Earnings instability and mobility over our working lives: Improving short- and long-term economic well-being for U.S. workers
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Overview
Rising inequality in earnings is a fact of the U.S. economic landscape. The rise in earnings inequality has occurred because earnings have become more unstable in the short term, and because the more stable, or permanent, part of earnings has become more unequal in the long term. As permanent earnings have become more unequal, workers find it harder to move up the earnings distribution over their careers.1
Instability in year-to-year earnings, or earnings volatility, can result from economywide trends such as increases in unemployment or decreases in work hours during recessions, or from more microeconomic trends such as changes in the prevalence of precarious work arrangements, job turnover, or bonuses and other types of performance pay.2 Some volatility, such as receiving a large bonus or switching to a higher-paying job, is welcome. Yet an unexpected negative earnings shock can be difficult to manage, especially for low-income workers facing an involuntary or unanticipated decline in earnings.3
Permanent earnings inequality reflects longer-term trends in the U.S. labor market such as changes in the returns to education and other skills, international trade and technological change, changes in unionization, and the value of the minimum wage.4 Growing permanent earnings inequality not only increases persistent disparities in living standards among workers but also is associated with declines in long-run earnings mobility. The result is that an increasing number of workers will have persistently low earnings while other workers will spend large parts of their working lives at the very top of the earnings distribution.5
In this essay, we briefly review what recent research suggests about trends in short-run earnings volatility, permanent earnings inequality, and mobility, as well as the causes of these trends. We then offer a number of policy recommendations that we think will help alleviate some of the negative effects of these recent changes. In particular, we discuss the merits of incentives and reforms to boost household incomes and savings alongside education reforms to help today’s workers find good jobs and our future workers be better prepared early in life to contribute productively over the long term.
What do we know about earnings volatility, permanent earnings inequality, and mobility?
Most evidence shows that year-to-year volatility in men’s wage and salary earnings increased considerably from the 1970s through the early 1980s as inequality increased rapidly.6 Since the 1980s, short-term earnings volatility for men is highly cyclical, increasing during recessions and declining during expansions, though whether the trend is broadly increasing, flat, or decreasing differs between datasets and studies.7
Earnings volatility is the highest for men with less education and with lower earnings—that is, for workers who likely have the hardest time maintaining their well-being during periods of low earnings.8 For women, earnings are more stable than in the past, with falling earnings volatility since the 1970s, though earnings volatility for women is higher than for men.9 Volatility in family income—which includes both wage and salary earnings and other sources of income such as transfers from government programs, including the Earned Income Tax Credit and Supplemental Nutrition Assistance Program—is rising over time, and government transfers are less able to buffer earnings fluctuations than in the past.10
Even ignoring the year-to-year fluctuation in earnings and focusing instead on the more constant part of earnings over a lifetime, permanent earnings inequality is growing rapidly. Much of this increase is driven by an increase in inequality in earnings early in workers’ careers.11 This increase in permanent earnings inequality means that individuals are more “stuck in place” in the earnings distribution throughout their careers, with smaller chances of upward mobility than in the past.12
What are the risks that U.S. workers face?
Workers face two distinct types of risk. Despite the relatively flat trend in short-term earnings instability since the 1990s for all workers, short-term earnings risk remains large and is growing for less-educated and lower-earning workers. Unanticipated declines in earnings are particularly problematic for low-income families and less-educated adults who have little in savings. Only 29 percent of low-income households have savings for unexpected emergencies, and 42 percent of adults with a high school degree or less could not pay their monthly bills if faced with an unexpected $400 expense.13 These workers have limited ability to weather earnings shocks because of the weakening of the public safety net, because low earnings make saving difficult, and because they lack access to formal low-cost credit markets.
At the same time, the vast majority of workers face a new risk: If early-career earnings are low, the likelihood that earnings remain low has increased. Workers with more education are more likely to have high earnings, but even for these workers, the likelihood of rising up through the earnings distribution over a career is declining.
These dual risks necessitate investment in policies that reduce short-run earnings volatility and enhance workers’ ability to cope with temporarily low earnings, particularly for workers with fewer resources, alongside policies to promote careers that provide for long-run upward mobility.
Policy remedies for short-term earnings volatility
Earnings can be volatile because of both positive changes such as end-of-year bonuses, or negative ones such as unexpected cuts in work hours. We focus on policies that address the source and consequences of negative earnings changes, particularly for families who are less likely to be able to adequately weather periods of lower earnings.
Policies to reduce volatility
Outside of employment transitions, we know relatively little about the sources of earnings volatility, which makes articulating policies that reduce volatility difficult. Reducing employment transitions reduces earnings volatility. We focus on policies to reduce earnings volatility from two specific sources—poor health and family caregiving responsibilities—that would be particularly helpful to lower-income families.
