Keister & Moller 2000 1 2 Killewald et al. 2017 3 Other Research C O N T E N T S
Introduction and Measures of Wealth Who was the most unequal industrial society in 1990s? (Top one percent – nearly 40% wealth) Net Worth: total assets – total liabilities/debt Keister & Moller 2000
Empirical Source Sources of Wealth Data and Limitations Scholars who tried to deal with data: • Wolff 1980, 1983 (income capitalization on census) • Greenwood 1983, 1987 (income capitalization on CPS) • Keister 2000b (microsimulation modeling on SFCC) Keister & Moller 2000
Trends in Wealth Inequality How much did top one percent of people own? 1950s: 35% 1962: 33.5% 1972: 29% 1976: 19% 1983: 33.8% (what bottom 80% owned declined) 1989: 37.4% (what top 0.5% owned increased more) 1995: 38.5% Keister & Moller 2000
Source: Keister & Moller 2000, p.67 Keister & Moller 2000
Explanation of Wealth Inequality • Macro Level market fluctuations (stock, real estate market) e.g. social pressure, solicitous insurance sales man, unstable financial market to family portfolio behavior • Micro Level Age, Race, Family Structure (marriage, widowhood, family size, family dissolution etc.) Keister & Moller 2000
Explanation of Wealth Inequality • Integration of Macro and Micro Level Stechkel & Krishman 1992 Angle 1986, 1993 Greenwood 1983, Keister 2000b, Wolff 1980 etc. Keister & Moller 2000
Intergenerational Processes, Mobility & Inheritance • How do we relieve extreme wealth inequality? • Poverty transmission? • Inequality exacerbation? Picture Source: twoeggz.com Keister & Moller 2000
Introduction and Measures of Wealth • Keister & Moller 2000; Spilerman 2000 • Part I: Challenges • Part II: Data • Part III: Effects and Determinants of Wealth Killewald et al. 2017
Part I: Conceptual and Methodological Challenges • To tackle concerns of inaccurate measurement: - Averaging income measures across several preceding years, when possible; - Modeling wealth accumulation using either lagged dependent variables or change models. Killewald et al. 2017
Part I (cont. more ways of tackling measurement problems) Operationalizing an Error-Prone, Highly Skewed Variable • Median regression • Log-transform net worth • Inverse hyperbolic sine (HIS) transformation • Wealth as independent variable (x) and dependent variable (y) Killewald et al. 2017
Part II: Wealth Data and Patterns Recall: Trends in Wealth Inequality Keister & Moller 2000 How much did top one percent of people own? 1950s: 35%, 1962: 33.5%, 1972: 29%, 1976: 19% 1983: 33.8%, 1989: 37.4%, 1995: 38.5% New: 1989 – 2013 (Pfeffer & Schoeni 2016) 2001: 32%, 2013: 36% Killewald et al. 2017
Large-scale Surveys Fielded in the US and Abroad
Trends in Wealth and Wealth Inequality (estimates from Pfeffer & Schoeni 2016) Killewald et al. 2017
Part III: Wealth Consequences and Determinants • Wealth as predictor (X) • Impact of Parental Wealth: offspring education, career, wealth • Impact of Individual Wealth: Financial resources, homeownership, employment, retirement, health and mortality, family structure (marriage, cohabitation, remarriage, fertility delay, parenthood), living environment, cultural status and achievement, political power etc. Killewald et al. 2017
Part III: Wealth Consequences and Determinants • Wealth as outcome (Y) Xs: income, housing, risky assets, family structure, health etc. • Exogenous Xs: Age Social Origins Education Race, ethnicity and nativity Gender Macro-level context and Policy Killewald et al. 2017
Conclusion: Wealth as Important Dimension of Social Stratification Some key words for future research • operationalizing net worth • data availability • components of wealth • qualitative research on wealth generation and use • racial/ethnic groups, nativity, and gender • macro-level determinants Killewald et al. 2017
More Research on Race and Wealth Inequality Oliver and Shapiro 1997 - black middle class Keister 2000 - high-risk asset ownership Scholz & Levine 2003 - income and demographic characteristics Altonji & Doraszelski 2005 - the role of permanent income …
Thank You!
Recommend
More recommend
