Estimation of quantile treatment effects with Stata
Markus Frölich
Universität Mannheim and
Institute for the Study of Labor
Bonn, Germany
[email protected]
|
Blaise Melly
Department of Economics
Brown University
Providence, RI
[email protected]
|
Abstract. In this article, we discuss the implementation of various estimators
proposed to estimate quantile treatment effects. We distinguish four cases involving
conditional and unconditional quantile treatment effects with either exogenous
or endogenous treatment variables. The introduced ivqte command covers four
different estimators: the classical quantile regression estimator of Koenker and
Bassett (1978, Econometrica 46: 33–50) extended to heteroskedasticity consistent
standard errors; the instrumental-variable quantile regression estimator of
Abadie, Angrist, and Imbens (2002, Econometrica 70: 91–117); the estimator for
unconditional quantile treatment effects proposed by Firpo (2007, Econometrica
75: 259–276); and the instrumental-variable estimator for unconditional quantile
treatment effects proposed by Frölich and Melly (2008, IZA discussion paper 3288).
The implemented instrumental-variable procedures estimate the causal effects for
the subpopulation of compliers and are only well suited for binary instruments.
ivqte also provides analytical standard errors and various options for nonparametric
estimation. As a by-product, the locreg command implements local linear
and local logit estimators for mixed data (continuous, ordered discrete, unordered
discrete, and binary regressors).
View all articles by these authors:
Markus Frölich, Blaise Melly
View all articles with these keywords:
ivqte, locreg, quantile treatment effects, nonparametric regression, instrumental variables
Download citation: BibTeX RIS
Download citation and abstract: BibTeX RIS
|
