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Logit-based alternatives to two-stage least squares

Denis Chetverikov, Jinyong Hahn, Zhipeng Liao, Shuyang Sheng

arXiv 16 Dec 2023 · Econometrics

arXiv:2312.10333 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

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main-text words

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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
1Blandhol, Bonney, Mogstad and Torgovitsky (2022) When is TSLS actually LATE?1.00074100%
2Dube and Harish (2020) Queens0.874112100%
3Angrist, Bettinger, Bloom, King and Kremer (2002) Vouchers for Private Schooling in Colombia: Evidence from a Randomized Natural Experiment0.87482100%
4Angrist and Evans (1998) Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size0.87482100%
5Imbens and Angrist (1994) Identification and estimation of local average treatment effects0.73732100%
6Abadie (2003) Semiparametric instrumental variable estimation of treatment response models0.64422100%
7Belloni, Chernozhukov, Fernandez-Val and Hansen (2017) Program evaluation and causal inference with high-dimensional data0.64422100%
8Kolesar (2013) Estimation in an instrumental variables model with treatment effect heterogeneity0.64422100%
9Sloczynski (2020) When should we (not) interpret linear IV estimands as LATE?0.64422100%
10Angrist and Pischke (2009) Mostly harmless econometric: an empiricist's companion0.51121100%

Showing the top 10 of 22 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
1Potential weights and implicit causal designs in linear regression0.40511