Testing for weak identification in possibly nonlinear models

Atsushi Inoue and Barbara Rossi

Journal of Econometrics, 2011, vol. 161, issue 2, 246-261

Abstract: In this paper we propose a chi-square test for identification. Our proposed test statistic is based on the distance between two shrinkage extremum estimators. The two estimators converge in probability to the same limit when identification is strong, and their asymptotic distributions are different when identification is weak. The proposed test is consistent not only for the alternative hypothesis of no identification but also for the alternative of weak identification, which is confirmed by our Monte Carlo results. We apply the proposed technique to test whether the structural parameters of a representative Taylor-rule monetary policy reaction function are identified.

Keywords: GMM; Shrinkage; Weak; identification (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (17)

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Working Paper: Testing for Weak Identification in Possibly Nonlinear Models (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:161:y:2011:i:2:p:246-261

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