
doi: 10.3982/ecta16274
handle: 1959.4/unsworks_76211
This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild misspecification. Moment misspecification causes bias in conventional GMM variance estimators, which can lead to severely oversized hypothesis tests. We show how to consistently estimate the correct asymptotic variance matrix. Our simulation results show that our methods are properly sized under both correct specification and mild to moderate misspecification. We illustrate the method with an application to the model of Acemoglu, Johnson, Robinson, and Yared (2008).
anzsrc-for: 3801 Applied Economics, anzsrc-for: 3803 Economic theory, 330, Estimation in multivariate analysis, 38 Economics, Analysis of variance and covariance (ANOVA), generalized method of moments, anzsrc-for: 1401 Economic Theory, misspecification, covariance matrix estimation, overidentification, 3801 Applied Economics, 3802 Econometrics, anzsrc-for: 1403 Econometrics, anzsrc-for: 38 Economics, Economic growth models, anzsrc-for: 1402 Applied Economics, Applications of statistics to economics, anzsrc-for: 3802 Econometrics
anzsrc-for: 3801 Applied Economics, anzsrc-for: 3803 Economic theory, 330, Estimation in multivariate analysis, 38 Economics, Analysis of variance and covariance (ANOVA), generalized method of moments, anzsrc-for: 1401 Economic Theory, misspecification, covariance matrix estimation, overidentification, 3801 Applied Economics, 3802 Econometrics, anzsrc-for: 1403 Econometrics, anzsrc-for: 38 Economics, Economic growth models, anzsrc-for: 1402 Applied Economics, Applications of statistics to economics, anzsrc-for: 3802 Econometrics
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