Publikation: Estimating constituency preferences from sparse survey data using auxiliary geographic information
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Measures of constituency preferences are of vital importance for the study of political representation and other research areas. Yet, such measures are often difficult to obtain. Previous survey-based estimates frequently lack precision and coverage due to small samples, rely on questionable assumptions or require detailed auxiliary information about the constituencies' population characteristics. We propose an alternative Bayesian hierarchical approach that exploits minimal geographic information readily available from digitalized constituency maps. If at hand, social background data are easily integrated. To validate the method, we use national polls and district-level results from the 2009 German Bundestag election, an empirical case for which detailed structural information is missing.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
SELB, Peter, Simon MUNZERT, 2011. Estimating constituency preferences from sparse survey data using auxiliary geographic information. In: Political Analysis. 2011, 19(4), pp. 455-470. ISSN 1047-1987. eISSN 1476-4989. Available under: doi: 10.1093/pan/mpr034BibTex
@article{Selb2011Estim-18980, year={2011}, doi={10.1093/pan/mpr034}, title={Estimating constituency preferences from sparse survey data using auxiliary geographic information}, number={4}, volume={19}, issn={1047-1987}, journal={Political Analysis}, pages={455--470}, author={Selb, Peter and Munzert, Simon} }
RDF
<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/server/rdf/resource/123456789/18980"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Selb, Peter</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/> <dc:language>eng</dc:language> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/18980/2/Selb_189800.pdf"/> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/18980/2/Selb_189800.pdf"/> <dc:rights>terms-of-use</dc:rights> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/18980"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/> <dcterms:bibliographicCitation>Political Analysis ; 19 (2011), 4. - S. 455-470</dcterms:bibliographicCitation> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-12T06:04:49Z</dc:date> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-12T06:04:49Z</dcterms:available> <dc:contributor>Munzert, Simon</dc:contributor> <dcterms:title>Estimating constituency preferences from sparse survey data using auxiliary geographic information</dcterms:title> <dcterms:issued>2011</dcterms:issued> <dcterms:abstract xml:lang="eng">Measures of constituency preferences are of vital importance for the study of political representation and other research areas. Yet, such measures are often difficult to obtain. Previous survey-based estimates frequently lack precision and coverage due to small samples, rely on questionable assumptions or require detailed auxiliary information about the constituencies' population characteristics. We propose an alternative Bayesian hierarchical approach that exploits minimal geographic information readily available from digitalized constituency maps. If at hand, social background data are easily integrated. To validate the method, we use national polls and district-level results from the 2009 German Bundestag election, an empirical case for which detailed structural information is missing.</dcterms:abstract> <dc:creator>Selb, Peter</dc:creator> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:creator>Munzert, Simon</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/"/> </rdf:Description> </rdf:RDF>