, the tax paid abroad may be deducted as an expense. Poland, Slovakia, and Romania establish the granting of a tax credit for taxes paid in a contracting country up to the limit of the amount of tax that should be paid in the country of residence for the same income. Some of the agreements concluded by Slovakia provide for the avoidance of double international taxation the use of the total exemption method, which means that those incomes taxed in the partner country will be excluded from taxation in Slovakia. Hungary, through the concluded treaties, grants an exemption or a tax credit for incomes taxed in a contracting country, and in the absence of an

9.1 Fiscal Policy: Implications from the Perspective of the National and. . .

173

international agreement to avoid double taxation, the national tax law provides for a tax credit for the taxes paid abroad (Dumiter & Jimon, 2016). Compliance with the provisions of the international treaties to which Romania is a party is guaranteed by the Constitution,1 so that “the fiscal regime of the incomes obtained on the Romanian territory is provided in the corroboration of the provisions of the Fiscal Code with the articles of the international fiscal conventions” (Covrig, 2012, pp. 427). Regarding the taxation of incomes obtained by nonresidents on the territory of Romania, the Fiscal Code stipulates their obligation to declare and pay the tax corresponding to each source of income,2 benefiting from the same tax treatment as residents, based on the legal instruments on the exchange of information signed by Romania.3 On the other hand, the residents of Romania who obtain income abroad have the obligation to declare, calculate and pay the tax related to these incomes, by income categories, considering the provisions of the conventions for international double taxation avoidance.4 This also applies to income from pensions, which according to the Tax Code are taxable. The obligation to calculate, withhold and pay the income tax from pensions distributed on Romanian territory belongs to each pension payer.5 The employer is responsible for the calculation, withholding, and payment of social security contributions related to wages and incomes assimilated to wages due by his employees, taking into account the provisions of European legislation on social security. Moreover, if the employer does not have a registered office, a permanent establishment, or a representative office on the territory of Romania, employees can make the declaration and payment of social contributions only under the terms of an agreement concluded with the employer,6 otherwise liability being of the employer.7

1 Art. 11—International law and domestic law, para. (1) of the Romanian Constitution stipulates that “the Romanian state undertakes to fulfill exactly and in good faith the obligations incumbent on it from the treaties to which it is a party.” Available online at: http://www.cdep.ro/pls/dic/site.page? id¼339. 2 According to Art. 129 of Law no. 227/2015. Available online at: https://static.anaf.ro/static/10/ Anaf/legislatie/Cod_fiscal_norme_11022020.htm. 3 According to Art. 128 of Law no. 227/2015. 4 According to Art. 130 of Law no. 227/2015. 5 According to Art. 101, Para. (1) of Law no. 227/2015. Alin. (2) of the mentioned article stipulates that “the tax is calculated by applying the tax rate of 10% on the monthly taxable income from pensions,” and according to Art. 100, Para. (1) “the monthly taxable income from pensions is established by deducting from the pension income the monthly nontaxable amount of 2,000 lei.” The date for paying the tax to the state budget is specified by Art. 101, Para. (3), respectively “until the 25th of the month following the month for which the pension is paid.” 6 According to Art. 146, Para. (4) of Law no. 227/2015. 7 Article 147, Para. (15) provides that “if among the employers provided in par. (13) and persons earning income from wages or assimilated to wages were not concluded agreements, the obligation to pay social contributions due by employers, withholding and payment of social contributions due by those individuals, and the submission of the declaration provided in para. (1) belongs to the employers.”

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9 Financial Sustainability of Public Pension System

60% 50% 40% 30% 20% 10%

Czech Republic

Hungary

Employee contribuon

Poland Employer contribuon

2009 2011 2013 2015 2017 2019 2008 2010 2012 2014 2016 2018

2009 2011 2013 2015 2017 2019 2008 2010 2012 2014 2016 2018

2008 2010 2012 2014 2016 2018

0%

Romania

Slovakia

Quota directed to Second Pillar

Fig. 9.1 Evolution of social contribution rates in CEE countries, period 2008–2019. Source: Author’s processing based on data published by the OECD (https://stats.oecd.org) and the tax legislation in force in Romania, 2008–2019

Globalization and free movement of persons presuppose the existence of legislative juxtapositions from the fiscal point of view, but in the context of international fiscal instruments, the fiscal regime of incomes obtained on the territory of a state by nonresidents is established both by internal fiscal provisions and by the provisions of articles of international tax conventions.

9.2

Social Contributions and Tax Compliance

Contemporary pension systems, either public or privately managed, are funded based on the contributions of the participants/insured persons. Social contributions, from a fiscal point of view, are part of the national tax system that ensures the financing of national pension systems and represent a mandatory pecuniary levy established by law or assumed by the insurance contract or the contract of adhesion to a mandatory/voluntary privately managed pension fund that individuals and/or legal entities pay from their income to the state social insurance budget or pension funds. The specific feature of social contributions is the granting of tangible benefits, respectively pensions and other social benefits, as a result of those contributions. Trigg and Lowe (2011) point out that participation in the public pension system is mandatory and benefits are guaranteed by the state. Social contributions to the public pension system in CEE countries are divided between employee and employer (Fig. 9.1). It is noted that there are distinct tax approaches regarding the compulsory social contributions in the five CEE countries included in the research. Thus, Czech Republic, Hungary, and Slovakia based the

9.2 Social Contributions and Tax Compliance

175

financing of social protection systems on contributions paid by employers, while Poland set higher social contribution rates for employees. Between 2009 and 2019, Czech Republic had the highest share of employer contributions (+33.8%) and the lowest share of employee contribution (+11%) among the five CEE countries. Hungary reduced the employer’s share of social contributions by 14.5 percentage points and increased the employee’s contribution share by 1.5 percentage points in the last 12 years. Slovakia increased the employer’s share of contributions by 5 percentage points, while employees remained constant (+13.4%). Romania has adopted a radical change in terms of social contributions, which since 2018 are borne by employees. The share of employees’ contributions to social insurance increased up to 25%, and contributions to social health insurance to 10%.8 The employer has only the obligation to calculate, retain and pay the employees’ contributions and in addition owes the labor insurance contribution, in the amount of 2.25%,9 as well as contributions related to jobs with special and unusual working conditions.10 Increasing the share of social contributions borne by an employee is not a sufficient measure to ensure the income necessary to finance pension expenses (Balteș & Jimon, 2018). The contribution to the contemporary pension funds is established according to the contributory capacity, the social contributions being conditioned by the level of realized incomes. In CEE countries included in the research, the salary incomes increased significantly between 2008 and 2019, the highest increase being registered in Romania. The annual value of the minimum income increased between 2000 and 2350 euros in the Czech Republic, Hungary, and Poland, and about 3000 euros in Slovakia and respectively 3600 euros in Romania. In the period 2008–2019, the average gross income increased on average by 40–50%, a higher percentage being registered in Romania (+121%). However, Romania has the lowest values of the average gross annual salary income, compared to the other four CEE countries (Fig. 9.2). The direct taxation of the incomes realized by individuals is realized through the income tax and the social contributions (Fig. 9.2). The income tax rate expresses the share in the gross income of income tax and social contributions borne by the employee, fewer tax deductions. Between 2008 and 2019, the income tax rate was around 25% in the Czech Republic, Poland, and Slovakia. Hungary and Romania had a tax rate of over 33%, although in Hungary, in the last 12 years, income taxes have decreased by about 5%. In the case of Romania, the income tax rate increased by 9.5 percentage points in the period 2008–2019, being the consequence of the increase in the share of social contributions borne by employees since 2018. However, according to data published by Eurostat regarding the labor force of Romania, compared to the other four CEE countries, had the lowest average hourly labor cost (7 euros/employee).

8

According to Art. 138, Point a) and Art. 156 of Law no. 227/2015. According to Art. 220, Para. (1) of Law no. 227/2015. 10 According to Art. 138, Point b) and c) of Law no. 227/2015. 9

Czech Republic

Hungary

Minimum gross income

Poland

Romania

Average gross income

2019

2016

2013

2010

0.00% 2017

0€ 2014

5.00% 2011

10.00%

2,000 € 2008

4,000 €

2018

15.00%

2015

6,000 €

2012

20.00%

2019

25.00%

8,000 €

2009

10,000 €

2016

30.00%

2013

35.00%

12,000 €

2010

14,000 €

2014

40.00%

2017

45.00%

16,000 €

2011

18,000 €

Tax rate

9 Financial Sustainability of Public Pension System

2008

Income

176

Slovakia Income tax rate

Fig. 9.2 Evolution of annualized wage income and wage income taxation rate in CEE countries between 2008 and 2019. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/database

The structure of tax revenues in EU countries reflects the predominance of labor taxation, social contributions averaging two-thirds of labor taxes (DirectorateGeneral for Taxation and Customs Union, 2019). The share of income taxes in total labor taxation between 2008 and 2018 was over 50% in the Czech Republic and Slovakia, with the employer’s salary contributions representing about 25%. In Poland and Romania, the level of salary taxation in total labor taxation increases increased in 2018 by 4.28 percentage points, respectively by 5.65 percentage points, and the most significant share was held by employee contributions. In Hungary, the share of income taxes in total taxes decreased by 5.16 percentage points, due to the reduction of the level of employers’ contribution faster than the increase of contributions paid by employees (Fig. 9.3). Excessive taxation of labor through social security contributions increases the tax burden, which inhibits productive activities in legal and taxed forms and favors “undeclared work” and the activities of the underground economy (Medina & Schneider, 2018), which will lead to reduced budget revenues from social contributions. On the other hand, lower rates of social contributions favor the business environment but do not guarantee the obtaining of the budgetary revenues necessary for the provision of social benefits, which have increased considerably in recent decades. An essential aspect related to the financing of social protection systems is the tax compliance and the taxpayer’s behavior regarding the fulfillment of tax obligations. Tax compliance considers compliance with legal tax provisions, including reductions and deductions provided by applicable law (Harun et al., 2014). From the perspective of pension systems, this is materialized in the correct definition of the calculation basis of the social contribution and the identification of legal deductions,

9.2 Social Contributions and Tax Compliance

177

60% 50% 40% 30% 20% 10%

Czech Republic

Poland

Romania

Social contribuons - employee

2018

2016

2012

2014

2010

2008

2018

2014

2016

2010

2012

2008

2016

2018

2014

2010

2012

2008

2016

Hungary

Social contribuons - employer

2018

2014

2010

2012

2018

2008

2016

2012

2014

2010

2008

0%

Slovakia Labor taxaon

Fig. 9.3 The share of taxes on salary income in total taxation. Source: Author’s processing based on data published by the European Commission’s Directorate-General for Taxation and Customs Union (https://ec.europa.eu/taxation_customs/business/economic-analysis-taxation/data-taxation_ en)

the application of the contribution rate, and the transfer of the contribution to the pension fund within the term provided by the legislation in force. Fiscal compliance can be assessed by the ratio between declared income and actual income (Fonseca & Myles, 2012). Coetzee (1996) argues that taxpayers’ unwillingness to pay taxes, fees, and social security contributions may be the result of the misunderstanding that the final beneficiaries of the funds formed are themselves. The literature presents fiscal conformity as a complex subject with multiple influences. The main factors identified as having a significant influence on the fiscal behavior of taxpayers are summarized in Table 9.2. Tax compliance is most often studied in terms of the relationship between the state and taxpayers. The motivation of taxpayers to pay their tax obligations is directly correlated with how the attitudes of the authorities and the quality of public services are perceived (Feld and Frey, 2001a). However, tax compliance must be analyzed in accordance with the organization of the tax system and the involvement of regulatory bodies, Gambo et al. (2014) highlighting the fact that a complex tax system is negatively correlated with the tax compliance of taxpayers. Cummings et al. (2009) consider tax compliance a component of human behavior, and Kiow et al. (2017) discuss the existence of “tax morality” as behavior that expresses the fulfillment of tax obligations. The study made by Feld and Frey (2001b) shows that “tax morality” is positively correlated with the freedom and sociopolitical involvement of citizens, and Williams and Krasniqi (2017) noted that “tax morality” is more developed in case of married people, with a higher level of education, employed on the labor market and active from a sociocultural point of view. Kemme et al. (2020) highlight the tendency of the population from the countries with a reduced “tax morality” toward tax evasion and the flow of income

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9 Financial Sustainability of Public Pension System

Table 9.2 Factors influencing tax compliance Author Fischer et al. (1992)

Chau and Leung (2009) Bătrâncea et al. (2012) Thức (2013)

Lawan and Salisu (2017) Lawan (2017)

Factors – Demographic structure – The taxpayer’s perception – Structure of the fiscal system – The existence of opportunities for fiscal noncompliance and sanctions – Structure of the fiscal system – Opportunity for noncompliance – Economic factors: business, industry – Sociological factors: culture, values – Psychological factors – Psycho-social factors: social norms, morality – Administrative factors: organization and management of the fiscal system – Legislative factors: regulations, control, sanctions – Economic factors: economic growth, economic structure, financial performance, inflation – Emotional intelligence – Motivation of (non)compliance – Perception of the efficiency of the use of fiscal resources – Perception of the quality of the tax administration