The first policy is to increase access to paid leave for workers’ own healthcare needs and for family caregiving. Employees’ access to such leave is more common among high earners than low earners, though eight states, the District of Columbia, and the federal government for its own employees have enacted paid leave policies. Access to paid leave may reduce the instability of earnings for workers who themselves become ill or whose family members (including infants) require care.14
Similarly, access to flexible, low-cost childcare may also promote stable earnings. Such childcare arrangements would provide insurance against unanticipated childcare needs that can disrupt work and would be compatible with the irregular work schedules that are common for low-income workers.15
Policies to help families cope with downward earnings shocks
Because unexpected negative earnings changes are inevitable, families must be able to maintain basic living standards during periods of low earnings.
The Supplemental Nutrition Assistance Program is one of the most effective transfer programs to help all families cope with temporary spells of unemployment or low earnings because benefits through this program can be obtained quickly.16 Eliminating work requirements for this program entirely or establishing a national unemployment trigger in which work requirements would be automatically suspended when unemployment is high would help workers during recessions when short-term earnings volatility spikes.17 Because low-income and less-educated individuals face persistently volatile earnings, policymakers also should increase the value of benefits—for example, by accounting for the time required for food preparation and the geographic variation in food prices—helping those workers who face volatile earnings in both recessionary and expansionary periods.18
Government policies can also help households save to self-insure against short-term earnings losses. A suite of small policy changes would facilitate higher levels of savings for low-income households. First, improving access to banking services for low-income families would encourage saving. Only 17 percent of households without a bank account report saving for unexpected emergencies, compared to more than 55 percent of households who have at least one checking or savings account.19 These expansions must encourage savings vehicles such as no-overdraft accounts to prevent households with low levels of savings from incurring substantial costs from banking.20
Second, we should provide incentives for individuals to save regularly from each paycheck or from lump sum amounts from government transfer programs such as the Earned Income Tax Credit or the child tax credit. Encouraging employers to offer nonretirement savings plans to workers though payroll deductions and for households to receive tax refunds through direct deposit to a bank account would both help encourage saving.21 Ten states and one city have enacted legislation allowing for state-facilitated retirement savings programs, some of which feature autoenrollment, and nonretirement savings plans could follow a similar model.22 Direct deposit of tax refunds from the Earned Income Tax Credit are particularly relevant for low-income families and are large, worth an average of $2,488 in 2018.23
Policy remedies to address long-term inequality and stagnant mobility over our working lives
Policy proposals to decrease long-term inequality and increase long-term economic mobility should help young adults start their careers in strong economic positions. Many of these policies would be cost effective because the costs of the programs are offset by increased tax revenues and decreased transfer payments over the working lives of adults.
These policies start from early childhood. Expanding access to high-quality preschool has been shown to increase educational attainment and to improve income and health in adulthood, particularly for children from low-income families.24 Moreover, these programs have high rates of return: $1 invested in the Perry Preschool program—one of the most successful high-quality preschool interventions for black children with risk factors of failing in school—returned $7 to $12 back to society.25
Promoting college graduation is also important for reducing long-term earnings inequality and increasing long-term earnings mobility. The gap in college completion between individuals from high- and low-income families is growing.26 Because college-educated workers have higher levels of long-term mobility than less-educated workers, and because these workers begin their career at higher points in the earnings distribution and are more likely to stay there throughout their working lives, promoting college completion among children from low-income families is critical.27
There are several policy options to consider. The expansion of Pell Grants, which target low-income college students, is one such policy. Its costs are recouped within 10 years.28 Increasing state funding for community colleges to provide more clear pathways to both associates degrees and four-year colleges would also improve graduation outcomes for low-income students.29
Because much of lifetime earnings inequality is driven by inequality in early-career earnings, and permanent inequality is growing even among college graduates, young adults must start their careers on a solid trajectory.30 Assisting four-year and community colleges to develop programs to teach students how to conduct a job search to find a high-quality first job or to establish explicit pathways to apprenticeships for high-demand careers is another step toward maximizing early-career earnings and improving long-term earnings mobility.31
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Conclusion
Workers in the United States face the risks of high short-term earnings volatility for less-educated and lower-income workers, declining rates of mobility, and increasing permanent earnings inequality for most workers. To cope with these risks, workers require a combination of more accessible and robust public safety net programs and incentives to increase private savings to buffer short-term declines in earnings and spells of unemployment, alongside investments in education and pathways to high-quality employment to reduce long-term earnings inequality. Importantly, increases in education and high-quality employment—both of which reduce long-term inequality and increase long-term mobility—also reduce the number of workers with particularly high levels of short-term earnings volatility, thus providing a double benefit to U.S. workers.
