Intergenerational Responsibility in the 21st Century 2018945718, 9781622735235, 7188778871, 2122295724

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Intergenerational Responsibility in the 21st Century Edited by

Julia M. Puaschunder The New School Columbia University Princeton University George Washington University Schwartz Center for Economic Policy Analysis

Series in Economic Development

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To future generations

Julia M. Puaschunder* The New School, Department of Economics, Schwartz Center for Economic Policy Analysis, 6 East 16th Street, 11th floor 1129F-99, New York, NY 10003, United States, [email protected], T 001 21222957004905, M 001 7188778871, F 001 2122295724, [email protected], http://juliampuaschunder.com/ Columbia University, Graduate School of Arts and Sciences, 116th Street Broadway, New York, NY 10027, United States, [email protected], http://blogs.cuit.columbia.edu/jmp2265/ Princeton University, 22 Chambers Street, Princeton, NJ 08544, United States, [email protected] George Washington University, South Hall, 2135 F Street, NW, Washington, DC 2005 George Washington University, CIBER Center for International Business Education and Research, Duquès Hall, George Washington School of Business, 2201 G Street, NW, Suite 450 Washington, DC 20052 [email protected] https://blogs.gwu.edu/jpuaschunder/climate-gains-losses/

* Financial support of the Academia B Young Research Award, Association for Social Economics, Austrian Academy of Science, Austrian Federal Ministry of Science, Austrian Office of Science and Technology at the Austrian Embassy to the United States of America, Bard Center for Environmental Policy, Research and Economy, Elisabeth und Helmut Uhl Stiftung, Eugene Lang Liberal Arts College of The New School, Fritz Thyssen Foundation, George Washington University, George Washington University Center for International Business Education and Research, HSBC Bank USA, ideas42, INSEAD Initiative for Learning Innovation and Teaching Excellence, International Association for Political Science Students, International Institute for Applied Systems Analysis, International Research Centre of Canada, Janeway Center Fellowship, the New School for Social Research, New School University (Endowment Stipend, Fee Board Scholarship, President’s Scholarship, Senate), Palgrave Macmillan, Prize Fellowship in the InterUniversity Consortium of New York, Science and Technology Global Consortium, Sistema B Internacional, University of Kent, University of Vienna, Vernon Art and Science and the Vienna University of Economics and Business is gratefully acknowledged. The author declares no conflict of interest. All omissions, errors, and misunderstandings in this piece are solely the author’s.

Table of Contents

Abbreviations

xi

Introduction

xv

Income and Opportunity Imbalances between Generations Chapter 1

Childhood income dynamics and intergenerational social stratification: Empirical evidence from selected countries

1

3

Veronika V. Eberharter University of Innsbruck, Austria Chapter 2

Invisible anger: Intergenerational dependence and resentment among precarious academics

33

Lara McKenzie The University of Western Australia, Australia Spatial and Racial Segregation Chapter 3

Housing, health, and history: Interdisciplinary spatial analysis in pursuit of equity for future generations Benjamin Wilson State University of New York Natalie June Kane University of Missouri - Kansas City Neal Wilson University of Missouri - Kansas City Peter J. Eaton University of Missouri - Kansas City Doug Bowles University of Missouri - Kansas City

55

57

Chapter 4

Wealth privilege: Reprising the Jim Crow System

83

Robert B. Williams Guilford College Migration Chapter 5

105 Climate-induced migrations: Legal challenges

107

Vera Ferreira University of Coimbra, Portugal Chapter 6

Gifts without borders: Intergenerational glue connecting over distance and time as pure international development in the age of migration

123

Julia M. Puaschunder The New School; Columbia University; Princeton University; George Washington University; Schwartz Center for Economic Policy Analysis Sustainable Development Chapter 7

Sustainable development: Substitutability is not the issue, but compensation is

155

157

Antoine Verret-Hamelin Université Laval, Canada Chapter 8

Philippine’s trash management policy: A critical examination

179

Li-Li Chen University of Florida External Shocks and Crises Resilience Chapter 9

Transgenerational supranationality spiral: Impact of exogenous shocks Anastasia Golofast Russian Academy of Sciences, Russia

197

199

Chapter 10

The Political Settlement in Sierra Leone: An evaluation

221

Désirée Bussi University of Vienna, Austria Intergenerational Responsibility Implementation Chapter 11

Intergenerational Responsibility in the 21st century: An independent agency as intergenerational lens

245

247

Marta Gonçalves Lisbon University Institute ISCTE, Portugal Federico Perali University of Verona, Italy Chapter 12

Global responsible intergenerational leadership: Coordinating common goods and economic stability

269

Julia M. Puaschunder The New School; Columbia University; Princeton University; George Washington University; Schwartz Center for Economic Policy Analysis Index

293

Abbreviations ABS

Australian Bureau of Statistics

Acc#

Account Number

AFRC

Armed Forces Revolutionary Council

AufenthG

Aufenthaltsgesetz, AufenthG

CMH

Children’s Mercy Hospital

CNEF

Cross-National Equivalent File

COCAL

Coalition on Contingent Academic Labor

CSR

Corporate Social Responsibility

DDR

Disarmament, Demobilization, Reintegration

EC

European Commission

EITI

Extractive Industries Transparency Initiative

EPA

Environmental Protection Agency

EU

European Union

GAD

Gender and Development

GIS

Geographic Information Systems

GLO

Ground-Level Ozone

GLOBE

Global Leadership and Organizational Behavior Effectiveness

GSTs

Generation Skipping Trusts

HBCUs

Historically Black Colleges and Universities

HOLC

Home Owners Loan Corporation

IAM

Integrated Assessment Model

ICSID

International Centre for Settlement of Investment Disputes

IGLOO

Intergenerational learning in organisations

IMF

International Monetary Fund

IPCC

Intergovernmental Panel on Climate Change

ISCO

International Standard Classification of Occupations

MAUP

Modifiable Areal Unit Problem

xii

Abbreviations

MOCKY

Movement of Concerned Kono Youth

MRN

Medical Record Number

MSW

Municipal Solid Wastes

MTO

Moving to Opportunity Project

NAPA

National Adaptation Program of Action

NBER

National Bureau of Economic Research

NGO

Non-governmental Organization

NHA

National Housing Authority

NHCS

Neighborhood Housing Condition Survey

NMPC

Nonlinear Model Predictive Control

NRP

Nonrecycled Plastics

NTEU

National Tertiary Education Union

OECD

Organisation for Economic Cooperation and Development

OLS

Ordinary Least Squares

PA21

Agenda 21

PCSD

Philippine Commission on Sustainable Development

PDIA

Problem-Driven Iterative Adaptation

PRSP

Poverty Reduction Strategy Paper

PSID

Panel Study of Income Dynamics

RUF

Revolutionary United Front

SCF

Survey of Consumer Finances

SCSL

Special Court of Sierra Leone

SDGs

Sustainable Development Goals

SMDRP

Smoky Mountain Development and Reclamation Project

SOEP

Socio-Economic Panel

SSC

Spatial Synoptic Classification

TASA

The Australian Sociological Association

TC&MEs

Transnational Corporations and Multinational Enterprises

TRC

Truth and Reconciliation Council

UN

United Nations

UNAMSIL

United Nations Mission in Sierra Leone

UNCITRAL

United Nations Commission on International Trade Law

UNHCR

United Nations High Commissioner for Refugees

UNICEF

United Nations Children's Fund

xiii

Abbreviations

USD

United States Dollars

WAD

Women and Development

WCED

World Commission on Environment and Development

WHO

World Health Organization

WID

Women in Development

WMU

Weapons of Mass Upliftment

WPR

What’s the problem represented to be?

