The Invisible Primary in an Agent-Based Model: Ideology, Strategy, and Competitive Dynamics

Abstract

Historical accounts of American presidential nominating contests suggest that candidates jockey over ideology and policy in ways that shape the outcomes of these races. Yet this aspect of competition has been difficult to analyze with the formal and statistical methods that dominate this research agenda. To address this gap, this article presents a computational agent-based model (ABM) of candidates’ ideological maneuvering during the invisible primary. We extend the framework developed by Michael Laver to study dynamic party competition in Europe, but recast it for the different context and to enable model fit to be more rigorously determined. Our analysis of data from the 2012 Republican invisible primary suggests the importance of ideological jockeying in this contest. Moreover, its dynamics can be well-explained by a basic version of the ABM in which candidates select between three strategies (aggregator, hunter or sticker) and then maintain that strategy over time. The fit of this model, particularly in the short run, can be improved by introducing a “momentum effect” that allows the candidates’ standing in the race to rise or fall without any accompanying ideological change.