Gender Inequality in the Eastern European Labour Market: Twenty-five years of transition since the fall of communism 2016022552, 9781138999855, 9781315657400

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Gender Inequality in the Eastern European Labour Market

Under communism there was, in the countries of Eastern Europe, a high level of gender equality in the labour market, particularly in terms of high participation rates by women. The transition from communism has upset this situation, with different impacts in the different countries. This book presents a comprehensive overview of gender and the labour market since the fall of communism in a wide range of Eastern European countries. Each country chapter describes the nature of inequality in the particular country, and goes on to examine the factors responsible for this, including government policies, changing social attitudes, levels of educational attainment and the impact of motherhood. Overall, the book provides an interesting comparison to the situation in Western developed countries, outlining differences and similarities. No one single Eastern European model emerges while, as in Western developed countries, a range of experiences and trends is the norm. Giovanni Razzu is Professor of Economics of Public Policy at the University of Reading, UK.

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Gender Inequality in the Eastern European Labour Market Twenty-five years of transition since the fall of communism Edited by Giovanni Razzu

First published 2017 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 711 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2017 Giovanni Razzu The right of the editor to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data Names: Razzu, Giovanni, editor. Title: Gender inequality in the Eastern European labour market : twenty-five years of transition since the fall of communism / edited by Giovanni Razzu. Description: Abingdon, Oxon ; New York, NY : Routledge, 2016. | Series: Routledge contemporary Russia and Eastern Europe series ; 73 | Includes bibliographical references and index. Identifiers: LCCN 2016022552 | ISBN 9781138999855 (hardback) | ISBN 9781315657400 (ebook) Subjects: LCSH: Sex discrimination in employment—Europe, Eastern. | Labor market—Europe, Eastern. | Equal pay for equal work—Europe, Eastern. | Women—Employment—Europe, Eastern. | Post-communism— Europe, Eastern. Classification: LCC HD6060.5.E852 G46 2016 | DDC 331.13/30947—dc23 LC record available at https://lccn.loc.gov/2016022552 ISBN: 978-1-138-99985-5 (hbk) ISBN: 978-1-315-65740-0 (ebk) Typeset in Times New Roman by Apex CoVantage, LLC

Contents

List of figures List of tables List of abbreviations List of contributors and affiliations Prologue 1 The wider context

vii xi xiii xiv xvi 1

G I O VA N N I R A ZZ U

2 Bulgaria

21

VA S I L T Z A N O V

3 Czech Republic

44

L E N K A F I L I P O VA AND MARI OL A P YT L I KOVÁ

4 East Germany

77

HEIKE TRAPPE

5 Estonia

100

R E I N V Ö Ö R M A NN AND JE L E NA HE L E MÄE

6 Hungary

136

E VA F O D O R

7 Lithuania

151

B O G U S L AVA S G RUZ E VS KI S AND VI DA KANOP I EN E

8 Poland J A N B A R A N , R OMA KE I S T E R, P I OT R L E WANDOW SK I A N D IG A MA G D A

169

vi

Contents

9 Romania

217

G I O VA N N I RAZ Z U

10 Slovenia

242

J A N A J AV O R NI K

Epilogue Index

269 275

Figures

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10 1.11 1.12 1.13 1.14 2.1 2.2 2.3 2.4 2.5 2.6 2.7 3.1 3.2 3.3 3.4 3.5 3.6

Population by age group, 1990 and 2014 Gini coefficient, 1990 and 2014 HDI, 1990 and 2013 Female labour force participation, 1990–2013 Gender gap in activity rate, 2000 and 2014 Gender gap in activity rate by age, 2000 and 2014 Female employment rate, 15+, 1991 and 2013 Gender employment rate gap, 15+, 1991 and 2013 Part-time employment rate by gender, 1998 and 2013 Gender employment rate gaps by sector, 2000 and 2013 Gender pay gap, mid-1990s and 2013 90/10 ratios in earnings by gender, 2010 Gender pay gap and female employment rate, 2013 Social attitudes on women and work, 1990 and 2008 Evolution and share of male and female employment in Bulgaria, 1980–2014 Employment rates of men and women (age 15+) in Bulgaria, 1980–2014 Unemployment rates of men and women in Bulgaria, 1991–2014 Annual gross earnings of men and women in Bulgaria, 1996–2013 Gender sectoral segregation index in Bulgaria, 1980–2014 Gender educational gaps in Bulgaria, 1985–2014 Average employment gap by age for the period 1995–2013 Main economic indicators, 1994–2014 Female economic activity rate by age, 1993–2013 Male economic activity rate by age, 1993–2013 Gender gap in unemployment, 1993–2013 Population by education, 1993 and 2013 Students enrolled in tertiary education, per cent by gender, 1995–2014

3 5 6 7 8 9 10 10 11 12 14 15 16 17 23 24 25 27 30 34 35 46 47 48 49 50 51

viii Figures 3.7 3.8 3.9 3.10 3.11 3.12 3.13 3.14 4.1 4.2 4.3 4.4 4.5 4.6 4.7 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 6.1 7.1 7.2 7.3

Proportion of women in management and on executive boards, European Union, 2003–2013 Ratio of wages of women over men, 1996–2013 Share of median wages of women to median wages of men by occupation, 2002–2013 Share of median wages of women to median wages of men by age, 2002–2013 Number of weeks of paid maternity and parental leave in 2012, OECD countries Recipients of parental allowance by gender (in thousands), 2001–2013 Spending on child, related to maternity/parental leave and birth grant, 2011, USD PPP Childcare (kindergartens and preschools), 3–6-year-olds: 30 hours per week, 2013, per cent Labor force participation rate, 1989–2014 Unemployment rate, 1991–2014 Employment rate, 1991–2014 Part-time employment rate, 1991–2014 Unadjusted gender pay gap, East and West Germany, 2006–2014 Unpaid work of working couples aged under 60, East Germany, 1992 and 2002 Attitudes towards female employment, 1991–2012 Importance of family and work by gender, 1985–2008 Employment rate of men and women aged 15–69, 1989–2014 Unemployment rate by gender, 1989–2014 Share of non-working persons aged 15–69, 1989–2014 Probability of labour force participation by gender and presence of small child in household, 2012 Probability of unemployment by gender and presence of small child in household, 2012 Male and female employment by economic sectors, 1989–2014 Horizontal and vertical gender segregation, 1989–2014 Gender pay gap, Estonia and EU average, 1994–2013 Lifelong learning by gender and education, 1997–2014 Participation in training by gender and presence of young child, 2011 Employment rate of women and men in Hungary, 1990–2015 (Q1/2) Employment rates by gender, 15–64, 1998–2014 Unemployment rates by gender, 15–64, 1998–2014 Activity rates by gender, 15–64, 1998–2014

53 54 55 56 57 58 59 60 81 82 83 85 87 90 91 110 115 116 117 118 119 120 121 123 123 125 139 154 155 155

Figures  ix 7.4 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19 8.20 8.21 8.22 8.23 8.24 8.25 8.26 8.27 8.28

Gender pay gap in unadjusted form, 1995–2014 159 Participation rate by gender, 15–64, 1992–2014 171 Employment rate by gender, 15–64, 1992–2014 172 Employment rate gender gap, 15–64, 1988–2014 172 Unemployment rate by gender, 15–64, 1992–2014 173 Effective labour market entry age by gender, 1992–2013 176 Effective labour market exit age by gender, 1993–2013 177 Age-specific employment rates of women by cohort, per cent 178 Age-specific gender employment rate gap by cohort 178 Evolution of employment by sector, 1981–2014 (thousands of people) 180 Sector-specific feminisation ratios, 1994 and 2002 182 Occupational gender segregation, 1995–2014 182 Response rate to a job application by gender of applicant and occupational groups, 2008 184 Number of women employed under open-ended and temporary contracts 185 Share of temporary workers in total employment of women by age group, 2000–2013 186 Men and women aged 15–55 who worked under contracts of mandate at least once in 2013 (in thousands) 187 Share of women and men who worked under contracts of mandate at least once in 2013 among all persons insured in ZUS aged 15–55 187 Average weekly hours of dependent workers, main workplace, full-time 188 Average weekly hours of dependent workers, main workplace, part-time 189 Ratio of women to men, monthly wages, 1985–1989 191 The post-transition women-to-men wage ratio 192 Relative wages in agriculture and whole economy, 1992–1994193 Average monthly wages by gender, 1985–2012 194 Difference in average wages of men and women as a percentage of men’s wages in European countries, 2002 and 2010 195 Unadjusted gender wage gap along the wage distribution, 2002–2010197 Favourable family models in Poland, 1997 and 2013 202 Time on care and household work by age group and gender, 2005 204 Distribution of family and occupational responsibilities in the life course of men and women born in the period 1969–1984 205 Time devoted to particular activities by economic status and gender, 2005 206

x Figures 8.29 Share of employed on maternity or parental leave by gender, 2014 207 8.30 Share of people with tertiary and basic vocational education, cohorts born between 1960–1990 209 8.31 Educational structure of working population in Poland, 1992–2014210 9.1 Activity rates by gender, 1990–2014 220 9.2 Employment rates by gender, 1990–2013 220 9.3 Unemployment rates by gender, 1990–2014 221 9.4 Gender gaps in activity and employment, 1997–2014 222 9.5 Female activity rates by age group, 1996 and 2014 222 9.6 Male activity rates by age group, 1996 and 2014 223 9.7 Gender gaps in activity rates by age group, 1996 and 2014 224 9.8 Gender gaps in employment rates by age group, 1996 and 2014 224 9.9 Employment rates by number of children, 2014 225 9.10 Part-time employment by age group, 1996 and 2014 226 9.11 Female employment as a proportion of total female employment by sector, 1997 and 2008 226 9.12 Female employment as a proportion of total female employment by sector, 2014 227 9.13 Employment by sector and gender, 1997 228 9.14 Employment by sector and gender, 2014 228 9.15 Female employment by occupation, 1997 and 2014 229 9.16 Gender employment by occupation, 1997 and 2014 230 9.17 Gender pay gap in hourly earnings, 1994 and 2013 231 9.18 Gender pay gap by sector, 2013 232 9.19 Social attitudes towards women and work, 1990–2008 236 10.1 Public attitudes to gender roles, 1992–2012 251 10.2 Part-time employment, men and women, 1993–2014 254 10.3 Female employment and activity rate, 1993–2014 254 10.4 Women’s wage as percentage of male, 1991–1996 256 10.5 Gender pay gap in unadjusted form by sector, 2007–2014 256

Tables

1.1 1.2a, b 2.1 2.2 2.3 2.4 2.5 2.6 3.1 3.2 3.3 3.4 A.1 4.1 4.2 5.1 5.2 5.3 5.4 6.1

Total population at the beginning of the year, 1990–2014 GDP per capita (constant 2005 US$, PPP), gap from EU, 1990–2014 Activity rates of the population (15–64 years) in Bulgaria, 1980–2014 Gender pay gap by economic activity, 2007–2013 Sectors with male and female overrepresentation, 1980–2014 Share of men and women by occupations and occupational segregation index, 1980–2014 Share of male and female employment by level of education, 1985–2014 Employment rates by age and sex, 1985–2013 Economic activity, employment and unemployment by gender, 1980–2013 Men and women in occupations, 1993 and 2013 Proportion of men and women in industries, 1993 and 2013 Determinants of monthly wages, 2011 Summary statistics of variables for men and women based on survey from 2011 Beyond the “male breadwinner” model Gendered work outcomes in East Germany, before and after reunification Indicators of a “normative contract,” married or cohabiting couples, 2010 Division of household tasks, 1985–2013 Division of household tasks among married and cohabiting couples, 2013 Average hours per week spent on unpaid and paid work among married or cohabiting couples aged 25–54, 2010 Odds of working, 25–49-year-olds, 2012

3 4 22 28 29 32 33 35 46 52 53 62 73 79 93 111 112 112 113 142

xii 6.2 6.3 7.1 7.2 7.3 7.4 7.5 8.1 8.2 8.3 8.4

Tables Impact of education on the parenthood penalty/premium, aged 25–49, 2012 Odds of being in a supervisory position by gender, aged 20–60, 2012 Educational attainment by gender, 1959–2011 Distribution of employment by gender, main NACE sectors, 1998–2014 Leadership positions by sector and gender, 2014 Gender pay gap by economic activities, 2007–2013 Gender pay gap by occupational groups, 2010 Decomposition of the gender employment gap, 2008 (in percentage points) Occupation-specific occupational segregation indices, Poland 2008 (in per cent) Division of household work by gender, 1996 Division of household work by gender, 2006

143 146 153 157 158 160 160 175 183 201 202

Abbreviations

CEDAW CEE CZSO EBRD EGEM EU EVS FRG GDP GDR HDI ILO ISCO ISSP LFS OECD SILC STEM UNDP UNESCO UNICEF USSR WDI

Convention on the Elimination of all forms of Discrimination Against Women Central and Eastern Europe Czech Statistical Office European Bank for Reconstruction and Development Estonian Gender Equality Monitoring European Union European Value Study Federal Republic of Germany Gross Domestic Product German Democratic Republic Human Development Index International Labour Organization International Standard Classification of Occupations International Social Survey Programme Labour Force Survey Organisation for Economic Co-operation and Development Statistics on Income and Living Conditions Science, Technology, Engineering, and Mathematics United Nations Development Programme United Nations Educational, Scientific and Cultural Organisation United Nations Children Fund Union of Soviet Socialist Republics World Development Indicators

Contributors and affiliations

Jan Baran Economist, Institute for Structural Research, Warsaw, Poland Lenka Filipova Assistant Professor and the Head of Department at the VSB Technical University of Ostrava, the Czech Republic Eva Fodor Professor of Gender Studies, Academic Director of Institute for Advanced Studies, Central European University, Budapest, Hungary Boguslavas Gruzevskis Director, Institute of Labour and Social Research, Vilnius University, Lithuania Jelena Helemäe Senior Research Fellow, Institute of International and Social Studies, School of Governance, Law and Society, Tallin University, Estonia Jana Javornik Senior Lecturer in Public and Social Policy, University of East London, UK Vida Kanopiene Professor, Mykolas Romeris University, Vilnius, Lithuania Roma Keister Analyst, Institute for Structural Research, Warsaw, Poland Piotr Lewandowski President of the Board, Institute for Structural Research, Warsaw, Poland Iga Magda Vice President of the Board, Institute for Structural Research, Warsaw, Poland Mariola Pytliková Assistant Professor, Center for Economic Research and Graduate Education – Economics Institute (CERGE-EI), Prague, Czech Republic

Contributors and affiliations

xv

Giovanni Razzu Professor of Economics of Public Policy, School of Politics, Economics and International Relations, University of Reading, UK Heike Trappe Professor of Sociology and Family Demography, Institute for Sociology and Demography University of Rostock, Germany Vasil Tzanov Professor of Economics and Head of Department, Economic Research Institute, Bulgarian Academy of Sciences, Sofia, Bulgaria Rein Vöörmann Senior Research Fellow, Institute of International and Social Studies, School of Governance, Law and Society, Tallin University, Estonia

Prologue

The gender dimension of labour markets in the Eastern European countries that have faced the transition from centrally planned to market economies has been the focus of a diverse set of literatures. It has received the attention of economists, sociologists and human resources specialists, who have all, with distinct methodological approaches, aimed to monitor and explain the impact that the transition has had, at various points in time, on gender inequality. These issues have also captured the interest of policy makers at the country level, as well as in international organisations such as the United Nations Development Programme (UNDP), the European Union (EU), the Organisation for Economic Co-operation and Development (OECD), the International Labour Organization (ILO) and, of course, the European Bank for Reconstruction and Development (EBRD). This specific geographic focus needs to be put into the wider context, whereby gender outcomes have in fact received substantial and growing attention from academics of various disciplines over time across the world. This has also been a reflection of the changing position of women in society and the labour market in developed, developing, emerging and transitional countries. In some nations, such as those in the developed world, girls have not only narrowed, but have even overtaken educational attainment gaps with boys. The participation rate of women in paid work has increased steadily over the past half a century (although this rate has slowed in the past two decades), at the same time as participation for working-age men seeing a sustained fall. However, the labour market outcomes of women, both the jobs they do and the pay they receive, often do not reflect their personal qualifications, at least relative to men, or their improvement in recent years. Despite the advancement in most dimensions of paid work, there is no evidence of gender gaps fully closing. Notwithstanding differences that arise from disciplinary backgrounds, philosophical and political perspectives and methodological approaches, it appears that we have some overlapping consensus amongst scholars of gender inequality in the developed context on key areas of intervention to address the persistent gender inequality in the labour market. There is an overall agreement that gender inequality in the labour market is the product of many factors, most notably of a structured system of institutions and norms in which gender plays a very important part. This widespread, although not complete consensus – certainly

Prologue

xvii

some disagree and would attribute gender inequality to choices women make – has led to a stronger focus, for instance, on the importance of the way gender gaps cumulate through the life cycle, start early and then develop from education to the transition into the labour market, motherhood and retirement. Within this overall approach, key areas of intervention are the gendered structure of education, particularly in some subject areas; the impact of motherhood and the household distribution of labour. Social attitudes on the role of women in the labour market are also very important, but represent a problematic area of intervention for policy makers. Moreover, the recent literature on gender gaps, while it acknowledges the role productivity and discrimination play in explaining gender inequality in the labour market, has explored different and fresh perspectives based on differences in preferences, attitudes and social norms (Croson and Gneezy, 2009; Flory et al., 2015; Leibbrandt and List, 2014, amongst others). Unfortunately, this kind of emerging consensus is not present in the case of transition economies. The existing literature in this field is extremely fragmented. Overall, before the fall of communism, these countries were characterised by high levels of gender equality in some dimensions of the labour market, although it is difficult to be precise given the lack of robust and credible data. In general, women’s labour market activity was high and countries had very high female employment rates as compared to the rest of the world, but gender gaps were still present to some extent, and more so in pay. Under communism, constitutions guaranteed the right to employment for the entire working-age population and the right to equal pay for equal work among men and women. There was no formal unemployment, and women generally worked full time throughout their adult lives. The public sector, which dominated the economy through state-owned enterprises, supplied jobs seemingly without limit. Women were seen as an essential economic input into the industrialisation process the countries embarked on. Was this enough to eliminate the gender gap in the labour market? Generally, the evidence shows this was not the case. Although women’s participation in the labour market was remarkable, important gaps remained, most notably in pay and the types of jobs in which women and men tended to be employed. Moreover, the double burden of paid and unpaid work was substantial (UNICEF, 1999, Figure 2.2), not helped by the generally strong pro-natalist policies of the various governments. However, in most cases, this was accompanied by a generous system of support for families, including nurseries, kindergartens and after school programmes, but also lavish parental leave benefits. What has happened since the collapse of the centrally planned economic system and the transition to a market-based economy? To what extent has the transition upset this situation, and has it done so with different impacts in various countries of Eastern Europe? This book discusses the experiences of eight countries that have gone through the transition and joined the European Union (Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Poland, Romania and Slovenia) and one other former country, East Germany, which has experienced the collapse of the centrally planned economic system and reunification with West Germany at the same time.

xviii Prologue A substantial amount of research has paid attention to the type of welfare systems the transitional countries have managed to develop since the collapse of centrally planned economic systems and the heavy state presence. The debates that have sprung up in this respect have seen a group of scholars suggesting that welfare systems in the region would eventually converge with those in Western Europe, the so-called Europeanisation of social policy paradigms in post-socialist countries (Lendvai, 2008; Toots and Bachman, 2010). On the other hand, another group of scholars suggest that post-socialist states might follow a different and non-traditional path, individually or as a region, in terms of welfare provision (Cerami and Vanhuysse, 2009; Manning, 2004). However, despite this sizeable focus on welfare state regimes, a considerable evidence gap exists about comparative evidence of gender equality in the labour market for the whole period of transition covering 1990 to 2015. This is not to say that assessments of gender equality in the labour market have not been carried out: many studies have looked at the gender gaps in the labour market for transitional countries, but these have not covered the full period or the same countries consistently and have tended to focus only on a very few of them. The year 2015 marks 25 years since the collapse of the regimes – what we normally think of as a generation, from the birth of a parent to the birth of a child. Such a long-term focus is important as it allows one to see fully how, for instance, the experience of women of different ages compares: a cohort of women and men are now entering the labour market having had no direct experience of the communist past. What circumstances are they finding? How different are these from those of their mothers, who started their experience in the labour market just when these regimes collapsed, or from those of their grandmothers, who lived their working lives almost entirely under communism? In 1993, in the very first year since the collapse of the centrally planned economic system, Barbara Einhorn (1993) in Cinderella Goes to Market provided a fascinating account of the impact of the early transition process on women’s lives: state socialism attempted to achieve women’s ‘emancipation’ via legislation and social provision, with a dominant focus on issues connected with the participation of women in the labour force. In contrast, the improvement of women’s status was not included on the agenda of the newly democratised regimes: the predominant focus on stabilising the macroeconomic situation from the huge shock it received with the collapse of the centrally planned economy did not take into account the potential role of women in the labour market. An unfortunate combination of political objectives and rejection of the socialist past, a growing nationalism and a resuscitated ideology of the family and the economy’s need to shed labour meant that the initial transition, in Einhorn’s view, relegated women to the primary responsibility for the family. The attack on abortion rights in many countries was also seen as symptomatic of attitudes towards the role of women. Has this changed during the rest of the 25 years since the transition?

Prologue

xix

Scope, objectives and limitations The preceding questions outline the main compass of this book. This book’s fundamental aim is therefore to examine the extent of changes in gender equality in the labour market in most of the countries of Eastern Europe that have experienced the collapse of communism and have then joined the European Union. Therefore, two comparative perspectives characterise this book’s approach: one is over time and one is cross-country. The time-based comparison answers the question: what is the extent of gender inequality in the labour market now as opposed to the period around the fall of communism? The country-based comparison, instead, aims to shed light on why and the extent to which some Eastern European countries differ in the way gender inequality in the labour market has changed over time. In order to address these points, we adopt a simple though systematic framework, based on an analysis of the most relevant factors that determine the extent of gender inequality in the labour market in the countries under analysis. This prologue is followed by an introductory chapter, which sets the wider context for the following eight chapters, one for each of the countries studied. In Chapter 1, therefore, we look at changes over time for, first, a set of wider economic and development indicators and, second, for a set of key labour market indicators. The aim is to establish a helpful context to interpret the more detailed country-focused analyses that follow in the subsequent chapters. Chapters 2 to 10 are devoted to each of the countries selected and are written by respective country experts on gender inequality. Although the experts’ backgrounds vary, ranging from economics to sociology and social policy, each of these chapters has a common approach, which is composed of two distinct elements. First, each chapter describes the extent of gender inequality in key labour market variables: employment, unemployment, inactivity, pay and occupational segmentation. The gender gaps in these variables are presented for both the latest available data point and for the one as close as possible to the fall of communism. This allows for a consistent description of the changes in labour market inequality in each country. Second, based on their deep knowledge of the country’s context, each contributor discusses those changes, looking to assess the main determining factors. These generally include assessment of policy interventions (i.e. childcare provision, taxation, legislation on discrimination), the role of educational and human capital factors and the role of motherhood, as well as changes in social attitudes. In this way, contributors can expand on the assessment of possible explanatory factors on the basis of their knowledge of the country’s experience. The result is, we hope, a journey through eight different countries, characterised by two common starting points: a political background of communism and the fact that for all of them, at the same point in time, through 1989 and early 1990, communism collapsed: the demise of a centrally planned economic system started the transition to a market economy. What have we learnt from this journey? The epilogue draws out the key messages.

xx

Prologue

However, before we start this journey, it is important to outline some of the key limitations. The first and perhaps the most relevant one is data issues. In order to assess changes over the entire period since 1990, we need both the latest available information and consistent data for the time as close as possible to the fall of communism. However, consistent and standardised data on labour market outcomes for the countries we study in this book are only available from Eurostat from around 1997. Therefore, these data do not allow us to capture, in a fully comparative way, the first years of the transition, when economic conditions deteriorated considerably. Some data exist from other sources, and when possible and relevant we make use of them. This lacuna needs to be kept in mind, particularly for the first chapter, when we look at the wider context from a regional, cross-country perspective. However, national data sources exist for most of the countries we study and each contributor uses them to assess changes over the entire period since the transition in the respective countries. Therefore, data for the earlier period of transition will be different in each country, depending on specific data development and availability issues: in some countries, for instance Germany, the labour force data go back much further than in other countries, where other sources, such as temporary surveys, have been carried out. Indeed, this is one of the reasons we have opted for a detailed assessment of individual countries’ experiences, within a mostly common framework. There are various dimensions of the experience of transition economies this book does not discuss, and particularly the theoretical ones. No specific theory characterises this book’s approach. Moreover, this book does not aim to enter the debate on what kind of welfare states transition economies can be classified as, which we have briefly mentioned in this prologue. The reason is simple: this is the product of various scholars, all with their own background and disciplinary approach. There is no dominant disciplinary approach but, instead, a recognition that gender inequality in the labour market is the product of a series of factors that relate to the economy, society, culture and politics, to mention only a few. Finally, a note on the geographical focus and the terminology used throughout this book. The aim of this book is to assess changes in gender inequality in the labour market in countries that have experienced the fall of the communist regimes, for the entire period since 1990. Due to time and resource constraints, some of these countries are not studied in this book. We have attempted to cover those countries that have joined the European Union, but even in this case, we have not been able to cover Slovakia, Latvia and Croatia. However, the experience of the eight countries and East Germany do provide a very rich account of the experience of transition economies in terms of gender equality. Terms like totalitarianism, communism, socialism and regime, but also, although to a lesser extent, transition economies, the fall of the Iron Curtain, centrally planned economies and democracy might all have a different meaning in different contexts. In some, a totalitarian regime prevailed in the immediate post-war period; in others, such a regime continued or strengthened up until 1989. Although all were characterised by a lack of free elections, it is arguable

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xxi

whether the main aspect of the transition we focus on here is that from a lack of democracy to a democratic system. For this reason, we use these terms interchangeably across the chapters of this book and do not define them precisely. This is because we use these terms to describe a specific point in time (i.e. 1989–1990) or a period of time (i.e. the transition since 1990), and therefore to define a time frame for the assessment of changes in gender equality in the labour market. Although we recognise that the pre-1990 legacy has affected the path taken from 1990 onwards, and various chapters make this point forcefully, we think the focus on the transition since 1990 does not require a full discussion on the meaning of terms such as communism, socialism, totalitarianism, regime and so on. The key dimension is the transition from a centrally planned to a market economic system.

Bibliography Cerami A. and Vanhuysse P. (eds.) (2009) Post-communist Welfare Pathways: Theorizing Social Policy Transformations in Central and Eastern Europe. Palgrave MacMillan, London. Croson R. and Gneezy U. (2009) Gender differences in preferences. Journal of Economic Literature, 47: 1–27. Einhorn B. (1993) Cinderella Goes to Market: Citizenship, Gender, and Women’s Movements in East Central Europe. London/New York: Verso Books. Flory J., Leibbrandt A. and List J. (2015) Do competitive work places deter female workers? A large-scale natural field experiment on gender differences in job-entry decisions. The Review of Economic Studies, 82: 122–155. Leibbrandt A. and List J. (2014) Do women avoid salary negotiations? Evidence from a large-scale natural field experiment. Management Science, 61 (9): 2016–2024. Lendvai E. (2008) EU integration and the transformation of post-communist welfare: traversing a quantum-leap? Social Policy and Administration, 42 (5): 504–523. Manning N. (2004) Diversity and change in pre-accession Central and Eastern Europe since 1989. Journal of European Social Policy, 14 (3): 211–232. Toots A. and Bachman J. (2010) Contemporary welfare regimes in Baltic states: adapting post-communist conditions to post-modern challenges. Studies of Transition States and Societies, 2 (2): 31–44. UNICEF (1999) Women in Transition. Regional monitoring Report 6. UNICEF ICDC Florence.