Source: Author’s processing based on the publications of the mentioned authors

through tax havens. In Romania, “fiscal morality” is positively correlated with the level of GDP/inhabitant, while between tax compliance and financial capacity, confidence in public administration and labor productivity is a negative relationship (Brezeanu et al., 2018). Beale and Wyatt (2017) identify two categories of factors that determine tax compliance, namely: systemic factors such as political stability and socioeconomic characteristics, and taxpayer behavior, suggesting that deficient legislation and corruption have a negative impact on the perception of fiscal equity and equality, and on the taxpayer’s trust in the tax system and the public administration. The World Bank provides a series of indicators regarding the perception of the quality of global political governance, namely: the degree of sociopolitical involvement of citizens, political stability, the effectiveness of governance and quality of public services, the quality of legislation and compliance, confidence in the legislation and corruption (Fig. 9.4). The values of these indicators can vary between –2.5 (lowest level of governance quality) and +2.5 (maximum level of governance quality). In CEE countries, it is a positive level of all six indicators, excepting Romania. However, compared to 1996, in the Czech Republic, the level of sociopolitical involvement of citizens, political stability, and control of corruption have deteriorated, while the quality of public services and regulations, as well as confidence in the legislative system, have strengthened. Similarly, in Poland, the degree of sociopolitical involvement of citizens, political stability, the effectiveness of governance and the quality of public services, confidence in the legislative system, and the

9.2 Social Contributions and Tax Compliance

179

1.50 1.00 0.50 0.00 -0.50

Czech Republic

Hungary

Socio-polical involvement of cizens Quality of public services Confidence in the legislave system

Poland

Romania

2000 2004 2007 2010 2013 2016

1998 2003 2006 2009 2012 2015 2018 1996 2002 2005 2008 2011 2014 2017

2000 2004 2007 2010 2013 2016

1996 2002 2005 2008 2011 2014 2017

-1.00

Slovakia

Polical stability Quality of regulaons Fighng corrupon

Fig. 9.4 Perception of the quality of political governance in CEE countries, period 1996–2018. Source: Author’s processing based on data published by the WB, available at https://info. worldbank.org/governance/wgi/

control of corruption have declined, while the quality of legislation and compliance has improved. In Hungary, all indicators decreased, and in Romania and Slovakia, except for political stability, all indicators increased. Even in these conditions, the values of the indicators regarding the quality of political governance in Romania have the lowest values, compared to the other four CEE countries, and the quality of public services and the fight against corruption remain with negative values. A low level of fiscal compliance in terms of social contributions indicates limited confidence in the quality of public pension schemes and the effectiveness of their management. McGillivray (2000) discusses the causes of the abusive behavior of taxpayers regarding social contributions and highlights the fact that a complex administrative-organizational structure of the social protection system, the taxpayer’s attitude toward risk and severity of sanctions, myopic behavior, moral hazard and lack trust in the social protection system are the main causes that determine the social contributions evasion. Schneider (2012) points out that any activity aimed to avoid the payment of taxes and social security contributions, as well as noncompliance with legal standards and labor market regulations, is a component of the informal or underground economy. The main causes identified by the author that underlie the development of the underground economy are: the increased level of fiscal pressure, low “fiscal morality,” the quality and limited effectiveness of state institutions, and poor labor legislation (Schneider, 2012). From the perspective of the labor market, the underground economy manifests as undeclared work, which in addition to limiting budget revenues, restricts respect for the right to social protection and access to benefits of social protection systems, as well as the provision of adequate benefits. Moreover,

180

9 Financial Sustainability of Public Pension System

by reducing the number of taxpayers and increasing the fiscal pressure, the functioning and sustainability of social protection systems are also threatened. Unregistered work is defined by ILO (2010) as any economic activity carried out that partially complies with or violates legal regulations. The European Commission (2013, pp. 9) specifies that “any act or omission to act in order to obtain or receive social security benefits or to avoid the obligation to pay social security contributions, contrary to the law of a Member State” constitutes fraud which is subject to sanctions established by the legal provisions in force. In addition to the “classic” forms of evasion such as: payment of wages in the form of other nontaxable benefits, non-declaration of the full amount of wages and working time, non-declaration of part-time contracts and fixed-term contracts, claiming unemployment or retirement benefits for disability in the limit of the law, employment of foreign workers or persons in refugee centers without legal forms, Mineva and Stefanov (2018) draw attention to new forms of tax and social contributions evasion through improper use of platforms and collaborative activities in the digital economy, electronic money transfers and the use of cryptocurrencies in transactions. All this suggests the need for additional measures both to protect workers’ rights and to strengthen sustainable socioeconomic development.

9.3

State Social Insurance Budget

The mobilization of the resources necessary for the functioning of public pension systems is achieved mainly by taxing the labor force through social contributions. However, the ability to raise funds is influenced by the tax system, legislation, taxpayers’ attitudes toward taxation, and budgetary administration (Ocheni, 2015). As a result, budgetary efficiency is expressed by the state’s ability to meet the needs of the population using the funds obtained (Al-Ttaffi & Abdul-Jabbar, 2015). The budget is the legal act by which are established and authorized public expenditures and their sources of financing (Bălan, 2007). The state social insurance budget (SSIB) is the document that presents the statement of revenues and expenditures of the public social protection system during a budgetary year. The synthetic situation of SSIB in CEE countries, in the period 2000–2017, according to data published by Eurostat, shows a relatively balanced situation, in some years even being recorded a budget surplus (Fig. 9.5). Both the level of revenue and the level of expenditure reflect an upward trend in all five CEE countries, with a higher rate of revenue growth than the rate of increase of expenditure, which is necessary to respect the principle of budgetary balance. The share of SSIB revenues and expenditures in GDP shows that in the case of the Czech Republic, Poland, and Romania the share of expenditures in GDP increased by between 0.6 and 1.3 percentage points, while in Hungary and Slovakia they decreased by 1.3 and, respectively 0.9 percentage points. The share of revenues in GDP increased in Czech Republic, Poland, Romania, and Slovakia with values

181

100

30%

90 25%

80 70

% GDP

Billions

9.3 State Social Insurance Budget

20%

60 50

15%

40 10%

30 20

5%

10 0

Czech Republic

Hungary

Total expenses

Poland

Total revenues

Romania Total expenses

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

2000 2003 2006 2009 2012 2015

0%

Slovakia Total revenues

Fig. 9.5 Evolution of BASS revenues and expenditures in CEE countries in the period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/ eurostat/data/database 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

Czech Republic Hungary Social contribuons - employer Social contribuons - freelancers Government contribuons

Poland

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

2000 2003 2006 2009 2012 2015

0%

Romania Slovakia Social contribuons - employee Social contribuons - other insured persons Other incomes

Fig. 9.6 SSIB revenue structure in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/database

between 0.3 and 1.8 percentage points, and in Hungary, these decreased by 1.9 percentage points (Fig. 9.5). For a complete picture of how the revenues from taxpayers’ levies cover the expenses with the benefits of the public social protection system, it was considered necessary the structure analysis of the financial sources and the destination of budget allocations. SSIB revenues are obtained from two main sources, namely mandatory social contributions, and government transfers (Fig. 9.6). Between 2000 and 2017,

182

9 Financial Sustainability of Public Pension System

revenues from social contributions paid by employers, employees, self-employed persons, and other insured persons represented over 70% of total SSIB revenues in the Czech Republic and a share between 60 and 70% of total SSIB revenues in Poland and Slovakia, in Hungary their share is between 50 and 60% of total SSIB revenues. In Romania, SSIB revenues from social contributions decreased until 2016 by approximately 20%, increasing to 73.5% in 2017. The highest share of SSIB revenue from social contributions in CEE countries in the period 2000–2017 was held by social contributions paid by employers (up to 50% of SSIB revenue). The budget revenues obtained from the employer’s contributions decreased by 16.7% in Hungary and by 13.8% in Romania, while in Poland their share increased by 5.8%. It is noted that the contributions actually paid by employers are lower by about 3–5% compared to the legal level, except for Romania, a state where the decrease is up to 15.7%, which draws attention to a low degree of tax compliance of employers regarding the payment of social contributions. The revenues collected from the contributions paid by employees, in the last 18 years held a share of 20–30% of the total SSIB revenues, observing their increase in Hungary by 16%, in Slovakia by 3%, and in Romania by 2.5%. Social contributions paid by self-employed and other insured persons in the five CEE countries accounted for between 2 and 5% of total budget revenues. In the Czech Republic and Slovakia, contributions paid by self-employed persons in 2017 registered 4–5% of SSIB revenues, while in Romania, 5.5% of SSIB revenues was made from social contributions paid by other insured persons (Fig. 9.6). Government contributions accounted for an average of 30% of SSIB revenues in the five CEE countries between 2000 and 2017. Their share has decreased in the last 18 years by 5% in Slovakia, by 3.3% in Poland and by 1.15% in the Czech Republic, while in Romania they registered an increase of 10%, and in Hungary of 2%. SSIB revenues from other sources represented on average about 5% of total budget revenues, excepting Poland where over 12% of SSIB revenues came from other sources (Fig. 9.6). SSIB revenues have as sources of origin either the central and local administrative apparatus or the private sector, represented by economic entities, households, and nongovernmental organizations (Fig. 9.7). The largest share of SSIB revenues comes from the private sector. On average, in CEE countries about 30% of SSIB revenues are made up of the contributions of the corporate financial and nonfinancial sector, their share being higher in the Czech Republic (about 50%). The share of SSIB income obtained from the population amounts to 20–30% of total revenues, while NGO contributions constitute less than 1.5% of SSIB revenues. SSIB revenues from the contribution of the national administrative apparatus accounted for 20–58% of total budget revenues. A percentage between 20 and 30% of the SSIB revenues of Romania and Slovakia came from the contribution of the central administrative apparatus, a share that reached 50% in the other three CEE countries, while the amount directed to SSIB by the territorial administrative units did not exceed average 5%. In Romania, a significant percentage of SSIB revenues between 2003 and 2015 were provided by government funds for social security

9.3 State Social Insurance Budget

183

Czech Republic

Hungary

Corporate sector (non-financial and financial) Central administraon Social security fund

Poland

Romania

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

2000 2003 2006 2009 2012 2015

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Slovakia

Households Territorial administrave units NGO

Fig. 9.7 Source of SSIB revenue in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/ database

which formed a percentage between 17 and 27% of total SSIB revenues of Romania, while in other CEE countries the share did not exceed 2% of total revenue. The use of SSIB revenues is made in three main directions, namely social benefits, administrative costs, and other expenditures. The highest share of financial allocations is for the provision of social benefits, which represents over 96% of total SSIB expenditures between 2000 and 2017, the share of administrative costs being 2–3% of the total volume of expenditures, and a share of no more than 1% was represented by other categories of expenditures (Fig. 9.8). SSIB expenditures for the provision of social benefits include all benefits provided by the state through all national social protection programs to ensure the social and financial protection of the population. The structure of SSIB expenditures between 2000 and 2017 reflects that between 60 and 70% of total budget expenditures are made for the provision of health care services and the provision of pensions, and a percentage of approximately 20% of SSIB expenditures are targeted at benefits for people with disabilities and survivors, while family allowances and child allowances accounted for about 10% of total SSIB expenditure. Expenditure with unemployment benefits, social housing, and social exclusion did not exceed 10% of total budget expenditure (Fig. 9.8). Expenditure for providing pensions in CEE countries accounted for 40–50% of total SSIB expenditure. Public pension systems provide four main categories of benefits, namely: old-age pension, early retirement pension, invalidity pension, and survivor’s pension, Romania also offering a partial early retirement pension. Compared to GDP, old-age pensions accounted for between 5 and 7% of GDP, with an upward trend over the last 18 years. The share of disability and survivors’ pensions in GDP did not change significantly, with values of about 1% of GDP, with slightly higher levels in Poland, but not exceeding 2% of GDP. Early retirement saw a

184

9 Financial Sustainability of Public Pension System

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

Czech Republic

Hungary

Health care Pensions Family support and child allowances Social housing Social protecon Other expenditures

Poland

Romania

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

2000 2003 2006 2009 2012 2015

0%

Slovakia

Disabilies Benefits granted to descendants Unemployment Social exclusion Administrave costs

Fig. 9.8 Structure of SSIB expenditures in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/data/ database

decline in the share of GDP, especially in the Czech Republic and Poland, while in Slovakia these increased slightly, but their values in all five CEEs did not exceed 1% of GDP in 2017 (Fig. 9.9). The highest share in total SSIB pension expenditure was held by old-age pensions (70–80%). Between 2000 and 2017, their share in total SSIB pension expenditures increased by 18% in Poland, by 13% in Hungary, and by 9% in the Czech Republic, while in Romania and Slovakia these had an increase of only 3% and, respectively 1%. The share of disability pension expenditures in total SSIB expenditures shows a downward trend in all five CEE countries, registering in 2017 values between 8 and 12% in Poland, Czech Republic, and Slovakia, while in Romania these represent only 3% of SSIB expenditures. Also, the share of survivor’s pension expenditures has decreased in CEE countries in the last 18 years with values between 1 and 3 percentage points, reaching in 2017 weights below 15% of total SSIB pension expenditures. Regarding early retirement expenditure, their share decreased by 2% in the Czech Republic and by 5% in Poland, while in Romania their level remained relatively constant, and in Slovakia and Hungary these increased by 3%, their level being in 2017 at most 7% of the total SSIB expenditures with pensions (Fig. 9.9). The reforms adopted by the CEE countries in recent decades aimed to offer adequate provisions to beneficiaries and the increase in budgetary expenditure reflects this. However, policies must also aim the budgetary consolidation in terms of resources, as social contributions only partially succeed in financing the social protection systems of the five CEE countries, and government transfers involve a

185

60 €

9% 8%

50 €

%GDP

Billions

9.3 State Social Insurance Budget

7% 40 €

6% 5%

30 € 4% 20 €

3% 2%

10 € 1% 0€

Czech Republic

Hungary

Old-age pension Invalidity pension Paral early rerement pension Early rerement pension

