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Economics of Mobility

Paper Session

Monday, Jan. 4, 2021 3:45 PM - 5:45 PM (EST)

Hosted By: American Economic Association
  • Chair: Oren Danieli, Tel Aviv University

Getting Beneath the Veil of Intergenerational Mobility: Evidence From Three Cities

Oren Danieli
,
Tel Aviv University
Tanaya Devi
,
Harvard University
Roland Fryer
,
Harvard University

Abstract

We develop a data driven way to design the optimal policy experiment for increasing chances of escaping poverty. We collected data from in-person surveys of almost 1,000 individuals who were reared in poverty in Memphis, Tulsa, and New Orleans, and asked about their childhood health, parental income, home environment as a child, childhood experiences, lifetime traumas, neighborhood safety, a host of psychological skills, beliefs, and current income. Using typical descriptive approaches to motivate an intervention implicitly assume one can alter individual characteristics in any way the data deem predictive – e.g. sending youth to college who have been the victims of abuse – even if one rarely observes that combination of characteristics in the data. We replace this with four axioms about the expected cost of altering any combination of individual characteristics. Under these axioms, the optimal experiment replicates the way people escape poverty in real life. We develop a method to identify the variable that should be most affected in an intervention and test it in various simulations. We find that educational attainment is the most important determinant of mobility. Yet, many other variables – traditionally ignored by economists – are almost equally important predictors: resilience, Big 5 personality skills, grit, self-esteem, the number of adults trusted, trouble with the police when young, and other adverse childhood experiences. Fathers present in own neighborhood did not matter. This suggest that income-increasing interventions for the poor need to be broader than simply human capital or place-based policies.

Intergenerational Mobility Over the 20th Century: Evidence From United States Survey Data

Suresh Naidu
,
Columbia University
Elisa Jacome
,
Princeton University
Ilyana Kuziemko
,
Princeton University

Abstract

Much recent work has focused on understanding geographic variation in intergenerational mobility for modern U.S. cohorts, but it is difficult to extrapolate from cross-sectional variation in intergenerational mobility to the relevant cross-cohort variation. Yet, because of data constraints, little if any work has examined variation over time during the 20th century. We take on this task, collecting all survey datasets we can find that ask both own family income and father’s occupation, and use father’s occupation as a proxy for childhood income. We find that IGE is u-shaped over the 20th century, whereas rank-rank coefficients decline from the 1910-1940 cohorts and remain generally flat from the 1940-1970 cohorts. Mechanically, the decline in IGE and rank-rank is driven by the decreasing connection between father’s occupation and own education for those born between 1910 and 1940.

Was the Arsenal of Democracy an Engine of Mobility? The World War II Industrial Expansion and the Roots of Mid-Century Manufacturing Opportunity

Andrew Garin
,
University of Illinois-Urbana-Champaign
Jonathan L. Rothbaum
,
U.S. Census Bureau

Abstract

This paper examines the long-run effects of the publicly-financed construction of large manufacturing facilities during World War II (WWII) both on local labor markets and on individual-level earnings mobility during the Postwar period. We study the wartime construction of large, new plants in that the United States military could not incentivize private firms to stake any capital on, and likely would not have been built in the selected locations if not for the war. We test for market-level effects by comparing counties that received plants for idiosyncratic war-related reasons to counties that observably similar in 1930, and find that plant sitings caused manufacturing employment to rise by 30 percent and average production earnings to rise by 10 percent after the war and to remain elevated through the year 2000. These manufacturing-sector effects are associated with a general increase in median family incomes and, to a lesser extent, with higher wages in other sectors. If individuals are spatially mobile in the long-run, these county-level earnings effects may be driven by selective migration rather than within-individual earnings growth. We therefore test for individual-level effects by studying the long-term earnings effects on workers based on where they resided before the war as children. We find that growing up in a locale where a large plant was constructed had an economically significant impact on mens’ adult wage incomes, but not those of women. These plants also increased upwards intergenerational household income mobility for children born to parents with below-median family incomes in 1940. Our results suggest that wartime policies causally contributed to the midcentury rise in upward mobility.

Mobility and Inequality in US Growth, 1968–2018

Yonatan Berman
,
London Mathematical Laboratory, City University of New York-Graduate Center, and Stone Center on Socio-Economic Inequality
François Bourguignon
,
Paris School of Economics

Abstract

This paper combines cross-sectional and longitudinal labor income data to present a comparison between anonymous and non-anonymous growth incidence curves in the United States during the past 50 years. If anonymous growth incidence tend to be upward sloping because of increasing inequality during that period, the same is not true of non-anonymous curves. The latter prove to be flat or non-significantly downward sloping, suggesting some neutrality of growth when initial income positions are accounted for. This is true when using either panel data or synthetic panels based on CPS data and one-parameter functional representations of income mobility. Flat non-anonymous curves are observed even in periods of increasing cross-sectional income inequality. Differences between anonymous and non-anonymous curves thus matter for the interpretation of inequality changes, social welfare and policy.
Discussant(s)
Thomas Lemieux
,
University of British Columbia
Bhash Mazumder
,
Chicago Federal Statistical Research Data Center
Anna Aizer
,
Brown University
Clara Martinez-Toledano
,
Imperial College Business School
JEL Classifications
  • J6 - Mobility, Unemployment, Vacancies, and Immigrant Workers