1

The wider context Giovanni Razzu

In this chapter, we describe key facts with the aim of providing the reader with the relevant context to interpret the more detailed country-focused analyses that follow in the subsequent chapters. We will focus on two kinds of facts: first, we will present the wider economic and development context, describing trends over the time period since the fall of the communist regimes in 1989–1990, in economic growth as well as in economic inequality and in human development; second, we will concentrate on crucial labour market variables from a comparative perspective. As said in the prologue, one of the objectives of this book is to understand the extent of the changes in gender equality in the labour market the countries under analysis have gone through over the past 25 years. Although we cannot assume they all started from a similar gender equality situation around 1990, when the centrally planned economies collapsed, as we will see in subsequent chapters, the Eastern and Central European countries discussed here did share one characteristic: they were united by a similar set of ideological principles about gender equality. This set of principles could be traced back to Friedrich Engels’ work on the interaction between the family, private property and the state, according to which, once the means of production pass into common property, private housekeeping is socialized and “the care and education of children becomes a public matter” (Engels, 1884). Although it can be argued that echoes of this can be seen in modern legislation on gender equality as well as in various policy initiatives on women and work in Western and economically advanced countries with no socialist or communist past, it is certain that an explicit commitment to gender equality from the state was common to our Eastern EU countries before the transition to a market economy. Moreover, this commitment was to be pursued through economic independence of women and active participation in the labour market, facilitated by direct provision of childcare facilities and the “socialization” of household duties. Naturally, this political commitment was accompanied by specific economic policies, and in particular those associated with a centrally planned approach whereby, for instance, wages were set in each sector of the economy. In some instances, the extent of gender inequality in the labour market during the totalitarian period was also determined by a recognition of the need to industrialize

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Giovanni Razzu

what had been traditionally rural societies: female participation was therefore required with the promise of equal pay for equal work (Brainerd, 2000). However, despite the fact that women in the former communist countries of Eastern Europe drove tractors, the socio-economic system did not prevent gender inequality in work, as will be evident in the country analyses when, for instance, we look at gender segregation, the division of labour within the household and, in some instances, the gender pay gap. As already pointed out, one aim of this book is to compare the experience of the Eastern EU countries during the past 25 years. Comparisons about changes over time are hampered by lack of consistent data on labour market outcomes for the earlier period around the fall of the centrally planned economic systems in 1990. This is one of the reasons we have opted for detailed assessments of individual countries’ experiences, within a mostly common framework. Therefore, in the remaining part of this chapter, we will provide a brief overview of the wider economic context and changes over time for a set of key variables for which consistent data for the earlier period can be presented with a degree of confidence. However, for the labour market variables, in this chapter we have to report changes over a shorter period of time, mostly from the beginning of the second half of the 1990s when consistent Eurostat data become available. This lacuna, however, will be more than compensated for in the individual chapters, which can fill the gap with national data sources and provide a detailed picture of changes over time. We start with the wider context, particularly the economic one. Although there is a tendency to group these countries together – a tendency sometimes justified by the fact they all shared a similar political regime and economic policy approach – an initial look does reveal this is a set of heterogeneous countries in many respects. Table 1.1, for instance, shows these were countries of different population size: Poland and Romania were large countries with populations of around 37 and 23 million people, respectively. Estonia, Slovenia and Lithuania were instead small countries, with populations of between 1.5 and 3.7 million people. In between, we find Hungary and the Czech Republic, with around 10 million people in 1990. The latest available data show that, by 2014, three countries (Slovenia, the Czech Republic and Poland) experienced positive, although very limited, population growth, while the others saw their populations decrease over the past 25 years, the most pronounced decreases occurring in Lithuania, Bulgaria, Estonia and Romania. Figure 1.1 shows the age distributions of the populations both in 1990 and in 2014. We have focused on three main age groups: the young (below 17), the main working-age population (18 to 59 years old) and those older than 60. Two main points emerge from this figure: first, no major differences are seen between the countries in the proportions of the three groups, in both years. Second, all countries experienced a reduction in the proportion of young people aged below 17 – which represented around a quarter of the total population in 1990 and around 18 per cent in 2014 – and an increase of the older population aged 60

Table 1.1 Total population at the beginning of the year, 1990–2014 1989

1990

1995

2000

2005

2010

2014

Male Population Czech 5,033,142 5,035,658 5,020,464 5,001,062 4,980,913 5,157,197 5,162,380 Republic Hungary 5,106,715 4,984,904 4,941,620 4,865,194 4,793,115 4,756,900 4,703,391 Poland 18,467,046 18,540,495 18,778,040 18,547,799 18,470,253 18,428,742 18,629,535 Slovenia 968,350 968,252 964,375 970,812 977,052 1,014,107 1,020,874 Estonia 731,392 734,538 671,264 653,080 631,710 620,800 614,919 Lithuania 1,738,953 1,747,473 1,717,208 1,644,301 1,562,264 1,450,199 1,355,995 Bulgaria 4,439,333 4,323,773 4,129,966 3,991,161 3,767,610 3,659,311 3,524,945 Romania 11,402,309 11,450,831 11,143,398 10,980,041 10,417,145 9,880,409 9,738,445 Female Population Czech 5,326,892 5,326,444 5,312,697 5,277,036 5,239,664 5,349,616 5,350,039 Republic Hungary 5,481,899 5,389,919 5,395,081 5,356,450 5,304,434 5,257,424 5,173,974 Poland 19,417,609 19,497,908 19,802,557 19,715,504 19,703,582 19,738,587 19,866,124 Slovenia 1,027,975 1,028,125 1,025,102 1,016,943 1,020,538 1,032,869 1,040,211 Estonia 834,270 836,061 776,811 748,170 727,140 712,490 700,900 Lithuania 1,935,849 1,946,235 1,925,783 1,867,773 1,792,956 1,691,777 1,587,477 Bulgaria 4,547,303 4,443,535 4,297,452 4,199,715 3,993,439 3,904,399 3,720,732 Romania 11,709,212 11,760,564 11,568,996 11,475,444 10,965,209 10,414,274 10,204,197 Source: Transmonee 2015 database

1990 100% 80% 60% 40% 20% 0% Czech Hungary Poland Slovenia Estonia Lithuania Bulgaria Romania Republic 0–17 18–59 60+

2014 100% 80% 60% 40% 20% 0% Czech Hungary Poland Slovenia Estonia Lithuania Bulgaria Romania Republic 0–17 18–59 60+

Figure 1.1 Population by age group, 1990 and 2014 Source: Transmonee 2015 database

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Giovanni Razzu

or older – which was 16–17 per cent of the total population in 1990 and became almost a quarter in 2014. The size of the population contributes not just to the overall size of the economy, but also to the per capita GDP, which we show in Table 1.2, also in terms of the gap from the average EU countries. Table 1.2a GDP per capita (constant 2005 US$, PPP), gap from EU, 1990–2014 10.1.1 GDP per capita (constant 2005 US$)

Czech Republic Hungary Poland Slovenia Estonia Lithuania Bulgaria Romania European Union Euro area

1990

1995

2000

2005

2010

2013

10,332 7,516 4,761 – – 6,726 2,859 3,820 21,820 25,064

9,944 7,601 5,235 12,423 4,995 3,975 2,597 3,509 23,316 26,760

10,939 8,916 6,874 15,316 7,102 5,122 2,780 3,327 26,697 30,368

13,318 11,092 7,976 18,168 10,336 7,851 3,786 4,652 28,844 31,938

14,640 11,109 10,038 19,326 10,364 8,871 4,560 5,635 29,672 32,610

14,638 11,430 10,782 18,634 11,997 10,549 4,808 6,073 30,241 32,789

From Transmonee 2015; Data source: World Bank, World Development Indicators database, accessed April 2015

Table 1.2b GDP per capita (constant 2005 US$, PPP), gap from EU, 1990–2014

Czech Republic Hungary Poland Slovenia Estonia Lithuania Bulgaria Romania Gap from EMU Czech Republic Hungary Poland Slovenia Estonia Lithuania Bulgaria Romania

1990

1995

2000

2005

2010

2013

2013–1990 difference

0.47 0.34 0.22

0.43 0.33 0.22 0.53 0.21 0.17 0.11 0.15

0.41 0.33 0.26 0.57 0.27 0.19 0.1 0.12

0.46 0.38 0.28 0.63 0.36 0.27 0.13 0.16

0.49 0.37 0.34 0.65 0.35 0.3 0.15 0.19

0.48 0.38 0.36 0.62 0.4 0.35 0.16 0.2

0.01 0.04 0.14 0.09 0.19 0.04 0.03 0.02

0.37 0.28 0.2 0.46 0.19 0.15 0.1 0.13

0.36 0.29 0.23 0.5 0.23 0.17 0.09 0.11

0.42 0.35 0.25 0.57 0.32 0.25 0.12 0.15

0.45 0.34 0.31 0.59 0.32 0.27 0.14 0.17

0.45 0.35 0.33 0.57 0.37 0.32 0.15 0.19

0.31 0.13 0.18 0.41 0.3 0.19

0.27 0.11 0.15

Source: OECD database; WDI for EU, Romania and Bulgaria Note: The first data for Hungary refers to 1991.

The wider context 5 In order to facilitate comparisons, we use GDP per capita at 2005 prices in US$. Unfortunately, the earliest comparable data we have for Slovenia and Estonia is for 1995, 4 years after Slovenia split from Yugoslavia and Estonia left the Soviet state and became independent countries. Using this indicator, again we can see that the extent of economic development in 1990, compared to the average in the European Union, varied widely across the countries we study here. The Czech Republic had a GDP per capita, at 2005 prices, equal to almost half that of the EU average, while Bulgaria and Romania had GDP per capita equal to 13 and 18 per cent of the EU average, respectively. In 1995, 5 years after the collapse of the centrally planned economy, the GDP per capita of Estonia was equal to 21 per cent of that of the European Union, similar to that of Poland. The table shows clearly that, for all countries (but Poland) for which we have data, GDP per capita, relative to the European Union, fell in the first 5 years of economic transition. For Lithuania, the fall in this measure of living standard was particularly marked. However, the latest data available show that the progress these countries have made in this respect has been mostly disappointing: although, overall, they have all started to fill some of the gap with the EU average GDP per capita, progress over the past 25 years has been almost nil for the Czech Republic but also negligible for Romania, Bulgaria, Lithuania and Hungary. Estonia and Poland have instead covered much more ground and increased their GDP per capita compared to the EU average by 19 and 13 percentage points. With Figures 1.2 and 1.3 we move beyond narrow measures of economic growth to show, first, the extent to which income is distributed among the population and, second, the extent of human development, and also changes over time in the two indicators. The Gini coefficient is a widely used measure of income inequality. As income can be measured in various ways, it is difficult to

Gini coefficient 40 35 30 25 20 15 10 5 0 BUL

CZE

EST

HUN

LIT

1990

POL

ROM

SLO

EU-15

2014

Figure 1.2 Gini coefficient, 1990 and 2014 Source: UNU-WIDER, World Income Inequality Database (WIID3.0b), September 2014

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Giovanni Razzu

1990

Bulgaria

Romania

Hungary

Lithuania

Poland

Estonia

Czech Republic

Slovenia

EU-15

High HDI

Very high HDI

HDI 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2013

Figure 1.3 HDI, 1990 and 2013 Source: HDRO calculations based on data from UNDESA (2013a)

construct a consistent and standard measure for the countries and the whole period under consideration here. Eurostat provides a standardized measure from around 2000. For the preceding 10 years since 1990 we use an average of various coefficients collected by UNU WIDER; the average has been computed on a set of coefficients for the years around 1990, using the same source as far as possible, excluding outliers and considering coefficients based mostly on household income. Although imperfect, these data suggest two main points: income inequality was low in the Eastern EU countries around the fall of communism in 1990 and relative to the EU-15; moreover, income inequality has grown in all the countries, and in some of them, such as Bulgaria, Romania and Lithuania, the increase has been substantial enough to have reached in 2014 higher income inequality than that in the EU-15 countries. The Human Development Index (HDI) is a composite indicator measuring average achievement in three basic dimensions of human development: a long and healthy life, knowledge and a decent standard of living. It is interesting to note, from data presented in Figure 1.2, not just shows that the HDI increased for all our countries between 1990 and 2013, but that the extent of human development in these countries has always been very high. Both in 1990 and 2013, the HDI of the countries we study here is much closer to that of the very high HDI countries, including the EU-15, than to that of the high HDI countries. Therefore, in terms of human development,

The wider context 7 the Eastern EU countries have had and have maintained a very high ranking, not dissimilar to that of the EU-15. This brief overview of some macro indicators reveals that the Eastern EU countries we are studying here are characterized by heterogeneous experiences of economic development and more homogenous experiences in terms of income inequality and human development, the former low and the latter high. In what follows we focus on the labour market outcomes that will be analyzed in more details in the individual country chapters. As reported earlier, the time period we cover here in a consistently comparable way is shorter than the 25 years since 1990. For some variables, we can use the data from the World Development Indicators database, which allow us to see changes since 1990. However, for more detailed breakdowns of the variables, we would need to rely on the standardized Eurostat data, which will allow us to show changes between 2000 and 2014. We start, in Figure 1.4, with female labour force participation rates as a percentage of the total labour force: the overall conclusion is one of limited or no progress in female participation over the past 25 years for most countries, only Lithuania and Hungary having experienced an increase over time. The other countries saw either a decrease in female labour market participation or no change at all. This is in stark contrast to the average of the EU-15 countries. Participation rates remain well below 50 per cent across the countries and over the time period under consideration, apart from the Lithuania figure for 2013, which is just above 50 per cent. Although this is revealing of very limited progress, if any at all, in female labour market participation over the past 25 years, it tells us nothing about the gender gap.

51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 BGR

CZE

EST

HUN 1990

LTU 2013

Figure 1.4 Female labour force participation, 1990–2013 Source: World Development Indicators database

POL

ROM

SVN

8

Giovanni Razzu

Figure 1.5 used Eurostat data to show the gender gap in the activity rate for the working-age population, aged 15 to 64, between 2000 and 2014. Over this time period, the gender gap has narrowed in all countries but Poland, the Czech Republic and Romania. Lithuania stands out as having the narrower gender gap in activity rates, and it is also a case where the gap has been halved over the past 15 years. However, it is notable that the gender gap was narrower in the countries with former centrally planned economies than in the average EU-15 countries in 2000, but that is not the case in 2014. Figure 1.6 shows the gender gap in the activity rates over time for three broad age groups, the young aged 15–24, the prime working-age group aged 25–54 and the older workers aged 55–64. Again, the diversity of experiences amongst the countries is evident. Whilst the EU-15 average saw a reduction in the gender gap for all three age groups, only Hungary has experienced the same. Romania has seen the gender gap increase over time for all three age groups. Poland, the other similarly populous country, has seen an increase of the gender gap for younger and older workers but a decrease amongst those aged between 25 and 54. It is interesting to note that, in Lithuania, the gender gap is minimal for those aged 25–54, but one of the largest amongst the young. Estonia, another Baltic country, has the smallest gender gap in the activity rates of older workers and has, moreover, seen the largest reduction over the past 15 years, from almost 20 per cent to just 2.6 per cent.

20 18 16 14 12 10 8 6 4 2 0 Bulgaria

Czech Republic

Estonia

EU-15

Hungary

2000

Lithuania

2014

Figure 1.5 Gender gap in activity rate, 2000 and 2014 Source: Eurostat database

Poland

Romania

Slovenia

The wider context 9

35 30 25 20 15 10 5 0 15–24

25–54

55–64

15–24

2000 Hungary

Bulgaria

25–54

55–64

2014 Czech Republic

Estonia

EU -15

25–54

55–64

25 20 15 10 5 0 15–24

25–54

55–64

15–24

2000 Lithuania

Poland

2014 Romania

Slovenia

EU -15

Figure 1.6 Gender gap in activity rate by age, 2000 and 2014 Source: Eurostat database

The female employment rate is shown in Figure 1.7, for women aged over 15 years. The key message is one of no overall change when the 1991 rate is compared to the 2013 rate. However, changes have occurred in between these two data points: in this measure, all countries but Romania experience a decrease in the female employment rate in the initial period of transition from a centrally planned economy, and a later subdued recovery. Using the same measure, Figure 1.8 shows the changes in the gender employment rate gap in 1991 and 2013. This has declined in all countries but Bulgaria,

70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 BGR

CZE

EST

HUN 1991

LTU

POL

ROM

SVN

POL

ROM

SVN

2013

Figure 1.7 Female employment rate, 15+, 1991 and 2013 Source: World Development Indicator database

20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 BGR

CZE

EST

HUN 1991

LTU 2013

Figure 1.8 Gender employment rate gap, 15+, 1991 and 2013 Source: World Development Indicator database

The wider context 11 where it is low, and Romania. The Czech Republic has the highest gender employment rate gap of the countries under consideration here, at around 18 per cent. Again, although not shown here, Eurostat data indicate that this is in contrast to the decreasing gender employment rate gap experienced in the average EU-15 countries, although the latter started from a higher level. There are, of course, important differences by age and educational qualification, to mention only two factors, which we do not report here but which will be discussed in some detail in each country chapter. Figure 1.9, instead, reports data on part-time employment, the earliest year we can report consistent data on is 1998, while Figure 1.10 shows data on gender gaps in employment in the three main economic sectors of agriculture, services and industry.

2014 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 EU-15 BUL

CZ

EST

LIT Males

HUN POL ROM SLO

UK

NL

UK

NL

Females

Gender gap 0.0 -10.0 -20.0 -30.0 -40.0 -50.0 -60.0 EU-15 BUL

CZ

EST

LIT

1998

HUN POL ROM SLO 2005

2014

Figure 1.9 Part-time employment rate by gender, 1998 and 2013 Source: Eurostat database

-6

Source: Eurostat database 2000

2000

0 Slovenia

-3

Slovenia

3 Romania

6

Romania

9 Poland

12

Poland

Agriculture Hungary

2014

Hungary

Lithuania

Estonia

Czech Rep.

Bulgaria

2000

Lithuania

Estonia

Czech Rep.

Bulgaria

0 EU-15

Slovenia

Romania

Poland

Hungary

Lithuania

Estonia

Czech Rep.

Bulgaria

EU-15

-30

EU-15

0

Services

-10

-5

-15

-20

-25

2014

Industry

30

25

20

15

10

5

2014

Figure 1.10 Gender employment rate gaps by sector, 2000 and 2013 (panels a, b and c)

The wider context 13 Panel a shows the part-time employment rate for both males and females in 2014, while panel b shows the gender gap between 1998 and 2014 (for Bulgaria we have data from 2005 only). In this figure, we also compare to the United Kingdom and the Netherlands, and not just to the EU-15 average, as they are two of the countries with the highest rates of female part-time employment. It is noticeable that female part-time employment and the gender gap are substantially lower in the countries we analyze here than in the EU-15 countries, and even more so when compared to the Netherlands. Excluding Slovenia, the other countries all report rates of female part-time employment just above or well below 10 per cent, Bulgaria’s female part-time employment rate being just above 2 per cent in 2014. Over the 16 years covered by these data, female part-time employment has increased, although not substantially, in four countries (Slovenia, Hungary, Lithuania and Estonia), remained the same in the Czech Republic and decreased in Poland and Romania. The gender gap, instead, has increased in Slovenia, Poland, Hungary and Lithuania, remained stable in Estonia and decreased in the Czech Republic and more pronouncedly in Romania. In terms of main economic sectors, we see that more women than men are employed in the services sector, where gender gaps in the countries we consider here are, overall, slightly higher than the average of the EU-15 countries, but for Romania, where the gap is much lower. In fact, while in the average EU-15 countries the gap has narrowed between 2000 and 2014, in the Eastern EU countries we analyze here the gap has increased. This latter pattern is also found in the industry sector, where the gender gap is instead positive. There is more diversity in this case with respect to the EU-15 average, with Bulgaria and Romania having a substantially lower gender gap than the average EU-15 countries and the Czech Republic, Estonia, Poland and Slovenia a larger one. Gender gaps are overall smaller in the agriculture sector. They are very small, and comparable to the EU-15 average, in Poland, the Czech Republic and Estonia, and larger in Bulgaria. Romania has a negative gender gap, more women than men being employed in the agriculture sector, although this gap has narrowed over time. The gender pay gap in transition economies has been the subject of many studies. There is no overall consensus yet. In the very early period, for instance, Fong and Paull (1993) predicted that gender inequality would increase as a result of wage liberalization. However, some evidence suggests the contrary in some contexts and countries: Brainerd (2000) found that women’s relative wages increased in Bulgaria, Hungary, Poland, the Czech Republic and Slovakia while they decreased in Ukraine and Russia (which are outside the scope of this book). This is confirmed in studies by Munich and colleagues (2005) for the Czech Republic, Riphahn and colleagues (2001) for East Germany, Orazem and Vodopivec (1995) for Slovenia and Rutowski (1996) for Poland. On the contrary, Newell and Barry (2000) found no substantial change in the gender wage gap during the first decade of transition. These divergent findings are due to the fact that comparability of analysis is hampered by data limitations and the time period the specific studies covered. The most consistent gender pay gap measure we

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Giovanni Razzu

35 30 25 20 15 10 5 0 EU-15

BUL

CZ

EST

LIT

Ealiest data point

HUN

POL

ROM

SLO

2013

Figure 1.11 Gender pay gap, mid-1990s and 2013 Source: Eurostat database

could use for the countries and the time period covered here is in Figure 1.11. This shows the gap in gross hourly earnings: the earliest data point differs for the countries (most being 1994 or 1995, but for Poland it is 1999 and for Estonia 2001) and is based on national data sources and the overall economy, while the latest data point is based on the Structure of Earnings Survey methodology and includes industry, construction and services except public administration, defense and compulsory social security. So the two data points are not exactly comparable, but they offer the best available approximation to changes in the hourly pay gap for all employees for most of the period under analysis here. No single pattern emerges from these data: some countries show a gender pay gap larger than the EU-15 average in both the early 1990s and 2013 and some countries a smaller one; for some, it was larger in the 1990s and smaller in 2013. According to this measure, a substantial reduction in the gender pay gap has been experienced by Slovenia, Romania, Poland and Bulgaria while Estonia and the Czech Republic saw the gender pay gap increase over this time period. However, it is difficult to make a robust assessment considering the limitations of the data available. In comparative terms, the main message is, again, one of diverse, heterogeneous experiences. As for employment, we find that the gender pay gap differs by age group and educational level, and for part-time work as well as for other factors.1 Here we focus instead on an issue often left aside in discussion about gender pay inequality.

The wider context 15

6 5 4 3 2 1 0 Bulgaria

Czech Estonia Lithuania Hungary Poland Romania Slovenia Republic Male

Female

Figure 1.12 90/10 ratios in earnings by gender, 2010 Source: Eurostat database

Figure 1.12 reports the 90/10 ratios in gross hourly earnings in 2010 for males and females. This is an indicator of the extent of pay inequality, more precisely, the gap between those with earnings in the top 10 per cent of the distribution and those with earnings in the bottom 10 per cent. It therefore offers us an indication of the extent of within-group inequality in pay. The 90/10 ratios are greater for men than for women in all countries but Poland, where pay inequality between high- and low-paid women is higher than between high- and low-paid men. This indicator is low for women in the Czech Republic, where high-paid women earn three times more than low-paid women. In the other countries, it ranges from 3.3 (or 330 per cent, in Slovenia) to 4.8 (or 480 per cent, in Poland). Important, this pay inequality is much greater than the gender pay gap between men and women, which, as we have seen in Figure 1.11, in 2013 ranged from 3 per cent in Slovenia to 30 per cent in Estonia. It therefore is a misconception to believe that addressing the gender pay gap would eliminate pay inequality. Before moving on to present data on social attitudes regarding gender equality in the labour market, we explore the relationship between gender pay and employment. Overall, cross-country data appear to show a trade-off between the gender pay gap and female employment: a higher female employment rate seems to be associated with a larger gender pay gap; in other words, we would need to accept a wider gender pay gap if we wanted to increase the rate of female participation in the labour market. Figure 1.13 plots this relationship for a set of countries in the European Union. Overall, there is a positive relationship between the gender pay gap and female

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Giovanni Razzu

Figure 1.13 Gender pay gap and female employment rate, 2013 Source: Eurostat database

employment rate. However, when we focus only on the countries under analysis here (the darker diamonds in Figure 1.13), this positive relationship breaks down completely. At one extreme, Slovenia has a very narrow gender pay gap and a high female employment rate; at the other end, a similarly high female employment rate in Estonia is associated with a very wide gender pay gap. We conclude this introductory chapter with a brief overview of social attitutes towards women and work. The European Value Study collected information on social attitudes through a series of standard questions relevant to our analysis and available for the period since the 1990s. These ask participants whether they agree or disagree with the following statements: • • • •

A job is alright but what most women really want is a home and children. A preschool child is likely to suffer if his or her mother works. Having a job is the best way for a woman to be an independent person. Both the husband and wife should contribute to household income.

The four panels in Figure 1.14 report the percentage of people who said they agree or strongly agree with these statements. We show this for 1990 and 2008

A job is alright but what most women really want is a home and children 100 80 60 40 20 0 BUL

CZE

EST

HUN

LIT

POL

1990

2008

ROM

SVN

DNK

Being a housewife is just as fulfilling as working for pay 100 80 60 40 20 0 BUL

CZE

EST

HUN

LIT

POL

1990

2008

ROM

SVN

DNK

Having a job is the best way for a woman to be an independent person 100 80 60 40 20 0 BUL

CZE

EST

HUN

LIT

POL

1990

2008

ROM

SVN

DNK

Figure 1.14 Social attitudes on women and work, 1990 and 2008 (five panels) Source: European Values Study

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Giovanni Razzu

Both the husband and wife should contribute to household income 100 80 60 40 20 0 BUL

CZE

EST

HUN

LIT

POL

1990

2008

ROM

SVN

DNK

A preschool child is likely to suffer if his or her mother works 100 80 60 40 20 0 BUL

CZE

EST

HUN

LIT

POL

ROM

SVN

DNK

1990 2008

Figure 1.14 (Continued)

and, for comparison, also consider the responses given in so-called more liberal Denmark. In 1990, a large majority of respondents – around 80 per cent – in all of the countries agreed that both the husband and the wife should contribute to household income, reflecting the positive role of women in paid work and the higher employment rates we have seen under centrally planned economies. This percentage has increased slightly in most countries (in Bulgaria reaching almost 100 per cent) but for a slight decline in Slovenia, Romania and the Czech Republic. Interesting, this was and remains a larger proportion of individuals than in Denmark, when around 70 and 78 per cent of respondents agreed in

The wider context 19 1990 and 2008, respectively. Instead, in 1990, there was much more variation between countries in those who agreed that having a job is the best way for a woman to be an independent person: around 60 per cent agreed or strongly agreed with this statement in Bulgaria, the Czech Republic, Estonia and Poland, but 47 and 41 per cent in Hungary and Lithuania and 68 and 73 per cent in Romania and Slovenia, while in Denmark it was just above 80 per cent. However, in 2008, around 80 per cent of respondents in all countries – and almost 90 per cent in Bulgaria – agreed with that statement. Substantial differences from Denmark appear when the implication of female employment on family life is taken into consideration: while in 1990 Denmark, a quarter of respondents agreed or strongly agreed with the statement “A job is alright but what most women really want is a home and children,” in the centrally planned economies we look at here, the rate was around 80 per cent, and 96 per cent in Lithuania. In 2008 Denmark, the proportion fell to 11 per cent, while in the Eastern EU countries it has decreased marginally but remains well above 70 per cent, and in Romania, it increased to 83 per cent. Similarly, the proportion of those who agreed or strongly agreed that “A preschool child is likely to suffer if his or her mother works” was around a third in 1990 Denmark while it was around 90 per cent in Estonia, Lithuania and Poland and between 60 and 80 per cent in the other countries. It decreased to 8.6 per cent in 2008 Denmark and to 35–40 per cent in Bulgaria, the Czech Republic and Slovenia and to around 60–70 per cent in the remaining countries. What do we make of this general comparative overview across a common set of indicators? What key messages emerge from this introductory chapter? One important point to make is certainly that the countries of Eastern Europe we analyze here appear to have had heterogeneous experiences during the transition from a centrally planned to a market economic system. Indeed, there does not appear to have been much in common, apart from the centrally planned economic systems and some high-level indicators in terms of income inequality and human development. These countries have had very diverse experiences in terms of gender equality since the transition from central planning to market economies. This is not surprising once the complexity and multidimensional character of gender labour market outcomes is acknowledged. The very many factors that contribute to gender labour market outcomes rarely move in the same direction and to the same extent in different countries, and, therefore, different experiences should be expected. This fully justifies a detailed focus on each country, the approach we take in the chapters that follow.

Note 1 See, for instance, Council of the European Union (2010). The gender pay gap in the member states of the European Union: quantitative and qualitative indicators. Belgian Presidency Report.

20

Giovanni Razzu

Bibliography Brainerd, E. (2000) Women in transition: changes in gender wage differentials in Eastern Europe and the former Soviet Union. Industrial and Labor Relations Review 54(1): 138–162. Council of the European Union (2010). The gender pay gap in the member states of the European Union: quantitative and qualitative indicators. Belgian Presidency Report. Engels, Frederick (1884) The Origins of the Family, Private Property and the State: in the Light of the Researches of Lewis H. Morgan. Chicago: C. H. Kerr & Company. Fong, M. S. and Paull, G. (1993) Women’s economic status in the restructuring of Eastern Europe, in Democratic Reform and the Position of Women in Transitional Economies, edited by V. Moghadam. Oxford: Clarendon Press, 217–247. Munich, D., Svejnar, J. and Terrell, K. (2005) Is women’s human capital valued more by markets than by planners? Journal of Comparative Economics 33(2): 278–299. Newell, A. and Barry, R. (2000) The gender wage gap in the transition from communism: some empirical evidence. Working Paper No. 305. William Davidson Institute, Ann Arbor, MI. Orazem, P. and Vodopivec, M. (1995) Winners and losers in transition: returns to education, experience, and gender in Slovenia. World Bank Economic Review 9(May): 201–230. Riphahn, R. T., Snower, D. J. and Zimmermann, K. F., eds. (2001) Employment Policy in Transition: The Lessons of German Integration for the Labour Market. Verlag, Heidelberg: Springer. Rutowski, J. (1996) High skills pay off: the changing wage structure during the economic transition in Poland. Economics of Transition 4: 89–112.

2

Bulgaria Vasil Tzanov

Introduction Labour market inequality between men and women is present in many countries irrespective of their economic systems and levels of socio-economic development. Bulgaria, one of the former socialist countries now part of the European Union, has made substantial political, social and economic reforms in the transition from a centrally planned to a market economy. These transformations have had a substantial impact on the functioning of the labour market in the country and on gender equality in the labour market. Gender inequality in Bulgaria has been the subject of a number of studies, from different disciplinary approaches, including economics and sociology, amongst others. The transition period has received particular attention. However, most of these studies focus on various aspects of inequality and cover short periods. Therefore, no studies exist of the overall picture of gender inequality in the country covering the whole period since the collapse of the regime. This chapter discusses the development of gender inequality in the labour market in Bulgaria during the past 35 years. Emphasis is placed on changes in the main indicators of the labour market: economic activity, employment, unemployment and wages; we also look at gender segregation, in both economic sectors and occupations, in the role of education and the possible presence of cohort effects.

The evolution of labour market characteristics of men and women Gender gaps in labour market participation Participation of the working-age population (15–64) in the labour market is essential for determining employment and household income. Data1 clearly show that men have greater labour market activity, regardless of the economic system and the level of economic development. The reasons are complex and derive from a combination of economic, institutional and social factors. Bulgaria, as a country that has made the transition from a planned to a market economy, does not differ from other countries in terms of the dominant role of

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Vasil Tzanov

Table 2.1 Activity rates of the population (15–64 years) in Bulgaria, 1980–2014

Total–(%) Male–(%) Female–(%) Gender activity gap – (percentage points)

1980

1984

1989

1995

2000

2005

2010

2014

69.7 73.6 65.7 7.9

69.1 70.0 68.1 1.9

66.1 66.1 66.2 −0.1

66.4 69.7 63.1 6.6

61.6 67.4 56.1 11.3

62.1 67.0 57.3 9.7

66.5 70.8 62.3 8.5

69.0 72.9 65.0 7.9

Source: Eurostat (2000–2014); Key Indicators of the Labour Market 8th Edition, ILO (1990–1999); author’s own calculations, based on employment data (1980–1989)

men in the labour market. This was evident in the centrally planned economy as well as in the period of transition to a market economy. A thorough study of labour activity2 of men and women in Bulgaria over a long period of time (1965–2001) shows that labour activity of men in the period 1965–1985 fluctuates between 70 and 77 per cent, while the labour activity of women ranges between 59 and 68 per cent but has an underlying increasing trend (BorissovaMarinova, 2011, p. 42). The period after 1990 saw a significant reduction in the labour activity of both males and females. Table 2.1 shows the activity rates3 of working-age women and men, while Figure 2.1 shows the corresponding gender gap for the period 1980–2014. Several specific features characterize the development of economic activity of men and women in Bulgaria over the past 35 years. The past 10 years of the planned economy era, between 1980 and 1989, saw a reduction in the gender gap in the economic activity rate: gender parity was indeed achieved in 1989 when male and female rates both stood at 66 per cent. This resulted from the increased activity of women and a reduction in the activity of men. Male activity decreased by 7.5 percentage points, while that of women rose by 0.5 percentage points. The reasons for the increase in economic activity of women during this period were several, related to the characteristics of a centrally planned economy. Among these is the legal requirement to provide employment to all active citizens, legislation that incentivizes mothers and severely restricts non-labour income sources (Borissova-Marinova, 2011, p. 52). However, the period since 1990 saw increased gender gaps in activity rates. This was particularly the case in the first years of reforms. In the period 1990–2000, the activity of men decreased by about 5.1 percentage points, from 72.5 per cent to 67.4 per cent. Among women, the reduction in labour activity over the same period was even more pronounced, about 15.5 per cent. Obviously, structural reforms during this period affected women more than men’s activity rates. After 2000, when the restructuring of the economy was generally completed, a gradual increase took place in the economic activity of both men and women, but the gender gap remained within 7–10 percentage points in favour of men. Labour activity began to decline for both men and women after the 2008 economic crisis.

