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Weak Instrumental Variables: Limitations of Traditional 2SLS and Exploring Alternative Instrumental Variable Estimators

Aiwei Huang, Madhurima Chandra, Laura Malkhasyan

arXiv 26 Apr 2021 · Econometrics · 1 citations (OpenAlex)

arXiv:2104.12370 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Instrumental variables estimation has gained considerable traction in recent decades as a tool for causal inference, particularly amongst empirical researchers. This paper makes three contributions. First, we provide a detailed theoretical discussion on the properties of the standard two-stage least squares estimator in the presence of weak instruments and introduce and derive two alternative estimators. Second, we conduct Monte-Carlo simulations to compare the finite-sample behavior of the different estimators, particularly in the weak-instruments case. Third, we apply the estimators to a real-world context; we employ the different estimators to calculate returns to schooling.

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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
1Joshua David Angrist, Guido W Imbens, and Alan B Krueger (1999) Jackknife instrumental variables estimation1.00087100%
2James H Stock, Jonathan H Wright, and Motohiro Yogo (2002) A survey of weak instruments and weak identification in generalized method of moments1.00054100%
3John Bound, David A Jaeger, and Regina M Baker (1995) Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory vari…1.00053100%
4Douglas Staiger and James Stock (1997) Stock (1997). instrumental variables with weak instruments0.92844100%
5Joshua D Angrist and Alan B Krueger (1991) Does compulsory school attendance affect schooling and earnings?0.87462100%
6Theodore W Anderson, Herman Rubin, et al (1949) Estimation of the parameters of a single equation in a complete system of stochastic equations0.84333100%
7James H Stock and Motohiro Yogo (2002) Testing for weak instruments in linear iv regression0.7373367%
8Sören Blomquist and Matz Dahlberg (1999) Small sample properties of liml and jackknife iv estimators: experiments with weak instruments0.64422100%
9Russell Davidson and James G MacKinnon (2006) The case against jive0.64422100%
10Anirudh L Nagar (1959) The bias and moment matrix of the general k-class estimators of the parameters in simultaneous equations0.64422100%

Showing the top 10 of 24 scored citations.