Poland Early rerement pension Old-age pension Invalidity pension

Romania

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

2000 2003 2006 2009 2012 2015

0%

Slovakia Paral early rerement pension Early rerement pension Old-age pension

Fig. 9.9 Structure of pension expenditure in CEE countries in the period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/eurostat/ data/database

reduction in resources allocated to other sectors of the economy, and often, funding is based on external resources. The consolidated budget of the CEE states reflects a budgetary deficit, excepting the Czech Republic in 2016 and 2017. Compared to GDP, the budget deficit decreased in all five CEE countries, the maximum value being recorded in Slovakia (–11.6%), followed by Czech Republic (–5.1%), Romania (–2%), Poland (–1.5%), and Hungary (–0.5%). However, between 2000 and 2017 the level of public debt increased considerably. Reported to the level of GDP, the public debt registered increases of over 17% in the Czech Republic and Hungary, while in Poland and Romania it increased by 14% and, respectively 12.6%. In Slovakia, public debt fell below 45% of GDP between 2004 and 2011, then rose to more than 0.8% of the value recorded in 2000. Compared to the budget deficit reference value, mentioned by the EU treaty, it is noted that the CEE countries in 2017 managed to meet the budget deficit limit of 3% of GDP, the Czech Republic even registering a budget surplus of 1.5% of GDP. Regarding the level of public debt, compared to the reference value of 60% of GDP, this limit is respected in the last 18 years, excepting Hungary where the external debt since 2005 exceeds this limit (Fig. 9.10). Even if from the point of view of the beneficiaries of public pension systems, the benefits received represent the main criterion by which their effectiveness can be assessed, from the perspective of financiers, the effectiveness of public pension systems is assessed according to the costs involved in their organization and operation. Thus, PAYG public pension systems present in CEE countries require funding based on contributions from taxpayers, employers, and insured persons, and

9 Financial Sustainability of Public Pension System

300 €

90%

250 €

75%

200 €

60%

150 €

45%

100 €

30%

50 €

15%

0€

0%

Czech Republic

Hungary

Government budget deficit/surplus Government budget deficit/surplus Budget deficit reference value

Poland

Romania

2002 2005 2008 2011 2014 2017

2002 2005 2008 2011 2014 2017 2001 2004 2007 2010 2013 2016 2000 2003 2006 2009 2012 2015

-15% 2000 2003 2006 2009 2012 2015

-50 €

% GDP

Billions

186

Slovakia

Public debt Public debt Public debt reference value

Fig. 9.10 Level of budget deficit/surplus and public debt in CEE countries, period 2000–2017. Source: Author’s processing based on data published by Eurostat, available at https://ec.europa.eu/ eurostat/data/database

from their perspective, the effectiveness of pension systems is related to the fiscal pressure of social contributions. On the other hand, at a macroeconomic level, the success of public pension systems is reflected in the budgetary balance, namely the financing of expenditure with social benefits from current income from social contributions, which is partly achieved in the five CEE countries (Balteș & Jimon, 2019). Given that the current SSIB revenues from social contributions manage to finance only part of the expenditure on social benefits, given the current and projected demographic situation, it appears questions regarding the long-term solvency of public pension systems in CEE countries. Plamondon et al. (2002) argue that the increase in SSIB spending on pensions does not indicate a problem of the unsustainability of the system but is a common issue in the case of immature pension schemes. Even so, in case of problems regarding their solvency and budgetary sustainability, in the context of the aging trend of the population, the solution is a national economy that grows and develops permanently and sustainably (Iparraguirre, 2020). Furthermore, Stanovnik (2004) also proposes to establish a closer link between the level of social contributions paid by taxpayers and the level of subsequent benefits, as well as the elimination of the possibility of arbitration between employers and employees by negotiating employment contracts with partially declared and taxed salaries.

References

9.4

187

Conclusions and Personal Contributions

Public pension schemes in CEE countries are financed based on the contributions of insured persons, being directly dependent on the number of taxpayers, the tax base, and the share of social contributions. As a result, the reduction in the birth rate and the increase in life expectancy raise the issue of the unsustainability of PAYG public pension systems. The main conclusion of this chapter highlights, on the one hand, the importance of the quality of the human factor and the development of the labor market and business environment, to ensure sustainable national economic growth, and on the other hand, the divergent relationship between the adequacy of the benefits provided by public pension systems and keeping the level of expenditure within the limits of the resources held.

9.5

Summary

This chapter presents the budgetary process of public pension systems in CEE countries, considering national fiscal policy, the Community fiscal framework, aspects of international tax law, and tax compliance of taxpayers. Also, there are exposed specific aspects regarding the structure of budgetary expenditures with social benefits and the situation of budgetary balance. The public pension systems implemented by the CEE countries operate based on the principle of contribution and solidarity because their financing is based on the compulsory social contributions paid by employees and employers. The sustainability of the budgets of the public pension systems in the CEE countries is conditioned by the balance between the revenues obtained from social contributions and the expenditures with the benefits granted to the beneficiaries.

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Fischer, C. M., Wartick, M., & Mark, M. (1992). Detection probability and taxpayer compliance: A review of the literature. Journal of Accounting Literature, 11, 1–46. Fonseca, M., & Myles, G. D. (2012). A survey of experiments on tax compliance. HMRC Research Report 198. Available online at: https://assets.publishing.service.gov.uk/government/uploads/ system/uploads/attachment_data/file/355001/Experimental_evidence_on_taxpayer_compli ance.pdf. Gambo, E. M. J., Mas’ud, A., Nasidi, M., & Oyewole, O. S. (2014). Tax complexity and tax compliance in African self-assessment environment. International Journal of Management Research & Review, 4(5), 575–582. Harun, R. J., Yusof, K. N. C. K., Bakar, M. J. A., & Tahir, I. M. (2014). A study on tax non-compliance among government servants. Australian Journal of Basic and Applied Sciences, 8(5), 84–90. Holzmann, R. (2016). Bilateral social security agreements and pensions portability: A study of four migrant corridors between EU and non-EU countries. International Social Security Review, 69 (3–4), 109–130. Holzmann, R., & Koettl, J. (2015). Stability of pension, health, and other social benefits: Facts, concepts, and issues. CESifo Economic Studies, 61(2), 377–415. ILO. (1952). Convention no. 102 on social security (minimum standards). ILO. Available online at: http://www.ilo.org/ilolex/english/convdisp1.htm. ILO. (2010). Labour inspection in Europe: Fighting undeclared work and trafficking. ILO. Available online at: https://www.ilo.org/wcmsp5/groups/public/%2D%2D-ed_dialogue/%2D %2D-lab_admin/documents/publication/wcms_120319.pdf. Iparraguirre, J. L. (2020). Economics and ageing—Volume III: Long-term care and finance. Palgrave Macmillan. Kemme, D. M., Parikh, B., & Steignerc, T. (2020). Tax morale and international tax evasion. Journal of World Business, 55, 1–12. Kiow, T. S., Salleh, M. F. M., & Kassim, A. A. B. M. (2017). The determinants of individual taxpayers, tax compliance behaviour in Peninsular Malaysia. International Business and Accounting Research Journal, 1(1), 26–43. Kirsch, M. S. (2009). The limits of administrative guidance in the interpretation of tax treaties. Texas Law Review, 87(6), 1063–1135. Lawan, J. U. (2017). A new look for the Fischer Tax compliance model: A positive plan for Nigeria. International Journal of Advanced Academic Research, Social & Management Sciences, 3(9), 3–51. Lawan, J. U., & Salisu, U. (2017). A review of Fischer tax compliance model: A proposal for Nigeria. International Journal of Advanced Academic Research, Social & Management Sciences, 3(7), 54–69. Lefter, C., & Chirică, S. (2010). Evitarea dublei impuneri internaţionale (Reglementări legale interne şi convenţii fiscale încheiate de România). Economie teoretică şi aplicată, XVII, 9 (550), 38–51. McGillivray, W. R. (2000). Contribution evasion: Implications for social security pension schemes. International Social Security Review, 54(4), 3–22. Medina, L., & Schneider, F. (2018). IMF working paper: Shadow economies around the world: What did we learn over the last 20 years?. International Monetary Fund. Mineva, D., & Stefanov, R. (2018). Evasion of taxes and social security contributions. European Platform Undeclared Work, European Commission. Ocheni, S. (2015). A causality analysis between tax compliance behaviour and Nigerian economic growth. Mediterranean Journal of Social Sciences, 6(1), 577–582. Plamondon, P., Drouin, A., Binet, G., Cichon, M., McGillivray, W. R., Bédard, M., & PerezMontas, H. (2002). Actuarial practice in social security. Quantitative methods in social protection. International Labour Organization/International Social Security Association. Schneider, F. (2012). The shadow economy and work in the shadow: What do we (not) know? (IZA Discussion Paper No. 6423).

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Stanovnik, T. (2004). Contribution compliance in central and eastern European countries: Some relevant issues. International Social Security Association, 57(4), 51–65. Taylor, C. J. (2010). Twilight of the neanderthals, or are bilateral double taxation treaty networks sustainable? Melbourne University Law Review, 34, 268–311. Thức, N. T. (2013). A review of factors impacting tax compliance. Australian Journal of Basic and Applied Sciences, 7(7), 476–479. Trigg, A. B., & Lowe, J. T. (2011). Comparing pension systems in the circular flow of income. American Journal of Economics and Sociology, 70(5), 1248–1281. van Panhuys, C., Kazi-Aoul, S., & Binette, G. (2017). Migrant access to social protection under Bilateral Labour Agreements: A review of 120 countries and nine bilateral arrangements (ESS—Working Paper No. 57). International Labour Office- Social Protection Department, Labour Migration Branch, Conditions of Work and Equality Department. Williams, C. C., & Krasniqi, B. A. (2017). Evaluating the individual- and country-level variations in tax morale: Evidence from 35 Eurasian countries. Journal of Economic Studies, 4(5), 816–832.

Chapter 10

Econometric Study on the Financial Sustainability of Public Pension Systems

This chapter aims the econometric study regarding the financial sustainability of public pension systems in CEE countries, by establishing correlations between the level of state social insurance budget revenues and expenditures, and the socioeconomic indicators specific to pension systems.

10.1

General Aspects Regarding the Sustainability of Public Pension Systems

The PAYG public pension systems implemented by CEE countries have as an operating principle the contributive and solidarity between generations, their success is conditioned by the equality between the revenues obtained from the social contributions collected from the insured persons and the expenditures with benefits offered to the beneficiaries. Currently, SSIB revenues from social contributions finance only a part of budget expenditures, which has drawn the attention of governments, international and national bodies, as well as of academic environment, about the long-term solvency and sustainability of public pension systems in CEE countries, mainly due to the aging trend of the population and the reduction of the birth rate. The sustainability of public PAYG pension systems is directly dependent on the level of social contribution collected and the number of beneficiaries, as well as the level of benefits provided. In this regard, Kolmar (2007) points out that the sustainability of public pension systems can be maintained both in case of systems based on Beveridge’s principles and in case of Bismarckian systems, the balance being dependent on economic growth rates and demographic, political, and technological parameters. The study of Godınez-Olivares et al. (2016) regarding the sustainability of European pension systems reflects that their sustainability is not guaranteed even © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_10

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if the dependency ratio of the elderly population decreases and the tax base of social contributions increases. Simões de Matos dos Santos and Domínguez Fabián (2009) also point out that in countries such as Germany, Austria, Belgium, Spain, Italy, Portugal, and Sweden, the sustainability of pension systems is independent of the wage withdrawals. Cristescu (2019) considers that the sustainability of public pension systems can be maintained by raising the retirement age, which will lead to an increase in the contribution period and an increase in salary income. However, indicators regarding the health of the population and their improvement must be taken into account, which may lead to increased budget expenditures due to health education programs and occupational and chronic disease prevention programs. Németh et al. (2019) study the sustainability of the Hungarian public pension system and point out that it depends on the number of social contributions and benefits granted, and with the increase in household income, budget revenues can increase, but on the other hand, the reduction of contribution rates favors the employment rate and increases the number of taxpayers and the tax base. Moreover, the results of the study made by Rotschedl (2015) on the sustainability of the Czech pension system, given life expectancy, social policies, and the income structure of the population, indicate that the factor with the greatest influence on the sustainability of pension systems is the level of education. De las Heras Camino et al. (2014) discuss the sustainability factor, a tool for quantifying the solvency of the Spanish social protection system based on retirement life expectancy rates, and point out that, although this instrument has a solid theoretical basis, is not enough to guarantee the sustainability of the system. However, a more recent study made by Alda et al. (2018) highlights the long-term effectiveness of the application of this instrument and the reduction of public pension system expenditures as life expectancy continues to rise. Liebman et al. (2009) look at workers’ attitudes toward the level of income taxation and point out that the population over the age of 52, who are approaching retirement, with a 10% increase in net income will postpone early retirement by at least 2 years. Simonovits (2015) also studies the situation of low-income workers with a short-sighted view regarding the contributions to pension schemes and retirement savings, suggesting that setting a minimum non-taxable threshold will encourage both the contribution of this category of population to public pension schemes and personal savings. Laub and Hagist (2017) examine the impact of the reforms of the social protection system in Germany, Norway, and Poland on future generations and emphasizes that through them, redistributions between generations have become more balanced and intergenerational pressure has been reduced. On the other hand, Verbič et al. (2006) point out that the reform of the public pension system in the case of Slovenia does not guarantee its success in the face of unfavorable demographic developments. Halaskova (2018) studied the sustainability of public pension systems from the perspective of the structure and volume of budget expenditures with social benefits using the hierarchical cluster method, the results obtained establishing the existence of specific elements for each state, even if the organization and functioning of public pension systems are based on the same typology of the social protection system.

