A Simple and Successul Method to Shrink the Weight

Type of Publication: Working Paper/Technical Report
URI (citable link): http://nbn-resolving.de/urn:nbn:de:bsz:352-0-274751
Author: Pohlmeier, Winfried; Seiberlich, Ruben R.; Uysal, S. Derya
Year of publication: 2013
Series: Working Paper Series / Department of Economics ; 2013‐05
Summary:
We propose a simple way to improve the efficiency of the average treatment effect on propensity score based estimators. As the weights become arbitrarily large for the propensity scores being close to one or zero, we propose to shrink the propensity scores away from these boundaries. Using a comprehensive Monte Carlo study we show that this simple method substantially reduces the mean squared error of the estimators in finite samples.
JEL Classification: C14; C21
Subject (DDC): 330 Economics
Keywords: Econometric evaluation, propensity score, penalizing, shrinkage, average treatment effect
Link to License: In Copyright
Bibliography of Konstanz: Yes

Cite This

Files in this item

[PDF]
Name: Pohlmeier_0-274751.pdf
Size: 529.7 KiB
Format: PDF
View/Open
Checksum: MD5:ce7406695309b82063797eb890003a16

POHLMEIER, Winfried, Ruben R. SEIBERLICH, S. Derya UYSAL, 2013. A Simple and Successul Method to Shrink the Weight

@techreport{Pohlmeier2013Simpl-29778, series={Working Paper Series / Department of Economics}, title={A Simple and Successul Method to Shrink the Weight}, year={2013}, number={2013‐05}, author={Pohlmeier, Winfried and Seiberlich, Ruben R. and Uysal, S. Derya} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/29778"> <dcterms:abstract xml:lang="eng">We propose a simple way to improve the efficiency of the average treatment effect on propensity score based estimators. As the weights become arbitrarily large for the propensity scores being close to one or zero, we propose to shrink the propensity scores away from these boundaries. Using a comprehensive Monte Carlo study we show that this simple method substantially reduces the mean squared error of the estimators in finite samples.</dcterms:abstract> <dc:contributor>Pohlmeier, Winfried</dc:contributor> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:title>A Simple and Successul Method to Shrink the Weight</dcterms:title> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-02-05T07:15:24Z</dcterms:available> <dc:creator>Seiberlich, Ruben R.</dc:creator> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/46"/> <dc:contributor>Uysal, S. Derya</dc:contributor> <dc:language>eng</dc:language> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:rights>terms-of-use</dc:rights> <dc:creator>Uysal, S. Derya</dc:creator> <dcterms:issued>2013</dcterms:issued> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/29778/3/Pohlmeier_0-274751.pdf"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/46"/> <dc:creator>Pohlmeier, Winfried</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-02-05T07:15:24Z</dc:date> <dc:contributor>Seiberlich, Ruben R.</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/29778"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/29778/3/Pohlmeier_0-274751.pdf"/> </rdf:Description> </rdf:RDF>

Downloads since Feb 5, 2015 (Information about access statistics)

Pohlmeier_0-274751.pdf 216

This item appears in the following Collection(s)

Search KOPS


Browse

My Account