Policy and the Structure of Roll Call Voting in the U.S. House

Abstract

Competition in the U.S. Congress has been increasingly characterized by competition along a single, left-right dimension. However, we challenge this characterization by showing the content of legislation has far more predictive power, particularly for members of the minority party, than the characteristics of members’ constituencies and their own characteristics, most notably their ideological position derived from scaling roll call votes. Using a machine learning approach, we identify a topics model for final passage votes in the 111th through the 113th House of Representatives and conduct out-of-sample tests to evaluate the predictive power of bill topics relative to other factors. We find that bill topics and congressional committees are important for predicting roll call votes but the other variables, including member ideology, lack predictive power. These findings raise serious doubts about the claim that congressional politics can be boiled down to competition along a single left-right continuum and shed new light on the debate about levels of polarization in Congress.