Inference on counterfactual distributions

Victor Chernozhukov, Ivan Fernandez-Val () and Blaise Melly ()

No CWP05/12, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: We develop inference procedures for policy analysis based on regression methods. We consider policy interventions that correspond to either changes in the distribution of covariates, or changes in the conditional distribution of the outcome given covariates, or both. Under either of these policy scenarios, we derive functional central limit theorems for regression-based estimators of the status quo and counterfactual marginal distributions. This result allows us to construct simultaneous con?dence sets for function-valued policy e?ects, including the e?ects on the marginal distribution function, quantile function, and other related functionals. We use these con?dence sets to test functional hypotheses such as no-e?ect, positive e?ect, or stochastic dominance. Our theory applies to general policy interventions and covers the main regression methods including classical, quantile, duration, and distribution regressions. We illustrate the results with an empirical application on wage decompositions using data for the United States. Of independent interest is the use of distribution regression as a tool for modeling the entire conditional distribution, encompassing duration/transformation regression, and representing an alternative to quantile regression. This is a revision of CWP09/09.

Date: 2012-02-13
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Citations: View citations in EconPapers (20)

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Related works:
Journal Article: Inference on Counterfactual Distributions (2013)
Working Paper: Inference on Counterfactual Distributions (2013)
Working Paper: Inference on counterfactual distributions (2013)
Working Paper: Inference on counterfactual distributions (2013)
Working Paper: Inference on counterfactual distributions (2012)
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Working Paper: Inference on counterfactual distributions (2009)
Working Paper: INFERENCE ON COUNTERFACTUAL DISTRIBUTIONS (2008)
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