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Activity Number:
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86
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Type:
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Invited
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Date/Time:
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Monday, August 3, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #302738 |
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Title:
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Testing for Identification in Possibly Nonlinear Models
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Author(s):
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Atsushi Inoue*+ and Barbara Rossi
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Companies:
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North Carolina State University and Duke University
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Address:
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Department of Agricultural and Resource Economics, Raleigh, NC, 27695-8109,
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Keywords:
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GMM ; shrinkage ; identification
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Abstract:
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In this paper we propose a chi-square test for identification. Our proposed test statistic is based on the distance between two bias-corrected shrinkage extremum estimators. The two estimators converge in probability to the same limit when identification is strong, and they converge weakly to different random variables 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 experiment results. We apply the proposed technique to test whether the structural parameters of a representative Taylor-rule monetary policy reaction function are identified.
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