Journal Article

Valid Inference in Partially Unstable Generalized Method of Moments Models

Hong Li and Ulrich K. Müller

in The Review of Economic Studies

Published on behalf of Review of Economic Studies Ltd

Volume 76, issue 1, pages 343-365
Published in print January 2009 | ISSN: 0034-6527
Published online January 2009 | e-ISSN: 1467-937X | DOI: http://dx.doi.org/10.1111/j.1467-937X.2008.00516.x
Valid Inference in Partially Unstable Generalized Method of Moments Models

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This paper considers time series Generalized Method of Moments (GMM) models where a subset of the parameters are time varying. We focus on an empirically relevant case with moderately large instabilities, which are well approximated by a local asymptotic embedding that does not allow the instability to be detected with certainty, even in the limit. We show that for many forms of the instability and a large class of GMM models, usual GMM inference on the subset of stable parameters is asymptotically unaffected by the partial instability. In the empirical analysis of presumably stable parameters—such as structural parameters in Euler conditions—one can thus ignore moderate instabilities in other parts of the model and still obtain approximately correct inference.

Keywords: C22; C32

Journal Article.  10966 words.  Illustrated.

Subjects: Multiple or Simultaneous Equation Models; Multiple Variables ; Single Equation Models; Single Variables

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