Bulgaria

23

Gender gaps in employment The main trend in the series of employment rates during the period 1980–2014 is the reduction in the number of employees. During the entire period, the total number of employees in the economy decreased by more than 21 per cent (about 929,700 people). Panel a in Figure 2.1 shows that this reduction began in the late 1980s. In fact, in the period between 1980 and 1989, employment fell by 2.8 per cent, which was mostly due to an 8.6 per cent decline in male employment. Female employment increased by 3.6 per cent over the same period. This resulted in a significant reduction in the gender gap and, in 1990, gender parity in employment was achieved, as shown in Panel b of Figure 2.1. 2300

Thousands

2100 1900 1700 1500

1100

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

1300

Male

Female

56 54

%

52 50 48

44

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

46

Male

Female

Figure 2.1 Evolution and share of male and female employment in Bulgaria, 1980–2014 Panel a: Evolution of employment; Panel b: Share of male and female employment Source: Eurostat (2000–2014); Key Indicators of the Labour Market 8th Edition, ILO (1990–1999); National Statistical Institute (1980–1989)

24

Vasil Tzanov

The first decade of the transition to a market economy, between 1990 and 2000, saw a pronounced decrease in employment. During this period, the number of employees has decreased by approximately 30 per cent, women being the most affected. Female employment, in fact, decreased by 33 per cent while male employment decreased by almost 28 per cent. This led to an increase in the gender gap. The relative share of women in total employment fell by about four percentage points. The collapse in employment during this period can be explained by the interaction of a complex set of factors, most notably the prolonged crisis of the Bulgarian economy associated with the economic restructuring and increasing trade liberalization, but also by changes in the institutional framework of the country (Tzanov et al., 2012). These factors affected mostly those sectors of the economy with a high concentration of female employment, such as the textile and apparel industry, banking and so forth. The Bulgarian economy entered a period of stable and high economic growth after 2001, which had a significant impact on employment. In the period 2001– 2008, the number of people in employment increased by almost 28 per cent: male employment increased by almost 31 per cent and female employment by almost 25 per cent. The substantial increase in male employment is largely explained by the development of the construction sector, which is dominated by male employment (Nikolova, 2011). The gender employment gap during this period has therefore not changed substantially. Since the latest economic crisis of 2008, the number of people in employment decreased by more than 11 per cent, with the decrease in male employment slightly larger than that in female employment, 12 and 10.4 per cent, respectively. Figure 2.2 shows the changes over time in the gender employment rate gap for men and women aged more than 15. Throughout the 35-year period, the employment

12

70 65

8

%

55

6

50 45

4

40 2

Male

Female

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

35 30

Percentage points

10

60

0

Gender employment gap

Figure 2.2 Employment rates of men and women (age 15+) in Bulgaria, 1980–2014 Source: Eurostat (2000–2014); Key Indicators of the Labour Market 8th Edition, ILO (1990–1999); author’s own calculations, based on employment data (1980–1989)

Bulgaria

25

rate of men remains higher than that of women. Although both the male and female series follow a similar pattern, the extent of the changes is clearly different. Notably, in our series, the male employment rate started to decrease in the early 1980s, and this continued until 2001. Therefore, during the 1980–2001 period, the male employment rate decreased by more than 18 percentage points, reaching its lowest value in 2001 at 45.5 per cent. In the period of economic growth between 2001 and 2008, the male employment rate increased by 10 percentage points and since the latest economic downturn it decreased again to almost 53 per cent. The male employment rate therefore has not yet fully recovered and is about 10 percentage points below its 1980 level. The trajectory of change in female employment is similar. During the 1980–1989 period, the female employment rate remained almost constant at just above 55 per cent. Between 1990 and 1999, it declined by nearly 20 percentage points. Between 2000 and 2008, it reached 45.5 per cent, an increase of 8.7 percentage points. The following points on the gender employment gap and its changes over time can therefore be drawn: a) the latest decade of the planned economy saw a substantial reduction in the gender employment gap excluding the late 1980s; b) the period since the country moved to a market economy has seen an increased gender employment gap; c) gender differences in employment are within the range of 8 and 12 percentage points. Gender gaps in unemployment

-1.5

Male

Female

Unemployment gap

Figure 2.3 Unemployment rates of men and women in Bulgaria, 1991–2014 Source: Statistical yearbook, different editions, NSI

Percentage points

-1.0

5

2013

7 2011

-0.5

2009

0.0

9

2007

0.5

11

2005

1.0

13

2003

1.5

15

2001

17

1999

2.0

1997

2.5

19

1995

3.0

21

1993

23

1991

%

Unemployment in Bulgaria, like in other Eastern European countries, began to emerge after the reforms of the 1990s. Figure 2.3 shows the unemployment rate for men and women and the gender unemployment rate gap between 1991 and

26

Vasil Tzanov

2014: as typical of the unemployment rate series, unemployment rates are more volatile; overall, the gender gap remains small. The first half of the 1990s, the early years of substantial reforms, was characterized by a rapid increase in unemployment: in 1993, the unemployment rate reached 21 per cent. Then, it began to decrease, and in 1998, it dropped to 12.6 per cent. As mentioned, the gender gap remained small during the entire period, but a clear upward trend is discernible. More specifically, between 2001–2008, when unemployment rates decreased, the gender gap dropped to reach almost parity in 2005. Between 2006 and 2008, male unemployment decreased faster than female unemployment, which resulted in an increased gender gap. A plausible explanation of this is the so-called construction boom during those years, which is associated with a predominant increase in male employment (Nikolova, 2011). However, the situation changes again in the years following the latest economic crisis (2009–2014). Overall, the unemployment rate has increased from 5.6 per cent in 2008 to 11.4 per cent in 2014. Male unemployment rose faster than female unemployment, about seven and five percentage points, respectively. As a result, the gender gap in the unemployment rate rose to 2.7 percentage points in 2012 followed by a marginal reduction in 2013–2014. Wage differentials between men and women Studies of the gender pay gap confirm the existence of the pay gap between men and women; they also trace the changes over time and the reasons the pay gap persists (UNICEF, 1999; Women, 2001; Pasi, 2002; Stojanova et al., 2008; Beleva et al., 2009; Nikolova, 2011). Unfortunately, the available statistical information refers to a short period of time, between 1996 and 2013. This means we cannot understand the extent of changes in the gender pay gap before the reforms of the early 1990s. Figure 2.4 shows that, during the period for which we have data, annual gross earnings of men and women increased. For the period 2000–2013, the average annual salary of men and women increased by more than three times and the increase for women was more significant. For the period until 2007, women’s earnings increased at higher rates than men’s earnings, resulting in a narrowing of the gender pay gap,4 while the opposite is true – although to a greatly reduced extent – after 2007. In fact, the gender pay gap decreased from 31.1 per cent in 1996 to 16.6 per cent in 2007, and then increased to 19.7 per cent in 2013. Thus, the ratio of women’s salaries to those of men increased from 68.9 per cent in 1996 to 83.4 per cent in 2007, and dropped to 80.3 per cent in 2013. Therefore, over the whole period for which we have data, the gender gap narrowed by more than 11 percentage points. Table 2.2 shows the differences in pay between men and women by economic activity for a much shorter period of time, covering 2007 to 2013 and using gross hourly earnings: these appear to be significant in almost all sectors of the economy. In fact, it is only in two of them, namely construction and administrative and

Bulgaria

12000

35

10000

30

27

25 %

BGN

8000 6000 20 4000 15

0

10

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

2000

Male

Female

Gender pay gap

Figure 2.4 Annual gross earnings of men and women in Bulgaria, 1996–2013 Source: Statistical yearbook, different editions, NSI; author’s own calculations

support services, where the pay for women is greater than that of men throughout the whole period, although this gap has decreased. Since in these sectors male employment is predominant, higher pay for women is probably related to a higherpaid position that women occupy in organizations. A significant reduction of the gender pay gap of around 10–12 percentage points was registered in the mining and quarrying, water supply, sewerage and waste management sectors. These sectors are characterized by high representation of men, and the reduction of the difference is probably due to the reduction of wages for work performed mainly by men. The largest differences in pay, 20–30 per cent, are found in the manufacturing, financial and insurance, human health and social work and the arts, entertainment and recreation sectors. It is interesting to note that these sectors are also characterized by an increasing gender gap over the period, the most significant in the human health and social work sectors (4.9 percentage points). The health sector is also a female-dominated sector in terms of employment. However, here we see the occupational segregation aspect vividly, between doctors (primary) and service personnel (secondary): the majority of employed women fall in the secondary labour market with low pay. Table 2.2 also shows that the majority of sectors are characterized by a gender gap of between 10 and 20 per cent. The number of sectors in which the differences are less than 10 per cent is very low. In addition, the number of sectors in which the differences are more than 20 per cent is also limited. The general trend in the reduction of the pay gap we have seen in Figure 2.4 is not characteristic of all the sectors. Some of them, in fact, have seen a substantial increase in the pay gap in the past decade or so: noticeable are the health

28

Vasil Tzanov

Table 2.2 Gender pay gap by economic activity, 2007–2013 Economic activity

2007

2008

2009 2010 2011

Total 10.6 11.4 12.5 Mining and quarrying 26.9 23.7 18.8 Manufacturing 24.2 25.0 24.2 Electricity, gas, steam and air 9.2 15.9 17.0 conditioning supply Water supply, sewerage, waste 14.5 12.2 8.2 management and remediation activities Construction −15.6 −10.3 −4.3 Wholesale and retail trade; repair 10.7 14.4 14.5 of motor vehicles and motorcycles Transportation and storage 14 15.3 12.6 Accommodation and food service 8.0 11.2 9.7 activities Information and communication 14 13.7 19.7 Financial and insurance activities 24.7 23.6 23.8 Real estate activities 2.2 7.1 3.4 Professional, scientific and −9.2 11.8 11.7 technical activities Administrative and support service −15.3 −13.0 −4.2 activities Public administration and defence; 4.9 10.8 13.0 compulsory social security Education 13.4 11.9 14.5 Human health and social work 26.0 30.2 30.5 activities Arts, entertainment and recreation 23.1 20.9 16.5 Other service activities −3.5 −3.7 0.8

2012

2013

12.3 15.9 24.1 15.7

12.2 15.5 24.9 19.6

14 19.4 25.7 12.9

12.6 14.4 25.8 9.4

8.2

2.8

2.6

2.6

−4.6 11.8

−8.3 9.5

−6.6 12.1

−9.3 11.6

16.3 9.6

15.5 12.2

14.4 14.6

11.3 10.5

13.8 24.5 −0.2 8.4

8.3 21.4 −4.2 6.8

12.2 26.7 1.1 13.5

14.3 26.6 −1.1 15.3

−7.5

−14.8 −13.1 −11.8

12.5

10.3

10.9

6.2

13.2 27.2

11.1 26.1

13.4 30.8

11.7 30.9

18.3 −0.8

22.1 2.6

26.2 −6.0

27.0 −9.6

Source: National Statistical Institute Note: The gender pay gap in unadjusted form is given as the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees.

and social work sectors again and, above all, professional, scientific and technical activities. However, the overall reduction in the gender pay gap is a result of a number of factors. Two factors can be distinguished: one is the managerial positions women hold and the other is the growth of the minimum wage (Beleva et al., 2009). In the Bulgarian economy, an increasing number of women occupy managerial positions in organizations, which are associated with higher wages. The impact of the minimum wage is based on the fact that the percentage of

Bulgaria

29

women with a minimum wage is higher than that of men.5 Increasing the minimum wage affects more women and therefore, with no other changes to the distribution of wages, this contributes to reducing the pay gap between them.

Employment patterns of men and women Gender gaps in employment by economic sector Table 2.3 shows that male employment dominates in some sectors of the economy, while in others women are overrepresented. This gender segmentation of the economic sectors has not significantly changed over the past 35 years covering the period before and after the transition to a market economy. The employment of men is concentrated in a few economic sectors where the proportion of men is as high as 90 per cent and not less than 75 per cent: in some of them, such as construction, it has also been increasing. Despite the high share of male employment, these sectors provide work for a small proportion of all employed men. While in 1980, the construction and transport sectors employed around 23 per cent of all working men, in 1988, their share rose slightly to 23.4 per cent. These two sectors employed 5.4 per cent of employed women in 1980 and 6.2 per cent in 1988. In the period 2000–2014, the share of employed men in the four maledominated sectors increased from 24.4 to 26.1 per cent, and that of women from 5 to 5.7 per cent. The extent of dominance in the female-dominated sectors is less pronounced than in the male-dominated sectors. Moreover, in the wholesale and retail trade sector, the concentration of employed women has decreased by 8.5 percentage points so that, in 2014, the share of men and women was almost equal. In the education and human health and social work sectors, instead, over the past 15 years, the share of women employed has increased to nearly 80 per cent. Unlike the male-dominated sectors, the female-dominated sectors tend to employ a significant

Table 2.3 Sectors with male and female overrepresentation, 1980–2014 Sector Male-dominated sectors Construction Transport Mining and quarrying Electricity, gas, water supply Female-dominated sectors Wholesale and retail trade Education Human health and social work activities Financial and insurance activities

1980 1985 1988 2000 2005 2010 2014 82.2 82.7 n.a. n.a.

81.4 80.4 n.a. n.a.

79.5 78.4 n.a. n.a.

86.0 72.7 81.2 72.6

92.0 73.8 84.5 74.8

91.7 76.9 83.0 78.5

90.2 79.1 82.6 75.9

62.7 74.3 74.3 77.8

64.1 75.5 73.6 80.1

65.1 75.8 73.8 82.3

50.3 80.3 77.3 66.3

50.9 79.2 77.3 62.2

54.8 81.9 80.6 64.1

54.2 80.8 79.1 68.3

Source: Statistical yearbook, different editions, NSI

30

Vasil Tzanov

share of all employed women. In 1980, the four female-dominated sectors employed 28 per cent of all employed women, while in 1988, their share reached 31 per cent. It increased to 38.9 per cent in 2000 and 43 per cent in 2014. Moreover, the female-dominated sectors provide employment to men as well. In fact, about 21 per cent of working-age men are employed in sectors dominated by women. The data on the employment of men and women by economic sectors therefore clearly show the presence of sectoral gender segregation in the labour market. An in-depth study of the European Union on issues of gender segregation shows that this is a feature of all countries of the European Union (European Commission, 2009). According to this study, Bulgaria belonged to the countries with a medium level of sectoral segregation in 2007. This group included Poland, the Czech Republic, Hungary and Estonia. Countries with high levels of sectoral segregation are Estonia, Lithuania, Latvia and Slovakia. Of the former socialist countries, only Romania is in the group with low gender segregation in economic sectors. Figure 2.5 reports the changes in the Duncan and Duncan (ID) index of segregation (Duncan and Duncan, 1955) for Bulgaria over the 1980–2014 period.6 The estimates show that in the period before the reforms up to 1990, gender segregation remained stable at 20 per cent despite the increase in female employment and the reduction in male employment we discussed in earlier sections. It is during the transition to a market economy that the level of segregation increases. In 2000, the index of sectoral segregation increased by four percentage points compared to the 1980s. After 2000, gender sectoral segregation increased again, and in 2010, it reached 29.5 per cent. The level in 2014 was slightly reduced to 28.3 per cent. Overall, during 1980–2014, gender sectoral segregation increased by 8.5 percentage points. Besides the traditional reasons for sectoral gender segregation, economic factors can explain this significant growth after 2000. In the period after 2000, the Bulgarian economy experienced significant growth and increased

35 30 25 %

20 15 10 5 0 1980

1985

1988

2000

2005

2010

Figure 2.5 Gender sectoral segregation index in Bulgaria, 1980–2014 Source: Author’s own calculations

2014

Bulgaria

31

employment. After 2005, the growth in the construction sector has been especially pronounced, and this has been a male-dominated sector. Data show that, in 2005, the construction sector employed about 11 per cent of all employed men and about 1 per cent of working women: in 2010, these rates were 15.3 and 1.5 per cent for men and women, respectively. Obviously, differences in employment between men and women in the construction sector had a significant impact on the increase in the segregation index. Occupational gender segregation Table 2.4 shows the changes, between 1980 and 2014, in the share of male and female employment in various occupations and the computed gender occupational segregation index: the top panel reports changes for the 1980–1990 decade and the bottom panel for the 2000–2014 period. Lack of data means we cannot assess changes over the very important period of 1990 when the transition to a market economy took place. In terms of changes over the first period, the data show a pattern of increasing equality. The changes regarded occupations dominated by men as well as those dominated by women. In the 1980s, the most significant changes occurred in the ‘managers’ and ‘support workers’ occupations. The former was a male-dominated while the latter was a female-dominated occupation. The share of women in management positions increased from one-fifth to one-third during the 10 years up to 1990. Even more significant is the change in the ‘support workers’ occupation, which includes cleaners, maids, guards and other staff. From a typical female occupation in 1980, it is transformed into a mixed one in which women make up slightly more than half of employees (57.5 per cent). As a result of these changes the extent of occupational gender segregation decreases. It is difficult to tell what changes occurred in the occupational segregation during the 1990s, but the extent of gender segregation in the latter period (2000 to 2014) suggests a pattern towards increased gender occupational segregation. However, since 2000, occupational gender segregation has decreased by 1.5 percentage points. This is due to the convergence in almost all occupations. The proportion of women in occupations dominated by men has been increasing. For example, in the ‘managers’ category, the proportion of employed women increased by 4.4 percentage points, while in the ‘craft and related trades workers’ category it increased by 0.7 percentage points. In other occupational categories, the share of men and women changed to varying degrees. In typically femaledominated occupations, such as clerical support and service and sales occupations, the proportion of women decreased, while in the ‘professionals’ occupation, it reduced only marginally. In comparison with other Eastern European countries, Bulgaria appears to be among the countries with the highest occupational gender segregation (European Commission, 2009, pp. 32–33). This group includes six Eastern European countries: Estonia, Lithuania, Latvia, Hungary, Slovakia and Bulgaria. The Czech Republic is located next to the group with the highest segregation, while Romania is in the group with the lowest level.

1985

1990

2000

2010

2014

80.5 36.2 57.1 27.0 16.5

19.5 63.8 42.9 73.0

76.8 33.8 56.8 27.3 18.0

23.2 66.2 43.2 72.7

67.8 30.5 54.5 42.5 15.7

32.2 69.5 45.5 57.5

55.8 74.8 60.7 41.6 25.5 26.4 44.4 12.0

31.5 44.2 25.3 39.3 58.4 74.5 73.6 55.6 86.9

32.1 46.4 23.8 39.0 56.5 74.3 70.0 56.7 89.9

53.6 76.2 61.0 43.5 25.7 30.0 43.3 10.1

66.0 34.1 31.9 68.1

67.7 32.3 33.6 66.4

30.6 54.3 28.5 40.6 63.1 73.6 75.1 59.6 86.4

45.7 71.5 59.4 36.9 26.4 24.9 40.4 13.6

63.3 36.7 32.3 67.7

Male Female Male Female Male Female Male Female Male Female Male Female

1980

Source: Statistical yearbook; LFS; NSI; author’s own calculations

Managers Professionals Workers Support workers Occupational segregation index (ID) Technicians and associate professionals Clerical support workers Service and sales workers Skilled agricultural, forestry and fishery workers Craft and related trades workers Plant and machine operators and assemblers Elementary occupations Other

Occupations

Table 2.4 Share of men and women by occupations and occupational segregation index, 1980–2014

Bulgaria

33

Employment differences by education In recent decades, the educational level of the Bulgarian population has increased significantly. Studies show that this process resulted in a transition from employment mostly dominated by persons with low and medium educational levels (86.3 per cent) to employment with a predominant participation of workers with secondary and higher education (89 per cent) (Tzanov et al., 2014). Table 2.5 shows the changes over time in the share of male and female employees by educational qualification. The most significant change is observed in the profile of employees with low education (lower secondary, primary or lower). Within a period of 35 years, the number of employees with low education decreased by about 1.9 million people, which represents a reduction of their share in total employment by nearly 36 percentage points. The most pronounced changes happened between 1985 and 2000, the years before and immediately after the reforms. During this period, the share of workers with low education in total employment fell from nearly half to one-fifth. Among those with low educational qualifications, men occupied a larger share, and this has decreased more rapidly than that of women over time. Figure 2.6 shows that the gender gap in the employment of low-educated persons decreased from 4.8 percentage points in 1985 to 2.2 percentage points in 2014. The relative share of workers with upper secondary education has increased over the period under consideration, although the total number of employees with that level of education increased from 1.5 to 1.8 million people. Figure 2.6 also shows that the gender gap has increased from 0.2 percentage points in 1985 to 9.3 percentage points in 2014. A similar trend, but with the opposite sign, can be observed for employees with higher education. During the same period, their number increased by more than 43 per cent, leading to an increase in their share in total employment by nearly 19 percentage points. Among graduates, employed women predominated in number and proportion. During the period, the number of employed women with higher education increased by 66 per cent, while that of men by slightly more than 19 per cent. Naturally, this leads to an increase in the gender gap, from -0.4 percentage points in 1985 to -6 percentage points in 2014. Table 2.5 Share of male and female employment by level of education, 1985–2014

Total Low education Male Female Secondary education Male Female High education Male Female

1985

1992

2000

2005

2010

2014

100.0 47.5 26.1 21.4 38.8 19.5 19.3 13.8 6.7 7.1

100.0 30.9 17.1 13.9 49.7 26.1 23.6 19.4 8.8 10.6

100.0 21.5 12.9 8.6 55.7 30.7 25.0 22.8 9.6 13.2

100.0 17.5 10.4 7.1 56.8 32.4 24.5 25.7 10.4 15.2

100.0 12.4 7.2 5.2 60.5 34.7 25.9 27.1 10.6 16.4

100.0 11.0 6.6 4.4 57.4 33.3 24.0 31.6 12.8 18.8

Source: Author’s own calculations using data from Eurostat and Borissova-Marinova (2011, p. 193)

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12 10 Percentage points

8 6 4 2 0 -2 -4 -6 -8 1985

1992

Low education

2000

2005

Secondary education

2010

2014

High education

Figure 2.6 Gender educational gaps in Bulgaria, 1985–2014 Source: Author’s own calculations

This leads to the following main conclusions: a) there has been a significant change over time in the educational qualifications of employed persons, with a substantial increase of employment of people with higher educational qualifications; b) a significant increase in the gender gap in the educational qualification of employees; c) the changes begun before, and continued at an accelerated pace after, the transition to a market economy. Cohort gender disparities The employment distribution of men and women in Bulgaria by age does not appear to be significantly different from that in other countries. In fact, Bulgaria experiences lower levels of employment of younger generations and elders and higher employment in the middle ages. Table 2.6 shows the employment rates of men and women by age groups, between 1985 and 2013. The differences in the periods before and immediately after the transition to a market economy appear to be more pronounced. Employment in all age groups was high during the totalitarian regime. This was a result of the ongoing policy at that time which aimed to provide work for everyone regardless of the needs of the country. However, gender gaps are evident, most significantly for the younger and elderly age groups. It is hard to explain the higher female employment rate in the 15–24 age group, but it is likely that this is due to the mandatory 2 years of military service for men after completing postsecondary education or the age of 18. Even more striking is the difference in the group of adults (55–64 years). This is possibly due to the early retirement and lower activity of women after retirement (Borissova-Marinova, 2011).

Bulgaria

35

Table 2.6 Employment rates by age and sex, 1985–2013 Age group

Male

15–24 25–34 35–44 45–54 55–64 65+

Female

1985

1995

2005

2013

1985

1995

2005

2013

48.4 96.9 98.1 94.5 64.6 15.0

35.1 88.3 91.7 85.6 35.8 4.4

23.9 75.6 78.1 73.3 45.5 4.0

24.0 71.7 78.6 74.3 51.9 5.1

64.0 90.9 96.8 90.8 24.9 2.5

33.8 78.2 89.3 82.1 8.0 1.1

19.3 63.0 76.1 71.0 25.5 1.4

18.4 61.3 76.8 75.8 43.4 2.0

Source: Author’s own calculations for 1985 using data from Borissova-Marinova (2011, pp. 197–198); ILO database; Eurostat

25

Percentage points

20 15 10 5 0 15–24

25–34

35–44

45–54

55–64

65+

Figure 2.7 Average employment gap by age for the period 1995–2013 Source: Author’s own calculations

The years during the transition have seen a significant reduction in employment rates, but the age pattern does not appear to change much. The employment rate of young people, aged 15–24, decreased and, in 2013, was 24 per cent for men and just above 18 per cent for women: it was 48 and 64 per cent, respectively, in 1985. Figure 2.7 shows the average (between 1995 and 2013) gender employment gap by age group. Two age groups stand out in the labour market with significant gender differences in employment. These are the groups of 25–34-year-olds and 55–64-year-olds. The first group consists of young people who are at the beginning of their careers and at the same time start to combine work with family responsibilities. This is the period of time in most women’s life when motherhood severely impacts their employment prospects: indeed, motherhood and childrearing appear to be the main reasons for the low employment of women in this age group. The employment rate of the 55–64-year-olds also decreased

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substantially over time, as seen in Table 2.6, but there is an interesting dynamic as well as a gender dimension. In fact, the reduction in their employment rate was indeed important in the initial transitional phase, while employment rates increased again in the period since the late 1990s. Although for men this increase has not been sufficient to recover the initial loss, the female employment rate for this age group increased to 43.4 per cent in 2013, almost double the rate in 1985 (25 per cent) and more than five times the rate in 1995 (8 per cent). This increase, however, still leaves a substantial gender gap. As this age group includes older workers, the gap might well be a result of the early retirement of women, low labour activity and job search, although as we have seen, these have increased over the past decade. In summary, these data suggest that in Bulgaria there are three cohort groups with unfavourable employment prospects. Young people aged 15–24 have very limited participation in the labour market. In this group, gender gaps are less important. Women 25–34 years old face restricted employment opportunities, mostly due to the impact of motherhood and the difficulties of combining work with family responsibilities. Men 55–64 years old have been hugely affected during the first years of transition, and their employment rate has not fully recovered since then.

Issues of gender inequality in Bulgaria Reconciliation of work and family life The problem in reconciling paid and unpaid work is one of the main causes of inequality between men and women in the labour market in Bulgaria: this is linked to the place the system of values gives to family. Many studies show that women bear the main brunt of work in the family (Kirova, 2007; Mihova et al., 2007; Stojanova and Kirova, 2008; Nikolova, 2011). Household work (including childcare) puts women at a disadvantage, whether working or not. Stojanova and Kirova (2008), based on data on the time distribution within an overnight shift (24 hours) for the period 1976–2001, found that the share of paid employment of men and women tends to decrease as gender differences in employment decrease (from 4.1 percentage points in 1976 to 2.7 percentage points in 2001); gender differences in unpaid household work remained despite the reduction in its share of total time; leisure time for men and women increased, but the gender difference increased significantly (from 15 minutes in 1976 to one hour and seven minutes in 2001). Therefore, they found that the total working time of women exceeded that of men as a result of a much higher share of time spent on various types of unpaid activity, such as taking care of the household and the family, and producing goods for family consumption (Stojanova and Kirova, 2008). Sociological surveys confirm these findings. For instance, a 2003 poll found that fathers spent half the time with their children as mothers (Mihova et al., 2007, pp. 164–171; Nikolova, 2011, p. 78). Another study found that about 28 per cent of female respondents spent between 20–30 hours a week with children and 30 per cent of them more than 30 (Aleksandrova, 2006).

