Logit-based alternatives to two-stage least squares

Fuente: arXiv
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Autori principali: Chetverikov, Denis, Hahn, Jinyong, Liao, Zhipeng, Sheng, Shuyang
Natura: Preprint
Pubblicazione: 2023
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author Chetverikov, Denis
Hahn, Jinyong
Liao, Zhipeng
Sheng, Shuyang
author_facet Chetverikov, Denis
Hahn, Jinyong
Liao, Zhipeng
Sheng, Shuyang
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2312_10333
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Logit-based alternatives to two-stage least squares
Chetverikov, Denis
Hahn, Jinyong
Liao, Zhipeng
Sheng, Shuyang
Econometrics
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.
title Logit-based alternatives to two-stage least squares
topic Econometrics
url https://arxiv.org/abs/2312.10333