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Three essays on semiparametric metho...

University of Michigan.

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Three essays on semiparametric methods for the evaluation of social programs.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Three essays on semiparametric methods for the evaluation of social programs./
Author:	Busso, Matias.
Description:	160 p.
Notes:	Adviser: Jeffrey A. Smith.
Contained By:	Dissertation Abstracts International70-01A.
Subject:	Economics, Labor. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3343019
ISBN:	9780549979562

Three essays on semiparametric methods for the evaluation of social programs.
Busso, Matias.

Three essays on semiparametric methods for the evaluation of social programs. - 160 p.

Adviser: Jeffrey A. Smith.

Thesis (Ph.D.)--University of Michigan, 2008.

This dissertation consists of three essays whose unifying topical theme is the study and application of semiparametric methods for the evaluation of social programs. The first essay evaluates the federal urban Empowerment Zone (EZ) program using an inverse probability weighting (IPW) difference-in-differences estimator. We use four decades of Census data on urban neighborhoods in conjunction with information on the proposed boundaries of rejected EZs. We find that neighborhoods receiving EZ designation experienced substantial improvements in labor market conditions and moderate increases in rents relative to rejected and future Empowerment Zones. No evidence exists of large scale gentrification.

ISBN: 9780549979562Subjects--Topical Terms:

1019135
Economics, Labor.

Three essays on semiparametric methods for the evaluation of social programs.
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020 $a 9780549979562
035 $a (UMI)AAI3343019
035 $a AAI3343019
040 $a UMI $c UMI
100 1 $a Busso, Matias. $3 1029916
245 1 0 $a Three essays on semiparametric methods for the evaluation of social programs.
300 $a 160 p.
500 $a Adviser: Jeffrey A. Smith.
500 $a Source: Dissertation Abstracts International, Volume: 70-01, Section: A, page: 0289.
502 $a Thesis (Ph.D.)--University of Michigan, 2008.
520 $a This dissertation consists of three essays whose unifying topical theme is the study and application of semiparametric methods for the evaluation of social programs. The first essay evaluates the federal urban Empowerment Zone (EZ) program using an inverse probability weighting (IPW) difference-in-differences estimator. We use four decades of Census data on urban neighborhoods in conjunction with information on the proposed boundaries of rejected EZs. We find that neighborhoods receiving EZ designation experienced substantial improvements in labor market conditions and moderate increases in rents relative to rejected and future Empowerment Zones. No evidence exists of large scale gentrification.
520 $a The second essay explores the finite sample properties of several semiparametric estimators of average treatment effects, including IPW, matching and double robust estimators. We first show that all these estimators can be understood as weighted least squares. This result is used to explain the equivalency of these estimators. Then we study the implications of the assumption of strict overlap in the distribution of propensity scores for treatment and control units. When there is good overlap, IPW estimators are preferred on bias grounds and attain the semiparametric efficiency bound even for samples of size n = 100. When overlap is close to failing, none of the estimators examined perform well, and n -asymptotics may be a poor guide to finite sample distribution of the estimators.
520 $a In the third essay I propose a variance estimator of IPW estimators of average treatment effects. I note that IPW is a sequential estimator which, in cases in which a parametric propensity score model is assumed, has a simple expression of the asymptotic variance. Using Monte Carlo simulations I find that tests based on the proposed variance estimator have good finite sample size and power compared to competing inference strategies. Tests based on the percentile-t bootstrap method have very similar size and power properties. I interpret this as an indication that the bootstrap percentile-t method is not providing any refinement to the proposed asymptotic variance, which indicates that the proposed variance estimator is a good enough approximation to the true variance of the treatment effect estimator.
590 $a School code: 0127.
650 4 $a Economics, Labor. $3 1019135
690 $a 0510
710 2 $a University of Michigan. $3 777416
773 0 $t Dissertation Abstracts International $g 70-01A.
790 $a 0127
790 1 0 $a Smith, Jeffrey A., $e advisor
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3343019