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Published August 15, 2017 | Submitted
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A Statistical Model for Multiparty Electoral Data


We propose an internally consistent and comprehensive statistical model for analyzing multiparty, district-level aggregate election data. This model can be used to explain or predict how the geographic distribution of electoral results depends upon economic conditions, neighborhood ethnic compositions, campaign spending, and other features of the election campaign or characteristics of the aggregate areas. We also provide several new graphical representations for help in data exploration, model evaluation, and substantive interpretation. Although the model applies more generally, we use it to help resolve an important controversy over the size of and trend in the electoral advantage of incumbency in Great Britain. Contrary to previous analyses, which are all based on measures now known to be biased, we demonstrate that the incumbency advantage is small but politically meaningful. We also find that it differs substantially across the parties, about half a percent for the Conservatives, 1% for the Labor Party, and 3% for the Liberal party and its successors. Also contrary to previous research, we show that these effects have not grown in recent years. Finally, we are able to estimate from which party each party's incumbency advantage is predominantly drawn.

Additional Information

Revised version. Original dated to August 1997. An earlier version of this paper was presented at the annual meetings of the Midwest Political Science Association, Chicago, Illinois, April 1997. Our thanks to Jim Alt, Larry Bartels, Neal Beck, M.F. Fuller, Dave Grether, Mike Herron, James Honaker, Ken Scheve, Ken Shepsle, Bob Sherman for helpful suggestions; Josh Tucker for useful suggestions and research assistance; Gary Cox for providing his British election data; and Selina Chen for help in collecting additional British data. Burt Monroe saw the virtues of using 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 U.S. National Science Foundation (grant SBR-932121). Published as Katz, J.N., & King, G. (1999). A statistical model for multiparty electoral data. American Political Science Review, 93(1), 15-32.

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