The (Un)Predictability of Primaries with Many Candidates: Simulation Evidence
It is common to describe the dynamic processes that generate outcomes in U.S. primaries as "unstable" or "unpredictable". In fact, the way we choose candidates may amount to a lottery. This paper uses a simulation approach, assuming 10,000 voters who vote according to a naive, deterministic proximity rule, but who choose party affiliation probabilistically. The voters of each party then must choose between two sets of ten randomly chosen candidates, in "closed" primaries. Finally, the winners of the two nominations compete in the general election, in which independent voters also participate. The key result of the simulations reported here is the complete unpredictability of the outcomes of a sequence of primaries: the winner of the primary, or the party's nominee, varied as much as two standard deviations from the median partisan voter. The reason is that the median, or any other measure of the center of the distribution of voters, is of little value in predicting the outcome of multicandidate elections. These results suggest that who runs may have more to do with who wins than any other consideration. Copyright 2000 by Kluwer Academic Publishers
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