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37

Although these studies suggest the occurrence of positive changes, such as the increase of leisure time at the expense of time spent on paid and unpaid work, they show that gender inequality in unpaid family work has persisted. Women spend twice as much time on the household as men. Moreover, gender differences in the combination of paid and unpaid work appear to be widening. While in 1976, the time for paid work of women constituted about one-third of the total paid and unpaid time, in 2001, this share dropped to one-fifth (Stojanova and Kirova, 2008, p. 38). However, contrary to expectations, polls do not suggest that women’s unpaid work in the family is an obstacle to their career development. For example, a striking 96 per cent of men and 91 per cent of women surveyed indicated that domestic work is not interfering in their careers (Nikolova, 2011, p. 82). It is hard to explain this response rate from women without relying on the deeply structured stereotypes and attitudes towards gender and work and family roles. Most women appear to accept as an obligation the caring for dependent family members, whether children, elderly parents or sick persons. Reconciling paid work with domestic duties largely depends on the value placed on both types of work. Traditional attitudes of Bulgarians tend to put the family at the centre of the values system, but the need to earn an income does not disregard the attitudes towards paid work and career development of the individual. Data from the ‘Hours, working conditions, demographic behaviour’ survey unequivocally confirm this hypothesis. Although more than half of the respondents (57 per cent) placed professional life and family as equally important, a third (38.9 per cent) of them put in first place the family, and only 4 per cent considered work and career the most important (Mihova et al., 2007, p. 199). While no significant gender differences (less than one percentage point) appeared in those who considered family and work equally important, among those who separately considered family and work most important, the gender differences were considerable: 5 per cent more women than men considered family a top priority, while 4.2 per cent more men than women considered work the most important. Of course, these responses depend on many factors, including the age, education and employment status of respondents. Mihova and colleagues (2007) show that the importance placed on work and career development decreases with age while that placed on family increases significantly. The educational qualification of the respondents is also a substantial factor. People with lower educational qualifications place more importance on the family, while those with higher and secondary education tend to consider work and family equally important. Overall, increased educational qualifications are associated with less importance placed on the role of the family and increased preferences towards reconciliation of work and family. Solutions to the reconciliation of paid and unpaid work issue, especially for women, depend on the creation of favourable working hours and the improvement of the system of childcare provision. Labour legislation in Bulgaria regulates both the transition from full- to part-time work and the provision of flexible working hours. Data show that the proportion of part-time employees is extremely low in Bulgaria: 2.7 per cent in 2013. More than half of part-time employees (57.3 per cent)

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are women. Switching from full-time to part-time work is a difficult process in the country, as 55.8 per cent of part-time employees choose part-time work under pressure. The main reason appears to be low pay associated with part-time work, especially with women: moving from full-time to part-time will result in a reduction of household income. Polls also confirmed that Bulgarians do not like to move from full- to part-time work. Only 3.4 per cent of respondents said they were willing to switch from full- to part-time work, 4.1 per cent for women and 2.7 per cent for men (Mihova et al., 2007). Moreover, about 12 per cent of men and women are willing to work full-time and overtime for payment. Obviously, the low wages in the country severely limit the opportunities to achieve a greater reconciliation between work and family. Providing flexible working time is not popular with employers. According to a study by Aleksandrova (2006), organizations, regardless of their type and property, do not offer flexible working time. About 66.7 per cent of women and 94.1 per cent of men indicated that the organizations in which they work do not apply flexible working hours. Despite this important barrier, the potential for implementation appear more realistic than those associated with switching from full-time to part-time work. To help families raising small children, Bulgaria has developed a system of social services for children in preschool. This was present even under the socialist regime. The system includes two types of public establishments: nurseries for children under 3 years of age and kindergartens for children from 3 to 6 years. Under socialism, it was an essential tool to assist families in raising children and was widespread throughout the country. Changes in social policy during the years of transition strongly limited the provision of these services. The number of kindergartens significantly decreased while the quality of services declined. In 2014–2015, for instance, the number of kindergartens was 1,991, while in 2000–2001, it was 3,249. Migration of the population from rural to urban cities resulted in greater pressure on and an increased shortage of childcare facilities. There is clearly a need to extend the scope of kindergartens in large cities and to improve the quality of services in them. Gender wage segmentation and income dependency Bulgaria is among the EU countries with low wage inequality between men and women. The gender pay gap in Bulgaria is smaller than the average for EU-27 (16.4 per cent) countries. However, a study of the labour market segmentation in Bulgaria, based on data from EU-SILC for the period 2007–2011, shows that women are overrepresented in the low-income groups, below the median income, while men predominate in the higher income groups (Beleva et al., 2014). For example, in 2010, about 57.3 per cent of working women received earnings below the median income. Data on gender segmentation in low-, medium- and high-income groups7 show that nearly one-third of women earn low incomes, while men with low incomes are about one-quarter. In the medium-income group, women also have greater representation: 45–48 per cent of medium earners are women, and 40–44 per

Bulgaria

39

cent are men. High-income groups are dominated by men, their share varying between 34–37 per cent, compared to 20–24 per cent for women. The presence of women at the extremes of the income distribution is growing steadily. The proportion of women in the group with the lowest incomes (onethird of the median gross income) increased by 8.7 per cent in 2007 to 11.1 per cent in 2010, and those in the highest income group (more than five-thirds of the median gross income) from 10.1 per cent to 13.7 per cent in 2010. Low income is the main determinant of the economic dependence of women in the family. According to feminist theory, this phenomenon is seen as a primary mechanism for maintaining the subordinate position of women in society (Hartmann, 1976; Delphy, 1984; Brines, 1994). Position of authority in family relations is in fact determined on the basis of the contributions of women to the family budget (Sorensen and McLanahan, 1987). There is no direct analysis of the prevalence and degree of economic dependence of women on men in the country, but some studies indirectly touch on this issue (Mihova et al, 2007; Modeva, 2007; Nikolova, 2011). According to Nikolova, the share of economically dependent women in Bulgaria is high. This dependence is widespread among women on maternity leave, mothers of many children, housewives, women not working for family reasons, long-term unemployed women, low-paid women and students. The author states that, for many of them, the relationship is temporary, while for another large part it is the result of free choice (Nikolova, 2011, p. 60). Confirmation of the financial dependence of women is given by a monitoring survey of large families in Bulgaria, conducted in 2005–2006 (Modeva, 2007). About 25 per cent of women responded that they do not get money from men to satisfy their personal needs (clothing, cosmetics, hobbies, etc.). Gender segregation As already noted, the Bulgarian labour market is characterized by a high degree of gender segregation (both occupational and sectoral). In addition, Bulgaria does not appear to take measures for its reduction. Numerous studies of labour market gender segregation in other countries find it is related to comparative biological advantages, under-investment in human capital (schooling, training), differential income roles, preferences and prejudices, socialization and stereotypes, entry barriers and organizational practice. Recent research has focused on four sets of factors: choice of subject of study, stereotypes, the demand for shorter or flexible work hours because of the unequal care burden and differential income roles and covert barriers and biases in organizational practices, including collective bargaining procedures (European Commission, 2009). In Bulgaria, not all of these factors are important in determining the high levels of segregation. In fact, the choice of subject studied in higher education does not show major gender differences. Men tend to have greater representation in technical sciences, while women more commonly study in the humanities, medicine and the economic and legal sciences. However, data from the Bulgarian Industrial Association show that one third of graduates in the country do not

40

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work in their area of study, and this trend is not new. The reason for this is that companies seek employees with skills that students do not acquire in universities. Stereotypes influence the choice of workplace. Social attitudes are engrained for ‘male’ and ‘female’ jobs, and this determines the choice of work. It is hard to motivate a man to start a job that society has considered feminine. Gender segregation in the country is directly related to income inequality and the evaluation of jobs. The majority of female-dominated sectors and occupations are characterized by high income inequality. For example, in the financial, educational and health sectors the pay inequality is high and the occupations of schoolteachers, cleaners, sales assistants and supermarket cashiers are low. These differences in pay support the thesis that in Bulgaria, female-dominated jobs are undervalued. Moreover, the majority of these jobs do not offer career development. Analysis of occupational gender segregation shows that despite successes, asymmetry still exists in favour of men in career development and access to managerial positions. The reasons are complex and are probably related to poor career opportunities in most female-dominated occupations, mechanisms and criteria for selection of managers in organizations and the lack of a working network among women to protect their interests (European Commission, 2009). Gender equality policies The gender equality policies the totalitarian regime applied are inapplicable under the conditions of democracy and the market economy. This circumstance demanded the elaboration of a new gender equality policy that would correspond to the new realities and international engagements. The new policy approach is based on the following principles: equal opportunities of men and women in all spheres of public, economic and political life; equal access of men and women to resources; equal treatment of men and women and non-admission of all types of discrimination and violence; gender balance in decision-making positions. The policy of equality between men and women integrates activities of the executive authority at all levels. It is carried out by the combination of the mainstreaming approach with interim targeting measures that require an effective institutional mechanism. For this purpose, the government, in 2004, established the National Council of Equality of Men and Women at the Council of Ministers, which coordinates the activities at the national level. The concrete policies concerning gender equality in the labour market place particular attention on measures to encourage employers to hire unemployed mothers with 3–5-year-old children and single parents with small children (younger than 3 years old). Another set of policies focus towards stimulation of men to substitute mothers for childcare and incentives for a better combination of time between work and household engagement. Some national plans contain stimuli for men to stay in work in the feminized sectors (predominately as teachers).

Bulgaria

41

Conclusions This chapter has studied the changes in gender inequality in the labour market in Bulgaria over the past three decades. The main findings are as follows. First, gender inequality has increased in most of the key labour market outcomes we have looked at. Overall, the transition to a market economy appears to have impacted women more unfavourably than men. The labour market prospects of women overall has deteriorated compared to the period before the reforms. Gender gaps in activity, employment and unemployment all deteriorated during this period, although to a differing degree for different subgroups of the population. Second, over the past 20 years, the gender pay gap has narrowed. The largest pay gap remains in female-dominated sectors. However, despite this positive trend, women are more likely to be present in the lower- and middle-income groups, while men predominate in the higher-income groups. Third, the Bulgarian labour market is characterized by a high degree of gender segregation (sectoral and occupational), which increased during the period under analysis. This is also the result of maintaining the stereotypes of division of labour between ‘male’ and ‘female’ sectors and occupations. Fourth, the educational qualifications of employed men and women underwent some important changes which continued at an accelerated pace in the transition period. In general, the educational qualification of employees has increased, particularly in the case of women. Fifth, three age groups can be identified as having diminished labour market prospects: women in their prime working age between 25 and 34 are severely impacted by motherhood; men aged 55–64 have seen their employment prospects substantially reduced in the first years of the transition, and the recovery has not yet been accomplished. Gender differences in the Bulgarian labour market highlight three important issues: the ability to reconcile paid and unpaid work for women; low pay for women and the high level of gender segregation. Solving these problems requires intervention of the state through the implementation of adequate policies to provide flexible employment, overcoming stereotypes of the division of ‘male’ and ‘female’ jobs and ensuring appropriate support for raising children.

Notes 1 Based on the Labor Force Survey (LFS). 2 Calculated as a percentage of the number of active persons aged 15 and over to the number of the population aged 15 and over. 3 Here were used different definitions of the labour force and sources of information for the separate periods: in the period of the planned economy (1980–1989), for the labour force the number of employees was accepted, since at that time there was no notion of ‘unemployed’. In the period 1990–2014, the labour force includes employed and unemployed persons. Data for the period 1990–1999 are from the ILO database and for the period 2000–2014 from the LFS.

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4 Calculated as the difference between average gross earnings of male paid employees and of female paid employees as a percentage of average gross earnings of male paid employees. 5 In 2002, 1.3 per cent of women received minimum wage, against 0.6 per cent for men. 6 For the period 1980–1988, the national classification contained 14 sectors, while for the period 2000–2014, we used data from the LFS on level NACE2 with relevant modifications. 7 Income groups are defined as follows: low incomes – below two-thirds of the median income; medium incomes – between two-thirds and four-thirds of the median income; high incomes – above four-thirds of the median income.

Bibliography Aleksandrova, M. (2006) Gender dimensions of the ‘work–family’ conflict (a survey of managers in Bulgaria), in Sex and Transition, Presentation at the Gender and Transition Conference. Centre of Women’s Studies and Policies. Sofia, Bulgaria. Beleva, I. (2008) Gender segregation in the labour market: root causes, implications and policy responses in Bulgaria, in Sex and Transition, Presentation at the Gender and Transition Conference. Centre of Women’s Studies and Policies. Sofia, Bulgaria. Beleva, I., V. Tzanov and D. Dimitrova (2014) Segmentation of the Labour Market in Bulgaria, Labour Market Segmentation of Employment and Income in Bulgaria. Academic Publishing House Marin Drinov. Economic Research Institute. Bulgarian Academy of Sciences (in Bulgarian). Beleva, I., V. Tzanov, and D. Velkova (2009) Labour Conditions and Quality of Employment in Bulgaria: Trends and Interactions. Sofia: Avangard Prima Publishing. Borissova-Marinova, K. (2011) Differences by Sex in Economic Activity Levels in Bulgaria. Labour Market Segmentation of Employment and Income in Bulgaria. Academic Publishing House Marin Drinov. Economic Research Institute. Bulgarian Academy of Sciences (in Bulgarian). Brines, J. (1994) Economic Dependency, Gender and the Division of Labour at Home. American Journal of Sociology, 100 (3). Delphy, C. (1984) Close to Home: A Materialist Analysis of Women’s Oppression. Amherst: University of Massachusetts Press. Duncan, O. D. and B. Duncan (1955) A Methodological Analysis of Segregation Indexes. American Sociological Review, 20 (2): 210–217. European Commission (2009) Gender Segregation in the Labour Market: Root Causes, Implications and Policy Responses in EU. UC, Directorate-General for Employment, Social Affairs and Equal Opportunities, Unit G1. Hartmann, H. (1976) Capitalism, Patriarchy and Job Segregation by Sex. Signs, 1 (3): 137–169. Kirova, A. (2007) Unequal position of women in different spheres of unpaid work at home, in Sex and Transition, Presentation at the Gender and Transition Conference. Centre of Women’s Studies and Policies. Sofia, Bulgaria. Loufti, M. F. (2001) Women, Gender and Work. International Labour Organization: Geneva. Mihova, G., D. Kergoat, M. Nikolova and D. Donev (2007) Working Hours, Working Conditions, Demographic Behaviours. Academic Publishing House Marin Drinov. Economic Reseach Institute. Bulgarian Academy of Sciences (in Bulgarian). Modeva, R. (2007) Gender inequality problems in families with more children, in Sex and Transition, Presentation at the Gender and Transition Conference. Centre of Women’s Studies and Policies. Sofia, Bulgaria.

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Nikolova, M. (2011) Socio-demographic Consequences from the Status of Women on the Labour Market in Bulgaria at the Beginning of the 21st Century. Marin Drinov. Economic Research Institute. Bulgarian Academy of Sciences (in Bulgarian). Pasi, P. (2002) Gender in Transition. Washington, DC: World Bank, May 21. Sorensen, A. and S. McLanahan (1987) Married Women’s Economic Dependency, 1940– 1980. American Journal of Sociology, 93 (3): 659–687. Stojanova, K. and A. Kirova (2008) Gender Inequalities in Paid and Unpaid Work in Bulgaria. Marin Drinov. Economic Reseach Institute. Bulgarian Academy of Sciences (in Bulgarian). Tzanov, V., P. Ivanova, S. Pantaleeva and B. Bogdanov (2014) Bulgaria: rising inequality in the period of transition and restrictive income policy, in Changing Inequalities & Societal Impacts in Rich Countries – Thirty Countries’ Experiences, Edited by Brian Nolan, Wiemer Salverda, Daniele Checchi, Ive Marx, Abigail McKnight, István György Tóth, and Herman G. van de Werfhorst. Oxford: Oxford University Press. Tzanov, V., G. Shopov, I. Beleva, J. Hristoskov and P. Lukanova (2012) Labour Market and Social Protection in the Context of Bulgarian Economic Development (1990–2011). Marin Drinov. Economic Research Institute. Bulgarian Academy of Sciences (in Bulgarian). UNICEF (1999) Women in Transition: Regional Monitoring Report, No 6, UNICEF.

3

Czech Republic1 Lenka Filipova and Mariola Pytliková

Introduction The two decades since the fall of the Iron Curtain in Czechoslovakia have been characterized by two substantial and, to some extent, turbulent events: the economic transition from a centrally planned to a market economy firstly and entry to the European Union secondly. Moreover, this period has seen not just improved economic conditions and opportunities and political, civic and economic freedoms, including the freedom of movement, but also an increase in inequality. Changes in gender inequalities in Czech society over this period are the focus of this chapter. Full employment has been a direct aim of centrally planned economic systems, in which wages and prices were centrally set and enterprises were funded to provide the needed jobs. The communist era in Czechoslovakia was thus characterized by a high rate of economic activity of the working-age population and a proclaimed equality amongst workers, which included gender equality. The low labour productivity was compensated for by the higher number of employed people. In 1980, according to the Population Census, 82.2 per cent of women and 92.7 per cent of men aged 15–59 were economically active and unemployment did not exist (CZSO, 2001). Women in particular experienced increased employment, educational levels and overall status in society. On the other hand, women were scarcely employed in top managerial, political and financial occupations. The gender model in socialist Czechoslovakia was also characterized by the early introduction of state-financed parental leave schemes, and by a dense network of publicly financed childcare facilities and kindergartens (Čermáková, 1997). Thus, the emancipation of women was very much sought through labour planning in contrast to the emancipation through feminist movements more typical of Western countries. However, despite the fact that Czechoslovakia was the country with the lowest overall earnings inequality in the world, the gender wage gap was quite high in comparison to other Central and Eastern European countries, and comparable to that present in Western economies. For instance, data from the 1988 Microcensus Survey show that, only 1 year prior to the fall of the Iron Curtain and the beginning of the transition, the unadjusted gender wage gap was equal to 31 per cent. More recent data from Eurostat confirms that the gender gap persists in the Czech Republic, which has in fact one of the highest gender wage gaps among the Central and Eastern European (CEE)

Czech Republic  45 countries (Mysíková, 2012), and much higher than that prevalent in most countries of Western Europe. The lower wages of women during communist times were usually attributed to the higher work performance of men and their willingness to work overtime. The latter was not supposed to be available to women as a consequence of their family duties (Čermáková, 1997). Another factor contributing to the gender wage gap has been the segregation of women into lower-paid occupations and sectors (Čermáková, 1997). The data in our chapter show that although the gender pay gap has narrowed over time as a result of different factors, gender segregation in work has instead increased compared to the pre-1989 period: women are overrepresented in the public sector, in particular in education, health services and social work, whereas men are overrepresented in managerial positions, among legislators and in industries such as mining, electricity, gas and steam supply, construction and transport. Overall, the gender approach during the period of centrally planned economy was based on helping women to enter the labour market and reconcile family and work life with a well-functioning system of childcare and maternity and parental leave schemes. However, women were segregated into lower-paid jobs. The gender wage gap, although the regime officially denied it, was high. The fall of the Iron Curtain followed by the turbulent period of economic transition and the period around entry to the European Union brought many changes – political, economic and social. The aim of this chapter is to describe and analyze the situation of women in the Czech labour market over the period of 25 years since the Velvet Revolution.

Women’s position in the labour market The Czech Republic is a small EU country with a little more than 10 million inhabitants situated right in the middle of the European Union. It resulted from the break-up of Czechoslovakia on January 1, 1993, which itself, following the Velvet Revolution, had broken free from the communist regime in November 1989. The Czech Republic rapidly adopted a series of reforms to transform the economy and has been considered a fast reformer. Figure 3.1 shows the change over time in three key indicators. The country has experienced two major economic recessions during the period we cover in this chapter: one, less pronounced, in the mid-1990s; and the major, recent one, in 2007–2008. According to Eurostat data, after the financial crisis of 2007, the Czech economy started to recover quickly and, in 2014, GDP per capita was 85 per cent of the EU average, the highest among the new EU member states. In 2015, the country became the fastest growing among the EU nations. Over the past 25 years, the country went through a number of changes that affected the relative position of women in the labour market. In the next subsections we first provide descriptive evidence of gender gaps in key indicators,2 then we describe and discuss major changes in policies and social institutions over the past 25 years that most likely affected the gender differences we describe. Table 3.1 shows that, in 1980, according to the Population Census, economic activity rates were 61.4 per cent for women and 75.4 per cent for men aged 15

12 10 8 6 4 2 0 -2

GDP growth at 2005 const. prices

Inflation rate

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2003

2004

2002

2001

2000

1999

1998

1997

1996

1995

-6

1994

-4

Unemployment rate

Figure 3.1 Main economic indicators, 1994–2014 Source: Czech Statistical Office and the Ministry of Labour and Social Affairs, the World Bank WDI

Table 3.1 Economic activity, employment and unemployment by gender, 1980–2013 Year

Male

Female

Rate of economic activity (population age 15 and older, %) 1980 75.4 61.4 1991 72.9 60.8 1993 71.3 52.3 2013 68.1 50.9

Gender gap (p. p.) 14.0 12.1 19.0 17.2

from which Employment rate (population age 15 and older, %)

1993 2013

Male

Female

Gender gap

68.9 64.0

49.5 46.7

19.4 17.3

–

–

Unemployment rate (labour force, %) 1980 – 1991 4* 1993 3.4 2013 5.9

5.4 8.3

2.0 2.4

Source: CZSO, 1980–1991 – Population Census 2001; 1993–2013 – Labour Force Surveys Note: definition of economic activity: employed + unemployed, employed includes working retirees, working students and mothers on maternity leave (in 1991, also people on parental leave). *figure only for men and women together

Czech Republic 47 and older. Economic activity rates for the working-age population, aged 15–59, were 82.2 per cent for women and 92.7 per cent for men. Unemployment virtually did not exist. Male activity rates have been higher than female rates throughout the entire period under analysis. Activity rates decreased for both men and women during the period following the collapse of the communist regime, but the decrease was more pronounced for women. Therefore, the gender gap in the rate of economic activity is higher than it was 25 years ago: 17.2 percentage points in 2013 compared to 12 percentage points in 1991. Further, we dig deeper and look at how trends in economic activity and employment changed over time for different groups by age and gender. Figures 3.2 and 3.3 show economic activity rates by age (5-year age bands) separately for females and males. Economic activity of young men aged 15 to 24 decreased significantly during this period, due to higher school and university participation: for men aged 15 to 19, economic activity dropped from 38 per cent in 1993 to 7 per cent in 2013; for those aged 20 to 24 the corresponding rates were 86 and 59 per cent. Men in the middle of their economic careers experienced stable economic activity during the period. This is in stark contrast to the situation of women of the same age, who are most likely affected by motherhood. In particular the activity rates for women aged 35–39 dropped from 90 per cent in 1993 to 81 per cent in 2013 and from 80 per cent to 67 per cent over the same period for those aged 30–34. Economic activity increased for women aged 25–29 from

100 90 80 70 60 50 40 30 20

age 20 to 24

age 25 to 29

age 30 to 34

age 35 to 39

age 40 to 44

age 45 to 49

age 50 to 54

age 55 to 59

age 60 to 64

65 and more

2013

2012

2011

2010

2009

age 15 to 19

Figure 3.2 Female economic activity rate by age, 1993–2013 Source: CZSO, LFS

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

0

1993

10

48

Lenka Filipova and Mariola Pytliková

100 90 80 70 60 50 40 30 20

age 15 to 19

age 20 to 24

age 25 to 29

age 30 to 34

age 35 to 39

age 40 to 44

age 45 to 49

age 50 to 54

age 55 to 59

age 60 to 64

65 and more

2013

2011

2012

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

0

1993

10

Figure 3.3 Male economic activity rate by age, 1993–2013 Source: CZSO, LFS

64 per cent in 1993 to 70 per cent in 2013. These trends were likely affected by an increase in the average age at which women bore their first child, as well as by reforms prolonging maternity and parental leave periods. As reported in Kalíšková and Münich (2012) and most recently in PertoldGebicka and Husek (2015), the labour force participation of Czech women in their early 30s is one of the lowest among the EU countries, yet at the same time women without children have one of the highest economic activity and employment rates in the European Union. The impact of the higher retirement age can be seen in the increased activity rates of both men and women aged 50 and older. The increase is particularly significant for women aged 55–59. The employment rates for both men and women also declined between 1993 and 2013, from 68.9 per cent to 64 per cent for men and from 49.5 per cent to 46.7 per cent for women. This resulted in a decrease in the gender employment rate gap from 19.4 to 17.3 percentage points over the same period. Similar patterns are found for employment rates by age and education, not shown here. The gender gap in unemployment has increased more during economic recession than economic recovery. The initial period of economic transition did not see the expected substantial increase in unemployment, which was also typical of other countries undergoing similar transition, and this was so in the case of female unemployment as well. Reasons for this were the emergence of the service sector that absorbed some of the workers threatened by unemployment, and the

Czech Republic 49

4 3.5 3 2.5 2 1.5 1

2013

2011

2012

2010

2009

2008

2007

2006

2005

2003

2004

2002

2001

2000

1999

1998

1997

1996

1995

1993

0

1994

0.5

Figure 3.4 Gender gap in unemployment, 1993–2013 Source: CZSO, LFS

slower pace of economic restructuring which ensure a prolonged existence of large, “old-fashioned” firms. Figure 3.4 shows that, in 2013, the gender gap in unemployment was around 2 per cent. Pytliková (2015) shows that large wage differences also appear between men and women with respect to parenthood. Based on Statistics on Income and Living Conditions (SILC) data from 2012, the author argues that for childless employees, the difference in median monthly wages is 15 per cent, and the gender wage gap increases with each additional child in the family. The difference in monthly median wages between men and women with one child is around 20 per cent, and 32 and 36 per cent between men and women with two and three children, respectively. Pytliková (2015) demonstrates that the gender wage gap is highest when children need most care and fully depend on their parents. The older the children, the lower the difference; however, the pay gap does not close when children reach adulthood; in fact, it remains higher than the difference in median wages of childless employees. In particular, the study shows that the gender gap in median monthly wages reaches around 39 per cent for parents with small children aged 3–5, and the gap then narrows down with the children’s ages. The wage gap between men and women with adult children is approximately 24 per cent, which is still quite far from the difference of 15 per cent in median monthly wages between childless men and women. Based on SILC data for 2012, Pytliková (2015) shows that the differences in median monthly wages may be partially explained by the differences in hours worked. On average, men without children work 2 hours longer a week than childless women. After a child is born, men usually increase their working hours, working an average of 44.4 hours a week

50

Lenka Filipova and Mariola Pytliková

when the children are small, whereas women with small children work an average of 38 hours a week. This difference narrows as the youngest child in the family grows up, and the difference in working hours for employees with adult children is around 2.5 hours (Pytliková, 2015). According to Večerník and colleagues (2007), communist Czechoslovakia did not place the same importance on education as did other Central and Eastern European countries. In fact, at the onset of the transition, the country had a considerable number of people with secondary education, but a low number of university-educated persons. By the end of the communist era, each additional year of schooling increased men’s earnings only by 4.1 per cent and women’s earnings by 5 per cent (Večerník et al., 2007). As expected, in the first decade of the transition towards a market economy, returns to schooling rose rapidly. According to Filer and colleagues (1999), one additional year of schooling increased men’s wages by 9 per cent in 1997. The post-communist period was instead characterized by increasing levels of education of the Czech labour force and a growing supply of university-educated individuals on the labour market. This trend has been particularly pronounced for women, as documented in Figure 3.5. The number of tertiary-educated women increased by about 10.7 percentage points compared to an increase of 7.1 percentage points for men. According to Figure 3.5, in 2013, the share of the population with a tertiary education was almost equal for both genders. At the same time, the share of the

120

1993

2013

100

80

60

40

20

0 Male Primary and without edu

Female Lower secondary edu

Male Higher secondary edu

Figure 3.5 Population by education, 1993 and 2013 Source: CZSO

Female Tertiary edu

Czech Republic  51

60 50 40 30 20 10 0

Female %

Male %

Figure 3.6  Students enrolled in tertiary education, per cent by gender, 1995–2014 Source: MŠMT (2015)

population with only basic or no education decreased substantially, particularly for women (by 17 percentage points), but also for men (by 8 percentage points). Figure 3.6 suggests that this trend is likely to continue into the future as the number of female students enrolled in tertiary education took over the number of male students since 2005. In fact, the data from the Ministry of Education show that the proportion of tertiary educated is already higher for women than for men among younger cohorts (i.e. in their 30s and younger). Clearly women are becoming an increasingly important part of the country’s talent pool and its highly educated workforce. In this section we describe changes since 1993 in industries and occupations in which men and women work. Table 3.2 shows that at the beginning of the economic transition, many more men than women worked as self-employed or employers, and this pattern continued until 2013, although the share of women increased. In 1993, women were much more likely than men to be classified as unpaid family members, and the gap has increased over time. The transition into a market-driven economy intensified the extent of gender segregation in the occupations as well as in industries. According to Table 3.2, in 1993, men dominated the occupations of managers and legislators (69 per cent), and in 2013, even more so (73 per cent).3 Craft and related workers and plant and machine operators are also maledominated occupations. On the other hand, clerical occupations were and remained female-dominated (72 per cent in 1993 and 79 per cent in 2013). The same trend is evident in the service and sales and elementary occupations. There is a significant change in the category of technicians and associate professionals

52

Lenka Filipova and Mariola Pytliková

Table 3.2 Men and women in occupations, 1993 and 2013 1993

Total employment in CZ I C S E[1] Employees and members of producers’ cooperatives Employers Own-account workers Unpaid family workers CZ – ISCO Managers and legislators Professionals Technicians and associate professionals Clerical support workers Service and sales workers Skilled agricultural, forestry and fishery workers Craft and related trades workers Plant and machine operators and assemblers Elementary occupations Armed forces occupations

2013

%male

%female

%male

%female

56.1

43.9

56.6

43.4

54.6

45.4

54.3

45.7

77.9 69.3 37.0

22.2 30.7 63.0

75.5 67.9 27.0

24.5 32.1 73.0

68.6 45.6 47.7 27.7 31.7 46.9

31.4 54.5 52.3 72.3 68.3 53.2

72.8 44.5 58.0 21.4 34.2 64.2

27.2 55.5 42.0 78.6 65.8 35.8

81.3 73.2 41.1 98.5

18.7 26.8 58.9 1.5

89.5 75.8 38.7 91.3

10.5 24.2 61.3 8.7

Source: CZSO Note: ICSE – International Classification by Status in Employment; ISCO – International Standard Classification of Occupations.

where the number of men increased from 48 to 58 per cent and exceeded the number of women. The share of women decreased also in agricultural, forestry and fishery occupations, from 34 to 30 per cent. Jurajda and Paligorová (2006) found that only 7 per cent of top-level Czech managers are women, and their wages are about 20 per cent lower than those of men. Data from the GMI survey show a large gender gap on the corporate boards of the largest listed companies in the European Union, where women represented only 16.6 per cent of the top managerial jobs in April 2013. Moreover, Figure 3.7 shows the increase of women’s representation on corporate boards has been very modest. With 15 per cent of women in the top managerial positions of the largest listed companies in 2012, the country ranks towards the middle of the EU member states (European Union, 2012). The underrepresentation of women on the corporate boards of the largest listed companies becomes even more significant when compared with, for instance, the proportion of women on the top level of public administration, at 30 per cent, or on executive boards of research institutions, at 22 per cent. Table 3.3 shows that women in the Czech Republic dominate the education and human health and social work sectors, which are also sectors with lower

100.0%

80.0%

60.0%

40.0%

20.0%

Female

April13

October12

January12

2011

2010

2009

2008

2007

2006

2005

2004

15.8% 16.6% 8.5% 9.0% 9.8% 9.7% 10.3% 10.7% 10.9% 11.8% 13.6% 13.8% 2003

0.0%

Male

Figure 3.7 Proportion of women in management and on executive boards, European Union, 2003–2013 Source: European Commission, database on women and men in decision making

Table 3.3 Proportion of men and women in industries, 1993 and 2013 1993

2013

%male

%female

%male

%female

NACE

56.1

43.9

56.6

43.4

Agriculture, forestry and fishing Mining and quarrying Manufacturing Electricity, gas, steam and air conditioning supply Water supply; sewerage; waste management and remediation activities Construction Wholesale and retail trade; repair of motor vehicles and motorcycles Transporting and storage Accommodation and food service activities Information and communication Financial and insurance activities Real estate activities Professional, scientific and technical activities Administrative and support service activities Public administration and defence; compulsory social security Education Human health and social work activities Arts, entertainment and recreation Other activities

64.4 83.4 58.1 73.6

35.7 16.6 41.9 26.4

70.4 88.5 66.5 79.9

29.6 11.5 33.5 20.1

67.5

32.5

79.0

21.0

89.0 42.6

11.0 57.4

92.0 45.2

8.0 54.8

68.5 41.9 45.6 32.2 45.1 52.5 61.0 66.6

31.5 58.1 54.4 67.8 54.9 47.5 39.0 33.4

74.0 40.9 76.5 44.2 52.8 49.8 55.6 53.2

26.0 59.1 23.5 55.8 47.2 50.2 44.4 46.8

27.0 21.1 51.6 37.6

73.0 79.0 48.4 62.4

23.2 19.8 49.4 30.1

76.8 80.2 50.6 69.9

Source: CZSO, LFS

54

Lenka Filipova and Mariola Pytliková

wages. At the same time, men are overrepresented in mining and quarrying, electricity, gas, steam and air conditioning supply, water supply, sewerage, waste management, construction and transport industries. Jurajda (2005) emphasizes three main factors as to why “female” occupations pay less: (i) discriminating employers may prevent women from working in high-wage occupations; (ii) female occupations may offer costly non-wage characteristics preferred by women; (iii) workers employed in female occupations may have lower labour quality. As mentioned in the introduction, the Czech labour market during the communist era was characterized by a large gender wage gap despite the proclaimed equality aims. Although the constitutions of communist countries included a clause about non-discrimination, there was no practical implementation and monitoring of this principle (Jurajda, 2005). Večerník and colleagues (2007) found that gender explained 31 per cent of the variance in earnings in 1988. According to Brainerd (2000), the mean female/male wage ratio was 68.5 per cent (and the median 66.7 per cent) in the pre-reform period; in the post-reform period, the corresponding figures were 72.1 and 71.5 per cent, respectively. Figure 3.8 shows changes in average and median wages by gender over the

86 84 82 80 78 76 74 72 70 68

Gender wage gap, mean

2013

2012

2011

2010

2009

Gender wage gap, median

Figure 3.8 Ratio of wages of women over men, 1996–2013 Source: CZSO

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

64

1996

66

Czech Republic 55 period 1996–2013, with 1996 the earliest comparable data point we could obtain.4 We can observe that the median gender gap has always been larger than the mean gender gap. Both wage gaps appear to increase during economic recession, particularly in the late 1990s, but also in the Great Recession. Overall, the gender pay gap has decreased over time, with the median pay of women now representing 84 per cent of the median pay of men. If we look at the gender wage gap across different occupations, we can observe in Figure 3.9 that the lowest gender wage gap is among skilled agricultural, forestry and fishery occupations, and this has remained stable between 2002 and 2013.

