The Long Run Evolution of Absolute Intergenerational Mobility (Forthcoming in the American Economic Journal: Applied Economics)

This paper combines cross-sectional and longitudinal income data to present the evolution of absolute intergenerational income mobility in ten developed economies in the 20th century. Absolute mobility decreased during the second half of the 20th century in all these countries. Increasing income inequality and decreasing growth rates have contributed to the decrease. Yet, growth is the dominant contributor in most countries. We show that detailed panel data are unnecessary for estimating absolute mobility over the long run.

Homoploutia: Top Labor and Capital Incomes in the United States, 1950–2020 (with Branko Milanovic)

Homoploutia describes the situation in which the same people (homo) are wealthy (ploutia) in the space of capital and labor income in some country. It can be quantified by the share of capital-income rich who are also labor-income rich. In this paper we combine several datasets covering different time periods to document the evolution of homoploutia in the United States from 1950 to 2020. We find that homoploutia was low after World War II, has increased by the early 1960s, and then decreased until the mid-1980s. Since 1985 it has been sharply increasing: In 1985, about 17% of adults in the top decile of capital-income earners were also in the top decile of labor-income earners. In 2018 this indicator was about 30%. This makes the traditional division to capitalists and laborers less relevant today. It makes periods characterized by high interpersonal inequality, high capital-income ratio and high capital share of income in the past fundamentally different from the current situation. High homoploutia has far-reaching implications for social mobility and equality of opportunity. We also study how homoploutia is related to total income inequality. We find that rising homoploutia accounts for about 20% of the increase in total income inequality in the United States since 1986.

Anonymous and Non-Anonymous Growth Incidence Curves: United States, 19682016 (with François Bourguignon)

This paper compares anonymous and non-anonymous growth incidence curves in the United States during the past 50 years. The former show income growth by distribution quantiles irrespectively of initial individual incomes, whereas the latter is conditional on original income ranks. While anonymous curves tend to be upward sloping due to increasing inequality, the same is not true of non-anonymous curves, which are generally flat or non-significantly downward sloping, suggesting some neutrality of growth when initial income positions are accounted for. The paper proposes a decomposition of non-anonymous curves into a mobility and a shape, or distributional change components. The former is always downward sloping, whereas the latter is upward sloping in periods of increasing inequality, so that flat non-anonymous curves can be observed even when income inequality is increasing. The paper then exploits that decomposition to show that the slope of non-anonymous incidence curves in the United States is mostly determined by the evolution of cross-sectional income distributions. It also proposes a generalized pro-poorness criterion to interpret the shape of non-anonymous incidence curves in social welfare terms. A simple approximate test is suggested, which permits inferring whether non-anonymous growth incidence curves exhibit this property.

On the Link Between Intergenerational Mobility and Inequality: Are They Truly Distinct?

Income inequality and income intergenerational mobility are negatively associated empirically across countries and across time. There is also a known mechanical relationship between measures of income inequality and intergenerational mobility. This paper tests whether the mechanical relationship explains the empirical association. We find that this relationship alone explains at least 64% of the variance in mobility across 36 countries. We also show that the mechanical relationship accords well with income inequality data across time for the United States. This suggests that policy aiming to achieve more equal outcomes will likely lead to more equal opportunities and vice versa. Yet, these findings also imply that validating empirically causal mechanisms for links between mobility and inequality require being over and above the mechanical relationship.

The Distributional Short-Term Impact of the COVID-19 Crisis on Wages in the United States

This paper uses Bureau of Labor Statistics employment and wage data to study the distributional impact of the COVID-19 crisis on wages in the United States by mid-April. It answers whether wages of lower-wage workers decreased more than others', and to what extent. We find that the COVID-19 outbreak exacerbates existing inequalities. Workers at the bottom quintile in mid-March were three times more likely to be laid off by mid-April compared to higher-wage workers. Weekly wages of workers at the bottom quintile decreased by 6% on average between mid-February and mid-March and by 26% between mid-March and mid-April. The average decrease for higher quintiles was less than 1% between mid-February and mid-March and about 10% between mid-March and mid-April. We also find that workers aged 16-24 were hit much harder than older workers. Hispanic workers were also hurt more than other racial groups. Their wages decreased by 2-3 percentage points more than other workers' between mid-March and mid-April.

Risk Preferences in Time Lotteries (with Mark Kirstein)

An important question in economics is how people choose when facing uncertainty in the timing of rewards. In this paper we study preferences over time lotteries, in which the payment amount is certain but the payment time is uncertain. In expected discounted utility (EDU) theory decision makers must be risk-seeking over time lotteries. Here we explore growth-optimality, a normative model consistent with standard axioms of choice, in which decision makers maximise the growth rate of their wealth. Growth-optimality is consistent with both risk-seeking and risk-neutral behaviour in time lotteries, depending on how growth rates are computed. We discuss two approaches to compute a growth rate: the ensemble approach and the time approach. Revisiting existing experimental evidence on risk preferences in time lotteries, we find that the time approach accords better with the evidence than the ensemble approach. Surprisingly, in contrast to the EDU prediction, the higher the ensemble-average growth rate of a time lottery is, the less attractive it becomes compared to a sure alternative. Decision makers thus may not consider the ensemble-average growth rate as a relevant criterion for their choices. Instead, the time-average growth rate may be a better criterion for decision-making.

WORK IN PROGRESS

A Simplified Mortality Multiplier Method: New Estimates of Wealth Concentration (with Facundo Alvaredo and Salvatore Morelli)

Long Run Inequality and Three Types of Intergenerational (Im)mobility (with Ravi Kanbur)

Do Inequality Changes Affect Electoral Behavior? Evidence from Israel, 20032006

PUBLISHED PAPERS OR IN PRESS

Absolute Intragenerational Mobility in the United States, 1962–2014 ((2022). Journal of Economic Inequality)

Inequality, Identity, and the Long-Run Evolution of Political Cleavages in Israel 19492019 (chapter in Political Cleavages and Social Inequalities, 2021, eds. Amory Gethin, Clara Martínez-Toledano and Thomas Piketty, Harvard University Press)

On the Distribution of Estates and the Distribution of Wealth: Evidence from the Dead (with Salvatore Morelli, chapter forthcoming in NBER book Measuring and Understanding the Distribution and Intra/Inter-Generational Mobility of Income and Wealth, eds. Raj Chetty, John N. Friedman, Janet C. Gornick, Barry Johnson, and Arthur Kennickell)

Wealth Inequality and the Ergodic Hypothesis: Evidence from the United States (with Ole Peters and Alex Adamou (2021). Journal of Income Distribution).

Microfoundations of Discounting (with Alex Adamou, Dio Mavroyiannis and Ole Peters (2021). Decision Analysis 18(4), 257272).