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GMM estimation of the covariance structure of longitudinal data on earnings

  • Aedın Doris

    (National University of Ireland–Maynooth)

  • Donal O’Neill


    (National University of Ireland–Maynooth)

  • Olive Sweetman

    (National University of Ireland–Maynooth)

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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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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