Adaptive Models and Electoral Instability

Abstract

The spatial model of voting is a benchmark in theories purporting to explain political behavior. Underlying the spatial model is the assumption that both voters and candidates possess complete information. Despite the fact that much of the survey literature fails to confirm this assumption, few formal theorists have modeled electorates where the voters and candidates lack full information. In large part, spatial theory's failure to illuminate problems of this kind stems from its reliance upon an unrealistic model of human cognition: substantive rationality. This paper returns to Downs' original statement of the importance of information costs in voter decision-making, and extends Down's analysis to include the constraints faced by candidates. In this paper, complexity theory provides the framework to construct computational experiments that explore the use of information by political actors. As in real elections, voters have a finite amount of attention they dedicate to political issues, and candidates possess a fixed budget with which to poll the electorate. The inclusion of the costs of acquiring information for both voters and candidates results in a broader set of electoral outcomes that challenge current formal results.