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Information Theoretic Approaches to Inference in Moment Condition Models

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  • Guido W. Imbens
  • Phillip Johnson
  • Richard H. Spady

Abstract

This paper develops a variant of one-step efficient GMM based on the KLIC rather than empirical likelihood. As in other one-step methods, the authors introduce M (the number of moments) auxiliary 'tilting' parameters which are used to construct a reweighting of the data so that the reweighted sample obeys all the moment conditions at the parameter estimates. Parameter and overidentification tests can be recast in terms of these tilting parameters; such tests are often startlingly more effective than their conventional counterparts. These performance differences cannot be completely explained by the leading terms of the statistics' asymptotic expansions.
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Suggested Citation

  • Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," Harvard Institute of Economic Research Working Papers 1736, Harvard - Institute of Economic Research.
  • Handle: RePEc:fth:harver:1736
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    References listed on IDEAS

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