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GMM estimation of the covariance structure of longitudinal data on earnings

Author

Listed:
  • 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.

Suggested Citation

  • Aedın Doris & Donal O’Neill & Olive Sweetman, 2011. "GMM estimation of the covariance structure of longitudinal data on earnings," Stata Journal, StataCorp LP, vol. 11(3), pages 439-459, September.
  • Handle: RePEc:tsj:stataj:v:11:y:2011:i:3:p:439-459
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj11-3/st0239/
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    References listed on IDEAS

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    4. Valentino Dardanoni & Giuseppe De Luca & Salvatore Modica & Franco Peracchi, 2012. "A generalized missing-indicator approach to regression with imputed covariates," Stata Journal, StataCorp LP, vol. 12(4), pages 575-604, December.
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    11. repec:hal:journl:peer-00815561 is not listed on IDEAS
    12. Jan R. Magnus, 2002. "Estimation of the mean of a univariate normal distribution with known variance," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 225-236, June.
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    Cited by:

    1. Aedín Doris & Donal O’Neill & Olive Sweetman, 2013. "Identification of the covariance structure of earnings using the GMM estimator," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(3), pages 343-372, September.
    2. Mirko Felchner, 2015. "Einkommensdynamik bei Selbständigen als Freie Berufe und abhängig Beschäftigte Eine dynamische Paneldatenschätzung mit Daten des Sozio-oekonomischen Panels," FFB-Discussionpaper 101, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.

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