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An Empirical Analysis of Income Dynamics among Men in the PSID: 1968–1989

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  • J. Geweke
  • M. Keane

Abstract

This study uses data from the Panel Survey of Income Dynamics (PSID) to address a number of questions about life-cycle earnings mobility. It develops a dynamic reduced-form model of earnings and marital status that is nonstationary over the life-cycle. A Gibbs sampling-data augmentation algorithm facilitates use of the entire sample and provides numerical approximations to the exact posterior distribution of properties of earnings paths. This algorithm copes with the complex distribution of endogenous variables that are observed for short segments of an individual’s work history, not including the initial period. The study reaches several firm conclusions about life cycle earnings mobility. Incorporating non-Gaussian shocks makes it possible to account for transitions between low and higher earnings states, a heretofore unresolved problem. The non-Gaussian distribution substantially increases the lifetime return to postsecondary education, and substantially reduces differences in lifetime wages attributable to race. In a given year, the majority of variance in earnings not accounted for by race, education, and age is due to transitory shocks, but over a lifetime the majority is due to unobserved individual heterogeneity. Consequently, low earnings at early ages are strong predictors of low earnings later in life, even conditioning on observed individual characteristics.

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Bibliographic Info

Paper provided by University of Wisconsin Institute for Research on Poverty in its series Institute for Research on Poverty Discussion Papers with number 1127-97.

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Handle: RePEc:wop:wispod:1127-97

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  1. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
  2. Horowitz, J.L. & Markatou, M., 1993. "Semiparametric Estimation of Regression Models for Panel Data," Working Papers 93-14, University of Iowa, Department of Economics.
  3. John Geweke, . "Posterior Simulators in Econometrics," Computing in Economics and Finance 1996 _019, Society for Computational Economics.
  4. Shorrocks, A F, 1976. "Income Mobility and the Markov Assumption," Economic Journal, Royal Economic Society, vol. 86(343), pages 566-78, September.
  5. Gottschald, Peter T, 1982. "Earnings Mobility: Permanent Change or Transitory Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 64(3), pages 450-56, August.
  6. Joel L. Horowitz & Marianthi Markatou, 1993. "Semiparametric Estimation Of Regression Models For Panel Data," Econometrics 9309001, EconWPA.
  7. Lillard, Lee A & Willis, Robert J, 1978. "Dynamic Aspects of Earning Mobility," Econometrica, Econometric Society, vol. 46(5), pages 985-1012, September.
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Cited by:
  1. Robert M. Sauer & Michael P. Keane, 2004. "A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables," Econometric Society 2004 North American Summer Meetings 136, Econometric Society.
  2. Shane T. Jensen & Stephen H. Shore, 2008. "Changes in the Distribution of Income Volatility," Papers 0808.1090, arXiv.org.
  3. Maury Gittleman & Mary Joyce, 1999. "Have family income mobility patterns changed?," Demography, Springer, vol. 36(3), pages 299-314, August.
  4. Tom Krebs, 2003. "Growth and Welfare Effects of Business Cycles in Economies with Idiosyncratic Human Capital Risk," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 846-868, October.

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