10.2

Research Methodology and Data Used

193

Alonso-Ortiz (2014) argues that variations between countries in the budgeting of public pension systems are the result of the generosity of social protection systems and national fiscal policy. Ștefan (2015) studied the administrative costs of pension schemes and identifies a positive relationship between them and the number of taxpayers, the number of unemployed people, and the real GDP growth rate, and Balazs (2013) analyzes the impact of transfers of social security contributions to the second pillar in Poland, noting that its elimination has a positive effect on the sustainability of the public pension system and reduces the level of public debt, even if nationalization of the second pillar reduces beneficiaries’ income replacement rates. On the other hand, Peng and Wang (2017) point out that a large part of the tax burden produced by the provision of pensions through public pension systems is the result of the postponement of social contributions payments. Beetsma and Oksanen (2008) study the effects of an aging population on public pension systems, given the provisions of the Stability and Growth Pact, which limit public debt and the level of the budget deficit, and point out that both reducing the income replacement rate and raising the standard retirement age, as well as the full privatization of pension funds will not reduce the budget deficit, but on the contrary, it will increase. Mladen (2012) analyzes the efficiency of public pension systems in CEE countries compared to other EU countries and finds that the Hungarian pension system is among the most effective in reducing poverty, having a modern structure, but presents an increased risk in terms of financial sustainability. Chybalski and Marcinkiewicz (2016) consider that the efficiency of a pension system cannot be defined only by the income replacement rate, but by an integrated approach that includes the median income level, the poverty rate, and income inequality. Applying this concept, Roman et al. (2018) use cluster analysis for a sample of 26 EU countries and show that the social protection systems in Hungary, Luxembourg, and Romania are the most effective, while the lowest efficiency is found in Greece, Portugal, and Italy. Pascuzzo (2015) studies the financial sustainability and adequacy of benefits of public pension systems, the results emphasizing the idea that usually states that provide adequate benefits face problems with the solvency and financial sustainability of pension systems, but DC pension schemes usually succeed to have good results both in terms of adequacy of benefits and in terms of maintaining sustainability.

10.2

Research Methodology and Data Used

To carry out the empirical study on the financial sustainability of pension systems implemented by CEE countries, a database was created containing budgetary indicators, indicators characteristic of public pension systems and indicators specific to income taxation of the population, as well as indicators of the medical status of the population. To compile the database the statistical data was used published by

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Eurostat for the period 2008–2017, for which all the variables considered relevant for the econometric study had values for the five CEE countries. The macroeconomic variables included in the study are the following: (I) Budgetary indicators: SSIB revenues (pSIBR), SSIB expenditures (pSIBexp), budget deficit (pNLNB), public debt (pGGD) (II) Indicators characteristic of public pension systems: number of beneficiaries (Ben) (III) Indicators of taxation of household income: minimum annual gross income (minaW), average annual gross income (avaGW), average annual level of social contributions (SS) (IV) Indicators of the medical status of the population: life expectancy at 65 years, according to gender (LEXf/LEXm), healthy life expectancy at birth, according to gender (HLYfB/HLYmB) pSIBR and pSIBexp express the total level of revenues and expenditures of SSIB incurred for the provision of the four categories of pensions, as a percentage of GDP. Ben expresses the number of people who on 31 December are beneficiaries of a regular benefit provided by a pension scheme. minaW defines the minimum wage established by national law for most sectors of the economy to be granted to each employee. avaGW expresses the average annual level of remuneration and other payments received by an unmarried person without children, before withholding taxes, fees, and social contributions, and the SS shows the number of social contributions paid by a person earning the average annual income. All indicators used are expressed in euros. HLYf and HLYm show the number of years that a female or male is expected to live without major or severe health problems, while the total number of years a person is alive after reaching the age of 65 years is represented as LEXf in case of females, respectively LEXm in case of males. The econometric study of the financial sustainability of pension systems was conducted using the software package EViews 10 University Edition, applying data analysis models by regression equations, taking into account, on the one hand, the revenues and on the other hand the SSIB expenditures. As a result, econometric testing of SSIB revenues was performed using the Generalized Method of Moments (GMM) method, and econometric testing of SSIB pension expenditures was performed using the Vector Autoregression (VAR) method. The two methods that allow econometric analysis in dynamics are often used in studies that analyze data with interconnected time series. The GMM method assumes the presence of endogenous variables and, similar to the 2SLS method, uses instrumental variables to eliminate their endogeneity, but using a weighting matrix and an estimation algorithm. The weighting matrix is in fact an estimator determined based on the initially calculated β coefficients, and in E-views it can be calculated by four methods, respectively: by the 2SLS method which determines the estimator based on the residual variance, by the White method which uses as estimator consistent heteroskedasticity a long-term covariance matrix, the HAC-Newey–West method that calculates the estimator of heteroskedasticity and

10.2

Research Methodology and Data Used

195

consistent autocorrelation using a long-term covariance matrix, and the method specified by the researcher, which allows the introduction of an own method for determining the estimator. As for the estimation algorithm, it involves determining the updated matrix by three methods, namely: the N-step Iterative method that allows specifying the number of repetitions of the calculations until the optimal matrix is established, the Iterate to Convergence method that involves repeating the calculations until parameter convergence and the Continuously Updating method that determines the estimator through a continuous adjustment.1 The econometric study of the sustainability of public pension systems in CEE countries based on SSIB revenues is based on the following regression equations: pSIBRit ¼ α þ β1  HLYfBit þ β2  HLYmBit þ β3  minaWit þ β4  avaGWit þ β5  SSit þ εit

ð10:1Þ

pSIBRit ¼ α þ 0:76  HLYfBit  1:09  HLYmBit  0:01  minaWit þ 0:01  avaGWit þ 0:01  SSit þ εit

ð10:1aÞ

pSIBRit ¼ α þ 0:36  HLYfBit  0:22  HLYmBit  0:01  minaWit  0:01  avaGWit þ 0:02  SSit þ εit ð10:1bÞ pSIBRit ¼ α þ 0:36  HLYfBit  0:55  HLYmBit  0:01  minaWit þ 0:01  avaGWit þ 0:03  SSit þ εit

ð10:1cÞ

pSIBRit ¼ α þ 0:77  HLYfBit  2:24  HLYmBit  0:01  minaWit þ 0:01  avaGWit  0:01  SSit þ εit ð10:1dÞ pSIBRit ¼ α  0:53  HLYfBit þ 0:33  HLYmBit  0:01  minaWit þ 11:60  avaGWit  86:56  SSit þ εit

ð10:1eÞ

where: • • • • • • •

α—free coefficient. pSIBR—BASS revenues expressed as a percentage of GDP. HLYfB—healthy life expectancy at birth for females. HLYmB—healthy life expectancy at birth for males. minaW—minimum annual income expressed in euro. avaGW—average annual income expressed in euros. εit—regression error.

The VAR method, on the other hand, supposes the elimination of the endogeneity of variables by structural modeling, which involves treating each endogenous variable as a system of functions of all endogenous variables, establishing a range

1 http://www.eviews.com/help/helpintro.html#page/content/gmmiv-Generalized_Method_of_ Moments.html.

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of variable lags.2 Thus, the VAR method uses regression equations based on both the current values of the variables and the values from previous periods, the estimation method being OLS. The regression equations used to model the sustainability of public pension systems in CEE countries based on pension expenditure are: pSIBexpit ¼ α1 þ β1  pSIBexpit ð1Þ þ β2  pNLNBit ð1Þ þ β3  pGGDit þ β4  LEXf it ð1Þ þ β5  LEXmit ð1Þ þ β6  Benit ð1Þ þ εit

ð10:2Þ

pSIBexpit ¼ α1 þ 0:96  pSIBexpit ð1Þ þ 0:16  pNLNBit ð1Þ  0:05  pGGDit þ 1:21  LEXf it ð1Þ  1:79  LEXmit ð1Þ  1:23Benit ð1Þ þ εit ð10:2aÞ pNLNBit ¼ α2 þ β7  pSIBexpit ð1Þ þ β8  pNLNBit ð1Þ þ β9  pGGDit þ β10  LEXf it ð1Þ þ β11  LEXmit ð1Þ þ β12  Benit ð1Þ þ εit ð10:3Þ pNLNBit ¼ α2  0:58  pSIBexpit ð1Þ  0:06  pNLNBit ð1Þ þ 0:13  pGGDit  2:51  LEXf it ð1Þ þ 5:56  LEXmit ð1Þ  1:41  Benit ð1Þ þ εit ð10:3aÞ

pGGDit ¼ α3 þ β13  pSIBexpit ð1Þ þ β14  pNLNBit ð1Þ þ β15  pGGDit þ β16  LEXf it ð1Þ þ β17  LEXmit ð1Þ þ β18  Benit ð1Þ þ εit

ð10:4Þ

pGGDit ¼ α3 þ 1:64  pSIBexpit ð1Þ þ 0:52  pNLNBit ð1Þ þ 0:62  pGGDit þ 1:69  LEXf it ð1Þ  5:88  LEXmit ð1Þ  5:08  Benit ð1Þ þ εit ð10:4aÞ

LEXf it ¼ α4 þ β19  pSIBexpit ð1Þ þ β20  pNLNBit ð1Þ þ β21  pGGDit þ β22  LEXf it ð1Þ þ β23  LEXmit ð1Þ þ β24  Benit ð1Þ þ εit

ð10:5Þ

LEXf it ¼ α4  0:04  pSIBexpit ð1Þ  0:09  pNLNBit ð1Þ þ 0:01  pGGDit þ 0:80  LEXf it ð1Þ þ 0:21  LEXmit ð1Þ  2:22  Benit ð1Þ þ εit

ð10:5aÞ

2 http://www.eviews.com/help/helpintro.html#page/content/VAR-Vector_Autoregressions_ (VARs).html.

10.3

Empirical Results

LEXmit ¼ α5 þ β25  pSIBexpit ð1Þ þ β26  pNLNBit ð1Þ þ β27  pGGDit þ β28  LEXf it ð1Þ þ β29  LEXmit ð1Þ þ β30  Benit ð1Þ þ εit

197

ð10:6Þ

LEXmit ¼ α5  0:02  pSIBexpit ð1Þ  0:09  pNLNBit ð1Þ þ 0:01  pGGDit þ 0:05  LEXf it ð1Þ þ 0:90  LEXmit ð1Þ  2:38  Benit ð1Þ þ εit ð10:6aÞ

Benit ¼ α6 þ β31  pSIBexpit ð1Þ þ β32  pNLNBit ð1Þ þ β33  pGGDit þ β34  LEXf it ð1Þ þ β35  LEXmit ð1Þ þ β36  Benit ð1Þ þ εit

ð10:7Þ

Benit ¼ α6  176, 655:5  pSIBexpit ð1Þ  127, 701:6  pNLNBit ð1Þ þ 34, 336:37  pGGDit  82, 295:65  LEXf it ð1Þ þ 452, 234:7  LEXmit ð1Þ þ 0:89  Benit ð1Þ þ εit ð10:7aÞ where: • • • • • • • •

α1, 2, 3, 4, 5, 6—free coefficient. pSIBexp—SSIB expenditure on pensions, expressed as a percentage of GDP. pNLNB—budget deficit, expressed as a percentage of GDP. pGGD—public debt, expressed as a percentage of GDP. LEXf—life expectancy of females at 65 years. LEXm—life expectancy of males at 65 years. Ben—the number of beneficiaries of the public pension system. εit—regression error.

10.3

Empirical Results

10.3.1 Model I: Sustainability of Pension Systems in CEE Countries Through SSIB Revenues Empirical Results from the Application of Model I to the Five CEE Countries The descriptive analysis of the variables used in the model for all five CEE countries reflects the abnormal distribution of the variables, according to the JB test for a significance threshold of 5%, except for budget revenues that show a normal distribution (Table 10.1). Also, SSIB revenues, minimum annual income, and social contributions show a positive asymmetry (Skewness > 0), while the other variables show a negative asymmetry (Skewness < 0). The vaulting coefficient shows the leptokurtic vaulting of the budget revenues and the minimum income (Kurtosis > 3), and the platykurtic vaulting of the other variables (Kurtosis < 3).

PSIBR 19.55000 19.35000 27.00000 15.20000 2.144309 1.359123 7.201390 52.16780 0.000000 977.5000 225.3050

HLYFB 59.88600 60.35000 65.00000 52.00000 3.758202 0.620406 2.304625 4.214916 0.121547 2994.300 692.0802

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

HLYMB 58.42600 59.05000 63.40000 52.10000 2.943468 0.570506 2.675468 2.931724 0.230879 2921.300 424.5362

MINAW 2007.920 1943.610 3895.980 849.7800 651.5939 0.721724 4.271275 7.707667 0.021198 100,396.0 20,804,158

AVAGW 9577.846 9852.250 13575.21 4998.230 2069.634 0.667572 2.771861 3.822201 0.147918 478,892.3 2.10E+08

SS 1414.945 1381.405 2232.160 730.4800 381.9824 0.014692 2.270172 1.111483 0.573647 70,747.23 7149618.

