Inference for distributional effects using instrumental quantile regression
By: Victor Chernozhukov [and] Christian Hansen
Contributors: Hansen, Christian Bailey, 1976-; Massachusetts Institute of Technology. Dept. of Economics
Series: Working paper series / Massachusetts Institute of Technology, Dept. of Economics -- working paper 02-20; Working paper (Massachusetts Institute of Technology. Dept. of Economics) -- no. 02-20.
Publisher: Massachusetts Institute of Technology, Dept. of Economics
Published: 2002
Place of publication: Cambridge, MA
Language: eng
Number of pages: 33
Description: on the entire distribution of outcomes, when the treatment is endogenous or selected in relation to potential outcomes. We describe an instrumental variable quantile regression process and the set of inferences derived from it, focusing on tests of distributional equality, non-constant treatment effects, conditional dominance, and exogeneity. The inference, which is subject to the Durbin problem, is handled via a method of score resampling. The approach is illustrated with a classical supply-demand and a schooling example. Results from both models demonstrate substantial treatment heterogeneity and serve to illustrate the rich variety of hypotheses that can be tested using inference on the instrumental quantile regression process. Keywords: Quantile Regression, Instrumental Quantile Regression, Treatment Effects, Endogeneity, Stochastic Dominance, Hausman Test, Supply-Demand Equations, Returns to Education. JEL Classification: C13, C14, C30, C51, D4, J24, J31.
Notes: "May 16, 2002."

Includes bibliographical references (p. 33-[34]).

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