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Replication data for: Estimating Intra-Party Preferences: Comparing Speeches to Votes

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: Estimating Intra-Party Preferences: Comparing Speeches to Votes
 
Identifier https://doi.org/10.7910/DVN/27702
 
Creator Schwarz, Daniel
Traber, Denise
Benoit, Kenneth
 
Publisher Harvard Dataverse
 
Description Well-established methods exist for measuring party positions, but reliable means for estimating intra-party preferences remain underdeveloped. While most efforts focus on estimating the ideal points of individual legislators based on inductive scaling of roll call votes, this data suffers from two problems: selection bias due to unrecorded votes, and strong party discipline which tends to make voting a strategic rather than a sincere indication of preferences. By contrast, legislative speeches are relatively unconstrained, since party leaders are less likely to punish MPs for speaking freely as long as they vote with the party line. Yet the differences between roll call estimations and text scalings remain essentially unexplored, despite the growing application of statistical analysis of textual data to measure policy preferences. Our paper addresses this lacuna by exploiting a rich feature of the Swiss legislature: On most bills, legislators both vote and speak many times. Using this data, we compare text-based scaling of ideal points to vote-based scaling from a crucial piece of energy legislation. Our findings confirm that text scalings reveal larger intra-party differences than roll calls. Using regression models we further explain the dif- ferences between roll call and text scalings by attributing differences to constituency-level preferences for energy policy.
 
Subject Legislative Politics
Text and Content Analysis
Quantitiative Methods
Ideal Point Estimation