10

Table 10.1 Descriptive analysis of model I variables

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10.3

Empirical Results

199

Table 10.2 Econometric test results—sustainability of public pension systems in terms of SSIB revenues—GMM method Dependent variable: PSIBR Method: Generalized method of moments Date: 05/18/20; Time: 13:52 Sample (adjusted): 1 50 Included observations: 50 after adjustments Linear estimation with 1 weight update Estimation weighting matrix: HAC (Bartlett kernel, Newey–West fixed bandwidth ¼ 4.0000) Standard errors & covariance computed using estimation weighting matrix Instrument specification: HLYFB HLYMB MINAW AVAGW SS Constantly added to the instrument list Variable Coefficient Std. error t-Statistic Prob. C 35.22692 11.98535 2.939164 0.0052 HLYFB 0.761409 0.501403 1.518556 0.1360 HLYMB 1.091953 0.678604 1.609115 0.1147 MINAW 0.001575 0.000794 1.984012 0.0535 AVAGW 0.000542 0.000174 3.120788 0.0032 SS 0.000352 0.001024 0.344322 0.7322 R-squared 0.308827 Mean dependent var 19.55000 Adjusted R-squared 0.230285 S.D. dependent var 2.144309 S.E. of regression 1.881275 Sum squared resid 155.7247 Durbin–Watson stat 0.693188 J-statistic 1.72E-41 Instrument rank 6 Source: Author’s processing using EViews 10 Academic Edition software

The first regression equation was applied globally, for all five CEE countries, using for the estimation of the estimator the HAC—Newey–West method, and for the estimation algorithm the N-step Iterative method, with N ¼ 1, so that the results obtained presents statistical relevance (Table 10.2). The test results reveal that the model is not significant, the value of the determination coefficient R2 being 0.31, and its adjusted value is 0.23. However, SSIB revenues in CEE countries are negatively correlated with the healthy life expectancy of the male population and the minimum annual income level, but positive correlations are established between SSIB revenues and the life expectancy of the female population, the average annual income, and social contributions. Thus, budget revenues increase with the increase of healthy life expectancy of women, the increase of the average annual income and social contributions, as well as the reduction of the life expectancy of the male population and the minimum annual income. Regarding the residuals of the model (Fig. 10.1), it is noted the normal distribution for the JB test with a significance threshold of 5%, positive asymmetry (Skewness > 0), and a leptokurtic vault (Kurtosis > 3). The model can be extended by applying the regression equation (10.1) for each CEE country. As a result, we proceeded to perform the tests for each CEE country

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12

Series: Residuals Sample 1 50 Observations 50

10 8 6 4 2 0

-3

-2

-1

0

1

2

3

4

5

6

Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

-6.47e-15 0.039880 5.804671 -2.836650 1.782710 1.287376 5.511246

Jarque-Bera Probability

26.94938 0.000001

Fig. 10.1 Residuals analysis of model I. Source: Author’s processing using EViews 10 Academic Edition software

included in the research, determining the estimator by the HAC—Newey–West method, for the estimation algorithm applying the N-step Iterative method, with N ¼ 1. However, in the case of Poland, the modeling results could not be determined, the E-views software establishing the existence of a single determination matrix. Also, in the case of Slovakia, the results of econometric estimates proved to be more statistically relevant by applying the 2SLS method for determining the GMM estimator.

Empirical Results from the Application of Model I in the Case of the Czech Republic The descriptive analysis of the variables for the Czech Republic reveals a normal distribution of the minimum annual income, according to the JB test with a probability of 5%, the other variables having an abnormal distribution (Table 10.3). The asymmetry coefficient shows the negative asymmetry of budget revenues and healthy life expectancy (Skewness < 0), and a negative asymmetry of the other variables. The vaulting coefficient shows the leptokurtic Kurtosis of SSIB revenues, minimum annual income, average annual income, and social contributions (Kurtosis > 3), the other variables showing a platykurtic vaulting (Kurtosis < 3). The results of the application of the regression equation (10.1b) reflect the fact that the model is statistically marginal significant (R-squared ¼ 0.82 and Adjusted Rsquared ¼ 0.60) in the case of the Czech Republic (Table 10.4). As a result, SSIB revenues in the case of the Czech Republic are positively correlated with the healthy life expectancy of females and social contributions, and negatively correlated with the life expectancy of males, the minimum annual income and the average annual income. In other words, budget revenues can be increased by the upward movement of healthy life expectancy of women and increasing social contributions, as well as

PSIBR 19.92000 20.05000 20.90000 18.40000 0.700476 0.819556 3.345872 1.169298 0.557301 199.2000 4.416000

HLYFB 63.76000 63.85000 65.00000 62.40000 0.787683 0.313293 2.379394 0.324067 0.850413 637.6000 5.584000

HLYMB 62.07000 62.25000 63.40000 60.60000 0.832733 0.367322 2.372849 0.388758 0.823346 620.7000 6.241000

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

Table 10.3 Descriptive analysis of model I variables in case of Czech Republic MINAW 2158.632 1911.900 3811.620 1786.020 614.7017 2.197846 6.510989 13.18715 0.001369 21,586.32 3400724.

AVAGW 11,760.24 11,686.38 13,575.21 10,663.40 824.1439 0.875470 3.481596 1.374053 0.503070 117,602.4 6112919.

SS 1310.021 1306.875 1493.270 1172.970 87.04875 0.588707 3.299722 0.615057 0.735262 13,100.21 68,197.36

10.3 Empirical Results 201

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Table 10.4 Results of econometric tests—sustainability of public pension systems in terms of SSIB revenues in the Czech Republic—GMM method Dependent variable: PSIBR Method: Generalized method of moments Date: 05/18/20; Time: 14:11 Sample (adjusted): 1 10 Included observations: 10 after adjustments Linear estimation with 1 weight update Estimation weighting matrix: HAC (Bartlett kernel, Newey–West fixed bandwidth ¼ 3.0000) Standard errors & covariance computed using estimation weighting matrix Instrument specification: HLYFB HLYMB MINAW AVAGW SS Constantly added to the instrument list Variable Coefficient Std. error t-Statistic Prob. C 10.60319 10.23942 1.035526 0.3589 HLYFB 0.361085 0.591335 0.610627 0.5744 HLYMB 0.215747 0.557810 0.386776 0.7186 MINAW 0.002456 0.001070 2.295741 0.0833 AVAGW 0.001715 0.001253 1.368598 0.2430 SS 0.019204 0.013661 1.405676 0.2325 R-squared 0.824379 Mean dependent var 19.92000 Adjusted R-squared 0.604852 S.D. dependent var 0.700476 S.E. of regression 0.440325 Sum squared resid 0.775544 Durbin–Watson stat 1.863699 J-statistic 8.06E-31 Instrument rank 6 Source: Author’s processing using EViews 10 Academic Edition software

by reducing the life expectancy of men and the minimum and average annual income. Regarding the residuals of model I in the case of the Czech Republic (Fig. 10.2), it is noted the abnormal distribution for the JB test with a significance threshold of 5%, positive asymmetry (Skewness > 0), and a leptokurtic vault (Kurtosis > 3).

Empirical Results from the Application of Model I in the Case of Hungary The descriptive analysis of the variables in the case of Hungary reflects an abnormal distribution of them, according to the JB test for a significance threshold of 5%. The asymmetry coefficient reflects the positive asymmetry of SSIB revenue, minimum and average annual income, and social contributions (Skewness > 0), while healthy life expectancy for both genders shows a negative asymmetry. The coefficient of vaulting shows the platykurtic vaulting of SSIB revenues, healthy life expectancy of both genders, and social contributions (Kurtosis < 3), as well as the leptokurtic vaulting of minimum and average annual income (Table 10.5). Following the application of the regression equation (10.1c), the empirical results reflect that model I on the sustainability of public pension systems, from the

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6

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5 4 3 2 1 0

-0.5

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Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

7.05e-16 -0.013107 0.670318 -0.335351 0.293550 1.075118 3.784934

Jarque-Bera Probability

2.183183 0.335682

Fig. 10.2 Residuals analysis of model I in the case of the Czech Republic. Source: Author’s processing using EViews 10 Academic Edition software

perspective of SSIB revenues, in the case of Hungary is marginally significant (Rsquared ¼ 0.89 and Adjusted R-squared ¼ 0.76). There is a positive correlation between SSIB revenues and the healthy life expectancy of females and the average annual income, as well as the negative correlation with the healthy life expectancy of males, the minimum annual income, and social contributions. Thus, increasing SSIB revenues in Hungary is possible by increasing the life expectancy of females and average annual incomes, as well as by decreasing the life expectancy of the male population and by reducing the minimum annual income and social contributions (Table 10.6). Analysis of model I residuals in Hungary reflects an abnormal distribution, according to the JB test with a probability of 5% (Fig. 10.3), the negative asymmetry (Skewness < 0), and leptokurtic distribution (Kurtosis < 3).

Empirical Results Following the Application of Model I in the Case of Romania The descriptive analysis of the model I variables in the case of Romania reflects their abnormal distribution for a significance threshold of the JB test of 5% (Table 10.7) and a platykurtic vaulting of all variables (Kurtosis < 3). The asymmetry coefficient highlights the negative asymmetry of SSIB revenues, healthy life expectancy of males, and social contributions (Skewness < 0), while the healthy life expectancy of females, minimum and average annual income shows a positive asymmetry (Skewness > 0). The empirical results obtained following the application of Eq. (10.1d) highlight the fact that the model I applied in the case of Romania is statistically significant

PSIBR 21.79000 21.05000 27.00000 18.00000 3.200851 0.613688 2.014530 1.032334 0.596804 217.9000 92.20900

HLYFB 59.66000 60.10000 60.80000 58.20000 1.037304 0.389021 1.544473 1.134962 0.566952 596.6000 9.684000

HLYMB 57.91000 58.55000 59.60000 54.80000 1.697351 0.688130 2.036120 1.176315 0.555350 579.1000 25.92900

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

MINAW 2072.226 2004.090 3390.120 1608.540 532.8473 1.610220 4.833864 5.722621 0.057194 20,722.26 2555336.

AVAGW 9919.892 9852.250 12065.75 8691.210 950.5944 1.055414 3.711127 2.067208 0.355723 99,198.92 8132667.

1785.062 1822.665 2232.160 1477.510 227.4060 0.458887 2.575645 0.425994 0.808159 17,850.62 465,421.3

SS

10

Table 10.5 Descriptive analysis of model I variables in case of Hungary

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Table 10.6 Results of econometric tests—sustainability of public pension systems in terms of SSIB revenues in Hungary—GMM method Dependent variable: PSIBR Method: Generalized method of moments Date: 05/18/20; Time: 14:18 Sample (adjusted): 1 10 Included observations: 10 after adjustments Linear estimation with 1 weight update Estimation weighting matrix: HAC (Bartlett kernel, Newey–West fixed bandwidth ¼ 3.0000) Standard errors & covariance computed using estimation weighting matrix Instrument specification: HLYFB HLYMB MINAW AVAGW SS Constantly added to the instrument list Variable Coefficient Std. error t-Statistic Prob. C 42.89045 105.7964 0.405406 0.7059 HLYFB 0.359091 1.243120 0.288863 0.7870 HLYMB 0.546311 1.923511 0.284017 0.7905 MINAW 0.001012 0.001733 0.583702 0.5908 AVAGW 0.003745 0.006656 0.562564 0.6038 SS 0.025734 0.038152 0.674520 0.5370 R-squared 0.894110 Mean dependent var 21.79000 Adjusted R-squared 0.761749 S.D. dependent var 3.200851 S.E. of regression 1.562367 Sum squared resid 9.763968 Durbin–Watson stat 2.297991 J-statistic 0.000000 Instrument rank 6 Source: Author’s processing using EViews 10 Academic Edition software 4 Series: Residuals Sample 1 10 Observaons 10

3

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1

0 -2.5

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-1.5

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Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

-8.53e-15 0.088729 1.195740 -2.255468 1.041578 -0.967064 3.205268

Jarque-Bera Probability

1.576243 0.454698

Fig. 10.3 Model I residuals analysis in the case of Hungary. Source: Author’s processing using EViews 10 Academic Edition software

PSIBR 17.49000 18.05000 19.20000 15.20000 1.575119 0.567438 1.721085 1.218153 0.543853 174.9000 22.32900

HLYFB 59.04000 58.65000 62.90000 57.00000 1.893967 1.033413 2.880628 1.785842 0.409458 590.4000 32.28400

HLYMB 58.77000 59.00000 60.00000 57.30000 1.019858 0.353787 1.671450 0.944044 0.623740 587.7000 9.361000

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

MINAW 1175.040 1056.060 1655.400 849.7800 308.4580 0.568976 1.805909 1.133662 0.567321 11,750.40 856,316.8

AVAGW 6169.665 5792.350 8129.050 4998.230 988.5728 0.850210 2.550670 1.288886 0.524955 61,696.65 8795486.

