Position-taking in House debate and the issue of immigration

Abstract

Traditional studies of legislative behavior often rely on analyses of roll-call votes. However, this approach ignores variation in legislator position that may not be expressed through a recorded vote. To better examine legislative position-taking, I rely on legislative speech and explore what factors motivate a member of Congress to take a position on immigration. I apply Wordfish, a text-scaling algorithm, to House debate from the 104th and 109th sessions of Congress in order to estimate each legislator's position on immigration. This approach facilitates a more nuanced understanding of legislative position-taking enabling us to speak to the degree of support or opposition to a particular policy – something we are unable to extract from studies relying on vote data alone. Results indicate first, the factors influencing legislative speech have changed over time, with institutional motivations playing a greater role than constituent preferences in determining positions; and second, the issue has become increasingly polarized with Republican members becoming more conservative in their speech over time, while Democrats less so.