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Robust Conditional Wald Inference for Over-Identified IV

David S. Lee, Justin McCrary, Marcelo J. Moreira, Jack Porter, Luther Yap

arXiv 27 Nov 2023 · Econometrics

arXiv:2311.15952 · PDF · DOI · OpenAlex · Extracted main text

Abstract

For the over-identified linear instrumental variables model, researchers commonly report the 2SLS estimate along with the robust standard error and seek to conduct inference with these quantities. If errors are homoskedastic, one can control the degree of inferential distortion using the first-stage F critical values from Stock and Yogo (2005), or use the robust-to-weak instruments Conditional Wald critical values of Moreira (2003). If errors are non-homoskedastic, these methods do not apply. We derive the generalization of Conditional Wald critical values that is robust to non-homoskedastic errors (e.g., heteroskedasticity or clustered variance structures), which can also be applied to nonlinear weakly-identified models (e.g. weakly-identified GMM).

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20
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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
1M. J. Moreira (2003) A Conditional Likelihood Ratio Test for Structural Models self1.000125100%
2James H. Stock \ Motohiro Yogo (2005) Testing for Weak Instruments in Linear IV Regression1.00073100%
3Isaiah Andrews (2016) Conditional Linear Combination Tests for Weakly Identified Models0.92843100%
4J-M. Dufour (1997) Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models0.73732100%
5Isaiah Andrews (2018) Valid Two-Step Identification-Robust Confidence Sets for GMM0.64422100%
6D. W. K. Andrews, M. J. Moreira \ J. H. Stock (2004) Optimal Invariant Similar Tests for Instrumental Variables Regression0.64422100%
7Isaiah Andrews, James H. Stock \ Liyang Sun (2019) Weak Instruments in Instrumental Variables Regression: Theory and Practice0.64422100%
8F. Kleibergen (2005) Testing Parameters in GMM without Assuming that they are Identified0.64422100%
9D. Staiger \ J. H. Stock (1997) Instrumental Variables Regression with Weak Instruments0.64422100%
10Whitney Newey \ Daniel L. McFadden (1994) Large Sample Estimation and Hypothesis Testing0.51121100%

Showing the top 10 of 21 scored citations.