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Statistical Model for Multiparty Electoral Data (ICPSR 1190)
Principal Investigator(s): Katz, Jonathan, University of Chicago; King, Gary, Harvard University
In this collection, a comprehensive statistical model for analyzing multiparty, district-level elections is proposed. This model, which provides a tool for comparative politics research analogous to what regression 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. Also provided are new graphical representations for data exploration, model evaluation, and substantive interpretation. The authors 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, the research demonstrates that the advantage is small but meaningful, varies substantially across parties, and is not growing. Finally, the authors show how to estimate from which party each other party's advantage is predominantly drawn.
These data are flagged as replication datasets and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.
These data are available to the general public.
Katz, Jonathan, and Gary King. Statistical Model for Multiparty Electoral Data. ICPSR01190-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2009-03-18. http://doi.org/10.3886/ICPSR01190.v1
Persistent URL: http://doi.org/10.3886/ICPSR01190.v1
Scope of Study
Geographic Coverage: United States
Data Collection Notes:
(1) The file submitted is katzking.zip. The zip file is binary and contains a README file and program and data files. (2) These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.
Original ICPSR Release: 1998-12-17
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