Figure 3.9 Share of median wages of women to median wages of men by occupation, 2002–2013 Source: CZSO

56

Lenka Filipova and Mariola Pytliková

Between 2002 and 2012, the gender gap in the managers, service and sales occupations has decreased. In fact, while the largest gender pay differentials (over 30 per cent) across all occupations in 2002 were in the managers occupations, this decreased to 18 per cent in 2012. On the other hand, the gender wage gap widened in professional occupations during this period. Technicians and associate professionals show a stable, although one of the highest, gender wage gap over time. Figure 3.10 shows how the gender wage gap differs across age groups: the highest gender wage gap is found for workers aged 35 to 44. For 120 100 80 60 40 20 0 2002

2006

age up to 19 age 35 to 39 age 55 to 59

age 20 to 24 age 40 to 44 age 60 to 64

2010

2013

age 25 to 29 age 45 to 49 age 65 and more

age 30 to 34 age 50 to 54

100 95 90 85 80 75 70 65 60 2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

age up to 19

age 20 to 24

age 25 to 29

age 30 to 34

age 35 to 39

age 40 to 44

age 45 to 49

age 50 to 54

age 55 to 59

age 60 to 64

age 65 and more

2013

Figure 3.10 Share of median wages of women to median wages of men by age, 2002–2013 Source: CZSO

Czech Republic 57 individuals aged 25 to 34, the gender gap appears to have narrowed over time. Motherhood duties, rising of the average age at which women bore their first child, and reforms promoting longer maternity and parental leave might be behind the trends in the gender wage gap we see in Figure 3.10.

Institutional factors affecting gender gaps in the labour market

180 160 140 120 100 80 60 40 20 0

Slovakia Poland Czech Republic Hungary Russia Estonia Austria South Korea Sweden Japan Germany Slovenia Denmark Canada Italy Finland France Luxembourg Netherlands United Kingdom Norway Belgium Portugal Iceland Ireland Australia Greece Spain Turkey New Zealand Switzerland Mexico United States of America Chile Israel

Over the past 25 years, a number of changes in policies and social institutions have likely affected gender differences in the labour market. Following EU accession, the Czech Republic started to conform to EU regulations according to Agenda 2000, including non-discrimination law. Relevant acts were implemented in the Labour Code in 2000 and 2004, as well as in some parts of the 2004 Employment Act. Although there was progress in the gender wage gap after the implementation of the EU standard set of antidiscrimination policies, the Czech Republic remains one of the countries with the largest gender wage gap within the European Union. According to 2013 data, Czech women’s wages were 22.1 per cent lower than men’s, which compares unfavourably with the EU average of 16.4 percent. Career breaks due to childbirth negatively affect work experience and consequently wages. This penalty is likely to be large in the Czech Republic as the total length of paid maternity and parental leave of 112 weeks is among the highest in the OECD countries, as can be seen in Figure 3.11. There is a long tradition of maternity and parental leave in the Czech Republic. Maternity leave of four weeks was introduced at the end of the nineteenth century. It was then gradually extended until 1987, when the maternity leave was increased

Figure 3.11 Number of weeks of paid maternity and parental leave in 2012, OECD countries Source: OECD

58

Lenka Filipova and Mariola Pytliková

400 4.9

350 300

3.4 2.1

2.3

4.1

6.3

6 5.4

4.2

2.4

5.8

5.3

5.2

5.1

250 200 150 100 50 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Female

Male

Figure 3.12 Recipients of parental allowance by gender (in thousands), 2001–2013 Source: OECD

to the current 28 weeks. The paid parental leave was introduced in 1964, initially regarded only mothers and was for a period of 1 year (52 weeks) for one child and up to 2 years (104 weeks) for two and more children. The parental leave period was increased further to 104 weeks for one child in 1970 and 156 weeks in 1989. Since 1990, it can be shared between mothers and fathers. The obligation of employers to keep the job of parents over the period of parental leave has been guaranteed only since 2001. In 1995, the length of parental leave was further extended until the child’s fourth birthday (208 weeks). In 2008, the government introduced a flexibility of choice between 2, 3 or 4 years of paid parental leave. Since 2012, parents can change between 2, 3 or 4 years of paid parental leave every quarter, but the total amount of parental leave payment cannot exceed 220,000 CZK. Although the leave can be shared between parents, in the vast majority of cases it is mothers who take up the parental leave. Figure 3.12 shows the numbers of recipients of parental allowance by gender. Although we can observe an increasing trend in the number of men taking parental leave, particularly up to the onset of the Great Recession in 2008, it is mothers who shoulder the burden of taking care of children. Maternity and parental leave in the Czech Republic is also very generous in comparison to other countries. Figure 3.13 shows spending on child-related leave and grants per childbirth, which, in the Czech Republic, is the fifth highest among the developed OECD countries after Luxembourg, Estonia and Nordic countries (such as Norway, Sweden and Finland), traditionally considered very lavish.

Czech Republic 59

40000.00 35000.00 30000.00 25000.00 20000.00 15000.00 10000.00

0.00

Luxembourg Norway Estonia Sweden Finland Czech Republic Denmark Slovenia Hungary Slovak Republic Iceland OECD Average Canada Germany Italy United Kingdom France Portugal Belgium Japan Spain Poland Switzerland Austria Australia Ireland Greece Israel Chile New Zealand Korea Turkey Mexico Netherlands United States

5000.00

Figure 3.13 Spending on child, related with maternity/parental leave and birth grant, 2011, USD PPP Source: OECD

Maternity and parental leave is meant to improve mothers’ health and in particular to increase children’s welfare. Proponents further argue that childcare leave promotes gender equality as it allows mothers to retain their valuable firm-specific human capital and it helps them to come back to the labour market due to the job protection over the maternity and parental leave period. Thus, proponents argue that childcare leave helps women to keep their careers and wages on track (Schönberg and Ludsteck, 2014). But the long and generous maternity and parental leave considered almost sacred by most of Czech society may be working against women who want to advance in their careers. Such a long leave from work is likely to influence negatively women’s work experience and wages in comparison with the same cohort of men. Long career breaks may also result in lower human capital such as lower tenure and work experience, but also in depreciation of skills, which may show up in lower occupational positions after a return to work. One may also expect that the longer the period of leave, the higher the costs borne by employers. This might be one reason behind employers’ decision to indirectly discriminate against female employees by giving them lower wages or hiring men. All three factors point towards a negative effect of long periods of leave on workers’ wages.5 Pre-1989, there was a strong commitment to the full integration of women in the economic sphere, and therefore the state provided generous public childcare facilities and the right for women to go back to work after the period of leave. However, since 1989, alongside the reforms on parental leave, the government substantially decreased spending on crèche. Currently it is difficult to find a publicly financed childcare facility for a child younger than 3 in the Czech

60

Lenka Filipova and Mariola Pytliková

Romania Netherlands United Kingdom Ireland Austria Poland Greece Croatia Luxembourg Spain Cyprus France EU28 Germany Czech Republic Finland Malta Slovakia Hungary Lithuania Italy Sweden Latvia Bulgaria Belgium Portugal Slovenia Estonia Denmark Iceland

95 100 91 82 90 81 77 80 72 80 67 68 69 70 70 70 59 60 61 54 55 60 46 46 47 50 39 34 37 40 27 29 30 30 21 21 20 15 15 10 0

Figure 3.14 Childcare (kindergartens and preschools), 3–6-year-olds: 30 hours per week, 2013, per cent Source: Ministry of Education (MŠMT)

Republic. Parents have to rely on the help of families or costly private facilities. Yet the requirements of the European Union on improving childcare availability is perceived negatively by Czech society as something that returns to the communist system of collective childcare outside the family. On the other hand, the lack of suitable childcare facilities generates a barrier for parents in their efforts to reconcile family and work and might result in an implicit support to employers’ unwillingness to recruit women. Women with children between the ages of 3 and 6 have a better chance to find a nursery school, although in the past 6 years these childcare facilities have also become insufficient due to the demographic boom the country has experienced. This can be seen in Figure 3.14, which shows that 55 per cent of children aged 3 to 6 are in kindergartens more than 30 hours per week, which is above the EU-28 average of 47 per cent.

The determinants of the gender wage gap Although most of the research on wages in the Czech Republic in the first years after the fall of the Iron Curtain focused on the general development of earnings differentials, the country being one of the post-communist countries with the most equal distribution (Večerník, 1991), a number of studies analyzed gender wage differences (Chase, 1998; Filer et al., 1999; Flanagan, 1995; Gottvald, 2002; Munich et al.,1999; Večerník, 1995, 2001). These studies showed a significant increase of return to education in both sexes during the transition period with a more rapid increase for men. On the other hand, the importance of experience and tenure decreased. Thus, over a short period of time, education became the most important factor of wage differentiation.

Czech Republic  61 The most comprehensive studies on the gender wage gap in the Czech Republic are those of Jurajda (2001, 2005), which focus mainly on the role of segregation. Based on 1998 data from medium and large firms, Jurajda (2005) finds that employment segregation is related to more than one-third of the overall pay difference between the genders in the Czech Republic and Slovakia. Jurajda and Paligorová (2009) examine gender gaps in employment and wages among managers in the Czech Republic. Using matching-based decomposition techniques, they find small, unexplained wage gaps. The authors found the representation of women and the structure of the gender wage gap in the managerial positions similar to those in the United States. Pytliková and colleagues (2012) use data from a survey of a representative sample of employees in the Czech Republic in 2011, which covered various aspects of work and family life, preferences, personality and other characteristics of employees and their jobs, but also included novel variables, including a set of psychological factors, such as grit, derived from research in psychology (Duckworth and Quinn, 2009), and gender identity and family situation variables. This unique survey enables us to investigate a wider model of wage determinants than typically done and shed some light on factors explaining the gender wage gap as a whole. In what follows, we present results from an analysis of the determinants of the gender pay gap using the data mentioned earlier.6 Descriptive statistcs, summarized in Table 1 in the Appendix, shows that: women have higher educational attainment in maths than men; they tend to have lower tenure; they are much more likely to take maternity and parental leave; they are more likely to be evaluated objectively rather than subjectively in their jobs; they are more likely to have a female boss; they are more likely to work in the state sector; they prefer higher job security, job flexibility, career advancement, less stressful jobs and a good atmosphere in the workplace over a higher wage. Moreover, women prefer to share income and household responsibility equally with their partners, but in reality men prefer to be responsible for income and less responsible for households. Women tend to score higher than men in the locus of control, but less in competition, negotiation, risk and grit. The analysis uses the following Mincerian wage model: � � ln wi = λ � Femalei � + β X i + εi (1) where wi stands for monthly earnings, Femalei is a dummy equal 1 for a female, 0 otherwise, and λ is the coefficient of our interest. The matrix X contains a number of control variables divided into the following subsets: demographic factors, family factors, human capital characteristics, job characteristics, gender identity factors and preferences, family–career balance, psychological traits and health and appearance. We first run the analyses with the female dummy and a constant on the RHS to show the raw differences in terms of gender, and then we add additional controls as mentioned earlier. We further run this model separately for men, women and women with children. These are in the five columns of Table 3.4. It is important

Table 3.4 Determinants of monthly wages, 2011 Female dummy (all observ.) Variables Female Region

−0.253*** (0.016) No

Demographic and family Age Age squared Children Marital status: b Single Married Single, partnership, no cohabitation Single, partnership, cohabitation Divorced/widow, without partner Divorced/widow, partner., no cohabitation Divorced/widow, partner, cohabitation No of household members No. of brothers No. of sisters

All controls (all observ.)

Men

Women

Women with children

DepVar: log(monthly wage) −0.032 – – (0.029) Yes Yes Yes

Yes

0.023*** (0.009) −0.000*** (0.000) 0.024** (0.012)

0.035*** (0.013) −0.000*** (0.000) 0.037** (0.017)

0.007 (0.012) −0.000 (0.000) −0.010 (0.021)

0.000 (0.019) 0.000 (0.000) 0.000 (0.022)

0.046* (0.025) 0.016 (0.031)

0.049 (0.036) 0.024 (0.042)

0.058 (0.039) −0.004 (0.051)

0.026 (0.068) −0.012 (0.122)

0.048* (0.027)

0.047 (0.036)

0.055 (0.043)

0.066 (0.084)

0.017 (0.027) 0.086** (0.041)

0.019 (0.042) 0.045 (0.069)

0.014 (0.039) 0.111** (0.055)

−0.030 (0.064) 0.099 (0.079)

0.030 (0.039)

0.023 (0.064)

0.044 (0.049)

0.011 (0.077)

0.009 (0.008) −0.008 (0.010) 0.003 (0.009)

0.012 (0.012) −0.016 (0.013) 0.009 (0.013)

0.007 (0.012) −0.005 (0.014) −0.013 (0.013)

0.019 (0.015) −0.021 (0.017) −0.019 (0.016)

0.107 (0.174) 0.045 (0.194) 0.086 (0.191)

0.041 (0.188) −0.241 (0.199) −0.114 (0.226)

−0.060 (0.200) −0.330 (0.268) −0.405* (0.236)

0.201 (0.299) 0.062 (0.193)

0.146 (0.321) 0.226 (0.223)

−0.093 (0.266) 0.269 (0.233)

Education of mother: b no or basic 0.012 Secondary and (0.019) vocational −0.101* Postsecondary (0.060) non-tertiary −0.008 Short-cycle (0.056) tertiary and Bachelor 0.014 Master and PhD (0.038) 0.057 Childhood (0.076) without mother

–

Female dummy (all observ.) Education of father: b no or basic Secondary and vocational Postsecondary non-tertiary Short-cycle tertiary and bachelor Master and PhD Childhood without father Czech nationality All my other earnings Social benefits Living standards would decrease

All controls (all observ.)

Men

Women

Women with children

0.024 (0.028) −0.007 (0.055) 0.032 (0.049)

0.518*** (0.129) 0.404*** (0.155) 0.438** (0.221)

0.012 (0.230) 0.005 (0.241) 0.079 (0.231)

0.121 (0.246) 0.132 (0.256) 0.212 (0.247)

0.087** (0.037) 0.025 (0.041) 0.068 (0.058) −0.000 (0.000) −0.000*** (0.000) −0.001 (0.015)

0.548*** (0.135) 0.481*** (0.134) 0.006 (0.105) 0.000 (0.000) −0.000*** (0.000) 0.027 (0.024)

0.091 (0.227) 0.026 (0.239) 0.125* (0.069) −0.000 (0.000) −0.000 (0.000) −0.015 (0.022)

0.263 (0.246) 0.123 (0.264) 0.028 (0.080) −0.000 (0.000) −0.000 (0.000) 0.007 (0.028)

0.026 (0.033) 0.069 (0.045) 0.095** (0.041)

0.045 (0.051) 0.088 (0.077) 0.006 (0.072)

0.020 (0.061) 0.113 (0.074) 0.128* (0.073)

0.094 (0.068) 0.133 (0.086) 0.203** (0.086)

0.138*** (0.044) −0.028** (0.011)

0.142** (0.065) −0.027* (0.015)

0.118 (0.077) −0.041** (0.017)

0.245*** (0.082) −0.026 (0.020)

−0.010 (0.016) 0.011*** (0.003) −0.000** (0.000) −0.015*** (0.004) 0.009 (0.014) 0.004 (0.006)

−0.029 (0.023) 0.009** (0.004) −0.000* (0.000) −0.008 (0.016) −0.013 (0.020) 0.008 (0.007)

0.006 (0.023) 0.008* (0.005) −0.000 (0.000) −0.002 (0.007) 0.025 (0.021) −0.001 (0.009)

0.047* (0.027) 0.008* (0.005) −0.000 (0.000) −0.006 (0.007) 0.043* (0.024) −0.003 (0.010)

Human capital Education: b no or basic Secondary and vocational Postsecondary non-tertiary Short-cycle tertiary and Bachelor Master and PhD Math grade (1 highest–5 lowest) Satisfied with math grades Tenure Tenure squared Maternity leave Training No of employers so far

(Continued )

Table 3.4 (Continued) Female dummy (all observ.) Job characteristics ISCO Match of education and job Specialist Objective job evaluation Scheduled working hours Real working hours

All controls (all observ.)

Men

Women

Women with children

Yes 0.009 (0.006)

Yes 0.017* (0.009)

Yes 0.001 (0.010)

Yes 0.003 (0.012)

0.035** (0.014) −0.020*** (0.007) 0.013*** (0.003) 0.005*** (0.001)

0.057*** (0.021) −0.019* (0.011) 0.009* (0.005) 0.004*** (0.001)

0.032 (0.021) −0.019* (0.010) 0.015*** (0.004) 0.006*** (0.002)

0.007 (0.024) −0.027** (0.011) 0.016*** (0.005) 0.004* (0.002)

−0.039 (0.030) −0.042 (0.031)

−0.006 (0.033) −0.028 (0.033)

−0.012 (0.038) −0.046 (0.039)

−0.021 (0.042)

−0.006 (0.042)

0.011 (0.052)

−0.090* (0.049)

0.012 (0.042)

0.027 (0.053)

−0.058* (0.033)

−0.007 (0.035)

−0.016 (0.039)

−0.191 (0.117)

−0.169 (0.135)

−0.121 (0.146)

−0.042 (0.052) 0.015 (0.010) 0.050** (0.020) Yes Yes

−0.025 (0.068) −0.010 (0.009) −0.006 (0.021) Yes Yes

−0.014 (0.084) −0.003 (0.011) 0.019 (0.025) Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes

Yes

Yes

Way of getting employment: b Employer´s offer −0.020 Somebody’s (0.021) recommendation −0.027 Somebody’s (0.022) information on vacancy −0.010 Job (0.029) advertisement in media −0.036 Information (0.030) from employment office −0.027 Applied for a (0.023) job without job vacancy −0.132 Establishment (0.089) of his/her own company −0.041 Other (0.042) Teamwork 0.005 (0.007) Work and job 0.028** tasks freedom (0.014) Gender of boss Yes Relation with Yes boss Flexitime Yes Work from Yes home Changing Yes workload

Female dummy (all observ.)

All controls (all observ.)

Men

Women

Women with children

0.025*** (0.008) Yes Yes Yes

0.022* (0.013) Yes Yes Yes

0.026** (0.011) Yes Yes Yes

0.029** (0.013) Yes Yes Yes

−0.006 (0.011) 0.004 (0.013) −0.007 (0.014) −0.010 (0.013) −0.008 (0.014)

−0.007 (0.013) −0.044*** (0.013) 0.018 (0.015) 0.003 (0.013) −0.020 (0.013)

0.007 (0.016) −0.042*** (0.015) 0.013 (0.017) 0.001 (0.015) -0.023 (0.015)

Responsibility for income – pref.: b Exclusiv. me 0.009 0.008 Mainly me (0.023) (0.025) −0.033 −0.026 Me and partner (0.027) (0.030) equally −0.049 −0.044 Mainly partner (0.032) (0.085) −0.019 −0.070 Exclusively (0.037) (0.347) partner

0.150 (0.187) −0.110 (0.134) −0.121 (0.135) −0.091 (0.135)

0.318 (0.237) −0.077 (0.168) −0.068 (0.169) −0.047 (0.170)

Responsibility for income – reality: b Exclusiv. me −0.028 −0.032 Mainly me (0.020) (0.024) −0.033 −0.029 Me and partner (0.021) (0.030) equally −0.114*** −0.118** Mainly partner (0.025) (0.050) −0.109*** 0.151** Exclusively (0.036) (0.065) partner −0.094 −0.117** Parents whom I (0.055) (0.074) live with

−0.029 (0.049) −0.036 (0.037) −0.117*** (0.039) −0.136*** (0.049) −0.148** (0.068)

−0.033 (0.062) −0.064 (0.047) −0.157*** (0.050) −0.163*** (0.060) −0.111 (0.139)

Responsibility for households – pref.: b Exclusiv. me 0.034 0.112 Mainly me (0.033) (0.100) 0.026 0.077 Me and partner (0.034) (0.079) equally 0.038 0.088 Mainly partner (0.037) (0.077)

0.015 (0.041) 0.007 (0.043) 0.120 (0.095)

0.041 (0.046) 0.016 (0.048) 0.074 (0.110)

Monopson NACE Firm size Ownership of firm

Gender identity and position in the family Job security −0.009 (0.008) Job flexibility −0.020** (0.009) Career 0.005 advancement (0.010) Less demanding −0.001 and stressful job (0.009) Good −0.014 atmosphere (0.009)

(Continued )

Table 3.4 (Continued) Female dummy (all observ.)

All controls (all observ.)

Men

Women

Women with children

0.017 (0.043)

0.063 (0.081)

0.142 (0.147)

0.120 (0.125)

Responsibility for households – reality: b Exclusiv. me −0.002 −0.008 Mainly me (0.019) (0.047) 0.021 0.054 Me and partner (0.021) (0.039) equally 0.024 0.039 Mainly partner (0.024) (0.035) 0.033 0.049 Exclusively (0.029) (0.039) partner 0.001 0.031 Parents whom I (0.062) (0.084) live with Charity −0.004 −0.026 (0.018) (0.028)

−0.023 (0.024) 0.001 (0.029) 0.021 (0.059) 0.027 (0.080) 0.000 (0.073) 0.021 (0.026)

−0.008 (0.029) 0.029 (0.035) 0.029 (0.077) −0.013 (0.103) 0.086 (0.128) 0.059** (0.029)

Lifestyle – reality: b Working career −0.003 Family (0.015) −0.004 Free time and (0.026) hobbies −0.042 Volunteer, non(0.076) paid activities

−0.018 (0.024) −0.006 (0.033) −0.184*** (0.069)

0.019 (0.021) −0.029 (0.049) 0.078 (0.095)

0.023 (0.025) 0.012 (0.075) 0.000 (0.122)

Lifestyle – pref.: b Working career −0.020 Family (0.017) −0.014 Free time and (0.023) hobbies 0.074 Volunteer, non(0.120) paid activities Help in 0.033*** households (0.013) Help with kids −0.017 (0.016)

−0.037 (0.024) −0.027 (0.030) 0.166 (0.229) 0.021 (0.019) −0.019 (0.025)

0.005 (0.026) 0.026 (0.040) 0.120 (0.141) 0.042** (0.020) −0.006 (0.022)

−0.020 (0.032) −0.013 (0.064) 0.047 (0.161) 0.057** (0.023) 0.000 (0.024)

0.007 (0.012) 0.032** (0.013) 0.002 (0.014) −0.073*** (0.019) 0.005 (0.004)

−0.001 (0.011) 0.019 (0.013) 0.011 (0.014) 0.007 (0.019) 0.002 (0.004)

−0.007 (0.014) 0.008 (0.014) 0.019 (0.016) −0.024 (0.023) 0.002 (0.005)

Exclusively partner

Psychological traits Locus of control Competition Self-esteem Negotiation Risk (1–10)

0.003 (0.008) 0.028*** (0.009) 0.006 (0.009) −0.022* (0.013) 0.004 (0.003)

Czech Republic 67 Female dummy (all observ.) Grit (Determination) Health and appearance Health BMI Height Constant Observations Adjusted R-squared

9.964*** (0.011) 1.984 0.116

All controls (all observ.)

Men

Women

Women with children

0.027*** (0.009)

0.026** (0.013)

0.028** (0.013)

0.020 (0.015)

−0.032 (0.021) −0.000 (0.002) 0.002** (0.001) 8.013*** (0.348) 1.978 0.535

−0.016 (0.028) −0.001 (0.003) 0.003*** (0.001) 7.307*** (0.453) 1.046 0.422

−0.034 (0.031) −0.000 (0.002) 0.001 (0.002) 8.933*** (0.490) 932 0.527

−0.064* (0.034) −0.002 (0.003) −0.000 (0.002) 9.293*** (0.650) 673 0.536

Source: Authors’ own calculations Notes: Dependent variable: ln (monthly wage). Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

to emphasize that we report estimated relationships between our variables and wages as correlations rather than causal effects. The results of the most basic model specification with a female dummy as the sole explanatory variable show 25.3 per cent of the gender wage difference, and the model explains approximately 11.6 per cent of the variance in monthly wages (adj. R-squared). Adding the rich subsets of variables substantially decreases the coefficient of the female dummy to 3.2 per cent, with no significance, and our full model specification explains 53.5 per cent of variance of monthly wages. The novel characteristics from the subsets of gender identity and position in the family, psychological traits and appearance play a significant role in explaining wage differences. The results show that age, often used as a proxy for labor market experience, is statistically significant only for men. The number of children does not appear to be related to wages of women (the effect is negative, but does not gain statistical significance), but men with more children tend to have significantly higher wages. On the other hand, marital status is not significant for men. Women with partners living separately and with no children tend to have significantly lower wages in comparison with those who are single. The findings are consistent with results by Gupta and colleagues (2005) that there is no marriage premium for men, but rather a fatherhood premium. Parental education, a proxy for socioeconomic background, seems to influence wages of children of the same gender. Master’s and PhD-level education of mothers correlates significantly with wages

68

Lenka Filipova and Mariola Pytliková

of women without children; the education of fathers has a positive effect on men’s salaries. The education of respondents is positively correlated with wages, and this is especially the case for the master’s and PhD categories compared to basic education. Proxy for ability (math grades at grammar school) are important wage determinants for men and women without children in the sense that better marks at school lead to higher wages. Tenure is an important wage determinant for men as well as women with children. Maternity leave has a significantly negative effect on wages when running regression with all respondents, but has no significant influence in regressions done separately for men and women. Job characteristics seem to explain some differences in the wages of men and women. For instance, being a specialist or having freedom in working tasks is associated with higher wages for men, but not for women. Larger and foreign-owned firms tend to pay men better, whereas the coefficients do not attain statistical significance for women. Some of the variables that capture the family-work reconciliation issue are statistically insignificant. However, a few interesting significant results are worth mentioning here. For instance, any form of help with housework is correlated with higher wages for mothers. A set of variables attempts to capture lifestyle preferences and reality in terms of focusing on working career, family, free time and hobbies or voluntary work. Results show these are not statistically significant for both women and men, apart from the expected statistically significant result that men tend to have lower wages if they focus on work in non-paid activities than if the main focus, in real life, is on a working career. Preference of job flexibility over wages is negatively correlated with the wages of women, and especially those with children (at the 1 per cent level). The results indicate that women with children prefer job flexibility in order to be able to balance family and career at the expense of lower wages. In Czech society, men are thought to be the breadwinners. As expected, the results show that women with children have significantly lower wages if their partners are the main breadwinners. However, the results for men are not so definitive. Although they tend to have lower wages if their partners are the main breadwinners, the opposite is the case when partners are the exclusive breadwinners. The variable “Responsibility for household chores” tries to test the relationship between responsibility for household chores and wages. In Czech society, women are mostly responsible for household chores. However, results are not statistically significant in this respect. The results for psychological traits and health and appearance factors reveal interesting differences. Competition is a significant wage determinant for men, but not for women. The results are surprising in the case of negotiation, where the literature suggests that men have higher wages because they are more likley to negotiate for higher wages. However, the results indicate that men who negotiate for better pay tend to have significantly lower wages. This may be due to reverse causality: men who have lower wages negotiate for higher ones. Unfortunately, the effect of reverse causality cannot be addressed with the data

Czech Republic 69 at hand. The variable “Determination” tests the hypothesis that people who can overcome barriers have higher wages. The results support this for both men and women to a very similar extent.

Conclusions In this chapter we described and analyzed the major changes in gender labour market inequalities in the Czech Republic since the beginning of the economic transition from a centrally planned towards a market economy. We found that, during the past 25 years, women lost in terms of labour market participation. Under the socialist regime, around 61 per cent of women were economically active and the unemployment rate was virtually non-existent. By 2013, the rate of female economic activity dropped to around 50 per cent. Important, the gender gap in labour market participation has increased significantly over time. More specifically, the gender gap developed particularly for individuals in the middle of their careers, in the age affected by maternity, whereas for women younger than 30 and older than 50, economic activity has increased over time. Those numbers are high when compared with the labour force participation of young and older women in other developed countries. These trends were likely affected by an increase in the average age at which women bore their first children, as well as by reforms that increased maternity and parental leave. This is of real concern, as women in the Czech Republic are an increasingly important part of the skilled labour force, as documented by the development in educational levels by gender. Furthermore, we found that gender occupational and industrial segregation have also increased. Yet we observe a certain improvement in the so-called glass ceiling, where the number of women in top managerial positions reached 16.6 per cent in 2013. The gender wage gap is, however, quite large in comparison to other developed countries, with larger wage differentials between men and women in average wages (around 22 per cent in 2013 compared to the EU average of around 16 per cent). The gap in median wages was lower at around 16 per cent in 2013. We observed the counter-cyclicality of the gender wage gap: it increases in times of economic recessions and decreases during upswings. We found that the largest gender pay differentials are for workers aged 35 to 44 (again, a group clearly affected by motherhood), and for professionals. The gender pay gap within managerial occupations has decreased substantially, from 30 to 18 per cent, between 2002 and 2012. The 25 years since the fall of the Iron Curtain have been characterized by a number of changes in policies and social institutions that have likely affected the gender gaps in the labour market. First of all, in connection with its EU accession, the Czech Republic started to conform to EU regulations according to Agenda 2000, including the EU non-discrimination laws. Second, a number of institutional factors affecting the so-called motherhood penalty changed significantly over time. For instance there have been a number of reforms of maternity and parental leave schemes, making the Czech Republic the country with the

70

Lenka Filipova and Mariola Pytliková

longest and most generous paid maternity and parental leave system in the world. Although the leave can be shared between parents, an option available since 1990, it is mothers who take up parental leave. Such a long absence from paid work puts women who want to advance in their careers at a disadvantage. Such a long leave from work is likely to influence negatively women’s work experience and wages in comparison with the same cohort of men. This is confirmed by our empirical analysis, in which we show that women earn less than men overall, but the difference is due to observable factors. The unexplained part of the gap, often considered in the literature an indicator of discrimination, is negligible in our 2011 data. We find that women tend to work fewer hours and have lower job tenure, and these are associated with wages. Women spend much more time outside the labour market due to maternity and parental leave, and this has a significantly large effect on wages. Finally, we find that women prefer more flexible job arrangements, such as flexible working hours, working from home and so forth, which are often necessary to make it possible to reconcile their careers with their family lives. Our conclusion is that the overall increase in gender inequality that we have documented for the Czech Republic over the past 25 years might be mostly due to institutional changes. The existing legislation, in particular the long and generous parental leave, alongside the lack of support for childcare encourages women to stay home as long as possible, instead of helping them to balance their work and family lives. The existing policy framework also fails to engage fathers in childcare, as seen by the proportion of men taking parental leave. One of the possible policy recommendations on how to reduce the differences between men and women in the Czech labour market is therefore to encourage women to return to work earlier after parental leave. Among possible measures could be: (i) shortening the length of parental leave; (ii) proposing a compulsory sharing of parental leave between both parents; and (iii) increasing the capacity of publicly financed childcare, especially for children under the age of 3. At the same time, it would be helpful to promote flexible forms of employment in both the public and private sectors in order to help families to balance their work and family lives.

