The problem of instrument proliferation and its consequences—overfitting of the endogenous explanatory variables, biased instrumental-variables and generalized method of moments estimators, and weakening of the power of the overidentification tests—are well known. This article introduces a statistical method to reduce the instrument count. Principal component analysis is applied on the instrument matrix, and the principal-component analysis scores are used as instruments for the panel generalized method of moments estimation. This strategy is implemented through the new command pca2.
Titolo: | Implementing a strategy to reduce the instrument count in panel GMM |
Autore/i: | BONTEMPI, MARIA ELENA; MAMMI, IRENE |
Autore/i Unibo: | |
Anno: | 2015 |
Rivista: | |
Abstract: | The problem of instrument proliferation and its consequences—overfitting of the endogenous explanatory variables, biased instrumental-variables and generalized method of moments estimators, and weakening of the power of the overidentification tests—are well known. This article introduces a statistical method to reduce the instrument count. Principal component analysis is applied on the instrument matrix, and the principal-component analysis scores are used as instruments for the panel generalized method of moments estimation. This strategy is implemented through the new command pca2. |
Data stato definitivo: | 2016-01-11T15:37:44Z |
Appare nelle tipologie: | 1.01 Articolo in rivista |
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