Sooahn Shin presents Measuring Issue Specific Ideal Points from Roll Call Votes
Publication information:
Abstract
Ideal points are widely used to measure the ideology and policy preferences of political actors, ranging from voters and legislators to sovereign states. Yet, an outstanding challenge is to estimate ideal points specific to a single issue area. The conventional approach resorts to subsetting voting data, which results in the loss of valuable information and makes comparisons across issue areas ambiguous. To address this, I introduce IssueIRT, a hierarchical Item Response Theory (IRT) model that uses roll-call votes and user-supplied issue labels to estimate issue-specific axes, each running from left to right positions. This approach first estimates multidimensional ideal points using all available voting data, which are then projected onto issue-specific axes to generate single-dimensional, issue-specific ideal points. Furthermore, I develop a measure of issue similarity to compare the alignment of different issue areas on a unified left-to-right spectrum. I demonstrate that IssueIRT effectively captures issue-specific voting behaviors through simulations and applications studies. Specifically, I show cross-party, regional division over monetary policy in the US House of Representatives during the depression of the 1890's. Finally, I show that polarization in Congress has markedly increased across 32 separate issues from 1979 to 2023. The R package issueirt is available for implementing IssueIRT.
The paper is available on: https://sooahnshin.com/issueirt.pdf
Full text
Ideal points are widely used to measure the ideology and policy preferences of political actors, ranging from voters and legislators to sovereign states. Yet, an outstanding challenge is to estimate ideal points specific to a single issue area. The conventional approach resorts to subsetting voting data, which results in the loss of valuable information and makes comparisons across issue areas ambiguous. To address this, I introduce IssueIRT, a hierarchical Item Response Theory (IRT) model that uses roll-call votes and user-supplied issue labels to estimate issue-specific axes, each running from left to right positions. This approach first estimates multidimensional ideal points using all available voting data, which are then projected onto issue-specific axes to generate single-dimensional, issue-specific ideal points. Furthermore, I develop a measure of issue similarity to compare the alignment of different issue areas on a unified left-to-right spectrum. I demonstrate that IssueIRT effectively captures issue-specific voting behaviors through simulations and applications studies. Specifically, I show cross-party, regional division over monetary policy in the US House of Representatives during the depression of the 1890's. Finally, I show that polarization in Congress has markedly increased across 32 separate issues from 1979 to 2023. The R package issueirt is available for implementing IssueIRT.
The paper is available on: https://sooahnshin.com/issueirt.pdf