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Optimal Comparison of Misspecified Moment Restriction Models

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Author Info
Vadim Marmer (University of British Columbia)
Taisuke Otsu () (Cowles Foundation, Yale University)

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Abstract

This paper considers optimal testing of model comparison hypotheses for misspecified unconditional moment restriction models. We adopt the generalized Neyman-Pearson optimality criterion, which focuses on the convergence rates of the type I and II error probabilities under fixed global alternatives, and derive an optimal but practically infeasible test. We then propose feasible approximation test statistics to the optimal one. For linear instrumental variable regression models, the conventional empirical likelihood ratio test statistic emerges. For general nonlinear moment restrictions, we propose a new test statistic based on an iterative algorithm. We derive asymptotic properties of these test statistics.

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File URL: http://cowles.econ.yale.edu/P/cd/d17a/d1724.pdf
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Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 1724.

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Length: 46 pages
Date of creation: Aug 2009
Date of revision:
Handle: RePEc:cwl:cwldpp:1724

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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Related research
Keywords: Moment restriction; Model comparison; Misspecification; Generalized Neyman-Pearson optimality; Empirical likelihood; GMM;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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