Notes 1 The work on this chapter was funded in part by SGS Research Grant No. SP2016/138, “Gender wage gap – evidence from the Czech Republic” and by Czech Science Foundation Grant P402/12/G130. 2 It is important to note that gender data for the period immediately following the fall of the regime are almost unavailable and/or inconsistent, which makes it very difficult to analyze trends in detail. We have consistent data since 1993 when the Labour Force Survey started to be administered: regarding wages, we have reliable data since 1996 when detailed statistics about wages started to be collected. For the end of the communist period and the beginning of the transition we use various databases, but mostly the Population Census. 3 The glass ceiling effect is discussed later in this chapter. 4 The wage data are from the Average Earnings Information System (ISPV), which is available only from 1996, see www.ispv.cz/en/homepage.aspx. Unfortunately, there are no reliable data for earlier period, which would be comparable with the ISPV.

Czech Republic 71 5 See for instance the work of Albrecht et al. (1999), Anderson et al. (2002), Kunze and Ejrnaes (2004), Schönberg and Ludsteck, (2012) and Spivey (2005) for empirical analysis of the effects of maternity and parental leave on women’s post-birth labour market outcomes. 6 A detailed description of variables alongside a description of the questionnaire can be found in the study by Pytliková et al. (2012).

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Appendix

Table A.1 Summary statistics of variables for men and women based on survey from 2011 (Pytliková et al. 2012) Variable Income

Gender

Obs

M 1,048 W 936 Region M 1,048 W 936 Demographic and family factors Age M 1,048 W 936 Kids M 1,048 W 936 Marital status M 1,048 W 936 No. of household M 1,048 members W 936 No. of brothers M 1,048 W 936 No. of sisters M 1,048 W 936 Education of M 1,048 mother W 936 Education of M 1,048 father W 936 Czech M 1,048 nationality W 936 My all other M 1,048 earnings W 936 Social benefits M 1,048 W 936 Living standards M 1,048 would decrease W 936

Mean

Std. Dev.

Min

Max

22,558.98 17,550.09 7.464695 7.489316

8,434.87 6,331.193 4.546974 4.566782

6,000 4,000 1 1

90,000 60,000 14 14

39.0792 38.92949 0.9895038 1.133547 2.273855 2.589744 2.76813

8.86643 8.603155 0.9234732 0.8801474 1.67697 1.937102 1.09

25 25 0 0 1 1 1

54 54 4 4 7 7 7

2.839744 0.5343511 0.5416667 0.5458015 0.5544872 3.535305 3.445513 3.945611 3.808761 0.990458 0.9871795 800.1813 589.3494 399.2405 322.9776 0.8368321 0.8002137

1.151591 0.6705451 0.6986427 0.6825716 0.6931453 1.384418 1.334536 1.878318 1.68376 0.0972623 0.1125597 3,147.784 2,311.995 1,499.163 1299.506 0.3696952 0.4000534

1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0

9 4 6 4 5 10 10 10 10 1 1 32,000 25,300 12,000 12,000 1 1 (Continued )

Table A.1 (Continued) Variable Human capital Education Math grade Satisfied with math grades Tenure Maternity leave Training No. of employers so far

Gender

Obs

Mean

Std. Dev.

Min

Max

M W M W M W M W M W M W M W

1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936

4.101145 4.279915 2.459924 2.258547 0.3520992 0.4027778 8.009466 6.774915 0.0753817 3.313034 0.4837786 0.5 3.082061 2.929487

1.678358 1.656187 0.8742943 0.8499334 0.4778527 0.490719 6.881736 6.045813 0.6862303 2.641965 0.4999754 0.5002673 1.784723 1.671192

2 2 1 1 0 0 0.08 0.17 0 0 0 0 0 0

9 8 4 4 1 1 37 34 10 11 1 1 12 12

1,048 936 1,048 936

5.239504 4.287393 2.604962 2.639957

2.371609 2.041204 1.163129 1.20944

1 1 1 1

9 9 4 4

1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936

0.5124046 0.4989316 2.089695 2.229701 39.76336 38.85844 43.50954 40.49573 3.307252 3.291667 2.57729 2.418803 0.4666031 0.4594017 1.140267 1.495726 3.645038 3.553419 2.47042 2.517094 2.791985 2.825855 2.798664 2.721154 2.116412 2.095085

0.5000847 0.5002662 0.8901288 0.9143036 2.92852 4.391045 8.08408 6.711789 1.832807 1.729695 0.9208087 0.9386696 0.4991216 0.4986155 0.3938165 0.5252785 0.8871115 0.8371898 0.8413178 0.8219752 0.5885347 0.5419457 0.5083055 0.5760098 0.7543555 0.8014275

0 0 1 1 15 4 15 5 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1

1 1 4 4 75 60 168 85 8 8 4 4 1 1 3 3 6 6 3 3 3 3 3 3 4 4

Job characteristics ISCO M W Match of M education and W job Specialist M W Objective job M evaluation W Scheduled M working hours W Real working M hours W Way of getting M employment W Teamwork M W Work and job M tasks freedom W Gender of boss M W Relation with M boss W Flexitime M W Workhome M W Changing M workload W Monopson M W

Variable

Gender

Obs

Mean

Gender identity and position in the family Job security M 1,048 2.817748 W 936 2.99359 Job flexibility M 1,048 1.936069 W 936 2.070513 Career M 1,048 2.096374 advancement W 936 2.181624 Less demanding M 1,048 2.125954 and stressful job W 936 2.33547 Good M 1,048 2.451336 atmosphere W 936 2.673077 Responsibility M 1,048 2.174618 for income – W 936 3.613248 preferences Responsibility M 1,048 2.118321 for income – W 936 3.082265 reality Responsibility M 1,048 3.667939 for household W 936 2.482906 chorespreferences Responsibility M 1,048 3.568702 for household W 936 1.969017 chores – reality Charity M 1,048 0.1145038 W 936 0.1442308 Lifestyle – M 1,048 1.507634 reality W 936 1.547009 Lifestyle – M 1,048 1.817748 preferences W 936 1.88141 Help in M 1,048 0.5648855 households W 936 0.5363248 Help with kids M 1,048 0.4074427 W 936 0.5 Psychological traits Locus of control M W Competition M W Self-esteem M W Negotiation M W Risk (1–10) M W Grit M W

1,048 936 1,048 936 1,048 936 1,048 936 1,048 936 1,048 936

2.080153 2.19765 2.625 2.478632 2.983779 2.969017 0.5715649 0.417735 5.482824 4.491453 2.877863 2.78953

Std. Dev.

Min

Max

0.8293735 0.7283132 0.7536708 0.7871604 0.778941 0.7593439 0.7553528 0.7715963 0.8324359 0.8090144 0.7423889 0.7239196

1 1 1 1 1 1 1 1 1 1 1 1

4 4 4 4 4 4 4 4 4 4 5 5

1.121692 1.314121

1 1

6 6

0.7560281 0.6439571

1 1

5 5

1.29397 0.997377

1 1

6 6

0.3185742 0.3515114 0.7019817 0.6029621 0.7089211 0.5567635 0.4960087 0.4989454 0.4915931 0.5002673

0 0 1 1 1 1 0 0 0 0

1 1 4 4 4 4 1 1 1 1

0.7665818 0.7714386 0.8056777 0.8153426 0.737017 0.772593 0.4950882 0.4934497 2.253659 2.292497 0.7722296 0.7818375

1 1 1 1 1 1 0 0 0 0 1 1

4 4 4 4 4 4 1 1 10 10 4 4 (Continued )

Table A.1 (Continued) Variable

Gender

Health and appearance Health M W BMI M W Height M W

Obs

Mean

Std. Dev.

Min

Max

1,048 936 1,048 936 1,048 936

0.1164122 0.1271368 26.38673 24.09222 179.7529 167.8996

0.3208717 0.3333042 3.466106 3.96001 7.061403 6.043033

0 0 17.35892 16 160 138

1 1 45.97079 41.01562 205 190

4

East Germany Heike Trappe

Introduction1 East Germany represents a special case among the former state socialist societies due to its particular history of separation and reunification. During the four decades following World War II, Germany was divided into two countries. Between 1949 and 1989, East Germany (the German Democratic Republic or GDR) had a state socialist system, a centrally planned economy, and socialist employment and family policies, whereas West Germany (the Federal Republic of Germany or FRG) had a multiparty parliament, a market economy, and a conservative-corporatist welfare state. The two countries were officially reunified in October 1990, and the West German constitution, known as the Basic Law, became the constitution of united Germany. The division of Germany had major implications for equality between men and women, especially with respect to divisions of labor in paid and unpaid work. During the divided years, East Germany expected and needed both men and women to be paid workers, while West Germany’s socially conservative welfare state generally relegated women to unpaid homemaking and men to breadwinning. These widely varying ideas about gender relations at home and in employment were also a direct expression of a competition between a socialist and a capitalist society. Not surprising, East German women achieved greater equality in employment than did their counterparts in West Germany. A divergence between East and West German women’s employment started as early as the 1950s, and East–West differences in labor force participation were strongest among women born around 1940 (Trappe et al., 2015). The implicit competition between the two systems might have been the most important reason the GDR went further than other socialist countries in integrating women, and particularly mothers, into the labor force but also in giving them freedom regarding their reproductive rights (Haney, 2002). However, despite the East German government’s stated commitment to eradicating gender inequality, employed women in East Germany failed to achieve full gender parity, especially with regard to earnings, occupational integration, and the division of labor at home, even as late as the 1980s, and even among younger cohorts (Kolinsky, 2002; Schenk, 2002).

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In 1989, as state socialism collapsed across Eastern Europe and in the Soviet Union, the West German government took over East Germany, setting in motion a rapid transformation of East German institutions and employment structures, a process characterized as institutional incorporation (Mayer, 1994). Following reunification, East German women’s employment status changed markedly again, owing to a combination of factors, including policy change, industrial and occupational restructuring, and acute labor market crisis. The separation – and later reunification – of East and West Germany offers a powerful case study of the interplay between states, markets, and women’s economic integration into society. Twice, new state and market arrangements were abruptly imposed in the East, setting up a social experiment of sorts concerning the influence of policy and institutional configurations on gender equality. The aim of this chapter is to present a detailed synthesis of existing research on economic gender equality in East Germany before and after reunification, and to a lesser extent, a comparison between East and West Germany. Therefore, this chapter focuses on a comparison of different dimensions of economic gender equality. We look at labor force participation, unemployment and employment, working time, the gender wage gap, occupational sex segregation, the division of unpaid work at home, and the normative support for women’s and mothers’ employment, both in the late 1980s and around 2014, the most recent data available. This offers a powerful comparison because the social experiment can be arguably better interpreted when the change in the system – the “before” and “after” – falls in a narrow historical period, therefore allowing us to assume that a host of other factors are comparatively constant. However, it is important to note that considerable migration has taken place between both parts of Germany since reunification, and particularly from East to West Germany, for economic or other reasons. Between 1991 and 2013, about 3.3 million people moved from East to West Germany and 2.1 million people moved the other way around. Over the whole time period, there was a negative migration balance for East Germany, but since 2013, migration between both parts of Germany has been almost equal (Statistische Ämter des Bundes und der Länder, 2015).2 In that sense, the population has been constantly changing. Immediately after reunification, young and well-qualified women disproportionally left East Germany for educational reasons, but this seems to have ended. Regional mobility within Germany is largely at the expense of rural regions and more so in East Germany (Grünheid, 2015).

Theorizing change over time Feminist scholars have shown that the institutional structures of the welfare state promote gendered divisions of paid and unpaid work (Gornick and Meyers, 2009). Crompton (1999a) offers a continuum of gendered arrangements, from the traditional “male-breadwinner/female-caregiver” arrangement, over current partial modifications, to an idealized “dual-earner/dual-caregiver” society that blends caring time with gender equality (Table 4.1). It is one of the very few

East Germany

79

Table 4.1 Beyond the “male breadwinner” model Traditional gender division of labor

Less traditional gender division of labor

Male-breadwinner/ female-caregiver

Dual-earner/ state-caregiver OR Dual-earner/ marketized-caregiver

Dual-earner/ female part-time caregiver

Dual-earner/ dual-caregiver

Source: Crompton, 1999a: 205

concepts to include formerly socialist societies and provides a flexible framework for envisioning variation across states and particularly change over time. Its underlying idea is that gendered divisions of care and employment would be associated with varying degrees of traditionalism in gender relations (Crompton, 1999a). Each of these gendered models depicted in Table 4.1 could be encouraged or supported by a unique institutional configuration. The male-breadwinner/ female-caregiver model was historically enabled by the presence of a male wage high enough to support a worker and his dependent family. The second model, male breadwinners with female partners splitting their time between paid work and care, would be enabled by policies that support part-time work and assure moderate levels of childcare. The third model, the dual-earner/state-caregiver arrangement, requires by definition a large public childcare sector; its counterpart with market-based childcare could operate with little state support. The dualearner/dual-caregiver model would be enabled by a generous policy package, including generous childcare provision, paid leave options with incentives for male take-up, and an economy-wide reduction in employment hours. Whereas no existing society has achieved the fully gender-egalitarian outcome envisioned in this model, some European welfare states, most notably the Scandinavian countries, have enacted policy packages that strongly encourage it. In this concept, gender is understood as structured by different institutions, generated by states, markets, and families, and at different levels through legislation, organizations, households, and in couple relationships (Crompton, 1999a). It also implies that gender relations and gender inequality are multidimensional and that they might change at different paces in different domains. They are shaped not only by social policies, but also by particular normative contexts and labor market institutions. In this sense, Crompton (1999a) emphasizes that the third model represents a transitional state, from which gender relations might either shift in a less traditional direction or remain relatively traditional. In order to contextualize the empirical evidence presented in this chapter, I will very briefly sketch the most important developments regarding the labor market and social policies with relevance to gender inequality in East Germany following reunification. West German formal institutions provided a “ready-made state” for East Germany (Rose and Haerpfer, 1997), which implied that the institutional support for employment and family extended to East Germany, with consequent pronounced setbacks in the support for working mothers. Prior to

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reunification, at the end of the 1980s, social policies in West Germany (e.g., tax law, health insurance, social security) largely enabled a modernized breadwinner model with a part-time working wife (e.g., limited childcare supply especially for young children) – model 2 in Crompton’s schema in Table 4.1 – whereas in East Germany, a dual-earner model with two full-time working partners was encouraged, as in model 3. After reunification, social policies and the supporting institutions mostly converged, with two important exceptions: public provision of childcare remained higher in the East, as did the percentage of jobs in the public sector (Statistische Ämter des Bundes und der Länder, 2015). Important, these post-unification policy shifts were intertwined with extreme economic dislocation. The sudden exposure of industries and jobs to market forces led to a rapid and drastic reduction in labor demand, and to unemployment rates far higher than those seen in the West. Overall, the process of economic integration has been much more difficult than originally expected and is still being characterized as a stalled, catch-up modernization of East Germany with long-standing lower productivity, wages, investments, and innovation (Ludwig, 2015). This economic situation means that the subjective perception of economic insecurity is particularly strong, and many couples feel the need to counter it through a dual-earner arrangement. Since reunification, there have been changes in social policies toward a departure from a male breadwinner model but without a clear underlying concept for the future, thus providing women and men with an increasingly ambivalent institutional incentive structure to reconcile family life and employment. The current institutional context, on one hand, provides strong incentives for women to participate in gainful employment and to be economically independent, for instance, in the form of employment policies in favor of “employability” and “activation,” changes in alimony regulations, parental leave reform with a “partner bonus” expansion of public childcare. On the other hand, Germany’s cultural background and other social policies still in place, such as a tax system that directly penalizes wives’ full-time employment, health and unemployment insurance for dependent household members, mini-jobs without social security, cultivate a system that undermines women’s, and particularly mothers’, labor market attachment.

Gender labor market inequality since the fall of the Berlin Wall Before reunification, women’s labor force participation in the former GDR was extremely high, in fact, among the highest in the world, and comparable to men’s. Figure 4.1 shows that, in 1989, women’s labor force participation rate was 89 percent, compared with 92 percent for men.3 The high overall participation rate was largely due to the fact that women and men started to work early in the life course and had short employment interruptions (Huinink et al., 1995). The small difference between women’s and men’s labor force participation resulted from an increasing convergence of women’s and men’s employment histories over

East Germany

81

100

90

80

70

50

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

60

Women

Men

Figure 4.1 Labor force participation rate, 1989–2014 Source: Bothfeld et al., (2005), Institut Arbeit und Qualifikation der Universität Duisburg-Essen (2015), Statistisches Bundesamt (2015a)

time. Among those who entered the labor force during the 1970s and 1980s, women’s cumulative employment experience approached that of men’s (Sørensen and Trappe, 1995), most likely because family policies in the GDR, including generous childcare and family leave benefits, favored short employment interruptions in relation to childbirth (Trappe, 1996). At the end of the 1980s, women’s participation rates varied little by marital or parenting status in the GDR (Ostner, 1993), in contrast to West Germany, where women’s engagement in paid work was very sensitive to the presence and ages of children, more so than in many other Western countries (Gornick, 1999). East German women’s, particularly mothers’, very high labor force participation before reunification has been attributed to several interdependent factors, such as the structure of women’s employment opportunities and the pressure on them to work for pay, deeply rooted norms about the public care of young children, official rhetoric on gender equality, and extensive policy programs for reconciling employment and family obligations (Schenk, 2002). Over time, all this, alongside the economic necessity of two incomes within families, contributed to women’s strong preferences for qualified employment (Adler and Brayfield, 1997; Künzler et al., 2001). In the first half of the 1990s, women’s and men’s labor force participation rates dropped remarkably in East Germany, women’s more so than men’s,

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25 20 15 10

0

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

5

Women

Men

Figure 4.2 Unemployment rate, 1991–2014 Source: Bundesagentur für Arbeit (2015)

contributing to a widening of the gender employment gap. They stabilized thereafter and have risen steadily since 2005. By 2014, East Germany’s women’s labor force participation rate was about 76 percent and men’s was 82 percent.4 The temporal development of female and male labor force participation rate reflects to some extent the differential development of the unemployment rates, which is shown in Figure 4.2. Before reunification, unemployment did officially not exist under state socialism while underemployment was present because of failed attempts to fully plan an economy (Huinink and Solga, 1994). Over the whole course of the 1990s, the female unemployment rate was higher than the male. In fact, during the first half of the 1990s, it was almost twice as high. During the second half of the 1990s, the male unemployment rate increased and approached the high female level. Between 2005 and 2014, female and male unemployment fell from 20 and 21 percent to 10 and 12 percent, respectively. In 2014, women comprised 45 percent of the unemployed. The higher, longer female unemployment during the first half of the 1990s has often been offered as evidence that women have been the “losers of the reunification process” (Sommerkorn and Liebsch, 2002). Over time, this perspective has become more nuanced, distinguishing different risks and opportunities among women. Higher female unemployment was largely a result of problems in reentering the labor market after spells of joblessness, which resulted in women’s longer unemployment duration. The risk of unemployment was reduced for those employed in the public sector, who belonged to the “middle-age” category, younger than age 50 but without small children, or who were qualified for a semiprofessional or professional occupation (Solga and Diewald, 2001; Trappe, 2006).

East Germany

83

During the second half of the 1990s, the male unemployment rate increased because of a massive reduction of male-dominated jobs in production, and it approached the high level of female unemployment around the turn of the millennium. Since around 2005, unemployment has declined considerably because of economic recovery.5 Male unemployment slightly exceeds that of women in East Germany, although women are still unemployed for longer periods of time on average: in 2014, 42 weeks as compared to 38 weeks for men (Institut Arbeit und Qualifikation der Universität Duisburg-Essen, 2015). Women are still more likely than men to remain unemployed for a longer period of time, but they are less likely than men to become unemployed largely because of their concentration within the service sector. The temporal development of the employment rate, in Figure 4.3, mirrors the changing unemployment differentials by gender.6 Men’s considerably higher employment rate between 1991 and 2002 was largely due to their lower likelihood of unemployment. Over the whole course of the 1990s, women’s and men’s employment rates declined. Since 2003, a stable employment gap has existed between men and women of about five percentage points. In 2014, women’s employment rate stood at 71 percent and men’s employment rate at 75 percent. The employment gap between women and men is most pronounced among those 60 years and older, which might point to a particular disadvantage of older women in the labor market (Institut Arbeit und Qualifikation der Universität Duisburg-Essen, 2015; Trappe, 2006).7

100

90

80

70

50

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

60

Women

Men

Figure 4.3 Employment rate, 1991–2014 Source: Institut Arbeit und Qualifikation der Universität Duisburg-Essen (2015), Wirtschafts- und Sozialwissenschaftliches Institut (2015)

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Taken together, the developments described here suggest that before reunification, a gender employment gap hardly existed. It deepened immediately after reunification because of women’s disproportionate unemployment and has stabilized at a low level since about 2003. However, the employment rate masks gender differences in actual employment when considering those on parental leave, the quality of jobs, and particularly the volume of working time. Compared to other European countries, in the former GDR working hours were both long and heavily regulated. The standard workweek was 43.75 hours, set by labor law in 1968. For mothers of at least two children under the age of 16 and for persons regularly working at night, the workweek was 40 hours with full pay (Trappe, 1996).8 During the last two decades of the GDR’s existence, part-time work was considered exceptional, even for women, and especially among younger women (Winkler, 1990). It used to be commonplace for mothers of young children not only to work but also to be employed full-time, which was strongly supported by state family and employment policies. In 1989, 27 percent of employed women and 2 percent of employed men worked part-time (Schenk, 2002).9 Parttime work was mainly performed by older women as a bridge into retirement, part-time workers’ weekly hours tended to be long, and brought the same entitlements to social benefits as did full-time work. After reunification, average weekly work hours decreased in Germany, more so in the East than in the West. By 2013, average weekly hours were 34 for women and 39 for men in East Germany (Wirtschafts- und Sozialwissenschaftliches Institut, 2015). Most of this decrease in work hours was because of increases in part-time work. Immediately after reunification, part-time work among women sharply declined, as many of them quickly shifted to full-time work to secure their jobs. After that, however, part-time work began rising again, returning to pre-unification levels around 2003, and increasing further thereafter. In 2014, women’s part-time employment rate was 38 percent as compared to 12 percent for men in East Germany (Rengers, 2015).10 Figure 4.4 reveals that part-time work has not only been rising among women, but that there has been a steady but less pronounced increase among men as well. Nevertheless, the gender gap in part-time employment has been widening over time. The rise in part-time work has partly been attributed to an increase in involuntary part-time work and to an overall expansion of atypical forms of employment. In 2013, 40 percent of men and 37 percent of women employed part-time in East Germany reported that they did so because they could not find full-time work. However, the expansion of part-time work has been particularly strong among mothers and thus there was also a large percentage who gave familyrelated reasons: altogether 28 percent and among women with minor children 53 percent, as compared to 16 percent among men with minor children in East Germany (Wirtschafts-und Sozialwissenschaftliches Institut, 2015). The driving force behind the rise in part-time employment was a series of policy measures that provided a combination of rights, obligations, and incentives for both women’s employment and the maternal caregiver model (Leitner et al., 2004).

East Germany

85

50

40

30 % 20

10

0 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Year Women

Men

Figure 4.4 Part-time employment rate, 1991–2014 Source: Rengers (2015), Wirtschafts-und Sozialwissenschaftliches Institut (2015)

Although couples in East Germany are still much more likely to practice a dualearner model with two full-time working parents than couples in West Germany, the employment patterns of couples during childrearing years have shifted significantly, particularly with preschool-aged children; that contributed to an increasing prevalence of a modernized breadwinner model (Holst and Wieber, 2014). Attitudes about the division of labor within the household are largely in line with this development (Wanger, 2015). Recent research shows that the increasing generosity of leave entitlements in relation to childbirth led to a decline in mothers’ work commitment in both parts of Germany and that shifts in mothers’ preferences have contributed to delaying women’s labor force reentry especially to full-time employment (Gangl and Ziefle, 2015). Therefore, under the surface of a minor gender gap in employment, there has been a widening gap in working hours between women and men in East Germany over time. It has been largely due to women’s higher likelihood to work parttime during childrearing years, and thus points to a higher prevalence of gendered employment arrangements among couples. It is difficult to compare gender wage gaps in the GDR before and in East Germany after reunification because no published literature exists on this topic. The reunification process was accompanied by a currency union that took effect

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in July 1990. In East Germany, not only the consumption power changed rapidly, so did the absolute level of earnings. To ensure as much comparability as possible, I rely mainly on research that assesses relative pay at single points in time. Researchers have established that, contrary to public claims, state socialist societies failed to eradicate gender inequalities in pay (Brainerd, 2000). The former GDR was no exception (Sørensen and Trappe, 1995). The consensus in the literature is that, before reunification, the gender pay differential was about equivalent in East Germany and West Germany. Krueger and Pischke (1995) report an adjusted earnings gap of about 25 percent in both East and West Germany, based on the monthly gross earnings of full-time workers and controlling for years of schooling, qualifications, and labor force experience. Trappe and Rosenfeld (2000) studied monthly net earnings for two birth cohorts that started their full-time employment in the 1970s and 1980s; they also found a gap of about 20 percent in the East that remained nearly constant over the early adult life course. Szydlik (1994), studying net hourly earnings, showed that women earned about 15 percent less than men on average. After controlling for education, labor force experience, and tenure, this gap remained. Before reunification, the main source for the persistence of women’s pay disadvantage in East Germany was the continued low pay in the specific jobs women were employed in (Sørensen and Trappe, 1995). Women were largely employed in sectors – such as the textile industry and the health sector – and occupations that were paid below average, and they were less likely than men to hold leadership positions. In addition, women less often than men received fringe benefits for specific working conditions such as shift or hazardous work (Winkler, 1990). In 2012, Germany had a gender wage gap of full-time employees11 above the OECD average (OECD, 2015); among countries of the European Union, Germany’s gender pay gap in 2013 was one of the largest12 (Eurostat, 2015). Researchers have found that Germany’s poor position relative to other European countries is a result of women’s persistently low earnings in the former West Germany. Throughout the 1990s, while the gender pay differential narrowed considerably in the East, it hardly changed in the West. In 1997, the gender gap, based on full-time workers’ annual gross earnings, was 15 percent in the West compared with only 6 percent in the East. These gaps are narrower than those reported for the time before reunification because the data excluded very high and very low wages and particularly part-time workers. In addition, the gender gap in the East fell by two percentage points between 1993 and 1997 (Deutscher Bundestag, 2002). Since 2006, comparable data depict the unadjusted gender pay gap based on hourly gross earnings over time. As can be seen in Figure 4.5, the pay gap in West Germany is considerably higher than in East Germany, and began to decline only recently (Gärtner, 2014), while in East Germany, there is an increase from a very low level starting in 2009. It is noticeable how, even 25 years after reunification, earnings are on average still 24 percent lower in East than in West Germany and the earnings distribution is more compressed (Statistische Ämter des Bundes und der Länder, 2015). For 2010, the adjusted gender pay gap, which

East Germany

87

30 25 20 15 10 5 0 2006

2007

2008

2009

2010

West Germany

2011

2012

2013

2014

East Germany

Figure 4.5 Unadjusted gender pay gap, East and West Germany, 2006–2014 Source: Statistisches Bundesamt (2015b)

takes into account occupations and industries, performance groups, working time, and qualifications, was slightly larger than the unadjusted pay gap in East Germany. This suggests that employed women had characteristics that would justify higher hourly gross earnings than those of men (Joachimiak, 2013). Despite problems of data comparability, the temporal development of the gender pay gap in East Germany suggests a strong decline immediately after reunification in the early 1990s and a widening most recently. Many observers expected the gender pay gap in the East would widen after reunification as the socialist economy was converted to a market economy, but instead it narrowed. Researchers (Gang and Yun, 2001; Hunt, 2002) tend to agree that the gender pay gap declined considerably, especially in the early 1990s, but that this decline did not reflect a straightforward success story with respect to women’s wages. Hunt (2002) documents a sharp decline in the gender gap during the 1990–1994 period and attributes a substantial portion of that narrowing (about 40 percent) to low-skilled women involuntarily exiting the labor force. This compositional explanation is supported by Franz and Steiner (2000), who find that women with poor labor market opportunities disproportionately exited the labor force after being laid off and that, for public sector workers, the effect of experience on wages increased substantially after unification because of special collective agreements taken over from the West. Since reunification, women in the East have been overrepresented in the public sector, and their overrepresentation has increased over time, in part because of the high incidence of public works and training programs that included women, especially those with high education. Thus, in the East, the public sector has served as a shelter against the

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devaluation of human capital acquired under socialism, whereas, in the private sector, labor force experience accrued during the socialist years has been largely devalued. In contrast, the recent increase of the gender pay gap in East Germany has been attributed to differential wage gains in industries mainly occupied by women and men. For instance, wages of employees in processing trades (disproportionately men) increased by 12 percent between 2009 and 2013 in East Germany, whereas wages in the sector of health and social affairs (disproportionately women) increased by only 7 percent (Statistisches Bundesamt, 2015b). While in the 1990s mostly women benefited from the substantial wage gains within the public sector, men employed in industries and private services benefited more during the economic recovery since 2005. To summarize, despite the state’s public commitment to gender equality, wage gaps in the former GDR were no more favorable for women than they were in pre-unification West Germany. After reunification, pay differentials narrowed in the East partly because low-skilled and low-paid women were pushed out of the labor force and partly because of gains realized by women working in the public sector. Since 2009, the gender pay gap in East Germany has seen a slight increase, which has been attributed to differential wage gains across industries. Employment sector and occupational sex segregation In 1989, the industrial structure of East Germany resembled that present in West Germany in the mid-1960s, with a large proportion of agricultural and manufacturing jobs. The transition to a service economy had not yet fully started. Female-dominated occupations in East Germany were even more segregated than in West Germany, contributing to a slightly higher level of overall occupational segregation in the East. The differences in these patterns of sex segregation have been attributed to differences in official gender ideology, family policies, labor needs, industrial structure, and vocational training (Rosenfeld and Trappe, 2002). After reunification, East Germany’s basic industrial structure shifted markedly, especially between 1989 and 1991, when employment in the service sector increased by 11 percentage points. The East experienced a rapid, though mainly passive, move to a service economy. Job loss took place largely in the primary and secondary sectors, whereas the number of jobs in the tertiary sector remained relatively stable. Within the service industries, areas that had been underdeveloped during state socialism, such as financial services and insurance, expanded, while others, including public administration and transportation, shrank (Goedicke, 2002). Since 2000, the distribution of men and women across industries has been much the same in East Germany as it was in West Germany, with the exception that women in the East had and still have a higher share in the service sector (Statistisches Bundesamt, 2015a). This is partly because of their higher presence in the public sector with its greater job protection. According to Franz and Steiner (2000), in 1995, East German women’s share in the public sector was 43 percent,

