Conditional Inference With a Functional Nuisance Parameter
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Mikusheva_Conditional Inference.pdf
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351.05 KB
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Author(s)
Andrews, Isaiah
Mikusheva, Anna
Date Issued
July 2016
Journal
Econometrica
Publisher
The Econometric Society
Citation
Andrews, Isaiah, and Anna Mikusheva. “Conditional Inference With a Functional Nuisance Parameter.” Econometrica 84, no. 4 (2016): 1571–1612.
Version
Original manuscript
Abstract
This paper shows that the problem of testing hypotheses in moment condition models without any assumptions about identification may be considered as a problem of testing with an infinite‐dimensional nuisance parameter. We introduce a sufficient statistic for this nuisance parameter in a Gaussian problem and propose conditional tests. These conditional tests have uniformly correct asymptotic size for a large class of models and test statistics. We apply our approach to construct tests based on quasi‐likelihood ratio statistics, which we show are efficient in strongly identified models and perform well relative to existing alternatives in two examples.
MIT Department
Massachusetts Institute of Technology. Department of Economics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.3982/ECTA12868
