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The nature of countercyclical income risk

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  • Fatih Guvenen
  • Serdar Ozkan
  • Jae Song

Abstract

This paper studies the nature of business cycle variation in individual earnings risk using a dataset from the U.S. Social Security Administration, which contains (uncapped) earnings histories for millions of anonymous individuals. The base sample is a nationally representative panel containing 10 percent of all U.S. males from 1978 to 2010. We use these data to decompose individual earnings growth during recessions into "between-group" and "within-group" components. We begin with the behavior of within-group shocks. Contrary to past research, we do not find the variance of idiosyncratic earnings shocks to be countercyclical. Instead, it is the left-skewness of shocks that is strongly countercyclical. That is, during recessions, the upper end of the shock distribution collapses--large upward earnings movements become less likely--whereas the bottom end expands--large drops in earnings become more likely. Thus, while the dispersion of shocks does not increase, shocks become more left skewed and, hence, riskier during recessions. Second, to study between-group differences, we group individuals based on several observable characteristics at the time a recession hits. One of these characteristics--the average earnings of an individual at the beginning of a business cycle episode--proves to be an especially good predictor of fortunes during a recession: prime-age workers that enter a recession with high average earnings suffer substantially less compared with those who enter with low average earnings (such "asymmetry" is not evident in expansions). Finally, we find that the cyclical nature of earnings risk is dramatically different for the top 1 percent compared with all other individuals--even relative to those in the top 2 to 5 percent.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2013-25.

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Date of creation: 2013
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Handle: RePEc:fip:fedgfe:2013-25

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  1. N. Gregory Mankiw, 1986. "The Equity Premium and the Concentration of Aggregate Shocks," NBER Working Papers 1788, National Bureau of Economic Research, Inc.
  2. Almut Balleer, Thijs van Rens, 2012. "Skill-Biased Technological Change and the Business Cycle," Kiel Working Papers 1775, Kiel Institute for the World Economy.
  3. Karen E. Dynan & Douglas W. Elmendorf & Daniel E. Sichel, 2007. "The evolution of household income volatility," Finance and Economics Discussion Series 2007-61, Board of Governors of the Federal Reserve System (U.S.).
  4. Sam Schulhofer-Wohl, 2011. "Heterogeneity and tests of risk sharing," Staff Report 462, Federal Reserve Bank of Minneapolis.
  5. Constantinides,George & Duffie,Darrel, 1992. "Asset pricing with heterogeneous consumers," Discussion Paper Serie A 381, University of Bonn, Germany.
  6. CASTRO, Rui & COEN-PIRANI, Daniele, 2005. "Why Have Aggregate Skilled Hours Become So Cyclical Since the Mid-1980's?," Cahiers de recherche 2005-19, Universite de Montreal, Departement de sciences economiques.
  7. Wojciech Kopczuk & Emmanuel Saez & Jae Song, 2010. "Earnings Inequality and Mobility in the United States: Evidence from Social Security Data since 1937," The Quarterly Journal of Economics, MIT Press, vol. 125(1), pages 91-128, February.
  8. Abraham, Katharine G. & Katz, Lawrence F., 1986. "Cyclical Unemployment: Sectoral Shifts or Aggregate Disturbances?," Scholarly Articles 3442781, Harvard University Department of Economics.
  9. Lilien, David M, 1982. "Sectoral Shifts and Cyclical Unemployment," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 777-93, August.
  10. Sabelhaus, John & Song, Jae, 2010. "The great moderation in micro labor earnings," Journal of Monetary Economics, Elsevier, vol. 57(4), pages 391-403, May.
  11. Rui Castro & Daniele Coen-Pirani, . "Why Have Aggregate Skilled Hours," GSIA Working Papers 2006-E27, Carnegie Mellon University, Tepper School of Business.
  12. Giesecke, Matthias & Bönke, Timm & Lüthen, Holger, 2011. "The Dynamics of Earnings in Germany: Evidence from Social Security Records," Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48692, Verein für Socialpolitik / German Economic Association.
  13. Kjetil Storesletten & Chris I. Telmer & Amir Yaron, 2004. "Cyclical Dynamics in Idiosyncratic Labor Market Risk," Journal of Political Economy, University of Chicago Press, vol. 112(3), pages 695-717, June.
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Cited by:
  1. Nicholas Bloom, 2014. "Fluctuations in Uncertainty," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 153-76, Spring.
  2. Nikolai Roussanov & Michael Michaux & Hui Chen, 2011. "Houses as ATMs? Mortgage Refinancing and Macroeconomic Uncertainty," 2011 Meeting Papers 1369, Society for Economic Dynamics.
  3. Lars Ljungvist & Thomas Sargent, 2014. "Career Length: Effects of Curvature of Earnings Profiles, Earnings Shocks, Taxes, and Social Security," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(1), pages 1-20, January.
  4. Facundo Piguillem & Anderson Schneider, 2013. "Heterogeneous Labor Skills, The Median Voter and Labor Taxes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(2), pages 332-349, April.
  5. Stéphane Bonhomme & Laura Hospido, 2012. "The Cycle Of Earnings Inequality: Evidence From Spanish Social Security Data," Working Papers wp2012_1209, CEMFI.
  6. Kim, Seewon, 2013. "Prudent consumers: New evidence from the Consumer Expenditure Survey," Economic Modelling, Elsevier, vol. 33(C), pages 77-85.
  7. Fatih Guvenen & Greg Kaplan & Jae Song, 2014. "How Risky Are Recessions for Top Earners?," NBER Working Papers 19864, National Bureau of Economic Research, Inc.
  8. Athreya, Kartik B. & Sanchez, Juan M. & Tam, Xuan S. & Young, Eric R., 2014. "Labor market upheaval, default regulations, and consumer debt," Working Papers 2014-2, Federal Reserve Bank of St. Louis.

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