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An Empirical Investigation of Labor Income Processes

  • Economics
  • Education


An Empirical Investigation of Labor Income Processes� Fatih Guveneny August 25, 2005 Abstract The current literature offers two views on the nature of the income process. Ac- cording to the first view, which we call the “Restricted Income Profiles” (RIP) model (MaCurdy, 1982), individuals are subject to large and very persistent shocks, while facing similar life-cycle income profiles (conditional on a few characteristics). Accord- ing to the alternative view, which we call the “Heterogeneous Income Profiles” (HIP) model (Lillard and Weiss, 1979), individuals are subject to income shocks with mod- est persistence, while facing individual-specific income profiles. In this paper, we first show that ignoring profile heterogeneity, when in fact it is present, introduces an up- ward bias into the estimates of persistence. Second, we estimate a parsimonious pa- rameterization of the HIP model that is suitable for calibrating economic models. The estimated persistence is about 0.8 in the HIP model compared to about 0.99 in the RIP model. Moreover, the heterogeneity in income profiles is estimated to be substantial, explaining between 65 to 80 percent of income inequality at the time of retirement. We also analyze the differences in the income process by education and find that profile heterogeneity is significantly larger among higher educated individuals. Finally we show that the main evidence against profile heterogeneity in the existing literature— that the autocorrelations of income changes are small and negative—is also replicated by the HIP model, casting doubt on the previous interpretation of this evidence. JEL classification: C33, D31, J31. �I would like to thank Daron Acemoglu, Joe Altonji, Orazio Attanasio, Michael Baker, Mark Bils, Richard Blundell, Jeremy Greenwood, James Heckman, Hugo Hopenhayn, Lawrence Katz, Per Krusell, Lee Ohanian, Kjetil Storesletten, Gianluca Violante, the seminar participants at Harvard, MIT, Northwest- ern, NYU, New York FED, Rochester, UCLA, UPenn, USC, U

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