Introduction Intergenerational Responsibility has many faces. Childhood income dynamics and elderly wealth privilege, intergenerational social stratification, intergenerational dependence, age-sensitive responses to exogenous shocks, climate justice, and climate-induced migration, sustainable development as well as intergenerational aspects of civil warfare. Intergenerational Responsibility in st the 21 Century aims at highlighting multi-faceted intergenerational problem responses through legal and policy frameworks, governance and agency as well as leadership and the intergenerational glue in the social compound. The edited volume compiles academic as well as practitioner-oriented chapters that outline the different applications of intergenerational responsibility in the global arena. In its entirety, the edited volume touches on intergenerational responsibility regarding income and opportunity imbalances between generations (Part 2), spatial and racial segregation (Part 3), migration (Part 4), sustainable development (Part 5), external shocks and crises resilience (Part 6) as well as the implementation of intergenerational responsibility (Part 7). Veronika V. Eberharter from the University of Innsbruck, Department of Economics, Austria, EU, captures income inequality in Childhood income dynamics, and intergenerational social stratification in empirical evidence from selected countries. Based on nationally representative data from the German Socio-Economic Panel, and the Panel Study of Income Dynamics, the chapter analyzes income inequality from an intergenerational mobility perspective in Germany and the United States. The empirical results corroborate the negative relation between income inequality and income mobility in both countries, where younger age cohorts experience higher income inequality and lower income mobility. In the United States, the intergenerational income elasticity is more expressed. Additionally, the empirical results show country differences how the individual and parental socio-economic characteristics accentuate intergenerational income mobility. Lara McKenzie from the University of Western Australia, Department of Anthropology and Sociology, Australia, sheds light on Intergenerational dependence and resentment among precarious academics. Addressing the significant generational shift that is taking place in academia today across Western Europe, North America, and in many of former colonies such as Australia; scholars seeking academic careers are increasingly subject to extended or even

xvi

Introduction

indefinite periods of precarious employment, in contrast with a shrinking pool of relatively permanent tenured academics. Based on qualitative expert interviews, this chapter depicts intergenerational dependence and age-based hierarchies within the academic context. Besides an investigation of the critiques of and resistance to precarious academic work, the chapter gives hope by reporting precarious academics being increasingly visible in online platforms advocating for understanding and change. Benjamin Wilson, Natalie June Kane, Neal Wilson, Peter J. Eaton and Doug Bowles from the State University of New York, College at Cortland, the University of Missouri - Kansas City, Center for Economic Information, US, educate on Housing, health, and history: Interdisciplinary spatial analysis in pursuit of equity for future generations. Increasingly evidence suggests that where you live is a critical factor in determining socio-economic status and lifetime health outcomes. Based on these findings, the presented investigation tracks childhood asthma encounters from the hospital to the home and examines them in socio-economic and historical contexts. With the focus on health outcomes rooted at the individual level, this chapter offers a novel perspective on intergenerational health inequalities as manifested in cities, communities, and neighborhoods. Robert B. Williams from Guilford College Department of Economics, US, unravels in the Wealth privilege: Reprising the Jim Crow system how the Wealth Privilege system is increasing racial stratification, decreasing wealth mobility, and widening the racial wealth gap. The unique durability and transferability across generations mean that an existing racial wealth gap is a reflection of a racialized past. Among young families – those headed by persons 35 or younger – black and Latino-headed households are starting out in worse shape today despite an economy that has increased private household wealth by half over the past generation. Due to poorer starting positions, this cohort of young householders is prone to reproduce inequities in future generations. Vera Ferreira from the University of Coimbra, Faculty of Economics, Portugal, EU, writes about Climate-induced migrations with a particular focus on Legal challenges. As institutional and legal systems are currently reshaped to protect people that are exposed to climate threats, the chapter examines the relation between climate change and migration and arising legal challenges. By the particular cases of the small Pacific Ocean island states Tuvalu and Kiribati – two small nation island states that lack the technology and financial means to adapt to rising sea levels and whose population will be forced to migrate to other states soon – the legal predicaments of climate refugees become apparent fostering the urge for climate migrants to be legally recognized and protected by international law.

Introduction

xvii

Julia M. Puaschunder from Columbia University, Princeton University, The New School Department of Economics, George Washington University and the Schwartz Center for Economic Policy Analysis, US, considers Intergenerational gifts without borders by outlining Intergenerational glue connecting over distance and time as pure international development in the age of migration. Globalization led to unprecedented mobility and worldwide electronic monetary transfer opportunities. The chapter innovatively describes the influx of refugees and granting asylum as a means of pure international development as migrants send remittances to those left behind. Innovatively, intergenerational ties that let migrating populations transfer financial assets back to their left former homelands are unraveled as drivers of remittances. The intergenerational glue underlying remittances is portrayed as a way to develop postconflict societies free of technocratic, bureaucratic and institutional downfalls. Antoine Verret-Hamelin from Université Laval, Faculté de philosophie, Quebec, Canada, draws the case that in Sustainable development: Substitutability is not the issue, but compensation is. Facing the obligations of justice toward future generations, the chapter characterizes the content of intergenerational obligations in order to understand today’s requirements of sustainability and intergenerational fairness. Strong sustainability regards natural capital as non-substitutable, while weak sustainability is much more optimistic regarding the possibilities of substitution between different types of capital. Contrary to standard economic theory, the chapter concerns compensation in the pursuit of public policy and long-term targets such as the Sustainable Development Goals of the United Nations. Li-Li Chen of the University of Florida, Department of Political Science, US, examines how sustainable development can be achieved on the micro-level in Philippine’s trash management policy. The chapter detects a genderdiscriminating tendency in the model of sustainable development by unraveling the power structures and gender inequality in waste management. Feminism problematizes the underpinning power structures, which perpetuate gender inequality among actors. By analyzing the case of Philippines trash management policies announced by former president Fidel Ramos in 1995, this chapter shows that sustainability is far from a consistent construction and masked by its economic solution. Conclusions depict how to empower minorities and craft policies to ensure a more inclusive and just sustainability approach. Anastasia Golofast from the Russian Academy of Sciences, Institute of Philosophy, Russia, portrays the Transgenerational supranationality spiral and Impact of exogenous shocks to intergenerational networks from a global governance angle. By the example of the current refugee crisis as an external

