Editor’s Note: The full version of this paper is available at the website for the B.E. Journal of Economic Policy and Analysis. An earlier working version of the paper can be directly downloaded above.
Using a representative longitudinal survey of U.S. households, we find that household income became noticeably more volatile between the early 1970s and the late 2000s despite the moderation seen in aggregate economic activity during this period. We estimate that the standard deviation of percent changes in household income rose about 30 percent between 1971 and 2008. This widening in the distribution of percent changes was concentrated in the tails of the distribution. The share of households experiencing a 50 percent plunge in income over a two-year period climbed from about 7 percent in the early 1970s to more than 12 percent in the early 2000s before retreating to 10 percent in the run-up to the Great Recession. Households’ labor earnings and transfer payments have both become more volatile over time. As best we can tell, the rise in the volatility of men’s earnings appears to owe both to greater volatility in earnings per hour and in hours worked.
Researchers have found it relatively straightforward to document changes in the volatility of the U.S. economy as a whole over the last several decades. The aggregate U.S. economy entered a period of relative stability known as the Great Moderation in the mid-1980s and, much more recently, has been in dramatic flux since the onset of the financial crisis and Great Recession in 2007 and 2008. However, aggregate trends do not necessarily translate into trends in the experiences of individual households. For example, the Great Moderation is generally thought to be a period over which the economy became more dynamic, with globalization, deregulation, and technological change increasing the competitive pressures and risks faced by workers. Given these developments, it is not clear that the economic environment facing individual households was in fact more stable during this period. Thus, to the extent that one is interested in household economic security, one is compelled to consider micro data. Accordingly, a large literature has developed that directly examines the volatility of earnings and income at the household level. While income volatility is not the same thing as the risk or uncertainty faced by households, changes in volatility are likely to be associated with changes in risk and uncertainty.
To date, this literature has been inconclusive. Starting with the seminal work of Gottschalk and Moffitt (1994), many studies have found that individual earnings and household income have become more volatile during the past few decades. That said, there are some notable exceptions, which find no increase or a decline in the volatility of earnings and total household income (such as CBO, 2008, and Dahl, DeLeire, and Schwabish, 2011).
This paper examines household income volatility using data from the Panel Study of Income Dynamics (PSID). As the longest-running representative survey of U.S. households, the PSID is an ideal vehicle for considering how the household economic environment has changed. In contrast to much of the early literature in this area, we focus on the volatility of overall household income as opposed to the volatility of labor earnings. To be sure, the evidence on labor earnings provides important insights into labor market dynamics. We believe, however, that the broader concept of household income brings an important additional element to the table for two reasons. First, some important questions of economic welfare hinge more on the resources available to households (and the volatility of that stream of resources) rather than on the labor earnings of a single member of that household. Moreover, for macroeconomists interested in understanding the micro foundations of aggregate household-sector behavior, household income provides the natural starting point. Although a few other studies have looked at the volatility of household income in the PSID, we are the first (to our knowledge) to incorporate survey results through the late 2000s.
To make the analysis as transparent as possible, we do not estimate a formal model of income dynamics but rather document changes over time in the cross-sectional distribution of income changes. We carefully investigate, and correct for, measurement problems in the data. We also explore the evolving volatility and correlations of movements in various components of income (including earnings) and the evolving volatility of related characteristics such as hours worked and earnings per hour.
Professor of the Practice of Economics - Harvard University
Nonresident Senior Fellow - Peterson Institute for International Economics
Dean and Don K. Price Professor of Public Policy - Harvard Kennedy School of Government
former Director - Congressional Budget Office
To summarize our results, we estimate that the volatility of household income—as measured by the standard deviation of two-year percent changes in income—increased about 30 percent between the early 1970s and the late 2000s. The rise in volatility did not occur in a single period but represented an upward trend throughout the past several decades; it occurred within each major education and age group as well. Yet, the run-up in volatility was concentrated in one important sense: It stemmed primarily from an increasing frequency of very large income changes rather than larger changes throughout the distribution of income changes.
Turning to the components of income, we estimate notable increases in the volatility of labor earnings and transfer income and a small increase in the volatility of capital income. Household labor earnings (combining earnings of heads and spouses before estimating volatility at the household level) became more volatile even though the volatility of individual earnings (heads and spouses taken as individual observations) edged down. The explanation is that women’s earnings became less volatile while men’s earnings became more volatile, and the latter matters more for household earnings because men earn more than women on average. We show that rising volatility in men’s earnings owes both to rising volatility in earnings per hour and in hours worked, though our interpretation could be affected by changes in PSID methodology. And we demonstrate that earnings shifts between household members, as well as shifts in market income and transfer income, provide only small offsets to each other.
The limitations of our analysis bear emphasis. First, an increase in the volatility of household income does not imply a corresponding increase in risk or uncertainty. Our calculations distinguish only slightly between voluntary and involuntary changes in income, they do not include shocks to desired spending, and they do not account for adjustments to saving and borrowing that can buffer income shifts. Second, our findings are based on a particular methodology applied to a single dataset. Given the wide range of findings across studies that use different techniques and different data sets, further research is needed to reconcile the various results before economists can have a high degree of confidence in the facts about household income volatility. Moreover, our analysis ends in 2008 and therefore precedes much of the recent turmoil; once the relevant data become available, researchers undoubtedly have much work to do to establish how income dynamics changed following the Great Recession.
The next section of the paper discusses how we measure volatility using PSID data. Subsequent sections present our results on the evolution of volatility of individual labor earnings, of the components of household income, of household income, and of hours worked and earnings per hour. We then discuss how our results fit in with the broader literature. A final section concludes.
[On the ongoing trade negotiations] If we’re serious about resolving the core issues that the U.S. has with China, then this is going to be a way station that’s going to require a lot more continued focus by the administration for a number of months if not years.