SS 850.8790 843.9300 947.2400 730.4800 72.97986 0.147414 1.816186 0.620142 0.733395 8508.790 47934.54

10

Table 10.7 Descriptive analysis of model I variables in case of Romania

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Table 10.8 Results of econometric tests—sustainability of public pension systems in terms of BASS revenues in Romania—GMM method Dependent variable: PSIBR Method: Generalized method of moments Date: 05/18/20; Time: 14:29 Sample (adjusted): 1 10 Included observations: 10 after adjustments Linear estimation with 1 weight update Estimation weighting matrix: HAC (Bartlett kernel, Newey–West fixed bandwidth ¼ 3.0000) Standard errors & covariance computed using estimation weighting matrix Instrument specification: HLYFB HLYMB MINAW AVAGW SS Constantly added to the instrument list Variable Coefficient Std. error t-Statistic Prob. C 109.8866 19.41721 5.659240 0.0048 HLYFB 0.768919 0.384896 1.997731 0.1164 HLYMB 2.240198 0.708696 3.161013 0.0342 MINAW 0.003237 0.000702 4.609346 0.0100 AVAGW 0.000745 0.000490 1.522332 0.2026 SS 0.008147 0.002909 2.800596 0.0488 R-squared 0.965198 Mean dependent var 17.49000 Adjusted R-squared 0.921696 S.D. dependent var 1.575119 S.E. of regression 0.440764 Sum squared resid 0.777091 Durbin–Watson stat 2.748055 J-statistic 0.000000 Instrument rank 6 Source: Author’s processing using EViews 10 Academic Edition software

(R-squared ¼ 0.97 and Adjusted R-squared ¼ 0.92). SSIB revenues are positively correlated with the healthy life expectancy of females and the average annual income but are negatively correlated with the life expectancy of males, with the minimum annual income and social contributions. Thus, SSIB revenues will increase with the increase of healthy life expectancy of females and the average annual income, as well as by reducing the healthy life expectancy of males, by reducing the minimum annual income and social contributions. (Table 10.8). The residuals of model I applied in the case of Romania show their abnormal distribution by the JB test for a probability threshold of 5% (Fig. 10.4), with a positive asymmetry (Skewness > 0) and a platykurtic distribution (Kurtosis < 3).

Empirical Results from the Application of Model I in the Case of Slovakia Descriptive analysis of model I variables in the case of Slovakia highlights the abnormal distribution of model variables for the 5% significance threshold of the JB test (Table 10.9). The asymmetry coefficient shows the negative asymmetry of SSIB revenues, while all other variables show a positive asymmetry (Skewness > 0). The coefficient of vaulting shows the platykurtic vaulting of healthy life expectancy

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5

Series: Residuals Sample 1 10 Observaons 10

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Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

4.00e-15 -0.026866 0.463780 -0.531611 0.293842 0.019257 2.623738

Jarque-Bera Probability

0.059607 0.970636

Fig. 10.4 Analysis of model I residuals in the case of Romania. Source: Author’s processing using EViews 10 Academic Edition software

for both genders, the minimum and average annual income, as well as social contributions (Kurtosis < 3), while the SSIB revenues present a platykurtic vaulting (Kurtosis > 3). Model I in the case of Slovakia uses Eq. (10.1e), but unlike Model, I applied to all CEE countries included in the research, the estimation algorithm is determined by the 2SLS method, a method suggested by the E-views software as providing much more relevant results from statistically. The test results show that model I in the case of Slovakia is statistically significant marginally (R-squared ¼ 0.87 and Adjusted Rsquared ¼ 0.72). Thus, SSIB revenues are positively correlated with the healthy life expectancy of males and the average annual income but have a negative correlation with the life expectancy of females, the minimum annual income, and social contributions (Table 10.10). In other words, increasing SSIB revenues is possible by increasing the healthy life expectancy of males and the average annual income, as well as by reducing the life expectancy of females, the average income, and social contributions. Residuals of model I applied in the case of Slovakia reflect their abnormal distribution by the JB test with a significance threshold of 5% (Fig. 10.5), the negative asymmetry (Skewness < 0) and leptokurtic distribution (Kurtosis < 3).

10.3.2 Model II: Sustainability of Pension Systems in CEE Countries Through SSIB Pension Expenditures The descriptive analysis of the variables used in model II reflects, through the JB test with a significance threshold of 5%, an abnormal distribution of the model variables,

PSIBR 19.09000 19.30000 19.80000 17.30000 0.724875 1.600578 4.805995 5.628755 0.059942 190.9000 4.729000

HLYFB 53.91000 53.70000 57.00000 52.00000 1.668299 0.496397 2.054886 0.782867 0.676087 539.1000 25.04900

HLYMB 53.92000 53.95000 56.40000 52.10000 1.636256 0.149561 1.471387 1.010889 0.603237 539.2000 24.09600

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

Table 10.9 Descriptive analysis of model I variables in the case of Slovakia MINAW 2199.756 2069.100 3056.160 1773.000 401.5679 0.980694 2.990588 1.602973 0.448662 21997.56 1451311.

AVAGW 10019.30 9905.520 11,544.38 8820.000 876.4131 0.290823 2.026130 0.536140 0.764854 100,193.0 6912900.

1342.587 1327.345 1546.950 1181.880 117.4402 0.290788 2.026145 0.536093 0.764872 13,425.87 124,129.7

SS

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Table 10.10 Results of econometric tests—sustainability of public pension systems in terms of BASS revenues in Slovakia—GMM method Dependent variable: PSIBR Method: Generalized method of moments Date: 05/18/20; Time: 14:38 Sample (adjusted): 1 10 Included observations: 10 after adjustments Estimation weighting matrix: Two-stage least squares Standard errors & covariance computed using estimation weighting matrix Instrument specification: HLYFB HLYMB MINAW AVAGW SS Constantly added to the instrument list Variable Coefficient Std. error t-Statistic C 25.57738 7.554472 3.385726 HLYFB 0.531519 0.418448 1.270216 HLYMB 0.333651 0.392086 0.850963 MINAW 0.001356 0.000383 3.540625 AVAGW 11.59981 6.738594 1.721399 SS 86.56033 50.28683 1.721332 R-squared 0.874003 Mean dependent var Adjusted R-squared 0.716506 S.D. dependent var S.E. of regression 0.385954 Sum squared resid Durbin–Watson stat 2.383249 J-statistic Instrument rank 6

Prob. 0.0276 0.2729 0.4427 0.0240 0.1603 0.1603 19.09000 0.724875 0.595842 0.000000

Source: Author’s processing using EViews 10 Academic Edition software

6

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Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

1.60e-11 0.039415 0.321885 -0.622131 0.257303 -1.348091 4.618752

Jarque-Bera Probability

4.120733 0.127407

Fig. 10.5 Residuals analysis of model I in the case of Slovakia. Source: Author’s processing using EViews 10 Academic Edition software

PSIBEXP 18.60200 18.90000 22.70000 13.70000 2.176075 0.461787 2.770736 1.886560 0.389349 930.1000 232.0298

PNLNB 3.434000 2.850000 1.600000 9.100000 2.190481 0.469761 3.305530 2.033438 0.361780 171.7000 235.1122

PGGD 49.11800 47.85000 80.80000 12.30000 16.69418 0.428357 2.559214 1.933858 0.380249 2455.900 13,656.09

Source: Author’s processing using EViews 10 Academic Edition software

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis Jarque–Bera Probability Sum Sum sq. dev.

Table 10.11 Descriptive analysis of model II variables LEXF 18.79000 18.75000 20.50000 17.20000 0.820216 0.313150 2.178761 2.222265 0.329186 939.5000 32.96500

LEXM 14.93000 14.70000 16.20000 13.80000 0.674688 0.283413 1.963079 2.909370 0.233474 746.5000 22.30500

BEN 4371404. 2922438. 9965618. 1310522. 3025523. 0.867103 2.295037 7.300918 0.025979 2.19E+08 4.49E+14

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Table 10.12 Stationary of the variables of the model II Roots of characteristic polynomial Endogenous variables: PSIBEXP PNLNB PGGD LEXF LEXM BEN Exogenous variables: C Lag specification: 1 1 Date: 05/23/20; Time: 00:00 Root Modulus 0.859295 – 0.077677i 0.862799 0.859295 + 0.077677i 0.862799 0.791438  0.063788i 0.794004 0.791438 + 0.063788i 0.794004 0.400780  0.343595i 0.527903 0.400780 + 0.343595i 0.527903 No root lies outside the unit circle VAR satisfies the stability condition Source: Author’s processing using EViews 10 Academic Edition software

except for the number of beneficiaries (Table 10.11). The asymmetry coefficient highlights the negative asymmetry of SSIB expenditures with pensions and budget deficit (Skewness < 0), and the positive asymmetry of the other variables (Skewness > 0). The coefficient of vaulting shows the platykurtic vaulting of SSIB expenditures with pensions, public debt, life expectancy, and the number of beneficiaries (Kurtosis < 3), only the budget deficit showing a leptokurtic vault (Kurtosis > 3), which suggests a greater possibility to present extreme values. Model II for the econometric study of the sustainability of public pension systems in CEE countries used the system of regression equations for tests (10.2)–(10.7). The application of the VAR method involves as a first step the establishment of the stationary of the model, a condition fulfilled by the variables of the model, which have subunitary values (Table 10.12). In the second stage, is determined the optimal number of lags of the model, which according to the Schwarz and Hannan–Quinn criterion, is 1 (Table 10.13). The results actually reflect six regression models for each variable. We note, according to the coefficient of determination R2, that the models are marginally significant. As the set objective considers the financial sustainability of public pension systems in CEE countries, we will focus on the results of Eq. (10.2), respectively on the first model of test results by the VAR method (Table 10.14). The results of the econometric test reflect the existence of a positive correlation between the current expenditures of the SSIB with pensions and their previous level, as well as with the level of the budget deficit and life expectancy of females at 65, recorded in the previous period. The current expenditure of SSIB with pensions is negatively correlated with the previous level of public debt, the life expectancy of males, and the number of beneficiaries of public pension systems. In other words, the future SSIB pension expenditures will increase with the current increase in SSIB expenditures on pensions, the budget deficit, and the life expectancy of women, but

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Table 10.13 Testing the optimal number of lags for model II VAR lag order selection criteria Endogenous variables: PSIBEXP PNLNB PGGD LEXF LEXM BEN Exogenous variables: C Date: 05/22/20; Time: 22:27 Sample: 1 50 Included observations: 46 Lag LogL LR FPE AIC 0 1151.946 NA 2.95e+14 50.34550 1 990.4861 273.7806 1.28e+12 44.89070 2 946.9539 62.45924a 1.00e+12a 44.56321 3 921.8010 29.52738 2.00e+12 45.03482 4 874.6674 43.03504 1.97e+12 44.55075a

SC 50.58402 46.56033a 47.66395 49.56668 50.51372

HQ 50.43485 45.51615a 45.72477 46.73248 46.78452

LR, sequential modified LR test statistic (each test at 5% level); FPE, final prediction error; AIC, Akaike information criterion; SC, Schwarz information criterion; HQ, Hannan–Quinn information criterion Source: Author’s processing using EViews 10 Academic Edition software a Indicates lag order selected by the criterion

will be reduced by the current increase in the level of public debt, the life expectancy of the males and the number of beneficiaries (Table 10.14). To validate the correlations established between the level of SSIB expenditures and predictors, the VAR Granger Causality/Block Exogeneity Wald test was applied on predictors, for a significance threshold of 5%, the results showing that in the short term only public debt determines SSIB expenditures on pensions ( p ¼ 0.04), while all other predictors, as well as their association, do not cause SSIB expenditure on pensions in the short term (Table 10.15). E-views allow highlighting the coefficients of the predictors by the least-squares method, as a result, the representation of Eq. (10.2) was processed to highlight each coefficient of the predictors (Table 10.16). The Wald test was also applied to the coefficients of Model II, Eq. (10.2) to establish the validity of the coefficients. The test results reflect the fact that there is a causal relationship between predictors and the dependent variable ( p ¼ 0.00), as a result in the short term SSIB expenditure with pensions in CEE countries is influenced by predictors (Table 10.17). Regarding the model residuals, the Portmanteau autocorrelation test, as well as the LM test, confirm the null hypothesis that there is no autocorrelation between the model residuals (Table 10.18), nor in the case of the first lag considered in this model (Table 10.19). The analysis of the distribution of the residuals of Model II (Table 10.20) reflects, according to the JB test with a significance threshold of 5%, the normal distribution of residuals ( p ¼ 0.00), an aspect also supported by the asymmetry coefficient ( p ¼ 0.00) and the vaulting coefficient ( p ¼ 0.00). Model II used for the econometric study of the sustainability of public pension systems in CEE countries in terms of SSIB pension expenditures cannot be extended

Vector autoregression estimates Date: 05/22/20; Time: 22:28 Sample (adjusted): 2 50 Included observations: 49 after adjustments Standard errors in ( ) & t-statistics in [ ] PSIBEXP PSIBEXP(-1) 0.962847 (0.16460) [5.84947] PNLNB(-1) 0.159637 (0.13655) [1.16911] PGGD(-1) –0.045687 (0.02231) [–2.04815] LEXF(-1) 1.212811 (0.76301) [1.58950] LEXM(-1) –1.794827 (0.94500) [–1.89930] BEN(-1) –1.23E-07 (8.8E-08) [–1.39545] C 8.040935 (6.71489) [1.19748] PNLNB –0.576552 (0.15756) [–3.65928] –0.063677 (0.13070) [–0.48719] 0.129865 (0.02135) [6.08218] –2.514946 (0.73036) [–3.44345] 5.559591 (0.90455) [6.14626] –1.41E-07 (8.4E-08) [–1.67247] –34.42801 (6.42748) [–5.35637]

PGGD 1.638086 (1.12314) [1.45848] 0.520974 (0.93169) [0.55917] 0.617967 (0.15220) [4.06015] 1.688586 (5.20627) [0.32434] –5.871468 (6.44798) [–0.91059] –5.08E-07 (6.0E-07) [–0.84795] 48.69739 (45.8177) [1.06285]

LEXF –0.043766 (0.06475) [–0.67595] –0.094251 (0.05371) [–1.75482] 0.010008 (0.00877) [1.14060] 0.796506 (0.30013) [2.65387] 0.209630 (0.37171) [0.56396] –2.22E-08 (3.5E-08) [–0.64229] 0.793645 (2.64128) [0.30048]