xviii

Introduction

challenge that stimulates the EU’s authority delegation system to elaborate a coherent strategy of joint action; the chapter highlights the potential of crises to foster supra-nationality within the EU framework but also sheds light on the triggered associated risks. Crises are outlined as ‘windows of opportunity’ for the European Commission as an institutional entrepreneur to initiate supranationality strengthening by pushing the states to delegate more authority to the EU level. The institutional response to the influx of younger generations into society holds an invaluable intergenerational responsibility implementation global governance case study. Désirée Bussi from the Department of Political Science of the University of Vienna, Austria, EU, evaluates The political settlement in Sierra Leone from an intergenerational perspective as the democratization and stabilization processes in this African post-conflict area focused on the youth. Parts of the Political Settlement are detected as still fragile, visible in the renewed marginalization of the youth and former combatants, the dominance of international companies in the mining and agricultural sector, an unequal payment between foreign and native workers and the recruitment of people as security staff by political parties. Overall, the chapter provides insights on opportunities of post-crises settlement but also sheds light on concrete intergenerational challenges in peace making processes in the developing world. Marta Gonçalves Pimenta de Brito and Federico Perali from the Lisbon University Institute ISCTE, Portugal, and University of Verona Department of st Economics, Italy, EU, investigate Intergenerational responsibility in the 21 century from an independent agency intergenerational lens. Attributing an aging Western world population, the authors outline the societal need to pool resources and think intergenerationally. Enabling support that citizens can age well across the life course, this chapter highlights how an intergenerational agency is important to all countries where intergenerational issues are weakly respected and how such an intergenerational agency could be created and managed. Julia M. Puaschunder from Columbia University, Princeton University, The New School Department of Economics, George Washington University and the Schwartz Center for Economic Policy Analysis, US, concludes that globalization has led to an unprecedented interdependency of massive global systems causing systemic risk to increase exponentially in Global responsible st intergenerational leadership in the 21 century. Emerging societal long-term downfalls have created a quest for fairness to provide an at least as favorable standard of living to future generations as enjoyed today. Global systemic risks of climate change, overindebtedness in the aftermath of the 2008/09 World Financial Crisis and the need for pension reform in the wake of an aging Western world population, currently raise attention to intergenerational fair-

Introduction

xix

ness. The closing chapter proposes solutions on how to bring the public and private sector temporal foci closer together in order to harmoniously tackle the most pressing contemporary challenges of humankind. Julia M. Puaschunder remains more than grateful to Vernon Press for embarking on this fascinating endeavor and granting contributors from around the world and representing a broad spectrum of academic disciplines the opportunity to share their innovative work with the larger public. Special thanks is acknowledged to Claudia Morsut from the Centre for Risk Management and Societal Safety of the University of Stavanger for serving as a publication co-editor on one of the chapters. This book would not exist without Vernon Press and the generous gifts of time and collegial support of Vernon Press leadership and executives Rosario Batana, Argiris Legatos, Carolina Sanchez, and Javier Rodriguez. With this book, the authors hope to promote interdisciplinary dialogue and trans-national understanding of contemporary pressing issues of our time. We strive for shedding light on the most recent political, economic, social and international developments that affect the greater societal well-being now and may determine our common earth’s future. We wish all readers great insights gained that inspire to engage deeper with some of the most debated and contested challenges of our time. We remain most grateful for your kind interest in the book and with the highest appreciation for your noble gift of intergenerational care.

Income and Opportunity Imbalances between Generations

Chapter 1

Childhood income dynamics and intergenerational social stratification: Empirical evidence from selected countries Veronika V. Eberharter University of Innsbruck, Austria Abstract Based on nationally representative data from the German Socio-Economic Panel (SOEP), and the Panel Study of Income Dynamics (PSID), this chapter analyzes income inequality and determinants of intergenerational income mobility in Germany and the United States. The chapter starts from the hypotheses that the level of income inequality, as well as the extent and the determinants of intergenerational income mobility, differ with respect to the existing welfare state regime, family role patterns, and social policy design. The empirical results corroborate the negative relation between income inequality and income mobility. In both countries, younger age cohorts experience higher income inequality and lower income mobility. In the United States, the intergenerational income elasticity is more expressed. Additionally, the empirical results show country differences in how the individual and parental socio-economic characteristics accentuate the intergenerational income mobility. Keywords: Human capital; income inequality; intergenerational mobility; personal income, wealth and their distribution Acknowledgements: The author wishes to thank Julia M. Puaschunder and two anonymous referees for valuable comments and suggestions to clarify the exposition in several points. The shortcomings and errors remain the author’s as usual.

4

Chapter 1

1. Introduction Many industrialized countries are confronted by changing demographic and social conditions, and increasing economic and social inequalities. Though the social policies in these countries are focusing on alleviating social and economic inequalities, ‘stratification’ in terms of power, class and other forms of inequality are still continuing and intensifying. The link between intragenerational income inequality and intergenerational social mobility is complex and non-linear. Empirical research tends to show a negative relation between the intra-generational income inequality and the intergenerational mobility of social and economic status (Andrews & Leigh, 2009; Atkinson, 1975; Björklund & Jäntti, 1997; Corak, 2006; d’Addio, 2007; Friedman, 1962; OECD, 2010; Solon, 2004). Increasing income inequality experienced in childhood reduces the probability to move up the income or earnings scale relative to the parents. These inequities in social and economic outcome jeopardize the equality of opportunity. Low intergenerational mobility implies that the life chances of individuals will partly reflect characteristics for which they are not responsible. One explanation is that with higher income dispersion, returns to education are higher which may benefit individuals whose investment in education is not constrained by family background. Intergenerational mobility depends on individual and family-related characteristics that determine the individual economic and social success, e.g., related to the inheritability of traits (innate abilities). Parents influence their children through a hierarchy of ‘circumstances.’ Social connections that facilitate access to education and jobs, family culture and investments that influence skills, beliefs, and motivation, as well as the genetic transmission of ability, which means a broader definition of equality of opportunity that policy makers could potentially seek to level. Additionally, the environmental factors, which are loosely (social norms, work ethics, attitude towards risk and social networks) or heavily affected by social and economic policy. Typical examples are policies that shape access to human capital formation, such as public support for early childhood, primary, secondary and tertiary education, as well as redistributive policies that may reduce or raise financial and other barriers to accessing higher education (Corak, 2004; OECD, 2010; Roemer, 2004). The studies considered in Becker and Tomes (1986) support the hypothesis of non-linearities in the intergenerational income dynamics and report an intergenerational elasticity of log income or log earnings of about 0.2 in various industrialized countries indicating that the parental status does not strongly affect the children’s economic and social position. Solon (1999)

