OPTIMAL INVARIANT INFERENCE WHEN THE NUMBER OF INSTRUMENTS IS LARGE

Laura Chioda and Michael Jansson ()

Econometric Theory, 2009, vol. 25, issue 03, pages 793-805

Abstract: This paper studies the asymptotic behavior of a Gaussian linear instrumental variables model in which the number of instruments diverges with the sample size. Asymptotic efficiency bounds are obtained for rotation invariant inference procedures and are shown to be attainable by procedures based on the limited information maximum likelihood estimator. The bounds are obtained by characterizing the limiting experiment associated with the model induced by the rotation invariance restriction.

Date: 2009
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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:25:y:2009:i:03:p:793-805_09

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