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Generalized method of moments estimation of linear dynamic panel-data models

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  • Sebastian Kripfganz

    (University of Exeter Business School)

Abstract

In dynamic models with unobserved group-specific effects, the lagged dependent variable is an endogenous regressor by construction. The conventional fixed-effects estimator is biased and inconsistent under fixed-T asymptotics. To deal with this problem, "difference GMM" and "system GMM" estimators in the spirit of Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (1998) are predominantly applied in practice. The Stata community widely associates these methods with the xtabond2 command provided by Roodman (2009). I present the new xtdpdgmm command, which addresses some shortcomings of xtabond2 and adds further flexibility to the specification of the estimators. In particular, it allows one to incorporate the Ahn and Schmidt (1995) nonlinear moment conditions that can improve the efficiency and robustness of the estimation. Besides the familiar one-step and two-step estimators, xtdpdgmm also provides the Hansen, Heaton, and Yaron (1996) iterated GMM estimator.

Suggested Citation

  • Sebastian Kripfganz, 2020. "Generalized method of moments estimation of linear dynamic panel-data models," 2020 Stata Conference 14, Stata Users Group.
    • Handle: RePEc:boc:scon20:14
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
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    7. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
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