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Valid Wald Inference with Many Weak Instruments

Luther Yap

arXiv 27 Nov 2023 · Econometrics

arXiv:2311.15932 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper proposes three novel test procedures that yield valid inference in an environment with many weak instrumental variables (MWIV). It is observed that the t statistic of the jackknife instrumental variable estimator (JIVE) has an asymptotic distribution that is identical to the two-stage-least squares (TSLS) t statistic in the just-identified environment. Consequently, test procedures that were valid for TSLS t are also valid for the JIVE t. Two such procedures, i.e., VtF and conditional Wald, are adapted directly. By exploiting a feature of MWIV environments, a third, more powerful, one-sided VtF-based test procedure can be obtained.

Citation extraction

27
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Mikusheva, A. and L. Sun (2022) Inference with many weak instruments1.000174100%
2Chao, J. C., N. R. Swanson, J. A. Hausman, W. K. Newey, and T. Woute… (2012) Asymptotic distribution of JIVE in a heteroskedastic IV regression with many instruments1.00063100%
3Matsushita, Y. and T. Otsu (2022) A jackknife Lagrange multiplier test with many weak instruments1.00053100%
4Angrist, J. D., G. W. Imbens, and A. B. Krueger (1999) Jackknife instrumental variables estimation0.81142100%
5Moreira, M. J (2003) A conditional likelihood ratio test for structural models0.73732100%
6Stock, J. H. and M. Yogo (2005) Testing for Weak Instruments in Linear IV Regression, in0.64422100%
7Autor, D., A. Kostl, M. Mogstad, and B. Setzler (2019) Disability benefits, consumption insurance, and household labor supply0.51121100%
8Bhuller, M., G. B. Dahl, K. V. Lken, and M. Mogstad (2020) Incarceration, recidivism, and employment0.51121100%
9Dobbie, W., J. Goldin, and C. S. Yang (2018) The effects of pre-trial detention on conviction, future crime, and employment: Evidence from randomly assigned judges0.51121100%
10Kling, J. R (2006) Incarceration length, employment, and earnings0.51121100%

Showing the top 10 of 27 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Jackknife Instrumental Variable Inference0.51121
2An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models0.40511