LEXM –0.015883 (0.05729) [–0.27723] –0.090228 (0.04752) [–1.89855] 0.004849 (0.00776) [0.62454] 0.046282 (0.26557) [0.17428] 0.902294 (0.32890) [2.74333] –2.38E-08 (3.1E-08) [–0.77753] 0.437282 (2.33711) [0.18710]

Table 10.14 Results of econometric tests—sustainability of public pension systems in terms of SSIB pension expenditures—VAR method

BEN –176,655.5 (176761.) [–0.99941] –127,701.6 (146630.) [–0.87091] 34,336.37 (23,953.8) [1.43344] –82,295.65 (819365.) [–0.10044] 452234.7 (1014785) [0.44565] 0.887087 (0.09432) [9.40542] –3572329. (7210805) [–0.49541]

214 10 Econometric Study on the Financial Sustainability of Public Pension Systems

0.716224 0.675684 66.12378 1.254741 17.66733 –76.87084 3.423299 3.693560 –3.463265 2.203283 4.36E+11 1.73E+11 –1051.142 44.61803 46.23959 42

Source: Author’s processing using EViews 10 Academic Edition software

R-squared 0.688289 Adj. R-squared 0.643759 Sum sq. resids 72.16955 S.E. equation 1.310848 F-statistic 15.45668 Log likelihood –79.01434 Akaike AIC 3.510789 Schwarz SC 3.781049 Mean dependent 18.61633 S.D. dependent 2.196242 Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion Number of coefficients

0.745720 0.709394 3360.021 8.944300 20.52870 –173.1111 7.351473 7.621734 49.54286 16.59183

0.661270 0.612880 11.16619 0.515618 13.66544 –33.29422 1.644662 1.914922 18.78980 0.828715

0.605579 0.549233 8.742459 0.456239 10.74754 –27.29908 1.399963 1.670223 14.92245 0.679542

0.813420 0.786765 8.32E+13 1407657. 30.51738 –759.4657 31.28432 31.55458 4403296. 3048373.

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Table 10.15 VAR Granger causality/block exogeneity Wald test on model II predictors—Eq. (10.2)

VAR Granger causality/block exogeneity Wald tests Date: 05/23/20; Time: 11:48 Sample: 1 50 Included observations: 49 Dependent variable: PSIBEXP Excluded Chi-sq df Prob. PNLNB 1.366819 1 0.2424 PGGD 4.194916 1 0.0405 LEXF 2.526504 1 0.1119 LEXM 3.607330 1 0.0575 BEN 1.947275 1 0.1629 All 6.947693 5 0.2246 Source: Author’s processing using EViews 10 Academic Edition software

Table 10.16 Results of econometric tests—sustainability of public pension systems in terms of BASS pension expenditures—Eq. (10.2)—VAR method System: UNTITLED Estimation method: Least squares Date: 05/23/20; Time: 12:44 Sample: 2 50 Included observations: 49 Total system (balanced) observations 294 Coefficient Std. error t-Statistic Prob. C(1) 0.962847 0.164604 5.849471 0.0000 C(2) 0.159637 0.136546 1.169111 0.2435 C(3) 0.045687 0.022306 2.048149 0.0416 C(4) 1.212811 0.763015 1.589498 0.1132 C(5) 1.794827 0.944995 1.899297 0.0587 C(6) 1.23E-07 8.78E-08 1.395448 0.1641 C(7) 8.040935 6.714895 1.197477 0.2322 Equation: PSIBEXP ¼ C(1)*PSIBEXP(–1) + C(2)*PNLNB(–1) + C(3)*PGGD(–1) + C(4) *LEXF(–1) + C(5)*LEXM(–1) + C(6)*BEN(–1) + C(7) Observations: 49 R-squared 0.688289 Mean dependent var 18.61633 Adjusted R-squared 0.643759 S.D. dependent var 2.196242 S.E. of regression 1.310848 Sum squared resid 72.16955 Durbin–Watson stat 1.968204 Source: Author’s processing using EViews 10 Academic Edition software

to each country due to the limited number of observations currently available for the six variables, which determines that the results of VAR testing not to be statistically relevant.

10.4

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217

Table 10.17 Wald test for the causality of coefficients Wald test System: %system Test statistic Value df Chi-square 9975.525 7 Null hypothesis: C(1)¼C(2)¼C(3)¼C(4)¼C(5)¼C(6)¼C(7)¼0 Null hypothesis summary Normalized restriction (¼ 0) Value C(1) 0.962847 C(2) 0.159637 C(3) 0.045687 C(4) 1.212811 C(5) 1.794827 C(6) 1.23E-07 C(7) 8.040935 Restrictions are linear in coefficients

Probability 0.0000

Std. err. 0.164604 0.136546 0.022306 0.763015 0.944995 8.78E-08 6.714895

Source: Author’s processing using EViews 10 Academic Edition software Table 10.18 Portmanteau autocorrelation test

VAR residual portmanteau tests for autocorrelations Null Hypothesis: No residual autocorrelations up to lag h Date: 05/23/20; Time: 13:51 Sample: 1 50 Included observations: 49 Lags Q-Stat Prob.a Adj Q-Stat Prob.a 1 36.57222 – 37.33414 – 2 71.82191 0.0004 74.08382 0.0002 3 104.7378 0.0071 109.1464 0.0031 4 134.9541 0.0405 142.0486 0.0156

df – 36 72 108

df is degrees of freedom for (approximate) chi-square distribution Source: Author’s processing using EViews 10 Academic Edition software a Test is valid only for lags larger than the VAR lag order

10.4

Conclusions and Personal Contributions

The econometric study of the sustainability of public pension systems in CEE countries was carried out from a dual perspective, considering, on the one hand, budget revenues and, on the other hand, pension expenditures. The methods used for dynamic testing of SSIB sustainability were the Generalized Method of Moments (GMM) and Vector Autoregression (VAR). The first model used in the econometric study of the sustainability of pension systems in CEE countries used the GMM estimator and took into account SSIB revenues. Although the results of the model applied to all five CEE countries showed little significance in terms of the coefficient of determination R2, correlations are

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Table 10.19 LM autocorrelation test VAR residual serial correlation LM tests Date: 05/23/20; Time: 14:10 Sample: 1 50 Included observations: 49 Null hypothesis: No serial correlation at lag h Lag LREa stat df Prob. 1 56.01375 36 0.0179 2 39.53536 36 0.3150 3 36.44422 36 0.4480 4 33.16628 36 0.6041 Null hypothesis: No serial correlation at lags 1 to h Lag LREa stat df Prob. 1 56.01375 36 0.0179 2 81.04235 72 0.2179 3 125.2991 108 0.1222 4 159.5264 144 0.1780

Rao F-stat 1.668026 1.113705 1.016091 0.914671

df (36, 138.9) (36, 138.9) (36, 138.9) (36, 138.9)

Prob. 0.0191 0.3220 0.4553 0.6107

Rao F-stat 1.668026 1.145265 1.180322 1.049107

df (36, 138.9) (72, 141.8) (108, 116.1) (144, 83.9)

Prob. 0.0191 0.2457 0.1901 0.4096

Source: Author’s processing using EViews 10 Academic Edition software Edgeworth expansion corrected likelihood ratio statistic

a

established between SSIB incomes, the healthy life expectancy of the population, minimum and average annual income, and the level of social contributions. The first econometric model was also applied for each CEE country included in the research, excepting Poland, where the GMM estimator did not allow tests to be performed due to a single matrix. Following the results obtained by applying the first econometric model, it is noted that SSIB revenues can be increased by increasing the healthy life expectancy of the population and the income of the population. Indeed, a very good state of health is the first condition for a person to be able to carry out remunerated professional activities, subject to taxation. This suggests the need to strengthen the quality of medical services, promote a healthy lifestyle, prevention and screening programs for chronic diseases. However, the financial impact of these policies, which can relocate the budgetary pressure of pension systems, must not be overlooked. On the other hand, SSIB revenues increase with the increase of the population’s income, respectively the tax base. A sustainable increase in wage income must be correlated with labor productivity, as a result, the development of the entrepreneurial environment must be taken into account. The second model used in the econometric study of the sustainability of public pension systems in CEE countries used the VAR method. The six regression models resulting from the tests are marginally significant in terms of the coefficient of determination R2. Given the objective of this chapter, namely the econometric analysis of the sustainability of public pension systems in CEE countries in terms of SSIB pension expenditures, we analyzed only the first model resulted from the application of the VAR method, which takes into account this aspect.

10.4

Conclusions and Personal Contributions

Table 10.20 Analysis of the residue distribution of Model II

VAR residual normality tests Orthogonalization: Cholesky (Lutkepohl) Null hypothesis: Residuals are multivariate normal Date: 05/23/20; Time: 14:20 Sample: 1 50 Included observations: 49 Component Skewness Chi-sq df 1 2.095742 35.86909 1 2 0.270347 0.596883 1 3 0.968925 7.666997 1 4 0.523937 2.241832 1 5 0.082311 0.055330 1 6 0.391299 1.250438 1 Joint 47.68057 6 Component Kurtosis Chi-sq df 1 14.32788 261.9884 1 2 3.186902 0.071321 1 3 10.89543 127.2732 1 4 3.261392 0.139499 1 5 3.461011 0.433918 1 6 9.669234 90.81063 1 Joint 480.7170 6 Component Jarque–Bera df 1 297.8575 2 2 0.668203 2 3 134.9402 2 4 2.381330 2 5 0.489249 2 6 92.06107 2 Joint 528.3975 12

219

Prob.a 0.0000 0.4398 0.0056 0.1343 0.8140 0.2635 0.0000 Prob. 0.0000 0.7894 0.0000 0.7088 0.5101 0.0000 0.0000 Prob. 0.0000 0.7160 0.0000 0.3040 0.7830 0.0000 0.0000

Source: Author’s processing using EViews 10 Academic Edition software a Approximate p-values do not account for coefficient estimation

The results of econometric testing by the VAR method reflect the fact that there is a determining relationship between current SSIB expenditure and pensions and their previous value. Moreover, there is also a causal relationship between current SSIB expenditure on pensions and the previous level of the budget deficit, public debt, life expectancy, and the number of beneficiaries of public pension systems. Following econometric tests, it is noted that the future level of SSIB pension expenditure in CEE countries can be reduced by currently reducing them, as well as by reducing the budget deficit and life expectancy, but also by increasing public debt and increasing the number of beneficiaries. The decision to reduce the level of benefits provided by public pension systems generates a reduction in SSIB expenditures on pensions, as well as the level of the

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budget deficit, but also increases the risk of poverty and severe material deprivation among the elderly population. The reduction of life expectancy is manifested by the reduction of the period for which the benefits of public pension systems must be provided, which materializes in the reduction of the level of SSIB expenditures. On the other hand, with the increase in public debt and the need to borrow, which must be repaid, constraints arise in terms of directing public revenues, which can lead to a reduction in the level of benefits provided and, at the same time, a reduction in SSIB expenditures. Also, in the conditions in which the number of beneficiaries increases excessively, two options can be discussed: either the budgetary resources will be increased, or the benefits will be diminished, to maintain the budgetary balance, a condition that implies the need to reduce SSIB expenditures. The main conclusion of the study highlights, on the one hand, the importance of the quality of the human factor and the development of the labor market and business environment, to ensure sustainable national economic growth, and on the other hand, the divergent relationship between the adequacy of public systems pensions and keeping the level of expenditure within the limits of the resources held.

10.5

Summary

In this chapter was employed an econometric study on the financial sustainability of public pension systems in CEE countries, by establishing correlations between the level of budget revenues and expenditures on the one hand and socioeconomic indicators specific to pension systems, on the other. The results show that the sustainability of public pension systems can be strengthened in CEE countries by increasing the income and tax base of taxpayers while increasing the life expectancy of the population and maintaining good health. Also, the results reveal that the financial sustainability of the pension systems in CEE countries by reducing current SSIB expenditures, the budget deficit, and the life expectancy of the population after the age of 65, respectively the period for which benefits are granted.

References Alda, M., Marco, I., & Marzo, A. (2018). The reform of the Spanish public pension system: The sustainability factor. Journal of Finance and Economic Policy, 10(1), 45–63. Alonso-Ortiz, J. (2014). Social security and retirement across the OECD. Journal of Economic Dynamics & Control, 47, 300–316. Balazs, E. (2013). The impact of changes in second pension pillars on public finances in Central and Eastern Europe: The case of Poland. Economic Systems, 37, 473–491. Beetsma, R., & Oksanen, H. (2008). Pensions under ageing populations and the EU stability and growth pact. CESifo Economic Studies, 54(4), 563–592.

