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GMM estimation of the covariance structure of longitudinal data on earnings

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Author Info

  • Aedın Doris

    (National University of Ireland–Maynooth)

  • Donal O’Neill

    ()
    (National University of Ireland–Maynooth)

  • Olive Sweetman

    (National University of Ireland–Maynooth)

Abstract

In this article, we discuss generalized method of moments estimation of the covariance structure of longitudinal data on earnings, and we introduce and illustrate a Stata program that facilitates the implementation of the generalized method of moments approach in this context. The program, gmmcovearn, estimates a variety of models that encompass those most commonly used by labor economists. These include models where the permanent component of earnings follows a random growth or random walk process and where the transitory component can follow either an AR(1) or an ARMA(1,1) process. In addition, time-factor loadings and cohort-factor loadings may be incorporated in the transitory and permanent components.

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Bibliographic Info

Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 11 (2011)
Issue (Month): 3 (September)
Pages: 439-459

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Handle: RePEc:tsj:stataj:v:11:y:2011:i:3:p:439-459

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Related research

Keywords: gmmcovearn; permanent inequality; transitory inequality; generalized method of moments; GMM; covariance structure of earnings;

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