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Inequality in Unemployment Risk and in Wages

  • Josep Pijoan-Mas

    (CEMFI)

  • Hernan Ruffo

    (UTDT)

  • Claudio Michelacci

    (CEMFI)

Distinguishing between the relative roles of skills and luck in the determination of wages is a main concern for economic policy. Variation in observed characteristics of workers and firms typically account for one third of total variance in wages in the US. Luck, as a result of frictions in the process of job search, might explain some of the remaining proportion, but search models can only fill a tiny part of this gap when calibrated to mean transition rates. The aim of this paper is to highlight the existence of heterogeneity in finding and separation rates and to show its impact on inequality. In particular, we first reassess the role of frictions in wage dispersion by introducing heterogeneity in unemployment risk, both as exogenous fixed heterogeneity and with some duration dependence. Secondly, to endogenize this heterogeneity, we borrow from Ljungqvist and Sargent (1998), extending it to account for endogenous separation, and build a quantitative search model with human capital accumulation. In this context, a job is valuable for the inexperienced worker not only because of the wage but also for the opportunity to accumulate skills. At the same time, the unemployment spell is damaging for an experienced worker not only because of the foregone earnings but also for the loss of human capital that it entails. Thus, reservation wages and transition rates depend on individual labor market histories. We calibrate the model to match the observed heterogeneity in finding and separation rates and show that the implied wage dispersion is almost the residual wage dispersion in the data. Furthermore, when we shock the model to account for the change in human capital accumulation process in the US economy, we are able to explain all of the increase in inequality over the last decades. We conclude that heterogeneity in unemployment risk and the incentives related to human capital accumulation and depreciation are main drivers of frictional wage dispersions.

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Paper provided by Society for Economic Dynamics in its series 2012 Meeting Papers with number 794.

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Date of creation: 2012
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Handle: RePEc:red:sed012:794
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  1. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
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  9. Gueorgui Kambourov & Iourii Manovskii, 2000. "Occupational Mobility and Wage Inequality, Second Version," PIER Working Paper Archive 04-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 15 Jun 2004.
  10. Giovanni L. Violante, 2002. "Technological Acceleration, Skill Transferability, And The Rise In Residual Inequality," The Quarterly Journal of Economics, MIT Press, vol. 117(1), pages 297-338, February.
  11. Pedro Portugal, 2007. "U.S. Unemployment Duration: Has Long Become Longer or Short Become Shorter?," Working Papers 2007/17, Czech National Bank, Research Department.
  12. Andreas Hornstein & Per Krusell & Giovanni L. Violante, 2011. "Frictional Wage Dispersion in Search Models: A Quantitative Assessment," American Economic Review, American Economic Association, vol. 101(7), pages 2873-98, December.
  13. Audra J. Bowlus & Jean-Marc Robin, 2004. "Twenty Years of Rising Inequality in U.S. Lifetime Labour Income Values," Review of Economic Studies, Oxford University Press, vol. 71(3), pages 709-742.
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  17. Robert H. Topel, 1997. "Factor Proportions and Relative Wages: The Supply-Side Determinants of Wage Inequality," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 55-74, Spring.
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  24. Eric D. Gould, 2002. "Rising Wage Inequality, Comparative Advantage, and the Growing Importance of General Skills in the United States," Journal of Labor Economics, University of Chicago Press, vol. 20(1), pages 105-147, January.
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