—Emily E. Wiemers is an associate professor of public administration and international affairs at the Maxwell School of Citizenship and Public Affairs at Syracuse University. Michael D. Carr is an associate professor in the Department of Economics at University of Massachusetts Boston.
End Notes
1. Steven J. Haider, “Earnings Instability and Earnings Inequality of Males in the United States: 1967 – 1991,” Journal of Labor Economics 19 (4) (2001): 799–836; Wojchiech Kopczuk, Emmanuel Saez, and Jae Song, “Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937,” Quarterly Journal of Economics 125 (1) (2011): 91–128; Robert A. Moffitt and Peter Gottschalk, “Trends in the Transitory Variance of Male Earnings: Methods and Evidence,” Journal of Human Resources 47 (1) (2012): 204–236.
2. Moffitt and Gottschalk, “Trends in the Transitory Variance of Male Earnings: Methods and Evidence”; Donggyun Shin and Gary Solon, “Trends in men’s earnings volatility: What does the Panel Study of Income Dynamics show?” Journal of Public Economics 95 (2011): 973–982.
3. Richard Blundell, Luigi Pistaferri, and Ian Preston, “Consumption Inequality and Partial Insurance,” American Economic Review 98 (5) (2008): 1887–1921; Kopczuk, Saez, and Song, “Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937.” For a discussing of similar causes for rising in wage inequality, see David H. Autor, Lawrence F. Katz, and Melissa S. Kearney, “Trends in U.S. Wage Inequality: Revising the Revisionists,” Review of Economics and Statistics 90 (2) (2008): 300–323, and Thomas Lemieux, “Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?” American Economic Review 96 (3) (2006): 461–514.
4. Peter Gottschalk and Robert A. Moffitt, “The Rising Instability of U.S. Earnings,” Journal of Economic Perspectives 23 (4) (2009): 3–24; David H. Autor, David Dorn, and Gordon H. Hanson, “Untangling Trade and Technology: Evidence from Local Labour Markets,” Economic Journal 125 (584) (2015): 621–646.
5. Michael D. Carr and Emily E. Wiemers, “The Decline in Lifetime Earnings Mobility in the U.S.: Evidence from Survey-Linked Administrative Data.” Working Paper (Washington Center for Equitable Growth, 2016).
6. Haider, “Earnings Instability and Earnings Inequality of Males in the United States: 1967 – 1991”; Moffitt and Gottschalk, “Trends in the Transitory Variance of Male Earnings: Methods and Evidence”; Shin and Solon, “Trends in men’s earnings volatility: What does the Panel Study of Income Dynamics show?”; James P. Ziliak, Bradley Hardy, and Christopher Bollinger, “Earnings volatility in America: Evidence from matched CPS,” Labour Economics 18 (2011): 742–754. Though the paper focuses on household income volatility, for a table with results from many other studies of male earnings volatility, see Karen Dynan, Douglas Elmendorf, and Daniel Sichel, “The Evolution of Household Income Volatility,” The B.E. Journal of Economic Analysis & Policy 12 (2) (2012): 1–42.
7. Michael D. Carr and Emily E. Wiemers, “New Evidence on Earnings Volatility in Survey and Administrative Data,” American Economic Review Papers & Proceedings 108 (2018): 287–291; Molly Dahl, Thomas DeLeire, and Jonathan A. Schwabish, “Estimates of Year-to-Year Volatility in Earnings and Household Incomes from Administrative, Survey, and Matched Data,” Journal of Human Resources 46 (4) (2011): 750–774; John Sabelhaus and Jae Song, “Earnings Volatility Across Groups and Time,” National Tax Journal 2 (62) (2009): 347–364; John Sabelhaus and Jae Song, “The Great Moderation in Micro Labor Earnings,” Journal of Monetary Economics 57 (2010): 391–403.
8. Gottschalk and Moffitt, “The Rising Instability of U.S. Earnings”; Fatih Guvenen, Serdar Ozkan, and Jae Song, “The Nature of Countercyclical Income Risk,” Journal of Political Economy 22 (3) (2014): 621–660; Bradley Hardy and James P. Ziliak, “Decomposing Trends in Income Volatility: The ‘Wild Ride’ at the Top and Bottom,” Economic Inquiry 52 (1) (2014): 459–476.
9. Dynan, Elmendorf, and Sichel, “ The Evolution of Household Income Volatility”; Ziliak, Hardy, and Bollinger, “Earnings volatility in America: Evidence from matched CPS.”
10. Dynan, Elmendorf, and Sichel, “The Evolution of Household Income Volatility”; Hardy and Ziliak, “Decomposing Trends in Income Volatility: The ‘Wild Ride’ at the Top and Bottom.”
11. Kopczuk, Saez, and Song, “Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937”; Fatih Guvenen and others, “Lifetime Incomes in the United States over Six Decades.” Working Paper no. 23371 (National Bureau of Economic Research 2017).