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while in 2014, it was about 47 percent; the proportion of men employed in the public sector was about 20 percent (Statistisches Bundesamt, 2015a). The industrial shifts after reunification were accompanied by changes in occupational sex segregation understood as the tendency of women and men to do different kinds of paid work in different occupations (horizontal segregation). Occupational sex segregation is seen as a persistent source of social inequalities in advanced societies (Charles and Grusky, 2004). An initial horizontal segregation between women and men brings about “equal, but different” career prospects, which later in employment might turn into vertical segregation, promoting “different and therefore unequal” labor market chances (Leuze and Rusconi, 2009). During the 1990s, the overall level of occupational sex segregation increased in the East (Busch 2014; Falk, 2002; Rosenfeld and Trappe, 2002). By 1997, more than 64 percent of workers in the East compared with 57 percent in the West would have to change occupational categories for the occupational distributions to be gender-neutral. The increase in the level of sex segregation in the East was due to changes in occupational structure as well as changes in the sex composition within occupations. Men increased their engagement in occupations (e.g., social worker, bank employee, cook) that had previously been integrated or female-dominated, while at the same time occupations dominated by men became increasingly closed to women (Rosenfeld and Trappe, 2002). Evidence shows that in the period between 2005 and 2012, the extent of occupational sex segregation in East Germany has slightly declined and nearly converged to the level existent in West Germany (Achatz et al., 2010; BuschHeizmann, 2015). This decline seems to be mainly due to the falling quantitative importance of heavily segregated occupations and to a lesser extent to the redistribution of women and men across occupations (Beblo et al., 2008). In sum, prior to unification, occupational sex segregation in East Germany was high since the economy remained reliant on agriculture and manufacturing. During the 1990s, services grew rapidly and by 2000 the industrial distributions in East and West Germany were nearly the same for both women and men, with a slight overrepresentation of East German women in public services. The industrial restructuring in the 1990s was accompanied by occupational shifts that supported some occupational re-segregation, especially within the industrial sector and in agriculture, with occupations previously mixed or dominated by men becoming even more male-dominated. Due to the declining relevance of those occupations, there seems to be a slight and slow decline in the level of occupational sex segregation in East Germany more recently. Gender division of unpaid work States and markets influence the intra-family distribution of unpaid work, as well as the availability of services that enable families to shift care work to outside providers. Before reunification, this was done in East Germany via the extensive provision of public childcare. Despite a nearly universal coverage of public childcare even for young children, women’s primary responsibility for childcare

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6

5

4

Hours/Day 3

2

1

0 1991/92

2001/02

1991/92

Couples without children Men

2001/02

Couples with children Women

Figure 4.6 Unpaid work of working couples aged under 60, East Germany, 1992 and 2002 Source: Gille and Marbach (2004)

and domestic work had not truly been called into question (Trappe, 1996). Unfortunately, no reliable data on time use for the 1980s exist that allow a comparison over time.13 In 1991, the time-budget study of the Federal Statistical Office indicated that the division of labor in East Germany was moderately more egalitarian than in West Germany (Künzler et al., 2001). In 1990, women in East Germany spent about twice as much time on childcare and housework as men (Statistisches Bundesamt, 1991). Figure 4.6 shows that this difference seems to have become somewhat more favorable over time. In couples without children, there is a remarkable shift toward gender equality in unpaid work from the beginning of the 1990s to the beginning of the 2000s because women reduced their share while men increased their time in unpaid work. For couples with children, there is hardly any change; just a minor reduction of women’s time in unpaid work. Evidence is mixed as to whether the gender division of childcare is more equitable than the division of routine housework. Künzler and colleagues (2001) report that this is the case particularly in families whose youngest children have reached school age. Wengler and colleagues (2009) find that childcare is even more a women’s domain than routine housework. However, both studies conclude that time spent in paid work and gender role attitudes are the most powerful predictors of time spent in unpaid domestic work for both women and men throughout Germany. This suggests that equalizing women’s and men’s time spent in paid work, for instance by increasing women’s and reducing men’s time,

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is likely to result in a more equal division of housework and childcare. In addition, this redistribution of working time would be largely in line with parents’ desires (Holst and Wieber, 2014). A severe obstacle for a redistribution of working time between women and men is the presence of a gender pay gap. Taken together, before reunification, gender divisions in unpaid work seem to have been relatively unequal, although direct evidence is unavailable. The 1990s brought a shift toward less inequality, particularly among couples without children, while there was hardly any change among parents, which might be due to the high prevalence of part-time work among mothers. Attitudes toward gender roles Based on conventional indicators, attitudes toward women’s and particularly mothers’ employment and about the care of young children have become more favorable over time. It is difficult to sort out the causality between mothers’ employment and corresponding attitudes. Attitudes influence employment behavior, but at the same time, they are shaped by current and past employment patterns, and by enabling factors such as the availability and quality of childcare. Thus, it is clear that contemporary attitudes about gender roles are positively correlated with women’s and men’s employment behavior in the past (Braun et al., 1994). Figure 4.7 indicates that in 1991, almost 60 percent of the respondents in East Germany thought that a small child would suffer if his or her 60

50

40

% 30 agreed 20

10

0 1991

1996

2000

2004

2008

2012

Year It is much better for everyone concerned if the man goes out to work and the woman stays at home and looks after the house and children. It's more important for a wife to help her husband with his career than to pursue her own career. A small child is bound to suffer if his or her mother goes out to work.

Figure 4.7 Attitudes towards female employment, 1991–2012 Source: Blohm and Walter (2013)

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mother was in employment. This view was particularly prevalent among older respondents, perhaps a reflection of their own situation and the expectations to return quickly to the labor market after childbirth; moreover, social policies to reconcile employment and family were not very comprehensive at the time. By 2004, however, the share of respondents who agreed with this statement had halved.14 Women are slightly more supportive of female employment than men, there is a growing support with increasing education, and even married women who were actually not employed came to hold more favorable views over time. However, support for women’s employment seems to have levelled off at a high level by 2008, and there is no further increase anymore. In 2012, overall, 86 percent of the respondents shared egalitarian views on gender roles in East Germany, and 92 percent had a favorable assessment of the consequences of mothers’ employment on children, indicating a general social acceptance of maternal employment (Blohm and Walter, 2013).15 This high level of support can only be understood when taking into account secular changes toward a modernization of gender roles (Guetto et al., 2015). In East Germany in particular, the personal experiences of successive generations of coupled women and men in reconciling employment and family and the lower importance religion held might help to explain these data. The growing support for egalitarian gender role attitudes is no contradiction to the decreasing normative support of a dual-earner model with two full-time working parents because this model might not have been truly egalitarian regarding the division of domestic tasks and childcare. A modernized breadwinner with a part-time working mother is not only increasingly prevalent among parents but also in line with prevailing attitudes, and it is largely supported by social policies (Gangl and Ziefle, 2015).

Conclusions Following Crompton (1999a, 1999b), I have argued that dominant arrangements for dividing labor along gender lines vary across societies and even more within societies over time. In theory, divisions of labor vary from the highly genderdifferentiated “male-breadwinner/female caregiver” model to the gendersymmetrical “dual-earner/dual caregiver” arrangement depicted in Table 4.1. Before the unification between East and West Germany, East Germany had not achieved a gender-egalitarian division of labor and corresponding employment outcomes. On the eve of the fall of the Berlin Wall, East Germany could be characterized as a “dual-earner/state-caregiver” society, with two mainly full-time working parents and highly differentiated social policies, most notably an extensive provision of public childcare, in support of it. As the summary of labour market outcomes, given in Table 4.2, shows, there is an overall mixed balance. Policies adopted also because of economic necessity were quite successful in integrating women, even during childrearing years, into the labor force and enabling them to do qualified work. This changed women’s self-perception regarding their employment and gave them relative economic independence from their male partners. However, under

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Table 4.2 Gendered work outcomes in East Germany, before and after reunification Before reunification (late 1980s) Labor force participation

very high + hardly any gender difference Unemployment – Employment

Working time

Gender wage gap

very high + hardly any gender difference medium prevalence of part-time work (mostly among elderly women) medium

Occupational high sex segregation Women’s share moderate of unpaid work at home Attitudes toward gender roles

moderately supportive

After reunification (around 2014)

Direction of change

Main explanation

high + small slight gender difference disadvantage for women

women’s longer employment interruptions

slightly higher for men

slight disadvantage for men high + small slight gender difference disadvantage for women

reduction of male-dominated jobs in production elderly women’s disadvantage in employment

high prevalence widening of part-time work gender gap in (mostly among working time mothers)

strong support for part-time work among mothers

low

labor market exclusion of lowskilled women; differential wage gains across industries occupational restructuring

high

declining gender wage gap

hardly any change due to occupational inertia moderate slight change toward more equality among childless couples highly supportive change toward more egalitarian views

men’s higher share in housework among couples without children experiences with both partners’ employment across generations

the surface of an apparently similar labor force participation of women and men, inequalities regarding the rewards of paid work persisted over the whole period of state socialism. For example, a considerable pay disadvantage of women was facilitated by a high extent of occupational sex segregation. In addition, women carried a much greater share of unpaid work at home, exemplifying one of the basic contradictions of state socialism: while women were defined as mothers and workers, and became increasingly economically independent of their male

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partners, men’s breadwinning role was devalued, and there was no corresponding redefinition of men’s roles. After reunification, the two parts of Germany converged toward the “malebreadwinner/female part-time caregiver” arrangement with remainders of the previously dominant dual-earner model in the East. This resulted primarily from the transfer of social policies that partly encouraged re-familialization (e.g., generous leave regulations after childbirth), some voluntary reduction of women’s labor supply compounded by severe demand-side constraints that first disproportionally hit women and later men as well. The temporal developments show no unidirectional pattern with respect to varying dimensions of gender outcomes. While there has been hardly any change in the extent of occupational sex segregation, the overall gender wage gap has been declining, and the gender gap in working time has been widening. Obviously, gender inequality is multidimensional, and it changes at different paces in different domains. As the given explanations emphasize, the specific temporal developments depend on the social, normative, and economic context, as well as on institutional underpinnings. Moreover, the East German case clearly shows the context-dependent impact of social policies in at least two ways, economically and culturally. Social policies in support of re-familialization can only fully unfold their effect if economic conditions allow doing so. This potential seems limited by the weak economic position of men in East Germany, by the widespread perception of economic insecurity, and by the overall lower wages compared to West Germany. The cultural embeddedness relates to the idea that all social policies have normative foundations. To be effective, those normative convictions need to be shared by the population. Given the high support of gender egalitarian attitudes, it can be assumed that policies in favor of re-familialization are increasingly at odds with the needs and aspirations of women and men. Due to varying socio-economic and cultural conditions, similar policies still lead to different outcomes, as in the case of East and West Germany with respect to maternal employment. Whether future gender relations shift in a more or less traditional direction depends on the relative balance of supportive and hindering forces. Several factors favor the growth of gender-egalitarian policies, as well as changes in workplace practices and individual decision making. These include diverse pressures at the supranational level (e.g., EU), a rapidly aging and shrinking labor force, recent policy reforms that facilitate the reconciliation of work and family for both women and men, the continued erosion of the economic logic underlying the male-breadwinner model, rising qualifications among younger cohorts of women, and ongoing transformations of women’s and men’s gender role attitudes and care-giving preferences. Other factors are likely to impede the development of a “dual-earner/dualcaregiver” society in Germany in the near future. These include varied demandside factors that limit a fairer redistribution of working time and unpaid work among women and men, most important, a considerable gender wage gap, factors that increase selectivity into employment (e.g., an increasing educational divide

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between dual-earner and more traditional couples), institutional and/or political inertia (e.g., the maintenance of a tax system that directly penalizes wives’ fulltime employment), the overall inconsistency in policies to reconcile family and employment, and the persistent cultural tradition of subsidiarity in which parenthood and care work are viewed in highly privatized terms. Although enabling social policies to ensure gender symmetry are not sufficient alone, they are necessary. Insofar, the future depends in part on whether a cohesive policy package will be enacted that aims more strongly at de-familialization.

Notes 1 This chapter largely builds on a paper by Rosenfeld and colleagues (2004) and extends the empirical evidence on the extent of economic gender equality in East Germany to the most recent data currently available. 2 Based on population statistics, it is not possible to distinguish to what extent the same individuals moved between both parts of Germany, but evidence from social security data reveals that, since the 2000s, a considerable re-migration has occurred of younger, well-educated individuals to East Germany (Nadler and Wesling, 2013). 3 At the same time, West German women’s labor force participation rate was only 56 percent and was well less than men’s (82 percent) (Bothfeld et al., 2005). 4 Male labor force participation in Germany fully converged during the second half of the 1990s, whereas female labor force participation in West Germany was still slightly lower (72 percent in 2014) (Institut Arbeit und Qualifikation der Universität DuisburgEssen, 2015). 5 Despite this tendency, unemployment in East Germany is still about twice as high as in West Germany (Institut Arbeit und Qualifikation der Universität Duisburg-Essen, 2015). 6 Women and men who are temporarily not employed because of sickness or parental leave are counted as belonging to the working-age population. 7 Women’s employment rates in East and West Germany fully converged by 2014, whereas men’s employment rate in West Germany is slightly higher, at 79 per cent (Institut Arbeit und Qualifikation der Universität Duisburg-Essen, 2015). 8 There was also a paid housework day each month for all married women, mothers of children under 18, women or men who cared for dependents, women over the age of 40, and single fathers. Such policies thus granted societal recognition to housework, performed mainly by women (Dölling, 2002). 9 In 1989, in West Germany, 30 percent of women and an equally low 2 percent of men worked part-time (Bothfeld et al., 2005). 10 In West Germany, part-time employment among women was even more common (49 percent in 2014), but less so among men (10 percent) (Rengers, 2015). Still, major differences in working time exist between mothers between both parts of Germany (Holst and Wieber, 2014; Wirtschafts und Sozialwissenschaftliches Institut, 2015). 11 The gender wage gap is unadjusted, and is calculated as the difference between median earnings of men and women relative to median earnings of men. These earnings refer to gross earnings of full-time wage and salary workers (OECD, 2015). 12 It has been calculated as the percentage of difference between average hourly gross earnings of male and female employees, thus including part-time workers, and is unadjusted (Eurostat, 2015). 13 Data of the time-budget study for 2012–2013 have recently become available, but up to now there is no separate analysis of East and West Germany. 14 In West Germany, 76 percent of the respondents shared this opinion in 1991 and 49 percent still did so in 2012 (Blohm and Walter, 2013).

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15 In West Germany, 76 percent of the respondents shared egalitarian views on gender roles in 2012, and 74 percent considered mothers’ employment to have positive implications for their children (Blohm and Walter, 2013).

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5

Estonia Rein Vöörmann and Jelena Helemäe

Introduction Within the European Union, Estonia represents an interesting case in regard to gender inequality in the labour market for a number of reasons. In Estonia, the gender gap in employment is lower than the EU-28 average, due to higher levels of female employment. The impact of motherhood on women’s employment is substantial, and particularly so for mothers with very young children. Moreover, the gender pay gap and horizontal and vertical gender segregation in the labour market are amongst the highest in the European Union. Thus, Estonia is a country with low levels of gender inequality in terms of access to the labour market – participation is high especially for women without small children – but high levels of gender segregation within the labour market: although access to the labour market does not appear to be a major issue, the gender gaps that are present for people in work are substantial. It is important to understand how such patterns arise. In distinguishing access (female participation in major social institutions) from distributional (gender distributions within these institutions) patterns of gender inequality, Charles (2011) suggests that these arise from the varying effects created by forces for egalitarian change: for instance, in developed societies, some of the same structural and cultural forces that have facilitated female access to labour markets and educational systems have also contributed to sex segregation within these institutions. As in other developed Western and post-socialist countries, the position of women in the Estonian labour market is shaped by socio-economic, political and cultural trends. However, while the current labour market position of women in developed Western societies is influenced by demographic changes, the creation and development of the welfare state, structural changes in the labour market, changes in attitudes towards work and employment (Razzu, 2014), in Estonia, it is the relative strength, pattern and direction of these changes and their influences that are different: this is partially a consequence of the socialist legacy and the peculiarities of post-socialist transformations.1 Several theoretical frameworks have been proposed to explain changes in women’s position in the labour market during the post-socialist transformations.

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Women were considered one of the most disadvantaged groups, since the transition to capitalism failed to build on the gender equality advantage from the socialist legacy (Pollert, 2003). In this chapter we relate the Estonian experience of gender inequalities in the labour market to cultural, structural and institutional theories of gender inequality in the post-socialist labour market. The “re-traditionalization” thesis points to cultural mechanisms as affecting gender inequality in the transitional labour markets. According to this perspective, the prevalence of traditional gender role attitudes would bring about a return to the male-breadwinner family model. Women were expected to voluntarily withdraw from paid employment once the opportunity to choose the housewife role reappeared. Global cultural changes might counterbalance the forces towards re-traditionalization: the decreasing support for traditional roles is part of what Inglehart and Carballo (1997) characterize as “post-modernization” (Lück, 2006). Cultural forces are of great importance also for proponents of the “reserve army of labour” thesis: employers discriminate against women because of their cultural and traditional gendered views – citing, for instance, women’s family responsibilities (Motiejūnaité, 2010). Structural changes in the political and economic organization of society were considered the primary mechanisms affecting women’s labour market opportunities by proponents of the “market discrimination” thesis. With the disappearance of the socialist welfare state, the protection and enforcement of antidiscrimination laws disappeared as well. Under such circumstances, employers have real incentives to discriminate in favour of men or unmarried women without children (Heinen, 1995; Kotowska, 1995; Fuszara, 2000). While the aforementioned explanations predict women are more vulnerable than men in the labour market during the transition, according to the “revalued resources” thesis, some groups of women in post-socialist societies have certain advantages. This thesis, suggested by Fodor (1997), is structural and based on the evidence of job segregation. Women’s positions and work experience in the service sector, which was the least respected and most female-dominated sector of socialist economies, became important “revalued resources”: the expansion of this sector served to protect them from unemployment. Likewise, women also tended to have higher levels of education and experience in administrative positions than men, while men dominated manual jobs in heavy industry, which were contracting and rapidly losing their prestige. According to Glass and Kawachi (2005), these theories fail to explain how the strategies, character and timing of institutional reforms may affect women’s opportunities in both the short and long term. None of these theories adequately explains differences in employment trends across countries, and none provides an explanation for why such differences may occur. The authors therefore argued that differences in the character and speed of the reform process undertaken in post-socialist countries “will determine how, when and whether men and women will differently experience the effects of market reforms” (Glass and Kawachi, 2005). Institutional reforms, in turn, created preconditions for the way postsocialist societies adjusted to the impact of the global economy. Globalization

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has been suggested to have ambivalent, but mostly negative implications for women’s employment, largely depending on the country-specific institutional context, first and foremost its welfare state and employment regime (Blossfeld and Hofmeister, 2006). Women in post-socialist countries are considered “the most vulnerable with the most potential to gain and lose” (ibid.: 444). The following chapter is based on these conceptual positions and gives an overview of the different aspects of the relationship between the labour market and gender in Estonia. We start from the end of the 1980s, when Estonia was part of the Soviet Union, followed by an analysis of the developments of the independent state in the 1990s, and finishing with the 2000s, when Estonia joined the European Union. The main research question is: have the major sociopolitical changes the country experienced weakened or strengthened gender equality in the labour market in Estonia? We start from the institutional, structural and cultural changes as the backbone of labour market developments.

Institutional changes The welfare regime, employment relations, and educational, family and cultural systems all shape women’s labour market responses to changing global market pressures (Blossfeld and Hofmeister, 2006). These institutions affect the costs of having and raising children, the economic value of family responsibilities and the choices available between family activities and paid employment; this is why the responses to similar global market pressures are country-specific (EspingAndersen, 1999; Mayer, 2004; Blossfeld and Hofmeister, 2006). Different influences of international organizations on institution building in post-socialist Estonia, the weakness of civil society and the rather unusual government coalitions (for instance, between a social democratic party and right-wing parties) all contributed to the creation of a much more inconsistent institutional framework in Estonia compared to developed market economies. Certain tensions and contradictions appear in the institutional arrangements, policies and practices that we believe are peculiar to the country. Institutions’ signals are often rather controversial, producing a wide variety of women’s responses depending on their resources and attitudes. Regardless of their family status or motherhood, women are expected to be devoted full-time employees. At the same time, pro-natalist policies expect women to be devoted mothers, especially until their children reach the age of 3. Welfare state In Soviet Estonia, the state policy, the whole institutional framework and official ideology, supported full-time employment for women. The legal requirement to work, the necessity of two salaries to manage a household and the availability of public childcare services all contributed to this. In post-socialist Estonia, women’s full-time employment was no longer required by law or guaranteed by government policy. However, one of the most

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flexible labour legislations in the world (OECD, 2010), alongside a low level of support for those outside of the labour market, tends to push women into employment, resulting in high labour market insecurity for both men and women. In Estonia, flexibility is achieved through firing and hiring rather than using flexible forms of employment; women’s opportunities to combine paid and unpaid work are limited. Women have little choice but to either work full time or withdraw (at least temporarily) from the labour market (Eurofond, 2012). Estonian state family policies push women to withdraw from the labour market, being in clear contradiction with its overall liberal character. While liberal welfare states are typically “defamilistic” (Blossfeld and Drobnič, 2001), in the case of Estonia, aspects of familistic regimes have been found (Helemäe and Saar, 2006; Javornik, 2010). For instance, long parental leave survived from Soviet times and became part of the new gender contract in post-socialist Estonia, first of all because of pronatalist concerns. The duration of time women could spend at home on maternity leave was changed in Soviet Estonia, but more investments in its childcare policies came by the late 1980s (Javornik, 2010). By 1994, the duration of paid leave increased to 1.5 years (plus 1.5 years of unpaid childcare leave). Public childcare services for the youngest children were limited, especially for children under 3 (Javornik, 2010). During the transition, Estonia was part of a small group of countries where the coverage of financial provisions to families with children was kept fairly intact (Pascal and Manning, 2000; Iwinska-Nowak, 2011). But the number of childcare facilities was reduced, declining by 14 per cent (Orazem and Vodopivec, 2000: 285). Due to the decreased number of children, the share of children in daycare centres amounted to almost 70 per cent in the late 1990s (Ainsaar, 2001: 35). Currently, Estonia has a generous parental leave policy: a parental benefit is paid for a total of 435 days at the parents’ average monthly income of the previous calendar year. The greatest shortfall in childcare provision is for children between the ages of 18 months (when the parental benefit ends) and 3 years. In 2011, 19 per cent of children under 3 were enrolled in formal childcare, which is considerably less than in other EU countries. But the percentage of those over 3 who attend full-time childcare every week is considerably higher than in the European Union (Roosalu and Täht, 2010). Since the Estonian welfare state’s institutional arrangements do not support flexible employment, whilst the childcare system is mainly available for children over 3 and long parental leave with quite generous benefits is provided, the whole context favours parents, but in reality women stay absent from the labour market for long periods after the birth of a child.

Employment system The type of employment system (e.g. unions, collective bargaining systems, work councils etc.) influence the level of job security and how women experience (global) market pressures. Under state socialism, the employment of women was

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highly protected from economic turbulence, resembling a “ closed” system of employment relations. However, as the state was the main employer, social dialogue was irrelevant. Collective bargaining systems were underdeveloped, which is paradoxically a characteristic of “open” systems of employment relations. The Estonian transition to the market – characterized by so-called shock therapy – was aimed to radically deregulate employment relations and open the economy to the impact of market forces. The weakness of civil society, particularly of newly emerging social partners, against a backdrop of drastic reduction in labour demand, contributed to a situation whereby employers acquired extremely high power over a mostly non-organized labour force. Employers were free to violate regulations, while employees were not able to defend their legally protected rights for fear of losing their jobs. Job security had decreased; the mean tenure of prime-age women fell during the first half of the 1990s and remained about the same during the second half of the 1990s (Helemäe and Saar, 2006). The high degree of openness of the employment system, that is lack of protection against market pressures, might be illustrated by the fact that during the early stage of the transition to a market system, despite the rather rigid character of Estonian labour law of that period, both men and women were very mobile and a huge reallocation of labour occurred. Moreover, the Estonian system of open employment relations means that economically inactive people, especially women (but also young people), have difficulties (re)entering the labour market (Saar, 2005), while open employment relations are usually characterized by an easy (re)entry process (Mills and Blossfeld, 2005). It seems the institutional arrangements discussed earlier (unavailability of flexible work, long parental leave and scarcity of public childcare for families with children younger than 3) contribute to the creation of such barriers.

Education system In Estonia, men with university education outnumbered women in the workingage population until 1959, but the 1979 and 1989 Soviet censuses reported that women’s educational level was higher than men’s and increased more rapidly (Helemäe and Saar, 2006). The socialist education policy, which was directed towards an expansion of vocational education in order to increase the educational opportunities for underprivileged social classes, has had no effect on class inequalities, but has increased gender differences in educational opportunities (Saar, 1997; 2010). It occurred due to a deep differentiation of the secondary education system into vocational and academic streams (Saar, 1997) and a clear gender segregation by fields of study (Helemäe et al., 2000; Vöörmann, 2011). After obtaining basic education, girls were overrepresented among those continuing their education in academic secondary schools, while boys were overrepresented among drop-outs and students of vocational secondary education schools. The composition of the higher education institutions became feminized,

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as educational paths to university education went mainly through academic secondary education. The social changes of the early 1990s left the education system relatively intact. The education system retained a degree of stratification similar to that of the Soviet period, although the proportion of basic school graduates opting for a vocational track decreased (Saar, 2010). During the 1990s, higher education underwent rapid expansion, and this was accompanied by its further feminization. A decrease in the proportion of female students at the beginning of the 1990s was followed by an increase thereafter, so that in 2013 60 per cent of students in higher education were women. Gender segregation in terms of subject area is a legacy of the Soviet times that remains strong in the present. In recent years, the proportion of women in services and in health and welfare has been increasing particularly rapidly (Saar and Mõttus, 2013). Adult education In Estonia, the system of workers and executive directors’ training was established in the 1960s–1970s. Training of workers, technical employees and engineers (so-called specialists) was organized by the National Economy Board, and after its liquidation in the mid-1960s, training was included in the responsibilities of ministries. The organization of adult education and adult teaching, including continuing training, retraining and supplementary education, were mainly carried out by the universities. During the 1980s, a modernization of the theoretical, methodological and methodical bases of adult education took place (Märja, 2000). Since the early 1990s, adult education has become more relevant and is considered one of the factors behind social and economic change. According to the data of the Estonian Labour Force Survey, in 1997, more than 75 per cent of the respondents expressed the opinion that the new situation demanded constant self-improvement. Although half of the respondents argued that Soviet-era education was relevant to the new circumstances, in reality rapid structural reforms in the process of the transition to the market economy revealed inconsistencies between the knowledge acquired during the Soviet period and the world of work of the new era. From the beginning of the transition period, adult education and lifelong learning became one of the priorities for development. These processes coincide with a change in the paradigm of adult education in the mid-1990s. From then on, education and learning were considered an organic part of the working process (Jarvis, 2007), which was confirmed by the increasing number of participants over the years, as well as by their motives.

Family system Couples “do gender” through the ways in which they choose to divide work, avoid work and create work from among their available options (Bellah et al., 1985; Hochschild, 1989). These choices are influenced by constraints and incentives created by the institutional framework and the cultural context. The concept

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of a “gender contract“ helps to reveal the peculiarities of the Estonian family system as it emerged from the influences of institutional arrangements and cultural values and norms. Prior to the transition, the Estonian government, similarly to the governments of the whole USSR and other CEE countries, promoted an official gender contract that prescribed combining full-time employment with motherhood. Despite the official rhetoric of gender equality, the state was hardly concerned with the egalitarian everyday contract (for instance, the division of work within the family). Moreover, public support for mothers in paid employment was uneven throughout the socialist era, with political and expert discourses shifting between the “pro-worker” and pro-natalist positions (Kirschenbaum, 2001; Bicskei, 2006). No efforts were made to encourage men to take on any responsibilities for domestic tasks (Iwinska-Nowak, 2011). Communist ideology supported a normative gender contract that valued women’s participation in the paid labour force, although this participation did not have to be of the same value or intensity as that of men (Fodor et al., 2002). The division of work within the family (everyday gender contract) was extremely gendered (Iwinska-Nowak, 2011). In the post-Soviet period, the former official gender contract of the working mother continued to dominate, while becoming more differentiated in terms of female employment: work-oriented career woman, part-timer, stay-at-home mother (Rotkirch and Temkina, 1997; Hansson, 2011). In post-Soviet Estonia, gender equality is legally guaranteed not only by the 2004 Gender Equality Act, but also by other labour and family policies. Policy measures aimed at facilitating the reconciliation of work and family-related roles and supporting working parents (not just working mothers) are part of the official Estonian gender contract (Hansson, 2011). However, this new official gender contract is not without controversies, particularly with regard to the institutional arrangements discussed earlier. In reality, women in Estonia do follow an adaptive work-balance strategy. Financial pressures, created partly by weak collective bargaining and partly by weak social protection, are one of the possible factors behind the high women’s employment of institutional barriers to combining paid and unpaid work. It indicates that an approach to the understanding of women’s employment behaviour which is based on the complex influences of the country-specific institutional framework is of high relevance in Estonia. The high level of education and the availability of jobs in the public service sector may also favour women’s employment, as per Fodors’s “revalued resource” thesis.

Socio-economic context During the past 25 years, Estonia had to overcome major political, economic and social changes (Lauristin and Vihalemm, 1997; 2009). We distinguish three major periods: the end of the 1980s, 1990s and 2000s. Although each period could be divided into several sub-periods, this division helps us to give an adequate picture of the changes in Estonia.

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The end of the 1980s was characterized by the breakdown of the old political and economic system. Although by that time the first cooperatives were set up – examples of an economy based on private property – the socialist planned economy was still predominant. This meant total state control of all resources, infrastructures and employment, being part of an all-Union budget, belonging to the rouble zone and Russia’s market. All people had a right to work, and unemployment officially did not exist; similarly for social stratification. After Estonia regained its independence in 1991, a new constitutional and social order started to be developed, alongside the juridical and financial breakup from the Soviet system and a rapid turn to the West. Westernization included changes in almost all areas of social life (Lauristin and Vihalemm, 1997). Economic reforms were carried out in a radical and comprehensive way, the transition to a market economy occurring quickly compared to several other post-socialist countries. However, this was also a time when the economy experienced a deep economic downturn: the European Bank for Reconstruction and Development (EBRD) estimated that between 1990 and 1994, GDP fell by 38 per cent (Kukk, 2014), which greatly impacted the Estonian labour market. Of the post-socialist member states of the European Union, Estonia stands out as a country with a substantial loss in employment, which did not fully recover before the 2008 crisis (Fodor and Nagy, 2014). Some argued that this was due to the rapid privatization process (Scharle, 2012). In the first half of the 1990s, about 100,000 people left the labour market; two-thirds of them left Estonia (Eamets, 1996). The introduction of a market economy and the formation of entrepreneurship and capitalist market relations brought an increase in real incomes; however, they also led to a rapid rise in income inequality. During the years 1990–1992, income inequality increased remarkably: the Gini coefficient rose from 0.23 to almost 0.38. So the social cost of reforms in Estonia was very high. According to a NordicBaltic survey of living conditions, families reported feelings of deprivation in terms of their capacity for preserving a certain lifestyle or consuming certain goods and services (Lauristin, 2003). In 1999, 13 per cent could not afford meat, chicken or fish at least three times a week; 11 per cent could not cover urgent medical expenses; 72 per cent could only dream about a week’s holiday abroad; 47 per cent could not afford to buy fashionable clothes; 26 per cent had to give up visits to theatres, cinemas or concerts once a month; 20 per cent could not afford to host friends (Living Conditions, 2000). The second half of the 1990s was characterized by rapid economic growth and continued restructuring of the economy. Growth in social inequality continued; particularly affected were underprivileged ethnic minorities, persons with low levels of education and residents of rural regions (Emign et al., 2001). Poverty was equally distributed between men and women: in 1997, the absolute poverty rate was 29 per cent for men and 31 per cent for women. Subsequent years were characterized by strong average economic growth, but also by considerable volatility across the business cycles (Masso et al., 2014).