Childhood income dynamics and intergenerational social stratification

5

among others showed that the high intergenerational mobility was partly due to sample selection and transitory fluctuations in earnings. Using better quality data, more representative samples, multi-year income variables and correcting for measurement errors, the second generation of analyses (Corak & Heisz; 1999; Solon, 1992, 1999, 2002) found empirical evidence of intergenerational income elasticity ranging between 0.20 and 0.60. The analysis of the dynamics of the intergenerational income mobility (Corcoran, 2001) reveals a decreasing effect of the parental income status on the income and social position of the children (Mayer & Lopoo, 2005; Solon, 2004). Corak and Heisz (1999) and Hertz (2004) found empirical evidence for a roughly S-shaped relationship between parent and child incomes across the income distribution, being close to zero for those with parents in the bottom of the income distribution, and then rising. This suggests that children growing up in lowincome households are caught in the low-income and poverty trap as adults if intergenerational income mobility does not compensate economic and social inequality (Mayer & Lopoo, 2005). The social policy focus on combating child poverty becomes more important because children have no personal responsibility for their own economic and social situation. Understanding the mobility of economic and social status experienced in childhood gains in importance from the perspective of caring about the equality of opportunity in the life-course, because child poverty often feeds a vicious circle that implies a higher risk of impoverishment in adulthood (Atkinson, Maynard & Trinder, 1983; Causa, Dantan & Johansson, 2009; Corak, 2006; Corcoran, 2001; Mehrotra, 2006; Redmond, 2008; Robeyns, 2005; Sen, 1992; Smeeding & Rainwater, 2004; Vleminckx & Smeeding, 2001). Empirical analyses of intra-generational economic mobility stress the relation between the income variable of persons in different stages of their life. The few empirical analyses of intra-generational income dynamics in childhood focus on the push-factors driving the movements into and out of poverty (Bane & Ellwood, 1986; Bradbury, Jenkins & Micklewright, 2001; Finnie & Sweetman, 2003; Picot, Zyblock & Pyper, 1999) or the dynamics and the duration of affluence and the factors associated with moving up or down the income distribution (Burton, Phipps & Zhang, 2014). From a socio-political perspective, the level and determinants of intra- and intergenerational social and economic mobility in a society open new insights about the effectiveness of policy measures to guarantee equal opportunity (Smeeding & Rainwater, 2004). The policy instruments and transfer packages are constituted by the countries’ welfare state regime, which defines a com-

6

Chapter 1

plex of legal and organizational properties, the role of the state interacting alongside the market, the civil society, and the family in the provision of welfare (Arts & Gelissen, 2002; de Swaan, 1988; Therborn, 1995). Based on the level of decommodification and stratification, EspingAndersen (1990, 1994, 1999) clusters democratic industrial societies into liberal, conservative, and social democratic welfare state regimes. The liberal welfare state regime (United States, Great Britain, Canada, Australia, New Zealand) is characterized by low decommodification and strong individualistic self-reliance. The public philosophy is grounded on the idea of opportunity reflecting individual efforts, which indicates an open, liberal and dynamic social system. The distributional consequences of the market forces are accepted. A relatively unregulated labor market fosters the creation of low-paid jobs and large earnings dispersions. Labor market policies offer less protection for workers and do little to ameliorate market-based risks. The market rather than the state is promoted in guaranteeing the welfare needs of the citizens. These countries are characterized in terms of minimal assistance to allow the worker the opportunity to gain entry back into the market should circumstances dictate a temporary departure. The state reacts only in case of social failures and limits the help to special groups. The transfers are modest, and the rules for entitlement are very strict. The principle of stratification leads to low-income state dependents, and people not being able to afford social insurance plans. The education systems are less stratified and standardized which may induce a higher social mobility. Contrary, privately financed higher education suggests intergenerational social immobility (Charles, Buchmann, Halebsky, Powers & Smith, 2001; Couch & Dunn, 1997; Dustmann, 2004; Gornick & Meyers, 2003; Hall & Soskice, 2001; Mortimer & Krüger, 2000). The conservative-corporatist welfare state regime (Germany, Austria, France, Italy) is typified by a modest level of decommodification. Government policies ensure against market-based risks and protect those who are unable to succeed in the market place. The direct influence of the state is restricted to the provision of income maintenance benefits. The labor market institutions and labor market policies ensure employment stability. Health care, welfare, social insurance, national assistance, and old age pensions are provided at government expense. Social policy is designed to focusing on economic and social equality, and on alleviating poverty and social exclusion, and a high permeability of the society. Family policies facilitate the incorporation of women into the labor force (e.g., child care, paid maternity leave, job return guarantees) and support the transition from the traditional male breadwinner model to the adult worker model. On the other hand, tax policy (e.g., tax splitting) favor men as breadwinners and women foremost as mothers, which

Childhood income dynamics and intergenerational social stratification

7

reinforces the preservation of traditional family role patterns concerning the allocation of time into paid work (Charles et al., 2001; Lewis, 2006). The educational system is formal and coordinated, and higher education is publicly provided. In Germany, the vocation-oriented educational “dual system” relies on occupation-specific credentials, and results in socially stratified and sexsegregated outcomes. The federal states have the primary responsibility for organizing the educational system, which results in a high level of standardization, and constitutes the mechanisms for perpetuating social inequalities (Mortimer & Krüger, 2000; OECD, 2012). The social democratic approach to welfare and social policy (Scandinavian countries) is especially committed to creating equal opportunities, reducing social risks, and diminishing social divisions. The level of decommodification is high, and stratification is directed to achieve a system of highly distributive benefits. These countries advocate for full employment and promote equality including the provision of a safety net that no one should be allowed to fall through. Social policy aims at maximizing the capacities of individual independence. Women are encouraged to participate in the labor market. The chapter aims to contribute to a better understanding of the underlying mechanisms of intra-generational inequality and the causal processes determining the social and economic success of the children relative to their parents (Atkinson, Cantillon, Marlier & Nolan, 2002; Corak, 2006). The chapter analyzes the level of inequality in childhood and as adults, and quantifies how the economic success of children is related to that of their parents. The chapter uses different inequality measures, which are sensitive at different points in the income distribution. These quantify the intra-generational income mobility in childhood using transition matrices in order to analyze the extent and the determinants of the intergenerational transmission of economic and social status using regression techniques. Two age cohorts in Germany and the United States are observed. These countries with different welfare state regimes, labor market institutions, family role patterns, and social policy design are chosen to get more insight into the driving forces of the heritage of social and economic status in order to derive economic and social policy implications. The chapter starts from the hypotheses that the link between social stratification and income dynamics works differently according to the social policy and the existing welfare state regime, and the traditional role settings. In more traditional societies, family background characteristics are more important for the economic and social status of an individual and exert differential effects on social skills, and on human capital investment. The work tests these

8

Chapter 1

hypotheses for two age cohorts of children in Germany, and the United States – countries differ concerning the welfare state system, and the permeability of the society (Dustmann, 2004). H1: Due to weaker impact of redistributive policy in the United States, a higher income inequality in the United States compared to Germany is hypothesized. H2: Due to more traditional family role models, a stronger link between generations is supposed and a more pronounced influence of parental background on income mobility in Germany than in the United States. H3: In both countries, the author hypothesizes that family structures, labor market behavior, life satisfaction, and health conditions of the parents contribute to intergenerational income mobility. H4: In both countries, the author hypothesizes that the intra-generational mobility experienced in childhood affects the intergenerational income mobility. In the United States, the author hypothesizes that individual and household characteristics as adults outperform the influence of the parental attributes on intergenerational income mobility. The chapter is organized in 5 sections: section 2 focuses on the theoretical background of the heritage of social and economic disadvantages, section 3 reports the data and sample organization, section 4 outlines the methodology. Section 5 presents the empirical results. Finally, section 6 concludes with a summary of findings and derives policy implications and directions for further research. 2. Theoretical background The research on intergenerational economic and social mobility sets out to explain the fact that the children’s economic and social positions are correlated with that of their parents. There are two major theories concerning the mechanisms of the intergenerational transmission of economic and social advantages and disadvantages. According to the family resource model, it is not a lack of economic resources, but other characteristics of the parents that are correlated with economic status that influence the parental abilities to provide stimulating environments for their children to have economic success. The family environment and the socio-psychological situation the children experience when growing up influences their mental and health development. Low-income parents more likely possess disadvantageous characteristics, and therefore they fail to provide stimulating environments for the improvement of their children’s socio-economic status (Mayer, 1997).

