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Global Representation of the Conditional LATE Model: A Separability Result

Yu-Chang Chen, Haitian Xie

arXiv 16 Jul 2020 · Econometrics · publishedOxford Bulletin of Economics and Statistics (2021) · 2 citations (OpenAlex)

arXiv:2007.08106 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper studies the latent index representation of the conditional LATE model, making explicit the role of covariates in treatment selection. We find that if the directions of the monotonicity condition are the same across all values of the conditioning covariate, which is often assumed in the literature, then the treatment choice equation has to satisfy a separability condition between the instrument and the covariate. This global representation result establishes testable restrictions imposed on the way covariates enter the treatment choice equation. We later extend the representation theorem to incorporate multiple ordered levels of treatment.

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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
1Heckman, J. J. and Vytlacil, E (2005) Structural equations, treatment effects, and econometric policy evaluation 11.00053100%
2Vytlacil, E (2002) Independence, monotonicity, and latent index models: An equivalence result0.87472100%
3Vytlacil, E (2006) Ordered discrete-choice selection models and local average treatment effect assumptions: Equivalence, nonequivalence, and repres…0.64441100%
4Kitagawa, T (2015) A test for instrument validity0.58531100%
5Abadie, A (2003) Semiparametric instrumental variable estimation of treatment response models0.51121100%
6Imbens, G. W. and Angrist, J. D (1994) Identification and estimation of local average treatment effects0.51121100%
7Vytlacil, E (2006) A note on additive separability and latent index models of binary choice: representation results0.51121100%
8Carneiro, P., Heckman, J. J., and Vytlacil, E. J (2011) Estimating marginal returns to education0.40511100%
9Cornelissen, T., Dustmann, C., Raute, A., and Schönberg, U (2018) Who benefits from universal child care? estimating marginal returns to early child care attendance0.40511100%
10Dahl, C. M., Huber, M., and Mellace, G (2020) It's never too late: A new look at local average treatment effects with or without defiers0.40511100%

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1Personalized Subsidy Rules0.40511