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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 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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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
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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. 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.).
  2. Constantinides,George & Duffie,Darrel, 1992. "Asset pricing with heterogeneous consumers," Discussion Paper Serie A 381, University of Bonn, Germany.
  3. Rui Castro & Daniele Coen-Pirani, . "Why Have Aggregate Skilled Hours Become So Cyclical Since the Mid 1980s?," GSIA Working Papers 2006-E27, Carnegie Mellon University, Tepper School of Business.
  4. Sam Schulhofer-Wohl, 2011. "Heterogeneity and tests of risk sharing," Staff Report 462, Federal Reserve Bank of Minneapolis.
  5. Lilien, David M, 1982. "Sectoral Shifts and Cyclical Unemployment," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 777-93, August.
  6. Katharine G. Abraham & Lawrence F. Katz, 1987. "Cyclical Unemployment: Sectoral Shifts or Aggregate Disturbances?," NBER Working Papers 1410, National Bureau of Economic Research, Inc.
  7. Almut Balleer & Thijs van Rens, 2008. "Skill-biased technological change and the business cycle," Economics Working Papers 1079, Department of Economics and Business, Universitat Pompeu Fabra, revised May 2012.
  8. Rui Castro & Daniele Coen-Pirani, . "Why Have Aggregate Skilled Hours," GSIA Working Papers 2006-E27, Carnegie Mellon University, Tepper School of Business.
  9. 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.
  10. N. Gregory Mankiw, 1986. "The Equity Premium and the Concentration of Aggregate Shocks," NBER Working Papers 1788, National Bureau of Economic Research, Inc.
  11. 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.
  12. Sabelhaus, John & Song, Jae, 2010. "The great moderation in micro labor earnings," Journal of Monetary Economics, Elsevier, vol. 57(4), pages 391-403, May.
  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. 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.
  3. 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.
  4. 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.
  5. Nikolai Roussanov & Michael Michaux & Hui Chen, 2011. "Houses as ATMs? Mortgage Refinancing and Macroeconomic Uncertainty," 2011 Meeting Papers 1369, Society for Economic Dynamics.
  6. Stéphane Bonhomme & Laura Hospido, 2012. "The Cycle Of Earnings Inequality: Evidence From Spanish Social Security Data," Working Papers wp2012_1209, CEMFI.
  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. Kim, Seewon, 2013. "Prudent consumers: New evidence from the Consumer Expenditure Survey," Economic Modelling, Elsevier, vol. 33(C), pages 77-85.

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