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Reconciling Trends in U.S. Male Earnings Volatility: Results from a Four Data Set Project

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  • Robert A. Moffitt

Abstract

There is a large literature on earnings and income volatility in labor economics, household finance, and macroeconomics. One strand of that literature has studied whether individual earnings volatility has risen or fallen in the U.S. over the last several decades. There are strong disagreements in the empirical literature on this important question, with some studies showing upward trends, some downward trends, and some flat trends. Some studies have suggested that the differences are the result of using flawed survey data instead of more accurate administrative data. This paper provides an overview of a project attempting to reconcile these findings with four different data sets and six different data series--three survey and three administrative data series, including two which match survey respondent data to their administrative data. Using common specifications, measures of volatility, and other treatments of the data, the papers show almost uniformly a lack of any significant long-term trend in male earnings volatility over the last 30 years. Moreover, the survey and the administrative data almost entirely agree on that long-term stability when the comparison is done properly. Several possible explanations for the differing finds in past work are suggested by the papers. The stability of earnings volatility raises many questions for future research on trends in the U.S. labor market.

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  • Robert A. Moffitt, 2020. "Reconciling Trends in U.S. Male Earnings Volatility: Results from a Four Data Set Project," NBER Working Papers 27664, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:27664
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    Cited by:

    1. John Carter Braxton & Kyle F. Herkenhoff & Jonathan Rothbaum & Lawrence Schmidt, 2021. "Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter," Opportunity and Inclusive Growth Institute Working Papers 55, Federal Reserve Bank of Minneapolis.
    2. Kevin L. McKinney & John M. Abowd & Hubert P. Janicki, 2022. "U.S. long‐term earnings outcomes by sex, race, ethnicity, and place of birth," Quantitative Economics, Econometric Society, vol. 13(4), pages 1879-1945, November.
    3. Audra Bowlus & Émilien Gouin‐Bonenfant & Huju Liu & Lance Lochner & Youngmin Park, 2022. "Four decades of Canadian earnings inequality and dynamics across workers and firms," Quantitative Economics, Econometric Society, vol. 13(4), pages 1447-1491, November.
    4. Jonathan Heathcote & Kjetil Storesletten & Giovanni L. Violante, 2020. "How Should Tax Progressivity Respond to Rising Income Inequality?," NBER Working Papers 28006, National Bureau of Economic Research, Inc.
    5. Tao Wang, 2023. "Perceived versus Calibrated Income Risks in Heterogeneous-Agent Consumption Models," Staff Working Papers 23-59, Bank of Canada.
    6. Zachary Parolin & Megan Curran & Jordan Matsudaira & Jane Waldfogel & Christopher Wimer, 2022. "Estimating Monthly Poverty Rates in the United States," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(4), pages 1177-1203, September.
    7. Moshe Justman & Hadas Stiassnie, 2021. "Inequality in Lifetime Earnings, 1986-2012," Working Papers 579, ECINEQ, Society for the Study of Economic Inequality.

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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