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A Statistical Model for Multiparty Electoral Data

Katz, Jonathan N. and King, Gary (1999) A Statistical Model for Multiparty Electoral Data. American Political Science Review, 93 (1). pp. 15-32. ISSN 0003-0554. https://resolver.caltech.edu/CaltechAUTHORS:20140314-120456629

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Abstract

We propose a comprehensive statistical model for analyzing multiparty, district-level elections. This model, which provides a tool for comparative politics research analogous to that which regression analysis provides in the American two-party context, can be used to explain or predict how geographic distributions of electoral results depend upon economic conditions, neighborhood ethnic compositions, campaign spending, and other features of the election campaign or aggregate areas. We also provide new graphical representations for data exploration, model evaluation, and substantive interpretation. We illustrate the use of this model by attempting to resolve a controversy over the size of and trend in the electoral advantage of incumbency in Britain. Contrary to previous analyses, all based on measures now known to be biased, we demonstrate that the advantage is small but meaningful, varies substantially across the parties, and is not growing. Finally, we show how to estimate the party from which each party's advantage is predominantly drawn.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.2307/2585758 DOIArticle
http://www.jstor.org/stable/2585758JSTORArticle
http://resolver.caltech.edu/CaltechAUTHORS:20170814-155246837Related ItemWorking Paper
ORCID:
AuthorORCID
Katz, Jonathan N.0000-0002-5287-3503
King, Gary0000-0002-5327-7631
Additional Information:© 1999 American Political Science Association. An earlier version of this paper was presented at the 1997 meetings of the Midwest Political Science Association, Chicago, and won the Pi Sigma Alpha Award for the best paper presented there. Our thanks to Jim Alt, Larry Bartels, Neal Beck, Gary Cox, Nick Cox, Mo Fiorina, M. F. Fuller, Dave Grether, Mike Herron, James Honaker, Chuanhai Liu, Ken Scheve, Ken Shepsle, and Bob Sherman for helpful suggestions; Josh Tucker for useful suggestions and research assistance; Gary Cox for his British election data; and Selina Chen for her help and expertise in collecting additional British data. Burt Monroe saw the virtues of the compositional data analysis literature at essentially the same time as we did, and we appreciate his comments. For research support, Jonathan N. Katz thanks the Haynes Foundation, and Gary King thanks the National Science Foundation (SBR-9729884), the Centers for Disease Control and Prevention (Division of Diabetes Translation), the National Institutes on Aging, the World Health Organization, and the Global Forum for Health Research. All information, data, and software necessary to replicate the results in this article are available in a replication data set to be deposited in the ICPSR's Publication Related Archive upon publication (ICPSR PRA #1190).
Funders:
Funding AgencyGrant Number
John Randolph and Dora Haynes FoundationUNSPECIFIED
NSFSBR-9729884
Centers for Disease Control and PreventionUNSPECIFIED
National Institute on AgingUNSPECIFIED
World Health OrganizationUNSPECIFIED
Global Forum for Health ResearchUNSPECIFIED
NIHUNSPECIFIED
Issue or Number:1
Record Number:CaltechAUTHORS:20140314-120456629
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140314-120456629
Official Citation:A Statistical Model for Multiparty Electoral Data Jonathan N. Katz and Gary King The American Political Science Review , Vol. 93, No. 1 (Mar., 1999) , pp. 15-32 Published by: American Political Science Association Article Stable URL: http://www.jstor.org/stable/2585758
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:44335
Collection:CaltechAUTHORS
Deposited By: Jonathan Katz
Deposited On:17 Mar 2014 15:22
Last Modified:09 Mar 2020 13:18

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