The problem of instrument proliferation and its consequences (overfitting of the endogenous explanatory variables, biased IV and GMM estimators, weakening of the power of the overidentification tests) are well known. This paper introduces a statistical method to reduce the instrument count. The principal component analysis (PCA) is applied on the instrument matrix, and the PCA scores are used as instruments for the panel generalized method-of-moments (GMM) estimation. This strategy is implemented through the new command pca2.
pca2: implementing a strategy to reduce the instrument count in panel GMM
Bontempi, Maria Elena
;Mammi, Irene
2014
Abstract
The problem of instrument proliferation and its consequences (overfitting of the endogenous explanatory variables, biased IV and GMM estimators, weakening of the power of the overidentification tests) are well known. This paper introduces a statistical method to reduce the instrument count. The principal component analysis (PCA) is applied on the instrument matrix, and the PCA scores are used as instruments for the panel generalized method-of-moments (GMM) estimation. This strategy is implemented through the new command pca2.File in questo prodotto:
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