Comparing Group and Subgroup Cohesion Scores: A Nonparametric Method with an Application to Brazil

Abstract

This article builds a nonparametric method for inference from roll-call cohesion scores. Cohesion scores have been a staple of legislative studies since the publication of Rice's 1924 thesis. Unfortunately, little effort has been dedicated to understanding their statistical properties or relating them to existing models of legislative behavior. I show how a common use of cohesion scores, testing for distinct voting blocs, is severely biased toward Type I error, practically guaranteeing significant findings even when the null hypothesis is correct. I offer a nonparametric method—permutation analysis—that solves the bias problem and provides for simple and intuitive inference. I demonstrate with an examination of roll-call voting data from the Brazilian National Congress.