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Efficient semiparametric estimation of quantile treatment effects
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2003-01)
This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation ...
Inequality treatment effects
(Escola de Pós-Graduação em Economia da FGV, 2005-05-05)
This paper presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this paper are those that capture summarized ...
Identification and estimation of distributional impacts of interventions using changes in inequality measures
(Wiley-Blackwell, 2016-05)
This paper presents estimators of distributional impacts of interventions when selection to the program is based on observable characteristics. Distributional impacts are calculated as differences in inequality measures ...
Identification and estimation of interventions using changes in inequality measures
(2010-06-16)
This paper presents semiparametric estimators of changes in inequality measures of a dependent variable distribution taking into account the possible changes on the distributions of covariates. When we do not impose ...
Efficient estimation of data combination models by the method of Auxiliary-to-Study Tilting (AST)
(Amer Statistical Assoc, 2016-04-02)
We propose a locally efficient estimator for a class of semiparametric data combination problems. A leading estimand in this class is the average treatment effect on the treated (ATT). Data combination problems are related ...
Inverse probability tilting for moment condition models with missing data
(Oxford Univ Press, 2012-07)
We propose a new inverse probability weighting (IPW) estimator for moment condition models with missing data. Our estimator is easy to implement and compares favourably with existing IPW estimators, including augmented IPW ...
DPpackage: Bayesian Semi- and Nonparametric Modeling in R
(JOURNAL STATISTICAL SOFTWARE, 2011)
Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished ...