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Trends in Earnings Volatility Using Linked Administrative and Survey Data

Author

Listed:
  • James P. Ziliak
  • Charles Hokayem
  • Christopher R. Bollinger

Abstract

We document trends in earnings volatility separately by gender using unique linked survey data from the CPS ASEC and Social Security earnings records for the tax years spanning 1995–2015. The exact data link permits us to focus on differences in measured volatility from earnings nonresponse, survey attrition, and measurement between survey and administrative earnings data reports, while holding constant the sampling frame. Our results for both men and women suggest that the level and trend in volatility is similar in the survey and administrative data, showing substantial business-cycle sensitivity among men but no overall trend among continuous workers, while women demonstrate no change in earnings volatility over the business cycle but a declining trend. A substantive difference emerges with the inclusion of imputed earnings among survey nonrespondents, suggesting that users of the ASEC drop earnings nonrespondents.

Suggested Citation

  • James P. Ziliak & Charles Hokayem & Christopher R. Bollinger, 2022. "Trends in Earnings Volatility Using Linked Administrative and Survey Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 12-19, December.
    • Handle: RePEc:taf:jnlbes:v:41:y:2022:i:1:p:12-19
    DOI: 10.1080/07350015.2022.2102023
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    2. Robert Moffitt & Sisi Zhang, 2022. "Estimating Trends in Male Earnings Volatility with the Panel Study of Income Dynamics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 20-25, December.
    3. Kevin L. McKinney & John M. Abowd, 2022. "Male Earnings Volatility in LEHD Before, During, and After the Great Recession," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 33-39, December.
    4. Kyle Raze & Nicole Perales & Liana Christin Landivar, 2026. "Non-Random Assignment of Individual Identifiers and Selection into Linked Data: Implications for Research," Working Papers 26-06, Center for Economic Studies, U.S. Census Bureau.
    5. Michael D. Carr & Robert A. Moffitt & Emily E. Wiemers, 2020. "Reconciling Trends in Volatility: Evidence from the SIPP Survey and Administrative Data," NBER Working Papers 27672, National Bureau of Economic Research, Inc.
    6. Carr, Michael D. & Wiemers, Emily E., 2021. "The role of low earnings in differing trends in male earnings volatility," Economics Letters, Elsevier, vol. 199(C).
    7. J. Carter Braxton & Kyle Herkenhoff & Jonathan Rothbaum & Lawrence Schmidt, 2025. "Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter," American Economic Review, American Economic Association, vol. 115(12), pages 4438-4475, December.
    8. David Splinter, 2022. "Income Mobility and Inequality: Adult‐Level Measures From the Us Tax Data Since 1979," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(4), pages 906-921, December.
    9. 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.

    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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