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Semiparametric estimation of treatment effects parameters

Record Type:	Electronic resources : Monograph/item
Title/Author:	Semiparametric estimation of treatment effects parameters
Author:	Firpo, Sergio Pinheiro.
Description:	119 p.
Notes:	Chair: Guido W. Imbens.
Notes:	Source: Dissertation Abstracts International, Volume: 65-02, Section: A, page: 0615.
Contained By:	Dissertation Abstracts International65-02A.
Subject:	Economics, General.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3121475
ISBN:	049668826X

Semiparametric estimation of treatment effects parameters
Firpo, Sergio Pinheiro.

Semiparametric estimation of treatment effects parameters [electronic resource] - 119 p.

Chair: Guido W. Imbens.

Thesis (Ph.D.)--University of California, Berkeley, 2003.

Calculations of semiparametric efficiency bounds for treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound is shown for the semiparametric estimators proposed. An empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles of the earnings distribution.

ISBN: 049668826XSubjects--Topical Terms:

212429
Economics, General.

Semiparametric estimation of treatment effects parameters
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245 1 0 $a Semiparametric estimation of treatment effects parameters $h [electronic resource]
300 $a 119 p.
500 $a Chair: Guido W. Imbens.
500 $a Source: Dissertation Abstracts International, Volume: 65-02, Section: A, page: 0615.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2003.
520 # $a Calculations of semiparametric efficiency bounds for treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound is shown for the semiparametric estimators proposed. An empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles of the earnings distribution.
520 # $a This dissertation presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this dissertation are those that capture the distributional effects of the treatment. In particular, the focus is on quantile treatment effects and on the impact of the treatment on some inequality measures. The estimation procedure involves a first non-parameterc step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using a reweighing method to estimate functionals of the marginal distribution of potential outcomes, the second step minimizes a weighted sum of convex random functions whose weights depend on the estimated propensity-score. As the chosen inequality measures can be expressed in terms of the previous functionals, a third step that requires plugging in the second step estimators might be involved for some of those measures.
590 $a School code: 0028.
650 # 0 $a Economics, General. $3 212429
650 # 0 $a Statistics. $3 182057
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710 0 # $a University of California, Berkeley. $3 212474
773 0 # $g 65-02A. $t Dissertation Abstracts International
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790 1 0 $a Imbens, Guido W., $e advisor
791 $a Ph.D.
792 $a 2003
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