Childhood income dynamics and intergenerational social stratification

9

The structural hypothesis of intergenerational economic and social mobility emphasizes the view that limited parental resources during childhood restrict the social and economic status of the children as adults (Blanden, Gregg & Machin, 2005; Mayer & Lopoo, 2005). According to the logic of the neoclassical human capital approach (Becker, 1964; Mincer, 1974), the parental investments increase the children’s human capital, which is directly linked with childrens’ labor productivity, and increases childrens’ earnings capacity, their economic and social performance (Becker & Tomes 1986; Chadwick & Solon, 2002; Mazumdar, 2005; Solon 1992, 1999, 2002), their ability to gain non-labor income, and even their success on the marriage market (Pencavel, 1998). A central point of the models of intergenerational income mobility is to recognize that parents both care about and are able to influence the future labor market outcome of their children. As a result, parents allocate their time and money between current consumption and investments in the human capital of their children. Human capital is often equated with monetary investments in education and particularly higher education, but it also means investment in their physical and mental health as well as in their social development. The parents’ private investment in education inside and outside the educational system and the choice of schooling can affect productivity and economic and social status in the future. The extent to which productivity then is reflected in wages is influenced by labor market institutions and varies across countries. Parents may also affect the labor market success of their descendants indirectly through the transmission of social norms, work ethics or social networks (Bourguignon, Ferreira & Menendez, 2007, 2013). Gaps in the parents’ investment abilities impede the economic success of the offspring (Acemoglu & Pischke, 2000). Additionally, the intergenerational mobility is influenced by the inheritability of other endowments of the family – such as culture and family connections – to the children. However, it is difficult to disentangle the effect of parents’ socio-economic status from that of inherited abilities or disposition of the individuals that influence their educational achievement, productivity and income situation (Plug & Vijverberg, 2003; Sacerdote, 2002). Among the endowment conditions, parental education, employment behavior, occupational choice, family role patterns, as well as social capital environment are important (Finnie & Sweetman, 2003; Stevens, 1999). The degree of the inheritability of these endowments is influenced by the structure of the society and markets, into which the children grow up. The greater the parental preference for the future, the greater the return to any investment, and the greater the inheritability of other aspects of family background for earnings, the lower intergenerational economic and social mobility. Further, social institutions, as well as social and economic policy measures will in part de-

10

Chapter 1

termine the degree to which parental resources are passed on through the generations and the impact on earnings. This underscores the importance of identifying the most effective policy measures to reduce the inequalities of opportunities that are associated with different birth endowments (Couch & Lillard, 2004; d’Addio, 2007). 3. Data and sample design The empirical analysis is based on data from the German Socio-Economic Panel (SOEP), and the US Panel Study of Income Dynamics (PSID), which were made available by the Cross-National Equivalent File (CNEF) project at 1 the College of Human Ecology at Cornell University, Ithaca, N.Y., USA. The PSID started in 1980 and contains a nationally representative unbalanced panel of about 40,000 individuals in the United States. From 1997 on the PSID data are available bi-yearly. The SOEP started in 1984 and contains a representative sample of about 29,000 German individuals that includes households in former East Germany since 1990 (Wagner, Frick & Schupp, 2007). The surveys track the socio-economic characteristics of a given household. Each household member is asked detailed questions about age, gender, marital status, educational level, labor market participation, working hours, employment status, occupational position, economic situation of the members of a given family over time, as well as household size and composition. The income variables are measured on an annual basis and refer to the prior calendar year, so we use the income variables referring to the wave of the interview, but questioned in the following wave. The data allows monitoring the employment and occupational status, the income situation, and the socioeconomic characteristics of the individuals. The databases do not provide a sufficient long time horizon to observe the parents and the children at identical life cycle situations but cover a sufficiently long period to observe the socio-economic characteristics of the parents living with their children linked to the children’s socio-economic characteristics when becoming members of other family units. The databases do not allow identifying parents - children relations exactly: for this analysis we consider adults, whose marital status is “married,” or “living with partner” and who are living in households with persons with the marital status “child” as “fathers” and “mothers.”

1

For a detailed description of the databases see Frick, Jenkins, Lillard, Lipps & Wooden (2007).

Childhood income dynamics and intergenerational social stratification

11

The data allows to track two cohorts of children living in the parental household and to observe the social and economic status of these children as adults. Children aged 10 to 20 years are considered to include children at this age, who still live in the parental household and to avoid the overrepresentation of children staying at home until a late age. The German sample includes children born in the years 1984-1988 (cohort 1), respectively 1988-1992 (cohort 2). The US sample includes children born in the years 1982-1986 (cohort 1), respectively 1986-1990 (cohort 2). These persons were aged between 25 and 39 years when their social and economic situation was observed in the periods 2000-2007 respectively 2004-2011 (Germany), and 1997-2005 respectively 2001-2009 (USA). The data selection excludes persons with full-time education because their income situation differs from the rest of population. In the parental generation, persons up to 60 years are considered to avoid a too large bias of retired persons. The selection process leads to a sample of 4,380 (cohort 1) respectively 2,765 (cohort 2) persons living in Germany and 5,791 (cohort 1) respectively 7,827 (cohort 2) women and men from the United States. 4. Methodology Disposable household income (including earnings, capital income, public transfers, and pensions of all household members minus total household taxes) served as predictor for the individual income situation. Household income is preferred to individual earnings as a better measure of economic status. To consider the family structure, the Square Root Scale (OECD, 2008, 2011) was employed to calculate the permanent post-government household per adult equivalent. The income variable is deflated with the national CPI (2010=100) to reflect constant prices. To exclude transitory income shocks and cross-section measurement errors, the multiyear averages of the income variable was used. The referred income variables are employed from the databases, thus, the results do not make allowance for the bias of imputed values on income inequality and income mobility (Frick & Grabka, 2005). Following Fitzgerald, Gottschalk & Moffit (1998a, b), a compensatory set of sample specific weights was constructed to address non-random sample attrition. These weights do not account for attrition in general, but for attrition among the particular groups under study and its relation to the particular outcome. We estimate a probit equation that predicts retention in the sample (i.e., being observed as an adult) as a function of pre-determined variables measured during childhood (Fitzgerald, 1998a, b). Presuming that the samples are representative

12

Chapter 1

when the children are still children, a set of weights was constructed based on equation 1:
,  = 

 ⋮,   ⋮ 



(Equation 1)

where x denotes parental income as primary regressor, and z is a vector of covariates to predict attrition, indicated by A=1. Thus
,  will take higher values for people whose characteristics z make them more likely to exit the panel before their adult income can be measured. The variables considered in z are the child’s gender, the parental age, education and their squares. These variables are assumed to affect the attrition propensities, to be endogenous to the outcome that is to have an effect on the children’s income as adults conditional on the parental income. The weights
,  are then multiplied with the parental weights, which yields a set of weights that apply to the children as adults. The parental weights are assumed to depict the attrition effects and the weights,
, , compensate for subsequent non-random attrition. 4.1 Intra-generational income inequality The change in the overall level of income inequality is an important dimension of the well-being of the population in a country and reflects the functioning of economic and social policy. To evaluate the extent of income inequality, the coefficient of variation, Gini coefficient, Atkinson index, Generalized Entropy inequality measures, and 90:50 ratio were employed. These income inequality measures differ concerning their sensitivity to changes at the bottom or the top of the income distribution. The coefficient of variation

CV ( y ) =

1 y

1 n 2  n ∑ ( yi − y )   i =1 

1/ 2

=

σy y

(2)

captures the relation of the standard deviation of the income variable and its arithmetic mean: the higher the value of the coefficient of variation, the higher the degree of inequality. The Gini coefficient measures v-times the area between the Lorenz curve, which maps the cumulative income share on the vertical axis against the distribution of the population on the horizontal axis, and the line of equal distribution. The easiest mathematical expression of the Gini coefficient is based on the covariance between the income of an individual (yi) and the rank (F) the individual occupies in the income distribution. The rank takes a value

Childhood income dynamics and intergenerational social stratification

13

between zero for the poorest and one for the richest. Denoting

y as the mean

income, the Gini coefficient is then defined as

Gini(ν ) =

ν cov( y, Fν −1 ) y

(3) .

The parameter ν is used to emphasize various parts of the income distribution. The higher the weight, the more emphasis is placed on the bottom part of the income distribution. The parameter v = 2 characterizes the standard Gini coefficient

Gini =

2cov(Y , F ) y

(4)

which is more sensitive to changes at the bottom of the income distribution and ranges from 0 (perfect equality) to 1 (total inequality). The inequality measures of the Generalized Entropy class

GE(α ) =

α  1  1 n  yi   ∑   −1 2 α − α  n i =1  y   ,

(5)

are sensitive to changes at the lower end of the income distribution for α close to zero, equally sensitive to changes across the distribution for α equal 2 to one, known as Theil index (Theil, 1967), and sensitive to changes at the upper end of the distribution for higher values of α. The analysis here employs the GE (1) , and the G E ( 2 ) inequality measures

GE(0) =

y 1 n y 1 n y 1 n 2 log , GE(1) = ∑ i log i , and GE(2) = ∑ ∑( yi − y ) n i =1 yi n i=1 y y 2ny 2 i=1 (6)

The higher the value of these measures, the higher the degree of inequality. The Atkinson index counts among the welfare-based inequality measures and is directly related to the class of additive social welfare functions (SWF). Assuming that social welfare is represented by average utility, the utility function U then is

2

The inequality measures of the Generalized Entropy class GE (α) for α=0 and α=1 are calculated by using a rule by de l’Hôpital, by which the limit of the undefined ratio between two functions of the same variable is equal to the limit of the ratio of their first derivative.

14

U ( yi ) =

Chapter 1

1 y i1− ε 1−ε

U ( yi ) = log yi

ε ≠1

ε =1

(7) (8)

where ε is the parameter of inequality aversion, respectively the sensitivity to inequality at different parts of the income distribution. The sensitivity parameter (ε) range from 0 (indifferent about the nature of the income distribution) to infinity (concerned with the income positions of the very lowest income group). An ε = 0 determines a utilitarian social welfare function, and (7) collapses to mean income, which implies the higher the mean income, the higher the social welfare. In this analysis, ε = 2 is employed, which denotes that the Atkinson index becomes highly sensitive to inequalities at the bottom of the income distribution. The Atkinson index ranges from 0 to 1, with 0 being a state of equal distribution. The Atkinson values can be used to calculate the proportion of total income that would be required to achieve an equal level of social welfare as at present if incomes were perfectly distributed. For example, an Atkinson index value of 0.20 suggests that we could achieve the same level of social welfare with only 1 − 0.20 = 80% of income. Finally, the relation between the income at the 90th percentile and the income at the 50th percentile – the 90:50 ratio – is used to evaluate the dispersion of the income distribution. 4.2 Intergenerational income mobility To evaluate how economic (dis)advantages are transmitted across generations, the slope coefficient from an ordinary least squares (OLS) regression of the natural logarithm of the permanent real equivalent household income (2010=100) of person i living in her own household as adult ( yi ) on the natural logarithm of the natural logarithm of the permanent real equivalent household income (2010=100) of person i living in the parental household ( yp ) was employed based on the following equation 9:

ln( yi ) = ß0 + ß1 ln( y p ) + ui .

(9)

Equation (9) is motivated by economic theory, specifically by the model of Becker and Tomes (1986). A central point is that income mobility across the generations and inequality within generations can be understood in a unified way by recognizing that parents both care about and are able to influence the economic and social status of their children. The constant term ß0 represents the change in the economic status common to the children’s generation. The

15

Childhood income dynamics and intergenerational social stratification

coefficient ß1 expresses the elasticity of the income variable of a person with respect to her parents’ income position, and represents the fraction of economic advantage that is on average transmitted across the generations. The larger ß1, the more likely a person will inhabit the same economic position as her parents, which implies a greater generational persistence of the relative income position. Depending upon the degree of inequality in parental incomes, small values of ß1 confer substantial advantages to the children to the better off. The closer to zero ß1, the weaker the relationship between parent and child outcomes, and the greater the generational income mobility. The random error component (ui) is usually assumed to be normally distributed 2 N(0, σ ) (Antmann & McKenzie, 2007; Corak, 2006; Greene, 2003; Wooldridge, 2002). The intergenerational elasticity indicates the average mobility measure but also sheds important light on the probabilities of economic success conditional to the economic background of the parents. The movement from one income position to another and the factors that influence them are the key issues from a welfare point of view (Heckman, 1981). The extension of equation (9) includes a set of parent and child characteristics as displayed in equation 10: n

ln( yi ) = ß0 + ß1 ln( y p ) + ∑ ßi X i + ui

(10)

i=2

The variables in (Χi) reflect individual and family background characteristics of a person i living in her own household and living in the parental household, which affect his or her present social and economic status. To the extent that the variables in (Χi) lower (raise) the coefficient ß1 compared to the model specification (9), they “account for” the raw intergenerational income elasticity (Björklund & Jäntti, 2009; Grawe, 2004; Hertz, 2004). The individual and household characteristics of the children as adults, indicated with subscript (c) in (Χi), partly express the indirect effects of parental economic outcome on the children’s income: the higher the income of the parents, the higher their investments in the education of the children, which in turn upgrades their social and economic status. The sex of the individual (GENc 1 male, 2 female) is included to hold gender effects on intergenerational income mobility. The human capital is considered by the years of education (EDUCC). In the case of missing values, the educational attainment is set equal to the amount reported in the next year, for it is possible to increase educational attainment but impossible to decrease it. Additionally, the number of children less than 16 years in the household (CHILDC) is included to

16

Chapter 1

consider the effects of care requirements in order to determine whether the household size interferes with intergenerational income elasticity. The marital status (MARc), which takes the value 1 if the person is “married” or “living in partnership,” and 0 if her marital status is “single,” “widowed,” “divorced,” or “separated,” captures the effect of the family structure in childhood on the economic and social mobility. In order to track the employment situation, a dummy variable EMPc, which takes the value 1 if the person is full-time employed, is added to the model. The occupational status (OCCc) of a person serves as an indicator of the impact of the social status on the intergenerational income elasticity. The 2-digit occupational categories in the database were reorganized, which are oriented at the ISCO-88 (International Standard Classification of Occupations) and include an occupational variable indicating 1 “academic/scientific professions/managers,” and “professionals/technicians/associate professionals,” occupations, and 2 “trade/personal services,” and “elementary occupations.” Additionally, the satisfaction with life status (SATLIFEc) is controlled for, which is known to have adverse effects on a person’s life and to affect the degree of economic and social integration and intergenerational transmission of economic and social (dis-)advantages. The database provides 10 categories of satisfaction with life from 1 to 10. A dummy variable is included, which takes the value 1 if the person rated the health satisfaction with higher than 5, and 0 else. To evaluate the effects of the intra-generational income mobility in childhood on the intergenerational income mobility, the real equivalent postgovernment household income [2010=100] of the parental household is considered when the children are aged 10-14 years and when they are aged 15-20 years to five equally populated ranked groups indexed by i and j. The elements

pij ≥ 0 of the transition matrix indicate the probability (in percent) th

that a child aged 15-20 years belongs to the j quintile of the income distributh tion given that he or she belongs to the i quintile of the income distribution when aged 10-14 years with

∑p =∑p ij

j

ij

= 1 (Formby, Smith & Zheng,

i

2004). The elements on the diagonal ( ) represent the stayers and the offdiagonal terms ( ) represent the movers concerning the income position. The difference between the subscripts represents the distance from the main diagonale, the further away from the diagonal, the greater is the intergenerational mobility of the income positions. The variable (MOBc) indicates whether the relative income position of person i worsens (MOB" = −1), persists

(MOB" = 0), or turns to the better off (MOB" = +1) in childhood.

Childhood income dynamics and intergenerational social stratification

17

The characteristics of the parental household in (Χi) are indicated by subscript p, and consider that the intergenerational income correlation might not really be due to income per se, but to the effects of the household structure, the parents’ education, their labor market behavior or their health status on the economic and social status of the children as adults. The sex of the household head (GENp 1 male 2 male) is included to measure the effect of gender and household organization on intergenerational income mobility. The parental human capital stock is considered, the years of education of the household head (EDUHHp) and her/his partner (EDUPp). Higher education is assumed to positively contribute to household income and the relative economic and social status. The age of the household head (AGEHHp) is included to control its impact on the intergenerational income mobility. The marital status of the household head (MARHHp), which takes the value 1 if the household head is “married” or “living in partnership,” and 0 if her marital status is “widowed,” “divorced,” or “separated,” captures the effect of the family structure in childhood on the economic and social mobility. The employment status of the household head is measured with a dummy variable (EMPHHP), which takes the value 1 if the person is full-time employed. Additionally, the occupational status of the household head (OCCHHp) is included to derive the impact of the social class on the intergenerational income elasticity. The occupational status variable takes the value 1 for “academic/scientific professions/managers,” and “professionals/technicians/associate professionals” occupations, and the value 2 for “trade/personal services,” and “elementary occupations.” Finally, the disability status of the household head (DISHHP 1 disabled), which is known as a factor with adverse effects on a person’s life, is tracked to measure the impact of physical or mental disability on the intergenerational income mobility. These variables are the same for all alternatives, but their effects on the income paths of the children of different cohorts are allowed to differ. To control for the impact of the different birth cohorts on the intergenerational income mobility, the data is pooled to include the variable (COH 1 cohort 1, 2 cohort 2) as visible in table 1.1.

18

Chapter 1

Table 1.1: Dependent and independent variables in the regression model Variable Description

yi

ln permanent equivalent post-government income (2010=100), children’s household as adults

yp

ln permanent equivalent post-government income (2010=100), parental household

GENc

sex: 1=male; 0=female

MARc

marital status: 1=married, living in partnership; 0=widowed, divorced, separated

EDUc

years of education

CHILc

number of children in the household

OCCc

occupation: 1=academic/scientific professions/managers, professionals/technicians/associate professionals; 2=trade/personal services, elementary occupations

EMPc

employment status: 1=employed; 0=not employed

SATLIFEc

satisfaction with health: 1=satisfied; 0=else

MOBc

income mobility in childhood: -1 negative; 0=persistent; 1=positive

GENHHp

sex household head: 1=male; 2=female

AGEHHp

age of the household head in years

MARHHp

marital status of the household head: 1=married, living in partnership; 0=widowed, divorced, separated

EDUHHp

education of the household head in years

EDUPp

education of the household head’s partner in years

EMPHHp

employment status of the household head: 1=employed; 2=else

OCCHHp

occupation: 1=academic/scientific professions/managers, professionals/technicians/associate professionals; 2=trade/personal services, elementary occupations

DISHHp

disability status of the household head: 1=disabled; 0=else

COH

cohort: 1=cohort 1; 2=cohort 2

6. Empirical results 6.1 Income inequality Table 2.2 shows the median income as well as the income inequality patterns for both cohorts in both countries. In both countries, the increasing median real equivalent household incomes (2010=100) in the life course went along with increasing income inequality. For both the US cohorts, the selected inequality measures reveal a higher income inequality pattern than in Germany, suggesting higher intergenerational income immobility compared to the German sample.

19

Childhood income dynamics and intergenerational social stratification

In both countries, the Generalized Entropy measures show increasing dispersion of the income distribution at the lower (GE(1)) as well as at the upper end (GE(2)) of the income distribution during childhood. The 90:50 ratio shows relatively constant dispersion of the income distribution in the observed stages of life. For persons in cohort 2, the increasing median incomes are accompanied by higher income inequality at the top as well as at the bottom of the income distribution compared to persons in cohort 1. The negative relation between income inequality and mobility (Friedman, 1962) suggests that the younger age cohorts of children experience a lower economic and social mobility as outlined in table 2.2. Table 2.2: Permanent real equivalent household income inequality measures cohort

median Coefficient of Variation Gini coefficient Atkinson (epsilon=2) Theil index = GE(1) GE(2) 90:50 ratio Nobs

cohort

median Coefficient of Variation Gini coefficient Atkinson (epsilon=2) Theil index = GE(1) GE(2) 90:50 ratio Nobs

a) Germany Cohort 1 Cohort 2 in early in in early in as adults as adults childhood childhood childhood childhood 14,492 15,870 19,724 15,985 17,542 19,645 .3910

