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Published February 1, 2002 | public
Journal Article

A Fast, Easy, and Efficient Estimator for Multiparty Electoral Data


Katz and King have previously developed a model for predicting or explaining aggregate electoral results in multiparty democracies. Their model is, in principle, analogous to what least‐squares regression provides American political researchers in that two‐party system. Katz and King applied their model to three‐party elections in England and revealed a variety of new features of incumbency advantage and sources of party support. Although the mathematics of their statistical model covers any number of political parties, it is computationally demanding, and hence slow and numerically imprecise, with more than three parties. In this paper we produce an approximate method that works in practice with many parties without making too many theoretical compromises. Our approach is to treat the problem as one of missing data. This allows us to use a modification of the fast EMis algorithm of King, Honaker, Joseph, and Scheve and to provide easy‐to‐use software, while retaining the attractive features of the Katz and King model, such as the t distribution and explicit models for uncontested seats.

Additional Information

© 2002 by the Society for Political Methodology. An earlier version of the paper was presented at the annual meetings of the American Political Science Association, Washington, DC, 2000. For research support, we gratefully acknowledge the John M. Olin Foundation, the National Science Foundation (IIS-9874747), the National Institutes of Aging (P01 AG17625-01), and the World Health Organization.

Additional details

August 19, 2023
October 26, 2023