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Testing for weak instruments in linear IV regression

Author: James H Stock; Motohiro Yogo; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2002.
Series: NBER technical working paper series, no. 284.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Abstract: Weak instruments can produce biased IV estimators and hypothesis tests with large size distortions. But what, precisely, are weak instruments, and how does one detect them in practice? This paper proposes quantitative definitions of weak instruments based on the maximum IV estimator bias, or the maximum Wald test size distortion, when there are multiple endogenous regressors. We tabulate critical values  Read more...
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Additional Physical Format: Print version:
Stock, James H.
Testing for weak instruments in linear IV regression.
Cambridge, Mass. : National Bureau of Economic Research, ©2002
(OCoLC)51678052
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James H Stock; Motohiro Yogo; National Bureau of Economic Research.
OCLC Number: 647593676
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (61, [10] pages) : illustrations.
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Series Title: NBER technical working paper series, no. 284.
Responsibility: James H. Stock, Motohiro Yogo.

Abstract:

Abstract: Weak instruments can produce biased IV estimators and hypothesis tests with large size distortions. But what, precisely, are weak instruments, and how does one detect them in practice? This paper proposes quantitative definitions of weak instruments based on the maximum IV estimator bias, or the maximum Wald test size distortion, when there are multiple endogenous regressors. We tabulate critical values that enable using the first-stage F-statistic (or, when there are multiple endogenous regressors, the Cragg-Donald (1993) statistic) to test whether given instruments are weak. A technical contribution is to justify sequential asymptotic approximations for IV statistics with many weak instruments.

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