.3836

.4475

.4158

.6573

.5275

.2018

.1992

.2375

.2045

.2131

.2559

.1231

.1294

.1932

.2150

.1509

.2401

.0683 .0765 1.583 4,380

.0667 .0736 1.549 4,380

.0927 .1932 1.714 4,380

.0747 .0865 1.645 2,765

.0807 .0932 1.676 2,765

.1241 .1517 1.753 2,765

a) United States Cohort 1 Cohort 2 in early in in early in as adults as adults childhood childhood childhood childhood 16,835 17,717 23,709 19,091 19,744 28,130 .6560

.7941

.7556

.7899

.8444

.8884

.3007

.3311

.3523

.2849

.3058

.3429

.2800

.3062

.3598

.2663

.2858

.3689

.1645 .2151 2.140 5,791

.2121 .3363 2.281 5,791

.2198 .2926 2.118 5,791

.2040 .4899 1.899 7,827

.2759 .4721 1.946 7,827

.2268 .3457 1.771 7,827

20

Chapter 1

6.2 Intergenerational income mobility Table 3.3 shows the results of the regression of the logarithm of the real equivalent post-government household income (2010=100) of the children on the logarithm of the real equivalent post-government household income of the parents (2010=100) for both the cohorts in Germany and the United States. The results corroborate the findings of various studies reporting a range of intergenerational income elasticity around 0.4 or even higher according to the analyzed countries, sample designs, time windows, age cohorts, and income variables (Aaronson & Mazumdar, 2008; Becker & Tomes, 1986; Lee & Solon, 2009; Mayer & Lopoo, 2005, 2008; Solon, 1992, 1999, 2002, 2004). The ß1 coefficient indicates a significantly higher intergenerational mobility in Germany than in the United States, which confirms the hypothesis of a lower social mobility in the United States. The intergenerational elasticity amounts at .3371 (cohort 1) respectively at .3593 (cohort 2) for the German samples compared to .5160 (cohort 1) and .5745 (cohort 2) for the US samples. In both countries, the intergenerational income elasticity for cohort 2 is higher than for cohort 1, which corroborates the empirical evidence of increasing income inequality patterns. The influence of the factors guaranteeing high intergenerational income mobility obviously is compensated and outperformed by the determinants inducing a higher intergenerational correlation of social and economic status. In both countries, the individual and family background attributes as adults (column 2) affect the intergenerational income mobility, but in a considerably varying amount. In Germany, the individual and family background characteristics contribute 4.44 percentage points (cohort 1) respectively 11.83 percentage points (cohort 2) to the “raw” intergenerational income elasticity. In the United States, these attributes lower the ß1 coefficient by 30.31 percentage points to .2129 for cohort 1 and by 32.9 percentage points to .2455 for cohort 2. These empirical findings corroborate that in the United States, the public philosophy is grounded on the idea of opportunity reflecting individual efforts. In both countries, women experience a lower intergenerational mobility, the women in cohort 2 in a significant way. To be married or living in a partnership significantly increases the intergenerational mobility for both cohorts, in the United States to a greater extent. Higher education significantly increases the intergenerational income mobility, which corroborates the human capital hypothesis. Living with children in the household significantly reduces intergenerational income mobility, in Germany to a greater extent than in the United States. Occupational choice matters. German individuals

Childhood income dynamics and intergenerational social stratification

21

in cohort 1 and United States individuals in cohort 2 with elementary occupations experience a lower intergenerational mobility than individuals with occupations with higher social status. In both countries, full-time employment significantly increases the intergenerational income mobility. In Germany, life satisfaction significantly increases the intergenerational income mobility; in the United States the effect is significantly negative. The positive intra-generational income mobility in childhood positively affects intergenerational income mobility, however, in a significant way only for individuals in cohort 1 in the German sample. The inclusion of a set of individual and family background characteristics of the own household as adults and when living in the parental household (column 3) accentuates the country differences of the intergenerational income elasticity. In Germany, the individual and family background characteristics contribute 7.77 percentage points (cohort 1) respectively 17.98 percentage points (cohort 2) to the “raw” intergenerational income elasticity. In the United States, these variables lower the ß1 coefficient by 32.4 percentage points to .1920 for cohort 1 and by 34.57 percentage points to .2288 for cohort 2. The empirical results confirm the hypothesis that economic success relates to a greater extent on individual and family background resources in the United States than in Germany. In Germany, social and family policy is obviously more successful to alleviate individual and family-based social mobility barriers. The results show that the intergenerational mobility of social and economic status originates in the economic and social environment of the parental household. Limited resources when living in the parental household restrict the economic and social chances during childhood and shape the social and economic performance as adults. In Germany, living with a female household head significantly lowers the intergenerational social mobility. In both countries, to live in a two-parent household with married or partnered parents increases intergenerational income mobility. In both countries, each additional educational year of the parents contributes to the children’s economic and social success. To live with a household head with academic or professional occupations significantly improves the relative income position compared to the parents. Living with disabled parents significantly lowers the intergenerational income mobility (see table 3.3).

22

Chapter 1

Table 3.3: Intergenerational income mobility Cohort 1

a) GERMANY abbreviation

description Permanent equivalent postgovernment income in the parental household

yp GENc

Gender 1 male 2 female

X3

MARc

Marital status 1 married 2 else

X4

EDUc

Years of education

X5

CHILc

X6

X2

Cohort 2

.3371*** .2927*** .2595*** .3593*** .2410*** .1795*** -.0161

-.0039

.0382

.0719***

-.0747*** -.0741***

-.0587*** -.0579***

.0074** .0110***

.0206*** .0184***

Children in the household

-.1357*** -.1345***

-.1596*** -.1693***

OCCc

Occupational status

-.0314*** -.0285***

X7

EMPc

Employment status 1 fulltime 0 else

X8

SATLIFEc

Satisfaction with life 1 satisfied 0 else

.0230*** .0200***

.0150*

.0158*

X9

MOBc

Income transition in childhood -1 neg; 0 persistant; 1 pos

.0742*** .0837***

.0204

.0275

X10

GENHHp

Gender household head 1 male 2 female

.1791*

-.0158*

.2080**

-.0077

.2187*** .2654**

-.1014*

-.2444***

.0014

.0002

.0360*

.0369*

Education in years household head

.0102*

.0197***

X 14 EMPHHp

Employment status household head 1 full-time 0 else

.0075

.0584**

X15

OCCHHp

Occupational status household head

.0023

.0060

X16

DISABHHp

Disability status household head 1 disabled 0 else

-.0330

-.1436***

X 11 AGEHHp

Age household head

X 12 MARHHp Marital status household head 1 married 0 else

X13

EDUHHp

R2adj

.0714

.1965

.2027

.0831

.2436

.2646

RMSE

.4389

.3752

.3774

.4863

.4040

.3962

LL -2,610

-1,410

-1,290

-1,930

-1,020

-876

Mean VIF

1.29

1.30

Nobs

4,379

2,765

Source: SOEP-BHPS-PSID 1980-2013, author’s calculations. Legend: * p