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Estimating Intra-Party Preferences: Comparing Speeches to Votes*

Published online by Cambridge University Press:  21 December 2015

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Abstract

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, as 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 differences between roll call and text scalings by attributing differences to constituency-level preferences for energy policy.

Information

Type
Research Notes
Copyright
© The European Political Science Association 2015 
Figure 0

Table 1 Allocation of Speaking Times in the Selected Energy Debate

Figure 1

Fig. 1 Box plots of MP one-dimensional ideal points from roll call votes (energy bill and entire 46th legislature, grouped by party) Note: SVP=Swiss People’s Party; FDP=Liberal Free Democrats; CVP=Christian-democrats; EVP=Protestant People’s Party; SP=Social-democrats; GPS=Greens; IRT=item response theory.

Figure 2

Fig. 2 Box plots of MP agreement with own party (energy bill votes and entire 46th legislature) Note: EVP=Protestant People’s Party; SP=Social-democrats; GPS=Greens; SVP=Swiss People’s Party; FDP=Liberal Free Democrats; CVP=Christian-democrats.

Figure 3

Table 2 Models to Predict Speech Act and Speech Length

Figure 4

Fig. 3 Text scaling results (Wordfish) for energy debates, grouped by party Note: EVP=Protestant People’s Party; SVP=Swiss People’s Party; FDP=Liberal Free Democrats; CVP=Christian-democrats; GPS=Greens; SP=Social-democrats.

Figure 5

Fig. 4 RCV scaling (IRT) versus text scaling (Wordfish) Note: Pearson’s r=0.94. IRT=item response theory; SP=Social-democrats; FDP=Liberal Free Democrats; GPS=Greens; SVP=Swiss People’s Party; CVP=Christian-democrats; EVP=Protestant People’s Party.

Figure 6

Fig. 5 Regional variation in support for (a) nuclear phase out and (b) the moratorium initiatives of May 18, 2003, and the locations of Switzerland’s five active nuclear reactors

Figure 7

Table 3 Ordinary Least Squares (OLS) Regression Models to Predict Text Scalings (Wordfish)