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Small Sample Properties of Bayesian Estimators of Labor Income Processes

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  • Nakata, Taisuke

    ()
    (Board of Governors of the Federal Reserve System (U.S.))

  • Tonetti, Christopher

    ()
    (Stanford GSB)

Abstract

There exists an extensive literature estimating idiosyncratic labor income processes. While a wide variety of models are estimated, GMM estimators are almost always used. We examine the validity of using likelihood based estimation in this context by comparing the small sample properties of a Bayesian estimator to those of GMM. Our baseline studies estimators of a commonly used simple earnings process. We extend our analysis to more complex environments, allowing for real world phenomena such as time varying and heterogeneous parameters, missing data, unbalanced panels, and non-normal errors. The Bayesian estimators are demonstrated to have favorable bias and efficiency properties.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2014-25.

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Length: 38 pages
Date of creation: 31 Mar 2014
Date of revision:
Handle: RePEc:fip:fedgfe:2014-25

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Related research

Keywords: Labor income process; small sample properties; GMM; bayesian estimation; error component models;

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  1. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
  2. 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.
  3. Fatih Guvenen, 2005. "An Empirical Investigation of Labor Income Processes," Macroeconomics 0508026, EconWPA.
  4. Lillard, Lee A & Weiss, Yoram, 1979. "Components of Variation in Panel Earnings Data: American Scientists, 1960-70," Econometrica, Econometric Society, vol. 47(2), pages 437-54, March.
  5. Geweke, John & Keane, Michael, 2000. "An empirical analysis of earnings dynamics among men in the PSID: 1968-1989," Journal of Econometrics, Elsevier, vol. 96(2), pages 293-356, June.
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