Consistent Model and Moment Selection Criteria for GMM Estimation with Applications to Dynamic Panel Data Models

Donald W. K. Andrews () and Biao Lu
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Biao Lu: Dept. Finance, Univ. Michigan Business School

No 1233, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

Abstract: This paper develops consistent model and moment selection criteria for GMM estimation. The criteria select the correct model specification and all correct moment conditions asymptotically. The selection criteria resemble the widely used likelihood-based selection criteria BIC, HQIC, and AIC. (The latter is not consistent.) The GMM selection criteria are based on the J statistic for testing over-identifying restrictions. Bonus terms reward the use of fewer parameters for a given number of moment conditions and the use of more moment conditions for a given number of parameters. The paper applies the model and moment selection criteria to dynamic panel data models with unobserved individual effects. The paper shows how to apply the selection criteria to select the lag length for lagged dependent variables, to detect the number and locations of structural breaks, to determine the exogeneity of regressors, and/or to determine the existence of correlation between some regressors and the individual effect. To illustrate the finite sample performance of the selection criteria and their impact on parameter estimation, the paper reports the results of a Monte Carlo experiment on a dynamic panel data model.

Keywords: Akaike information criterion; Bayesian information criterion; consistent selection procedure; generalized method of moments estimator; instrumental variables estimator; model selection; moment selection; panel data model; test of over-identifying restrictions (search for similar items in EconPapers)
JEL-codes: C12 C13 C52 (search for similar items in EconPapers)
Date: Written
Note: CFP 1015.
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Published in Journal of Econometrics (2001), 101(1): 123-164

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