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The Nature of Countercyclical Income Risk

  • Fatih Guvenen
  • Serdar Ozkan
  • Jae Song

This paper studies the cyclical nature of individual income risk using a confidential dataset from the U.S. Social Security Administration, which contains (uncapped) earnings histories for millions of 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 income 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 income 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 income movements become less likely--whereas the bottom end expands--large drops in income become more likely. Thus, while the dispersion of shocks does not increase, shocks become more left skewed and, hence, risky 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 income 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 (which is not the case during expansions). Finally, we find that the cyclical nature of income 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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File URL: http://www.nber.org/papers/w18035.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18035.

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Date of creation: May 2012
Publication status: published as The Nature of Countercyclical Income Risk (with S. Ozkan and J. Song), Journal of Political Economy, 2014, Vol. 122, No. 3, pp. 621-660.
Handle: RePEc:nbr:nberwo:18035
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  1. 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.
  2. Sam Schulhofer-Wohl, 2011. "Heterogeneity and tests of risk sharing," Staff Report 462, Federal Reserve Bank of Minneapolis.
  3. Almut Balleer & Thijs van Rens, 2013. "Skill-Biased Technological Change and the Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1222-1237, October.
  4. Alon Brav & George M. Constantinides & Christopher C. Geczy, 2002. "Asset Pricing with Heterogeneous Consumers and Limited Participation: Empirical Evidence," NBER Working Papers 8822, National Bureau of Economic Research, Inc.
  5. Serdar Ozkan & Jae Song & Fatih Karahan & Fatih Guvenen, 2013. "What Do Data on Millions of U.S. Workers Say About Labor Income Risk?," 2013 Meeting Papers 1271, Society for Economic Dynamics.
  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. Lilien, David M, 1982. "Sectoral Shifts and Cyclical Unemployment," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 777-793, August.
  8. R. Anton Braun & Tomoyuki Nakajima, 2012. "Uninsured Countercyclical Risk: An Aggregation Result And Application To Optimal Monetary Policy," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1450-1474, December.
  9. Bönke, Timm & Giesecke, Matthias & Lüthen, Holger, 2015. "The dynamics of earnings in Germany: Evidence from social security records," Discussion Papers 2015/26, Free University Berlin, School of Business & Economics.
  10. Rui Castro & Daniele Coen-Pirani, . "Why Have Aggregate Skilled Hours," GSIA Working Papers 2006-E27, Carnegie Mellon University, Tepper School of Business.
  11. Sabelhaus, John & Song, Jae, 2010. "The great moderation in micro labor earnings," Journal of Monetary Economics, Elsevier, vol. 57(4), pages 391-403, May.
  12. Constantinides, George M & Duffie, Darrell, 1996. "Asset Pricing with Heterogeneous Consumers," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 219-240, April.
  13. Abraham, Katharine G & Katz, Lawrence F, 1986. "Cyclical Unemployment: Sectoral Shifts or Aggregate Disturbances?," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 507-522, June.
  14. N. Gregory Mankiw, 1986. "The Equity Premium and the Concentration of Aggregate Shocks," NBER Working Papers 1788, National Bureau of Economic Research, Inc.
  15. 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.).
  16. 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, Oxford University Press, vol. 125(1), pages 91-128.
  17. Fatih Guvenen & Fatih Karahan & Serdar Ozkan & Jae Song, 2013. "What Do Data on Millions of U.S. Workers Say About Life Cycle Income Risk?," Working Papers wp302, University of Michigan, Michigan Retirement Research Center.
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