Victor Chernozhukov, Iván Fernández-Val, Sukjin Han, Kaspar Wüthrich
arXiv 9 Mar 2024 · Econometrics · 2 citations (OpenAlex)
arXiv:2403.05850 · PDF · DOI · OpenAlex · Extracted main text
We propose an instrumental variable framework for identifying and estimating causal effects of discrete and continuous treatments with binary instruments. The basis of our approach is a local copula representation of the joint distribution of the potential outcomes and unobservables determining treatment assignment. This representation allows us to introduce an identifying assumption, so-called copula invariance, that restricts the local dependence of the copula with respect to the treatment propensity. We show that copula invariance identifies treatment effects for the entire population and other subpopulations such as the treated. The identification results are constructive and lead to practical estimation and inference procedures based on distribution regression. An application to estimating the effect of sleep on well-being uncovers interesting patterns of heterogeneity.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chernozhukov, V. and C. Hansen (2005) An IV model of quantile treatment effects self | 1.000 | 10 | 4 | 100% |
| 2 | Chernozhukov, V., I. Fernández-Val, and S. Luo (2020) a): Distribution regression with sample selection, with an application to wage decompositions in the UK self | 1.000 | 9 | 5 | 100% |
| 3 | Imbens, G. W. and W. K. Newey (2009) Identification and estimation of triangular simultaneous equations models without additivity | 1.000 | 9 | 3 | 100% |
| 4 | Han, S. and E. J. Vytlacil (2017) Identification in a generalization of bivariate probit models with dummy endogenous regressors self | 1.000 | 8 | 4 | 100% |
| 5 | Imbens, G. W. and J. D. Angrist (1994) Identification and Estimation of Local Average Treatment Effects | 1.000 | 7 | 4 | 100% |
| 6 | Chernozhukov, V., I. Fernández-Val, and B. Melly (2013) Inference on Counterfactual Distributions self | 1.000 | 5 | 3 | 100% |
| 7 | Torgovitsky, A (2010) Identification and Estimation of Nonparametric Quantile Regressions with Endogeneity | 0.874 | 10 | 2 | 100% |
| 8 | Bessone, P., G. Rao, F. Schilbach, H. Schofield, and M. Toma (2021) b): The Economic Consequences of Increasing Sleep Among the Urban Poor* | 0.874 | 7 | 2 | 100% |
| 9 | Heckman, J. J. and E. J. Vytlacil (2007) Chapter 71 Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econo… | 0.874 | 5 | 2 | 100% |
| 10 | Vytlacil, E (2002) Independence, monotonicity, and latent index models: An equivalence result | 0.843 | 3 | 3 | 100% |
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