12. Carr and Wiemers, “The Decline in Lifetime Earnings Mobility in the U.S.: Evidence from Survey-Linked Administrative Data.”
13. Federal Deposit Insurance Corporation, 2017 FDIC National Survey of Unbanked and Underbanked Households (2017); Federal Reserve Board, Report on the Economic Well-Being of U.S. Households in 2018 (2019).
14. LeaAnne Derigne and others, “Paid Sick Leave and Preventive Health Care Service Use Among U.S. Working Adults,” Preventative Medicine 99 (2017): 58–62; Maya Rossin-Slater, Christopher J. Ruhm, and Jane Waldfogel, “The Effects of California’s Paid Family Leave Program on Mothers’ Leave-Taking and Subsequent Labor Market Outcomes,” Journal of Policy Analysis and Management 32 (2) (2013): 224–245.
15. Janice Compton and Robert A. Pollak, “Family Proximity, Childcare, and Women’s Labor Force Attachment,” Journal of Urban Economics 79 (2014): 72–90.
16. For a review of the effectiveness of SNAP, see Janet Currie, “U.S. Food and Nutrition Programs.” In Robert A. Moffitt, ed., Economics of Means-Tested Transfer Programs in the United States (Chicago: Chicago Press, 2003), pp. 199–289; Hilary Hoynes and Diane Whitmore Schanzenbach, “U.S. Food and Nutrition Programs.” In Robert A. Moffitt, ed., Economics of Means-Tested Transfer Programs in the United States, Volume 1 (Chicago: Chicago Press, 2016), pp. 219–301.
17. Hilary Hoynes and Diane Whitmore Schanzenbach, Strengthening SNAP as an Automatic Stabilizer (Washington: The Hamilton Project at The Brookings Institution, 2019).
18. James P. Ziliak, Modernizing SNAP Benefits (Washington D.C.: The Hamilton Project at The Brooking Institution, 2016).
19. Federal Deposit Insurance Corporation, 2017 FDIC National Survey of Unbanked and Underbanked Households.
20. Michael S. Barr, “Banking the Poor,” Yale Journal on Regulation 21 (1) (2004): 121–128.
21. Karen Dynan, “Proposal 6: Better Ways to Promote Savings though the Tax System.” In Michael Greenstone, Max Harris, Karen Li, Adam Looney, and Jeremy Patashnik, eds., 15 Ways to Rethink the Federal Tax System (Washington D.C.: The Hamilton Project and The Brookings Institution, 2013), pp. 36–40.
22. Georgetown Center for Retirement Initiatives, “State-Facilitated Retirement Savings Programs: A Snapshot of Program Design Features” (2019).
23. “EITC Fast Facts,” available at https://www.eitc.irs.gov/partner-toolkit/basic-marketing-communication-materials/eitc-fast-facts/eitc-fast-facts (last accessed October 4, 2019).
24. Pedro M. Carneiro and James J. Heckman, “Human Capital Policy.” In Benjamin Friedman, ed., Inequality in America: What Role for Human Capital Policies? (Cambridge, MA: MIT Press, 2003), pp. 77–240; David Deming, “Early Childhood Intervention and Life-Cycle Skill Development: Evidence from Head Start,” American Economic Journal: Applied Economics 1 (3) (2009): 111–134.
25. James J. Heckman and others, “The Rate of Return to the High/Scope Perry Preschool Program,” Journal of Public Economics 94 (1-2) (2010): 114–128; Nathanial Hendren and Ben Sprung-Keyser, “A United Welfare Analysis of Government Policies.” Working Paper (Opportunity Insists, 2019). Both show generally that programs targeted to children (including college students) have a high Marginal Value of Public Funds, or MVPF.
26. Martha J. Bailey and Susan M. Dynarski, “Inequality in Postsecondary Education.” In Greg J. Duncan and Richard J. Murnane, eds., Whither Opportunity? Rising Inequality and the Uncertain Life Chances of Low-Income Children (New York: Russel Sage Foundation and Chicago: Spencer Foundation, 2011), pp. 117–132.
27. Carr and Wiemers, “The Decline in Lifetime Earnings Mobility in the U.S.: Evidence from Survey-Linked Administrative Data.”
28. Jeffrey T. Denning, Benjamin M. Marx, and Lesley J. Turner, “ProPelled: The Effects of Grants on Graduation, Earnings, and Welfare,” American Economic Journal: Applied Economics 11 (3) (2019): 193–224.
29. Harry J. Holzer and Sandy Baum, Making College Work: Pathways to Success for Disadvantaged Students (Washington: Brookings Institution Press, 2017).
30. Guvenen and others, “Lifetime Incomes in the United States over Six Decades.”
31. Holzer and Baum, Making College Work: Pathways to Success for Disadvantaged Students.