Polborn and Krasa at the Comparative Politics Seminar
The Comparative Politics Seminar at UIUC played host to local professors Mattias Polborn and Stefan Krasa as they presented work on the salience of cultural and economic issues in U.S. elections.
The authors start the work with a formal model of party position. Parties have “natural abilities” that allow them to take more credibly particular positions than others (e.g. Democrats are more credible at delivering public goods, while Republicans are more credible at minimizing the size of government). From these constraints, parties can pick positions in a two dimensional space comprised of cultural and economic dimensions. In this space, one can imagine a line between the two parties separating voters by preference. If you are on the Democratic side of the line, you should prefer Democratic candidates, and likewise if you are on the Republican side of the line.
This model has some intuitive implications. If one party shifts position on one dimension, the position of the line shifts. If voters remain stationary on their preferences, this shift in position can result in greater electoral gains. Additionally, if both parties move an equal distance away from the splitting line along a perpendicular path, the line remains stationary. These results have an intuitive appeal and speak to an empirical puzzle: party polarization. Elites within parties appear to be more ideological now than in the past, yet survey results place American voters at roughly the same location. Polarization is costless from a party position as they can capture the same voters, even if they take more extreme positions.
The authors attempt to test this model using empirical data from the American National Election Study. They rate respondents on cultural and economic issues and then infer the party positions from respondent vote choices. In my reading and during the discussion, I found difficult to tell if their data collection supported their model for empirical reasons or by design. The party positions are not empirically verifiable. The fact that they exist and display some of the hypothesized properties may have more to do with modeling than with empirical fact.
Despite these misgivings, I found this an interesting paper. Were I trying to infer party positions, I might apply a clustering approach or a tool like a SVM, which I suspect is more or less identical to the technique the authors use. Perhaps the biggest difference is that a clustering tool or an SVM would not imply a probability distribution over the results, whereas the probit model employed by the authors does assume a Normal distribution over their latent variable. I would be interested to see how a different choice of clustering algorithm would change the slope of the line, and by implication the parameters of the authors’ formal model.