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Chybalski, F., & Marcinkiewicz, E. (2016). The replacement rate: An imperfect indicator of pension adequacy in cross-country analyses. Social Indicators Research, 126, 99–117. Cristescu, A. (2019). The impact of the aging population on the sustainability of public finances. Romanian Journal of Regional Science, 13(2), 52–67. De las Heras Camino, A., Gosalbez Raull, M. B., & Hernandez Gonzalez, D. (2014). The sustainability factor and the Spanish public pension system. Economia Espaniola y Protection Social, VI, 119–157. Godınez-Olivares, H., del Carmen Boado-Penas, M., & Haberman, S. (2016). Optimal strategies for pay-as-you-go pension finance: A sustainability framework. Insurance: Mathematics and Economics, 69, 117–126. Halaskova, R. (2018). Structure of general government expenditure on social protection in the EU member states. Montenegrin Journal of Economics, 14(4), 7–21. Kolmar, M. (2007). Beveridge versus Bismarck public pension systems in integrated markets. Regional Science and Urban Economics, 37, 649–669. Laub, N., & Hagist, C. (2017). Pension and intergenerational balance: A case study of Norway, Poland and Germany using generational accounting. Intergenerational Justice Review, 2, 64–77. Liebman, J. B., Luttmer, E. F. P., & Seif, D. G. (2009). Labor supply responses to marginal social security benefits: Evidence from discontinuities. Journal of Public Economics, 93, 1208–1223. Mladen, L. (2012). A comparative review over the pension systems’ performance in Central and Eastern European Countries. Journal of Knowledge Management, Economics and Information Technology, 5. Available online at: https://www.scientificpapers.org/wp-content/files/1311_ Luise_Mladen__A_COMPARATIVE_REVIEW_OVER_THE_PENSION_SYSTEMS_.pdf. Németh, A. O., Németh, P., & Vékás, P. (2019). Demographics, labour market, and pension sustainability in Hungary. Society and Economy, 41, 1–26. Pascuzzo, P. (2015). An international comparison of pension system performance in delivering adequate retirement incomes. Challenger Limited. Available online at: http://tinyurl.com/ zkms7hb. Peng, J., & Wang, Q. (2017). Affordability of public pension benefit: A historical and empirical analysis of US state and local government pension contributions. PEF, 16 (1), 21–42. Roman, D. M., Toma (Roșu), G. C., & Tuchiluş, G. (2018). Efficiency of pension systems in the EU countries. Romanian Journal of Economic Forecasting, XXI(4), 161–173. Rotschedl, J. (2015). Selected factors affecting the sustainability of the PAYG pension system. Procedia Economics and Finance, 30, 742–750. Simões de Matos dos Santos, T. C., & Domínguez Fabián, I. (2009). Financial solvency of the pension system in the European Union. Available online at: https://ecomod.net/system/files/ TANIA%20SANTOS_ECOMOD_15%20MAY.pdf. Simonovits, A. (2015). Socially optimal contribution rate and cap in a proportional (DC) pension system. Portuguese Economic Journal, 14, 45–63. Ștefan, G. M. (2015). A brief analysis of the administration costs of national social protection systems in EU member states. Procedia Economics and Finance, 30, 780–789. Verbič, M., Majcen, B., & Van Nieuwkoop, V. (2006). Sustainability of the Slovenian pension system: An analysis with an overlapping-generations general equilibrium model. Eastern European Economics, 44(4), 60–81.

Chapter 11

Conclusions and Final Remarks

The elaboration of this book is based on the theoretical and empirical study of the effects that the new demographic conditions and globalization show on the social protection systems and especially on the sustainability of the PAYG public pension systems implemented in CEE countries. The reason behind the formation and implementation of social protection systems is the right of the population to social protection, in the context of income inequality, which increases the risk of poverty and material deprivation. Pension schemes, part of the social protection system set up at a national level, have the role of ensuring the financial protection of people who are unable to obtain income due to old age, accidents, pathologies, or disabilities. Regardless of the form of organization, the way it works, the structure, and the principles on which it is based, the pension systems have the role of making financial distributions through which to reduce the risk of poverty and ensure a decent and dignified living at an old age. Worldwide, there are multiple types of pension systems. Noncontributory pension systems increase the well-being of beneficiaries, the positive effects being both material and psychological. On the other hand, contributory pension schemes limit the accessibility of financial benefits by meeting eligibility criteria of minimum contribution period and standard retirement age, and private pension funds present also the investment risk. The multi-pillar structure proposed by WB and supported by ILO is, from a theoretical point of view, the ideal form of protection for the elderly. However, in practice, the privatization of pension funds is not a solution for all countries. The current configuration and structure of national pension systems has its origins in the ideology of social policy applied by predecessors but must be adapted to the new social, demographic, cultural, economic, financial, fiscal, legal, and behavioral context. The analysis of the typologies and the organization and functioning of the pension systems of the EU Member States reflects the existence of their diversity in terms of structure and operating principles. In northwestern Europe, pension systems are liberal, based mainly on private structures, while the central-eastern part of the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0_11

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continent is more conservative, with the public pension system being the main pillar of protection for the elderly. It has been noted that democratic government systems support individual involvement in order to ensure the financial risks that arise with aging, and gradually this principle has been taken over by the CEE countries. The Czech Republic, Hungary, Poland, Slovakia, and Romania have descending structures of paternalistic socialist systems, but in recent decades have adopted numerous regulations on the reform of national social protection systems and public pension systems. Reforms have emerged on a similar socioeconomic background in all five CEE countries, characterized by declining employment rates, decreasing birth rate, increasing the number of beneficiaries of the pension system, increasing life expectancy, the lack of fairness and equality in accessing benefits. The reforms adopted by the five CEE countries have considered the maintenance of the financial sustainability of public pension systems and the adequacy of benefits. In this regard, the eligibility criteria for accessing benefits have been redefined, and through parametric reforms, the quotas of compulsory social contributions have been modified, the minimum contribution period and the standard retirement age have been increased, penalties for early retirement and benefits for continuing activity after reaching retirement age, the way of determining the number of benefits was redefined, as well as the way of updating and indexing the benefits. Efforts to provide adequate benefits through public pension systems in the five CEE countries are reflected in increasing the replacement of pension income, reducing poverty and material deprivation, and maintaining the level of consumption, and improving the health status of the population over the age of 65. On the other hand, these results are supported by the increase in expenditure on pension benefits. The direct link with the population structure and the contribution of the labor force represents, in the current demographic context, especially for Romania, where emigration is extensive, a threat to the financial sustainability of public pension systems. Regarding the structure of national pension systems in CEE countries, a multipillar structure has been adopted, based on three pillars promoted by the WB. However, the implementation of mandatory private pension funds did not have the expected effect. Underdevelopment of financial markets, negative rates of return, increased social contribution pressure, and increased spending on public pension systems have undermined public confidence and minimized the attractiveness of private pension funds in CEE. As a result, the restructuring of national pension systems on a three-pillar structure is currently maintained only in Romania and Slovakia, but also in these countries, the contribution is lower than the level initially established. On the other hand, Hungary and Poland have decided to nationalize compulsory private pension funds, and in the Czech Republic, this pillar has not yet been implemented. The investment policy of private pension funds is regulated by both Community and national law so that the structure of the portfolios respects a minimum level of prudence and protects the interests of the participants. However, the high share of investments in securities that finance the national budget deficit and the state

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administration is a real barrier to the profitability of mandatory private pension funds in Romania and Slovakia. The responsibility of the population to ensure the necessary income after retirement is an opportunity for the development of financial markets, but the lack of financial education and poor knowledge of financial concepts poses a major risk that the investments made will not produce the expected return. From this perspective, public pension systems eliminate this risk but instead present the risk of demographics and redistribution between generations. From the point of view of free movement and migration of population, the pension systems implemented by the five CEE countries ensure the coordination, cooperation, and exchange of information at an international level; therefore, the barriers in terms of the right to social protection of the migrant population have diminished considerably in recent years. However, poor information and procedures that require a fairly long time to process data and exchange information still pose challenges for the creation of an “optimal pension area” across the European Community. The econometric studies carried out in this book aimed to establish correlations between the financial sustainability of public pension systems and various variables that define the new social and economic conditions in CEE countries. Given the complexity of social and economic phenomena, the studies are not intended to capture the full range of factors influencing the sustainability of pension systems but highlight multiple perspectives. From an economic perspective, the empirical results confirm the direct correlation between the expenditures with social protection of population and the economic development of the country, the activity on the labor market, and the unemployment rate. Thus, strengthening the financial sustainability of social protection systems in CEE countries requires a higher level of activity and employment rate. Even if the empirical results reflect a reduction in long-term social protection spending as unemployment rises, this does not bring economic benefits and is not sustainable. From a social point of view, the empirical results reflect the correlation between social protection expenditure and demographic structure, net migration, and the average duration of working life of the population in the five CEE countries. As a result, strengthening the financial sustainability of social protection systems is possible by increasing the average population, reducing emigration, and increasing the period of professional activity. As regards the social and medical characteristics of the population in CEE countries, the empirical results establish correlations between social security expenditures and birth rate, fertility, mortality, natural change of population, the average age of women at birth, and the dependency rate of the elderly population. From this perspective, in order to maintain the sustainability of social protection systems, it is necessary to increase the birth rate and to ensure a positive natural change of population. At the macroeconomic level, pension systems are fulfilling their purpose only if they manage to provide an adequate financial flow to ensure a decent standard of living among the population. Under these auspices, the empirical results highlight

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the correlation between the median equivalized net income of the population and the level of inflation, the risk of poverty, and the rate of severe material deprivation, highlighting the need to adjust the benefits provided by pension systems in CEE countries with the inflation rate. From the perspective of personal savings for the retirement period, the empirical study highlights the correlations between the interest rate on bank deposits and equalized net income, the level of inflation, the share of the population with severe material deprivation, and the investment structure of private pension funds in CEE countries. As a result, once with the increase of the population’s income, the competitiveness of saving instruments will also increase. From a budgetary perspective, the empirical results highlighted, on one hand, the correlation between the incomes of SSB and the income level of the population, social contributions paid to SSB and healthy life years, and on the other hand, the determination of the expenditures of SSB on pensions by their previous value, the level of the budget deficit and public debt, life expectancy at the age of 65 and the number of beneficiaries. Strengthening the financial sustainability of pension systems in CEE countries, by increasing the collection of SSB incomes is possible by increasing the healthy life expectancy and the earned incomes. In addition, strengthening the financial sustainability of pension systems in CEE countries based on decreased expenditures requires a reduction in current BASS spending, a budget deficit, and the life expectancy of the population at 65 years old. The study of the specialized literature, legislation in the field of social protection, and the empirical results obtained from econometric studies showed that the efficiency and effectiveness of pension systems are conditioned by the adequacy of the national framework and it is determined by the influence of economic, demographic, social and medical, fiscal, financial, and budgetary factors. The authors believe that maintaining the sustainability of pension systems is possible only through the collaboration of all sectors of the economy in order to promote sustainable economic growth.

List of Abbreviations

α β εit 2SLS ACT ADSS art. A.S.F avaGW BB Ben BNR BSE BSSE BVB CARICOM CD CE CEE CIPRES CNPP CSSPP CZ DB DC DTr DTT DWL ECB

Free coefficient Beta coefficient, slope of the regression line Regression error Pooled instrumental variables (IV)—two-stage least squares Active population Association of Pension Management Companies Article Authority for Financial Supervision Average annual gross income The share of investment of private pension funds in government securities The number of beneficiaries of public pension systems The National Bank of Romania Budapest Stock Exchange Bratislava Stock Exchange Bucharest Stock Exchange Caribbean Community The share of investment of private pension funds in deposits Council of Europe Central and Eastern Europe Inter-African Conference on Social Security National House of Public Pensions Private Pension System Supervisory Commission Czech Republic Defined benefits Defined contributions Mortality rate Number of deceased persons Duration of working life European Central Bank

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. A. Jimon et al., Financial Sustainability of Pension Systems, Financial and Monetary Policy Studies 52, https://doi.org/10.1007/978-3-030-74454-0

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EFAMA EMP EQ EU Fr GCC GDP GDPcap GMM GPW HLYfB HLYmB HU ILO IMF INEMRC INS INTr2 JB LBr LBT LEXf LEXm mdENI mdENIaP mdENIbP minaW MISSOC mnAGEcb NCHPOP NDC NGO nMIGR OECD OISS OLDDr OLS OTH P0 P1

List of Abbreviations

European Funds and Assets Management Association Employed population The share of investment of private pension funds in shares European Union Fertility rate Gulf Cooperation Council Gross domestic product GDP per capita Generalized method of moments Warsaw Stock Exchange Healthy life expectancy at birth for females Healthy life expectancy at birth for males Hungary International Labor Organization International Monetary Fund National Institute of Medical Expertise and Work Capacity Recovery National Institute of Statistics Interest rate for bank deposits Jarque–Bera test Birth rate Number of birth rate Life expectancy at the age of 65 of females Life expectancy at the age of 65 of males Equivalised median net income Equivalised median net income before social transfers (excluding pensions) Equivalised median net income before social transfers (including pensions) Minimum annual gross income Social protection mutual information system The average age of women at birth Natural growth Notional accounts Non-governmental organizations Net migration Organization for Economic Co-operation and Development Ibero-American Multilateral Convention on Social Security Dependency rate of the elderly population Ordinary least squares The share of investment of private pension funds in other financial securities The “zero” pillar of non-contributory pension systems The “one” pillar of the pension systems formed by the contributory public component

List of Abbreviations

P2 P3 P4 pARPr PAYG pGExpSP pGGD pINFacp PL pNLNB POPt PSE pSIBexp pSIBR psMD RO SK SS SSIB TCHPOP TEU UN UNE USA USD VAR WB

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The “second” pillar of pension systems consists of privately managed pension funds The “three” pillar of the pension systems formed by the optional pension funds The “four” pillar of non-financial pension systems Poverty risk rate Pay-as-you-go Budget expenditures with social insurance The level of public debt Inflation Poland The level of the budget deficit Total population Prague Stock Exchange SSIB expenditures SSIB revenues Severe material deprivation Romania Slovakia The average annual level of social contributions State Social Insurance Budget Total change of population Treaty on European Union United Nations Unemployed population United States of America US dollar Vector autoregression World Bank