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Estimation of quantile treatment effects with Stata

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  • Markus Frolich

    ()
    (Universitat Mannheim)

  • Blaise Melly

    (Brown University)

Abstract

In this article, we discuss the implementation of various estimators proposed to estimate quantile treatment effects. We distinguish four cases involv- ing 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 consis- tent 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 Fr ̈olich 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 nonpara- metric 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).

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Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 10 (2010)
Issue (Month): 3 (September)
Pages: 423-457

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Handle: RePEc:tsj:stataj:v:10:y:2010:i:3:p:423-457

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Related research

Keywords: ivqte; locreg; quantile treatment effects; nonparametric regression; instrumental variables;

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