Restrictive Rules and Conditional Party Government: A Computational Model

Brigham Young University for helpful comments. Abstract: Conditional Party Government (CPG) is among the most widely applied theories of party influence in the U.S. Congress. Most applications of the theory assume a unidimen-sional policy space, contrary to the intentions of the developers of CPG. We develop a simple theoretical scenario where members decide to opt whether to empower their leaders to bring legislation to the floor under a restrictive rule. We find that in a strictly spatial application of CPG to this scenario, increased homogeneity and increased polarization do not lead to increased adoption of restrictive rules that would shift outcomes from the chamber median toward the party median. Using a computational model, we add a measure of complexity to the spatial model by introducing collective uncertainty about the location of the speaker’s preferences and the location of the chamber median. As uncertainty regarding the location of the chamber median relative to the level of uncertainty regarding the location of the speaker increases, we find that the predictions of conditional party government regarding the incidence of restrictive rules are better realized. 1