Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-19T03:05:27.911Z Has data issue: false hasContentIssue false

An Empirical Theory of Rational Nominating Behaviour Applied to Japanese District Elections

Published online by Cambridge University Press:  01 April 1999

ERIC C. BROWNE
Affiliation:
Department of Political Science, University of Wisconsin, Milwaukee
DENNIS PATTERSON
Affiliation:
Department of Political Science, University of Michigan State University, East Lansing

Abstract

Plurality electoral systems with multi-member districts and single nontransferable votes (SNTV) allow parties to win multiple seats in district elections by nominating multiple candidates, but they also penalize a party's seat share if the number of candidates offered is ‘too many’ or ‘too few’. Given an institutional incentive to nominate the ‘correct’ number of candidates, we seek to establish empirically that the nominating behaviour of parties in such systems results from a rational calculus of strategic choice. So we develop and test an empirical theory of rational nominating behaviour applied to Japanese district elections before the 1994 electoral reform. We establish, for all possible nominating strategies, the conditions on voting outcomes required for actors to maximize benefits in the context. The efficiency of actual strategy choices for maximizing benefits is found by comparing an observed outcome from voting (the distributed benefit) with the benefit that would be expected had the party chosen its ‘best’ alternative nominating strategy instead. Empirical testing indicates that Japanese parties discriminated between available nominating strategies and made choices that maximized benefits in the context, evidence that the nominating behaviour of parties in this test environment was based on rational calculation.

Type
Research Article
Copyright
© 1999 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)