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Logit-based alternatives to two-stage least squares

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  • Denis Chetverikov
  • Jinyong Hahn
  • Zhipeng Liao
  • Shuyang Sheng

Abstract

We propose logit-based IV and augmented logit-based IV estimators that serve as alternatives to the traditionally used 2SLS estimator in the model where both the endogenous treatment variable and the corresponding instrument are binary. Our novel estimators are as easy to compute as the 2SLS estimator but have an advantage over the 2SLS estimator in terms of causal interpretability. In particular, in certain cases where the probability limits of both our estimators and the 2SLS estimator take the form of weighted-average treatment effects, our estimators are guaranteed to yield non-negative weights whereas the 2SLS estimator is not.

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  • Denis Chetverikov & Jinyong Hahn & Zhipeng Liao & Shuyang Sheng, 2023. "Logit-based alternatives to two-stage least squares," Papers 2312.10333, arXiv.org.
    • Handle: RePEc:arx:papers:2312.10333
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    References listed on IDEAS

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    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    2. Horowitz, Joel L & Spokoiny, Vladimir G, 2001. "An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model against a Nonparametric Alternative," Econometrica, Econometric Society, vol. 69(3), pages 599-631, May.
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