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OPTIMAL INVARIANT INFERENCE WHEN THE NUMBEROF INSTRUMENTS IS LARGE

Published online by Cambridge University Press:  01 June 2009

Laura Chioda and
Michael Jansson
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Abstract

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This paper studies the asymptotic behavior of aGaussian linear instrumental variables model inwhich the number of instruments diverges with thesample size. Asymptotic efficiency bounds areobtained for rotation invariant inference proceduresand are shown to be attainable by procedures basedon the limited information maximum likelihoodestimator. The bounds are obtained by characterizingthe limiting experiment associated with the modelinduced by the rotation invariance restriction.

Information

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

Footnotes

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

References

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