Inference on counterfactual distributions
Rev.
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Author
Contributions
- Fernǹdez-Val, Ivǹ - Contributor
- Melly, Blaise - Contributor
- Massachusetts Institute of Technology. Dept. of Economics - Contributor
Publication
2008 - Massachusetts Institute of Technology, Dept. of Economics, Cambridge, MA, Massachusetts
Language
English
Word Count
17,250 words, Guess
Page Count
69 pages
Identifiers
- Internet Archiveinferenceoncount00cher2
- OCLC Control Number672345755
- Open LibraryOL24647306M
Description
In this paper we develop procedures for performing inference in regression models about how potential policy interventions affect the entire marginal distribution of an outcome of interest. These policy interventions consist of either changes in the distribution of covariates related to the outcome holding the conditional distribution of the outcome given covariates fixed, or changes in the conditional distribution of the outcome given covariates holding the marginal distribution of the covariates fixed. Under either of these assumptions, we obtain uniformly consistent estimates and functional central limit theorems for the counterfactual and status quo marginal distributions of the outcome as well as other function-valued effects of the policy, including, for example, the effects of the policy on the marginal distribution function, quantile function, and other related functionals. We construct simultaneous confidence sets for these functions; these sets take into account the sampling variation in the estimation of the relationship between the outcome and covariates. Our procedures rely on, and our theory covers, all main regression approaches for modeling and estimating conditional distributions, focusing especially on classical, quantile, duration, and distribution regressions. Our procedures are general and accommodate both simple unitary changes in the values of a given covariate as well as changes in the distribution of the covariates or the conditional distribution of the outcome given covariates of general form. We apply the procedures to examine the effects of labor market institutions on the U.S. wage distribution. Keywords: Policy effects, counterfactual distribution, quantile regression, duration regression, distribution regression. JEL Classifications: C14, C21, C41, J31, J71.
Subjects
Series Statement
- Working paper series / Massachusetts Institute of Technology, Dept. of Economics -- working paper 08-16 [2009 revision]
- Working paper (Massachusetts Institute of Technology. Dept. of Economics) -- no. 08-16, 2009.
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