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OPTIMAL INVARIANT INFERENCE WHEN THE NUMBER OF INSTRUMENTS IS LARGE

Published online by Cambridge University Press:  01 June 2009

Laura Chioda  and
Michael Jansson
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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.

Type
Research Article
Information
Econometric Theory , Volume 25 , Issue 3 , June 2009 , pp. 793 - 805
Copyright
Copyright © Cambridge University Press 2009

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Footnotes

The authors thank Whitney Newey, Jim Powell, a co-editor, and a referee for helpful comments.

References

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