GMM estimation of the covariance structure of longitudinal data on earnings
Aedín Doris
National University of Ireland–Maynooth
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Donal O'Neill
National University of Ireland–Maynooth and IZA Bonn
Department of Economics
Kildare, Ireland
[email protected]
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Olive Sweetman
National University of Ireland–Maynooth
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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.
View all articles by these authors:
Aedín Doris, Donal O'Neill, Olive Sweetman
View all articles with these keywords:
gmmcovearn, permanent inequality, transitory inequality, generalized method of moments, GMM, covariance structure of earnings
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