Inference for distributional effects using instrumental quantile regression

52 Pages·2002·1.5 MB·English

by  Chernozhukov, Victor

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Massachusetts Institute of Technology
Department of Economics
Working Paper Series
INFERENCE FOR DISTRIBUTIONAL EFFECTS USING
INSTRUMENTAL QUANTILE REGRESSION
Victor Chernozhukov, MIT
Christian Hansen, MIT
Working Paper 02-20
May 16,2002
Room
E52-251
50 Memorial Drive
MA
Cambridge, 02142
This paper can be downloaded without charge from the
Social Science Research Network Paper Collection at
http://papers.ssrn.coin/paper.taf?abstract_id:=313426

1°
Massachusetts Institute of Technology
Department of Economics
Working Paper Series
INFERENCE FOR DISTRIBUTIONAL EFFECTS USING
INSTRUMENTAL QUANTILE REGRESSION
Victor Chernozhukov, MIT
Christian Hansen, MIT
Working Paper 02-20
May 2002
1 6,
Room
E52-251
50 Memorial Drive
MA
Cambridge, 02142
This paper can be downloaded without charge from the
Social Science Research Network Paper Collection at
http://papers.ssrn.com/paper.taf?abstract_id=xxxxx

INFERENCE FOR DISTRIBUTIONAL EFFECTS USING
INSTRUMENTAL QUANTILE REGRESSION
VICTOR CHERNOZHUKOVAND CHRISTIAN HANSEN
Abstract. In this paper we describe how quantile regression can be used to evaluate
the impact of treatment 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 ofdistributional equality, non-constant treatment effects, conditional dominance,
and exogeneity. The inference, which is subject to the Durbin problem, is handled via a
method ofscore resampling. The approach is illustrated with a classical supply-demand
and a schooling example. Results from both models demonstrate substantial treatment
heterogeneityandserveto illustratetherich varietyofhypothesesthat can betestedusing
inference on the instrumental quantileregression process.
Key Words: Quantile Regression, Instrumental Quantile Regression, Treatment Effects,
Endogeneity, Stochastic Dominance, Hausman Test, Supply-Demand Equations, Returns
to Education
Address correspondence to V. Chernozhukov, Department ofEconomics, MIT, E52-262F, 50 Memorial
Drive, Cambridge, MA 02142 (e-mail [email protected].) This is a provisional draft and an MIT Department
of Economics Working Paper. March 2002. We thank the participants and organizers of the EC 2001
meetings in Louvain-La-Neuve, where the research reported in this paper was presented.