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Estonia had one of the highest growth rates in the European Union in the 2004–2006 period (e.g. in 2005–2006 about 10 per cent), but also the deepest decline in 2009, almost 15 per cent (Eurostat).2 Due to the open character of the Estonian employment system and the poor social protection, the latest economic crisis had a severe impact on the labour market. Similar to the period of transition, in the 2008 crisis, Estonia (together with Latvia and Lithuania) had the largest job losses among Eastern European countries (Fodor and Nagy, 2014). Moreover, in 2011, the Gini coefficient decreased to 0.26, but this should not lead to the conclusion that all social groups benefitted in the same way from increased income equality, as demonstrated by the continued segregation of the labour market and the considerable gender wage gap. The 2000s were also characterized by emigration. The 2013 Eurobarometer Survey revealed that 15 per cent of the Estonian population aged over 15 had worked or had been working abroad. This compares to 9 per cent for the European Union as a whole (Tarum, 2014). It is worth pointing out that, overall, the whole period since the transition from a socialist economy and the restoration of independence resulted in high levels of satisfaction in different areas. For instance, a worldwide Gallup poll conducted in 2009 revealed that more than half of the population of Estonia was satisfied with their freedom of choice, a higher proportion than in Latvia and Lithuania, but still significantly behind the Nordic countries (Vihalemm, 2011). According to the Bertelsmann Foundation Transformation Index,3 Estonia ranked third in 2013 in their Status Index, which ranks countries according to their quality of democracy and market economy. The only postsocialist country that outpaced Estonia was the Czech Republic. The year 2013 wasn’t an exception as Estonia has shown stable performance over the past 10 years.

Continuity and change of values Decline in gender inequality and progression towards a culture supporting gender equality are usually approached as part of wider cultural shifts towards egalitarian values. Inglehart and Norris (2003) relate the decline of the traditional family and growing access to employment and education with the first phase of modernization (from agricultural to industrial society) and a transition from traditional to secular-rational values. They link the rise of gender equality with the second phase of modernization from an industrial to a post-industrial society and a transition from survival to self-expression values. According to the data of the World Values Surveys, Estonia, together with Russia, Bulgaria and Ukraine, represents societies with high scores in secularrational and survival values (Inglehart and Welzel, 2005). Thus, the wider cultural context in Estonia supports equality of access and rejects discrimination, while at the same time supporting sex segregation within the household and more traditional gender roles.

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With regard to attitudes towards gender equality in access to employment and the importance of non-discrimination on gender grounds, the Estonian population has made significant progress since the 1990s. Kasearu (2013) has shown, using the European Values Study, that in the period between 1990 and 2008, support for women’s equal right to employment has grown more than in other CEE members of the European Union. But Estonia is still lagging behind Western European countries, especially Scandinavian countries. The support for employment as a precondition of women’s economic freedom4 has also increased: in 1990, only half of men and 60 per cent of women agreed, while by 2008 this proved a widely shared opinion of both men (almost 80 per cent agreed) and women (more than 80 per cent agreed). Female employment as an economic necessity5 was widely acknowledged already in 1990 (about 80 per cent of both men and women agreed); by 2008, the share approached 90 per cent among women and 85 per cent among men. The Estonian Gender Equality Monitoring (EGEM) 2013 demonstrated that 92 per cent of respondents supported equal pay for equal work. There is much less agreement with regard to attitudes towards segregation in the labour market, gender roles and sharing of household responsibilities in Estonian society. With regard to the labour market, EGEM data show that only 38 per cent said that there should be more women among senior executives and only one-third thought that men and women have similar abilities. As regards gender roles, Motiejūnaité (2008) has found that while between 1990 and 1997, the proportion of “traditionally” minded people dropped in all Baltic countries and in both parts of Germany, in 1999, “traditionalism” rose in Estonia. Data from the European Values Study also show continuing ambivalence towards employment when its importance is compared with the value placed on traditional gender roles. For instance, in 1990, 84 per cent of women supported the statement “A job is alright, but what most women really want is a home and children”; in 1999, it was 66 per cent, and in 2008, it was 67 per cent. This might be understood as the expression of the aforementioned low degree of post-modernization of value consciousness of the Estonian population. Gender culture in Estonia is not so traditional as to reject the importance of equal access to employment. In this sense the predictions of the “re-traditionalization” perspective seem implausible. But attitudes towards gender segregation and gendered division of labour are less supportive to gender equality, which might be partly explained not so much by “tolerance towards inequality” as pro-natalist concerns. Analysis of the EGEM data reveals clusters of the Estonian population with varying patterns of support for different types of gender inequality (Toimetanud Triin Roosalu, 2014). Only 22 per cent of the total population shows comprehensive support for gender equality in both private and public spheres. Another cluster (21 per cent) reveals attitudes in support of gender equality in the public sphere, but not in the private one, which could be interpreted as a favourable attitude towards traditional gender roles in housework and parenting. However, the largest segment (29 per cent) of the population supports gender equality in

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private life, but not in the public sphere. This should create favourable conditions for the justification of the gender wage gap. Other clusters are even smaller: 10 per cent of the population agrees that girls and boys should learn different skills. The members of this group also state their preference for hegemonic masculinity, which could be thought of as stressing fathers’ role in children’s upbringing.

Division of labour within the household Feminist scholars argue that gender equality is only possible when, in addition to an increase in labour market opportunities for women, the unpaid work in the home is distributed equally amongst partners (Ciccia and Bleijenbergh, 2014). Society is viewed as gender egalitarian if paid and unpaid work are equally valued (Fraser, 1994; Crompton, 1999) and the redistribution of unpaid work between a wide range of actors (men, women, families, the state and the market) is supported (Gornick and Meyers, 2009). Figure 5.1, using data from the “work, home and leisure” survey, reports the percentage of men and women of working age who considered family and work, respectively, very important. Higher proportions of both men and women considered family more important than work. But this similar preference for family over work does not presuppose equal sharing of both responsibilities between men and women either in Soviet times or in the contemporary Estonian Republic. The normative gender contract does not consider women free to choose between family or work responsibilities, at either the level of society or the level of a married or cohabitating couple. Societal values which consider women responsible for family and household care duties are still very much present in Estonia and remain dominant among 100 90 80 70 60

Women: Family

50

Men: Family

40

Women: Work

30

Men: Work

20 10 0 1985

1993

1998

2003

2008

Figure 5.1 Importance of family and work by gender, 1985–2008 Source: Hansson (2010: 42)

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Table 5.1 Indicators of a “normative contract,” married or cohabiting couples, 2010 Indicators of a normative contract – agreed with the statement

Type of everyday contract Both full-time paid work Male full-time, female not working Age groups All 25–54 years of age The whole population

Family as prime responsibility of women a

Men’s priority in right to jobb

Commitment to paid work c

Men

Women

Men

Women

Men

Women

45 40

41 51

16 16

15 15

43 43

53 61

46 52

47 52

18 26

15 24

41 43

56 53

Source: Authors’ own calculations on European Social Survey in Estonia, 2010 a “A woman should be prepared to cut down on her paid work for the sake of her family.” b “When jobs are scarce, men should have more right to a job than women.” c “I would enjoy having a paid job even if I did not need the money.”

both men and women (Table 5.1). At the same time, this norm is to some extent balanced by the negative attitudes towards gender discrimination in the labour market in terms of access to jobs, especially among prime-age people: only one in four supports these discriminatory attitudes, which is still a higher proportion than the EU average (Kasearu, 2013: 76). Such a normative context influences both everyday and normative contracts at the family level. Although some suggested that “the traditional division of labour at home seems to be giving way to a more shared division of domestic work” (HaavioMannila and Rannik, 1987) during the late 1970s and 1980s, Table 5.2 indicates this conclusion was premature. Changes over time have been in fact minimal: the percentage of households where the couple shared routine tasks, such as preparing meals and washing dishes, remained small. According to data of the EGEM 2013, the actual division of household tasks and responsibilities does not differ by whether married or cohabiting couples have children. Although the amount of housework is usually larger for families with children than in childless households, this did not bring about more equal sharing of routine tasks. The growing bulk of work was still mainly women’s responsibility. The only exception seems to be shopping (Table 5.3). This is similar to the situation during Soviet times: men’s participation in household work did not grow with the size of the family, while women’s share showed a considerable increase (Kelam, 1986). Data also illustrate the biased nature of subjective evaluations: women tend to perceive division of household tasks as more unequal than men do.

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Table 5.2 Division of household tasks, 1985–2013 Percentage of respondents who answered that household tasks are shared equally

Shopping, buying food Cooking Laundry Cleaning the house Building and repair work Repair of appliances

1985

1993

1998

2013

29 11 10 28 13 na

23 10 5 16 6 1

27 13 7 17 14 1

27 15 6 21 11 4

Sources: Authors’ own calculations on Everyday life and radical social changes in Estonia (Ed. A. Narusk), 1995: 120–121; Argielu Eestis (Ed. A. Narusk), 1999: 49; Database of EGEM 2013

Table 5.3 Division of household tasks among married and cohabiting couples, 2013 Respondents who answered that household tasks are shared equally % Married or cohabiting couples without children

Financial matters (household budget) Shopping, buying food Cooking Laundry Cleaning the house Dishwashing Building and repair work

Married or cohabiting couples with children

All respondents

Men

Women

All respondents

Men

Women

34

36

33

39

40

48

35 22 9 29 23 15

39 24 6 31 25 11

30 20 12 27 21 20

44 20 8 31 21 14

53 24 14 42 22 14

35 16 3 20 20 14

Source: Database of EGEM, 2013

The time-use surveys provide less perception-biased data about everyday gender contracts. In 2010, women aged 20–74 spent a total of 7 hours and 19 minutes a day on all types of work. For men, different work duties took up 6 hours and 28 minutes of their day. A large portion of women’s occupied time is unpaid time (56 per cent). Men, conversely, are more engaged in work activities outside the home, spending 60 per cent of their occupied time in this manner (Tasuja, 2011). The level of education has no influence on the division of household work between women and men, but it does influence the total volume of work. As people with higher education are more likely to be employed, the time spent on employment activities increases at higher levels of education. On the other hand, age matters: the largest workload has been observed in the case of women as well as men aged 25–44, which coincides with active childcare (Tasuja, 2011). Generally parenthood brings a more traditional division of housework

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between women and men. For men, children were found to increase time spent on paid work, whereas for women children were found to increase time spent on unpaid work (Hook, 2006), and this increase is usually greater than the corresponding male increase. The Parental Benefit Act of 2003 represented an important social policy in Estonia. In fact, according to this Act, parental leave can be either shared between parents or used by mothers only.6 This was the first time social policies encouraged mothers and fathers to negotiate who would focus on childcare and who would concentrate on paid work (Pajumets, 2010). A number of authors have stressed the potential of parental leave policy for changing the behaviour of fathers and ensuring greater gender equality (Gornick and Meyers, 2003; Ellingsaeter and Leira, 2006; Ray et al., 2010). But as the data from the years 2004–2010 show, although the share of men taking parental leave has increased, it is still small. While in 2004 the share of fathers who received parental benefits was 2 per cent, in 2011 it was a little bit higher, but still a modest 6 per cent (Biin et al., 2013). Division of paid and unpaid work between couples is also an important aspect of the everyday gender contract. Table 5.4 shows that couples arrange division of paid and unpaid work in different ways, but among prime working-age (25–54) couples, the double-earners model clearly dominates. The male-breadwinner model together with full-time male and part-time female wage earners is also widely represented (more than 35 per cent of prime-age couples), while female-headed couples make up only less than 10 per cent of prime-age couples. As made evident in the literature, in all family types, the average time men devote to housework tasks is about the same. The (double) Table 5.4 Average hours per week spent on unpaid and paid work among married or cohabiting couples aged 25–54, 2010 Type of contract

Unpaid work Men

Both full-time paid work Male full-time, female part-time Male full-time, female not working Female full-time, male part-time Female full-time, male not working Other All couples N

Women

Paid work Men

Women

Total workload Men

%of type of contract

Women

11 12

17 21

45 50

42 22

56 62

60 44

45 7

11

28

45

22

56

50

28

12

12

29

41

41

53

1

15

16

22

44

37

60

7

15 12 543

22 21 548

29 42 547

25 34 559

47 54 523

48 55 541

12 100 570

Source: Authors’ own calculations on data of the European Social Survey in Estonia, 2010

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burden of adjusting paid to unpaid work is largely women’s responsibility. Nevertheless, the transition has hardly influenced the everyday gender contract. Just as throughout Europe (Röhler and Huinink, 2010; Sani, 2014), in Estonia, housework is still mostly considered a female duty.

Main trends in the Estonian labour market Developments in the political, economic and social life of Estonia for more than 25 years, which we have discussed in the earlier parts of this chapter, have caused remarkable changes in gender equality in the labour market. At the end of the 1980s, the employment rate of men was 82 per cent and that of women 71 per cent, but as a result of the rapid economic reforms and restructuring of the economy, related to the process of economic transition, a lot of people lost their jobs. One of the reasons for that was a sharp decline in demand for labour (Paas et al., 2002). This took place in particular in the state sector. Although new jobs were created in the private sector, this was a time-consuming process and required extensive retraining and reorientation of labour. At the beginning of the 1990s, fewer jobs were created than lost and this led to an increase in unemployment (Rõõm and Viilmann, 2003). The private sector started to grow more rapidly in 1993, and, for the first time, the number of men working in the private sector exceeded those working in the public sector. This process took place among employed women some years later. In the 1990s as well as in the 2000s, the share of women employed in the public sector was higher than the share of men; in the 2000s, it was almost 70 per cent. Men, on the contrary, were more likely to be employed in the private sector. Such division has direct implications in terms of the gender pay gap. Labour market adjustment was partly attained by decreasing the supply of two groups of individuals in the labour force: some women turned to unpaid caregiving, while those of pension age were pushed away from the labour market, thereby lowering the inter-age competition among women (Helemäe and Saar, 2006). By the end of the twentieth century, this form of adjustment was completed. At the same time, the shadow economy started to emerge, with a considerable number of people engaged in the illegal labour market, especially in construction, agriculture and services (Eamets, 1996). The structural changes in the course of the transition process had an impact on the employment of men and women: Figure 5.2 shows that, in 2000, the employment rates of men and women were even lower than in 1995, 61 per cent and 54 per cent, respectively During the transition process, the share of working women and men decreased also in other Eastern European countries (Rutkowski, 2006). At the same time, the employment rates of men and women in Estonia remained higher than in most Western European countries (Vöörmann, 2000a). At the beginning of the new century, the employment rates of men and women started to grow again, and this trend lasted until the beginning of the global economic crisis in 2008. The new rise in employment began in 2011, and by

Estonia

115

90 80 70 60 50

Men

40

Women

30 20

2014

2013

2011

2009

2007

2005

2003

2001

1999

1997

1995

1993

1991

0

1989

10

Figure 5.2 Employment rate of men and women aged 15–69, 1989–2014 Source: Estonian Statistical Office

the year 2014, the male employment rate reached 70 per cent and the female rate was 63 per cent. The high employment rates are sometimes viewed as proof of the successful transition Estonia underwent since the 1990s (Rutkowski, 2006). Therefore, the gender gap in employment narrowed from almost 11 percentage points in 1989 to just below 7 percentage points in 2014. But differences occur by age groups. The gender gap in employment increased among working-age people (25–49), from 7.7 percentage points in 1989 to 12 percentage points in 2014. Among the youngest (15–24) and eldest (50–69) groups, the gender employment gaps are, respectively, 1.5 and 1.9 percentage points. Figure 5.3 shows how the unemployment rate steadily increased in Estonia from the end of the 1980s, from 0.6 per cent up to 17 per cent in 2010, which was the highest level during the whole period under consideration. During the transition, particularly in the early stages of the process, higher unemployment indicators are usually considered as intrinsically linked to the restructuring process, often even an indication of its scope (Rõõm and Viilmann, 2003). In 1992–1994, the first waves of dismissals affected women more than men (Eamets, 2001), but all in all in the first half of the 1990s, the unemployment rates of women were almost the same as those of men; from 1995 onwards, the male rate was higher than the female rate, a consequence of the restructuring process. Figure 5.3 shows that, by 2014, the male and female unemployment rates converged again. The largest difference over the whole period, however, was in 2009, in the aftermath of the financial crisis. One of the reasons is found in the jobs men and women do: men tend to work in sectors which are more affected by recession (primary and secondary sectors)

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18 16 14 12 Men

10

Women

8 6 4

2014

2011

2013

2009

2007

2005

2003

2001

1999

1997

1995

1993

1991

0

1989

2

Figure 5.3 Unemployment rate by gender, 1989–2014 Source: Estonian Statistical Office

whilst women are employed in more stable sectors (health, education, culture etc.) which are less affected by economic downturns. One of the most serious problems in Estonia is the high unemployment rate of young people (aged 15–24). During the period under consideration, the unemployment rate of young men ranged from 7 per cent in 1992 to 36 per cent in 2010; in 2014, it was 19 per cent. Young women’s unemployment rates ranged from 8 per cent in 1992 to 30 per cent in 2010. In 2014, it was 10 per cent. Long-term unemployment (12 months or more) is also of great concern in Estonia as in many other EU countries (Machin and Manning, 1999; Andersen, 2002; Jurajda and Münich, 2002). This was observed from the beginning of the 1990s (Marksoo, 2011). There have been two waves of very high long-term unemployment in Estonia during the years 1989–2014: the first after the Russian economic crisis in the year 2000, and the second during the global economic crisis in 2008–2010. Long-term unemployment rates are similar between men and women, usually only slightly lower among women, but at the peak of the recession this gender gap tends to widen. It indicates also that men are influenced more by recession than women, male-dominated jobs being more sensitive to economic cycles than female jobs. Figure 5.4 (panel a for men and panel b for women) shows, for both men and women, the substantial employment loss that occurred until 2000, followed by some recovery during the economic boom of the early 2000s and an abrupt reaction to the world economic crisis of 2008. For both men and women, adjustment to the changing economic context is achieved through changes in unemployment. But men are more vulnerable to decreasing demand for labour, their share of unemployment fluctuating to a greater extent than is the case for women.

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Men 50 45 40 35 Unemployed,% 30 Inactive,% 25 20 15 10 5 0 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2014

Women 50 45 40 Unemployed,% 35 30 Inactive,% 25 20 15 10 5 0 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2014

Figure 5.4 Share of non-working persons aged 15–69, 1989–2014 Source: Estonian Statistical Office

Economic cycles have less direct impact on the inactivity rate: the overall increase in men’s inactivity is largely attributed to increases in the involvement in studying, especially during the economic boom of the early 2000s. The share of inactive persons among men increased until the middle of the first decade of the 2000s and started to decrease amidst the economic boom, but increased again during the past recession. Changes in female inactivity are less pronounced than those of men. The share of inactive persons among women increased until 2000 and started to decrease during the economic boom. The economic crisis of 2008 hardly changed this pattern. The steady increase in involvement in studies countered by the steady decrease of the share of retired persons is the main driving force behind the

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Household without young child

Household with young child

dynamic of female inactivity. The share of those inactive for family reasons (being on parental leave or involved in caring) among inactive working-age women was stable over time: between 18 per cent and 22 per cent during 1993–2011 (higher only in 2009 at 24 per cent). After 2012, this share increased to 26 per cent. Parental leave is a more significant reason than caring. The employment rate of women with children is considerably lower compared with men who have children: in 2012, in households with at least one child under the age of 17, 92 per cent of fathers aged 20–49 were employed, while only 67 per cent of women were. But when the child was under the age of 2, the corresponding rates were 91 per cent and 23 per cent. Figure 5.5 shows that the probability of labour force participation of women with a child under 2 is significantly lower compared not only with men in the same type of households, but also compared with women without such a child. That the probability of labour force participation for women without small children is even higher compared with men from the same type of household is a strong indication of a “motherhood penalty” in the Estonian labour market. Similarly, the unemployment risk for women with children under 2 is significantly higher than that of women without small children and of men, as shown in Figure 5.6. The latter is in sharp contrast to the general evidence of women’s lower unemployment risk compared with men. Evidence also suggests that the experience and length of maternity leave is a significant risk factor for women’s future careers (Roosalu and Täht, forthcoming). The data show that the re-traditionalization thesis is hardly applicable to the Estonian case: women do not withdraw from the labour market despite traditional

Men

Women

Men

Women 0

0.2

0.4

0.6

0.8

1

1.2

Figure 5.5 Probability of labour force participation by gender and presence of small child in household, 2012 Data source: Authors’ own analysis based on the Estonian Labour Force Survey 2012 Note: Probabilities are calculated on the basis of the logistic regression model.

Household without young child

Household with young child

Estonia

119

Men

Women

Men

Women 0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Figure 5.6 Probability of unemployment by gender and presence of small child in household, 2012 Data source: Authors’ own analysis based on the Estonian Labour Force Survey 2012 Note: Probabilities are calculated on the basis of the logistic regression model.

attitudes towards gender roles. Theories that consider women victims are also questionable. It seems that those who are confident that overall gender equality in employment has deteriorated as a result of societal change (Iwinska-Nowak, 2011) are only partly right. The Estonian case appears to be in line with more nuanced approaches to gender inequalities in the labour markets of post-socialist societies (Fodor and Nagy, 2014). In particular, parental status has a strong influence on women’s position in the labour market (Glass, 2008). This fits with attitudes that see women as caregivers in the Estonian value system. This prevalent attitude also resonates with pro-natalist concerns and is supported by family policies, as discussed earlier. The result is that the impact of motherhood on the employment of women is substantial. Horizontal and vertical gender segregation Indicators such as the rate of employment and unemployment provide considerable information on the chances of entering the labour market, but give us very little evidence on the structure and quality of workers’ participation. In order to analyze the structure and quality of men’s and women’s position in the labour market, it is necessary to use other indicators, for example the level of gender segregation in the labour market. To avoid a unidimensional approach, we make the analytical distinction between two forms of distributional inequality: horizontal segregation and vertical segregation. Horizontal segregation refers to segregation across the manual–non-manual divide, specifically women’s underrepresentation in manual occupations and their overrepresentation in non-manual occupations.

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Vertical segregation refers to hierarchical inequality, specifically men’s domination of the highest-status occupations within the manual and non-manual sectors of the economy (Charles and Grusky, 1995; Grusky and Charles, 1998). In Estonia, the tendency for women to be clustered in low-paid, less prestigious jobs was evident already in the 1960s. After the 1950s baby boom, women returned to the labour market where they were recruited in low-paid sectors, including education and social work. Panels a and b in Figure 5.7 show how the restructuring of the economy resulted in a rapid decline in employment for both men and women in the primary sector, among men about five times and among women seven times. In 1989, the employment of women in both the primary and secondary sectors was lower than that of men. The majority of men were employed in the secondary sector. Conversely, women were more likely to be employed in the tertiary sector,

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2014 Primary

Secondary

Tertiary

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2014 Primary

Secondary

Tertiary

Figure 5.7 Male and female employment by economic sectors, 1989–2014 Source: Authors’ own calculations on Estonian Statistical Office

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121

constituting more than half of all women employed. The share of men employed in the service sector made up a little less than one-third of all men employed. The share of men employed in the secondary sector in 2014 remained the same as in 1989. The share of women in that sector decreased steadily. The share of employment in the tertiary sector has grown remarkably among men as well as women. At the beginning of the economic reforms, the tertiary sector was the largest employer for women. During the 1990s, it became the largest employer of men as well. But the growth in the share of women was more rapid than that of men: in 2014, more than 80 per cent of women were employed in the service sector. In addition to the fact that men and women are distributed unequally by industries, they are also unequally distributed by occupations, first of all by managerial positions (a reflection of the glass ceiling effect). The largest share of men during the period under consideration was employed as blue-collar workers: 60–72 per cent overall. The second largest occupation included higher white-collar workers (22–27 per cent) and the third lower whitecollar workers (6–15 per cent). Among women we find the same occupational ranking, but the shares are different: 43–52 per cent of women were employed as blue-collar workers, 24–33 per cent as higher white-collar workers and 23–29 per cent as lower white-collar workers. The share of women in the group of higher white-collar workers stayed stable during the whole period under consideration, and constituted in 2014 more than half of this group. The representation of women in the higher white-collar group could be explained by their higher level of education compared with men, although a big share of people with higher education is employed as blue-collar workers in Estonia (Kazjulja and Saar, 2014). Figure 5.8 shows the extent of both sector and occupation gender segregation as measured by the Duncan Index.7

60 50 40

Sector segregation

30

Occupational segregation

20

0

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2014

10

Figure 5.8 Horizontal and vertical gender segregation, 1989–2014 Source: Authors’ own calculations

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During the time under consideration, the horizontal gender segregation index fluctuated between the values 0.31–0.38. This means that to achieve a balanced gender structure in jobs, approximately 40 per cent of (fe)male employees had to change the sector they worked in. This is similar to values in some Western countries in the 1990s: 0.29 in Switzerland, 0.31 in Austria, 0.32 in Germany, 0.33 in Australia and 0.34 in the United States (Blau and Kahn, 1996). Occupational gender segregation is characterized by the vertical gender-based distribution of employment. Men make up the majority among skilled and unskilled manual workers, and they are clearly overrepresented among managers and legislators. This was the case also during the Soviet period. In the 1980s, women’s share among senior executives was less than half – 41 per cent. The probability that women could become senior executives was 2.5 times lower compared to men. However, the proportion of women among professionals with tertiary education was almost 60 per cent (Roots and Vöörmann, 1987). Looking at the index of occupational segregation, it is evident that the gender-based division of occupations has been rather deep in Estonia, even during the Soviet era. At the end of the 1980s, the index was at 0.49, which was followed by decline and then stabilization for 10 years at the level of 0.41–0.43. In the 2000s, the index fluctuated from 0.40 to 0.46. In other words, more than 40 per cent of all employed persons in Estonia had to change their occupations in order to reach an equal gender distribution. But Estonia is not an exception; the values of the occupational gender segregation index were very close to those in several Western countries, for example in Australia it was 0.38, in Austria 0.40, in Germany 0.42 and in the United Kingdom 0.44 (Blau and Kahn, 1996).

Gender pay gap Female pay was lower than male pay under communist rule, which compressed wages and forced near full labour force participation (Brainerd, 2000). During the Soviet period, basic wages were regulated by means of wage rate scales which were specific for each industry. Those scales reflected the importance of the industry in the economic system of the Soviet Union. Heavy industry was superior to light industry (respectively, production of means and production of goods), and the latter was in turn superior to such “non-productive” spheres as education, social system, health care and trade. In 1989, in Estonia the average wage in education constituted 66 per cent and in health and culture 61 per cent of that in heavy industry where men dominated. Although the wages were lower in education or culture, women often chose those professions as they could have shorter and more flexible working hours. As part-time work was limited under the Soviet Union, this was the only means by which women could reduce their total working time (Chapman, 1991). Figure 5.9 shows that Estonia stands out among European countries for its high gender wage gap: according to Eurostat data, in 2013, men earned on average 30 per cent more than women, the largest gap in Europe (Figure 5.10). In 1989, the gap was the same – and other sociodemographic and occupational

Estonia

123

35 30 25 Estonia

20

EU average 15 10 5 0 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2013

Figure 5.9 Gender pay gap, Estonia and EU average, 1994–2013 Source: Eurostat

25 20 15 Secondary education Tertiary education

10 5 0 Men

Women

Men

1997

Women 2005

Men

Women 2014

Figure 5.10 Lifelong learning by gender and education, 1997–2014 Source: Authors’ own calculations

characteristics were similar (Philips, 2001). During the first years of transition, the gender pay gap decreased in Estonia (Anspal et al., 2010). Vöörmann (2000b) showed that in the mid-1990s in Estonia, the gender wage gap was approximately 25 per cent. But since the early 2000s, the gender pay gap has started to increase (Anspal et al., 2010). While during Soviet rule Estonia was not an exception – the gender pay gap was also high in other socialist countries – the country became an exception at the beginning of the 2000s when in other CEE countries

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the gender pay gap decreased. This applied to all economic sectors (Anspal et al., 2010: 61). The gender pay gap is more than one-fourth in all age and education groups, and in one group (secondary education with vocational education, age group 30–39), it even exceeds 40 per cent. The gender wage gap is the smallest among people with higher education. About one-third of the gender wage gap in Estonia could be explained by differences in male and female human capital (Anspal and Rõõm, 2011). A large proportion (up to two-thirds) of wage differences is often attributed to discrimination against women in the labour market. Discrimination has been seen as the basis for the gender wage gap also in economic approaches such as those of Becker (1957). It can be divided into direct and indirect discrimination (Tomei, 2003; England, 2005; Thomson, 2006). Although in Estonia there are cases of direct discrimination, which is evidenced by the appeals of women to the Gender Equality and Equal Treatment Commissioner,8 indirect discrimination appears to be more prevalent. Such a situation is usually viewed as the result of restricted opportunities available to women. This might be the reason women compared to men earn an average of 20 per cent lower wages, despite levels of education, occupation and employment status, as revealed from the latest Estonian Labour Force Survey in 2014. An important source of the gender pay gap in Estonia is horizontal and vertical segregation (Anspal et al., 2010; Espenberg et al., 2014; Vassil et al., 2014), but their impact far from explains the entire pay gap. Moreover, due to childbirth, women have a higher degree of career interruptions than men and do not work overtime as much as men (Anspal et al. 2009). Inequality in the division of labour within the household is also an important source of the gender pay gap. In Estonia, studies have shown the existence of a motherhood penalty: women with children earn on average less compared to their female colleagues without children, while this difference is not statistically relevant for men (Anspal et al., 2010; Espenberg et al., 2014; Vassil et al., 2014). Moreover, the negative impact of children on women’s wages would probably be even greater, because it is the mothers, whose potential wages would be lowest if they worked, who are absent from the labour market the longest due to childcare (Anspal et al., 2010). Very limited help with childcare, including a shortage of preschool childcare institutions, has created a situation where women have no choice but to accept low wages compared with their male colleagues (Vassil et al., 2014). Gender equality requires collective actions for promoting equality in several areas, as we pointed out previously. It should also be taken into consideration that gender equality in pay is difficult to achieve while inequality still prevails in many other areas.

Women and men in lifelong learning Since the 1990s, women across the European Union have been participating in continuing training more actively than men (Simpson and Stroh, 2002; Jones

Estonia

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Household without child

Household with child