Trends in Income Inequality, Volatility, and Mobility Risk

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Abstract

A unified measure of inequality, volatility, and mobility risk is developed from well-known decompositions of a generalized entropy inequality measure. Decomposition by population subgroup is applied to panel data measuring income across people over time, where subgroups are taken to be individual people, so “within-group” inequality is a measure of the variability of individual income over time and “between-group” inequality is a measure of inequality in long-run mean incomes. The variability of individual income over time is further decomposed into “volatility” and “mobility risk” using individual-specific trends in income. I apply the decompositions to several decades of U.S. data and find every component (inequality, volatility, and mobility risk) increasing over time, and a large impact of taxes. I further find large swings in the progressivity of income growth after taxes that are not observed in pretax income, consistent with the known tax regimes in recent U.S. history.

Introduction

There has been a renewed interest in recent years in income inequality, but also economic mobility (both moving up and moving down), and income volatility, the year-to-year variations in income that families may or may not be able to smooth over. This is not just about the business cycle: the percentage of Americans worried about being laid off nearly quadrupled from 12 to 46 percent from 1982 to 1998, as the economy improved dramatically. Over the same time frame, workers reported their subjective probability of job loss fell from close to 20 to less than 10 percent.

To address these concerns, researchers, journalists, and politicians have joined the fray, seeking to measure and explain income inequality, mobility and volatility. These related phenomena have different implications; as Senator Schumer said, “If you’re holding a job but your share of the pie is getting smaller, that’s a different set of policy needs than if you keep losing your job” (quoted by Leonhardt 2007). To date, however, there has been no unified approach to measuring these phenomena.

I define an aggregate measure of income risk as half the squared coefficient of variation (or the general entropy measure with parameter 2, denoted GE2) of incomes measured over both people and time. The aggregate measure can be decomposed into an inequality component measuring dispersion in mean incomes, a volatility component measuring the average dispersion of fluctuations about person-specific trends, and a mobility component measuring the dispersion of person-specific trends. I then apply this decomposition to Panel Study of Income Dynamics (PSID) data from the United States to characterize trends in inequality, volatility, and mobility over the last several decades. I also examine the regressivity of income growth in these data.

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