(with Jon C. Rogowski)
Published June 2016 at Political Science Research and Methods
Abstract: A large class of theoretical models posits that voters choose candidates on the basis of issue congruence, but convincing empirical tests of this key claim remain elusive. The most persistent difficulty is obtaining comparable spatial estimates for winning and losing candidates, as well as voters. We address these issues using candidate surveys to characterize the electoral platforms for winners and losers, and large issue batteries in 2008 and 2010 to estimate voter preferences. Questions that were answered by both candidates and citizens allow us to jointly scale these estimates. We find robust evidence that vote choice in congressional elections is strongly associated with spatial proximity. Individual-level and contextual variables commonly associated with congressional voting behavior condition the importance of spatial proximity for vote choice, yet ideological considerations still continue to play a substantial role in vote choice. Our results have important implications for theories of voter decision-making and electoral institutions.
(with Thad Kousser and Justin Phillips)
Accepted August 2015 at Political Science Research and Methods
Abstract: Can electoral reforms such as an independent redistricting commission and the top-two primary create conditions that lead to better legislative representation? We explore this question by presenting a new method for measuring a key indicator of representation – the congruence between a legislator’s ideological position and the average position of her district’s voters. We do this by combining two cutting-edge methods: the joint classification of voters and political candidates on the same ideological scale using a common policy survey, along with multilevel regression and post-stratification to estimate the position of the average voter across many districts in multiple elections. After describing and validating our approach, we use it to study the recent impact of electoral reforms in California. We draw on the predictions of reforms and the logic of spatial voting to show how the Citizens Redistricting Commission and the top-two primary might lead to a better fit between the state’s voters and lawmakers. Then, by comparing levels of congruence and other trends in elections before (2010) and after (2012) the implementation of reform, we show that California’s electoral experiments did not bring their hoped-for effects. If anything, legislators strayed further from their district’s average voter in 2012. In sum, this paper lays out a replicable, practical method of gauging legislative representation, and applies it to show that attempts to improve representation do not always bear fruit.
(with Craig Volden, Dan Butler, and Adam Dynes)
Forthcoming in the American Journal of Political Science
Accepted June 2015, Published online July 2015
Abstract: We introduce experimental research design to the study of policy diffusion in order to better understand how political ideology affects policymakers’ willingness to learn from one another’s experiences. Our two experiments–embedded in national surveys of U.S. municipal officials–expose local policymakers to vignettes describing the zoning and home foreclosure policies of other cities, offering opportunities to learn more. We find that: (1) policymakers who are ideologically predisposed against the described policy are relatively unwilling to learn from others, but (2) such ideological biases can be overcome with an emphasis on the policy’s success or on its adoption by co-partisans in other communities. We also find a similar partisan based bias among traditional ideological supporters, who are less willing to learn from those in the opposing party. The experimental approach offered here provides numerous new opportunities for scholars of policy diffusion.
Polarization without Parties: Term Limits and Legislative Partisanship in Nebraska’s Unicameral Legislature
(with Seth Masket)
Published in the State Politics and Policy Quarterly (March 2015)
Abstract: Despite a long history of nonpartisanship, the Nebraska state legislature has polarized rapidly within the past decade. Using interviews and campaign finance records, we examine politics in the modern Unicam to investigate nonpartisan polarization. We find that newly-instituted term limits created opportunities for the state’s political parties to recruit and finance candidates in an increasingly partisan fashion. Social network analysis suggests that there is a growing level of structure to campaign donations, with political elites increasingly less likely to contribute across party lines. The results offer a compelling example of parties overcoming institutions designed to eliminate them.
(with Virginia Gray, John Cluverius, Jeffrey Harden and David Lowery)
Published in American Politics Research 43:2 (March 2015)
Interest system density influences internal dynamics within interest organizations, how they lobby, and policy conditions. But how do political conditions influence interest system density? How does politics create demand for interest representation? We examine these questions by assessing how legislative party competition and ideological distance between parties in state legislatures affect the number of lobby groups. After stating our theoretical expectations, we examine 1997 and 2007 data on legislative competition and party polarization to assess their influence on system density. We find mixed results: Whereas politics slightly influenced the structuring of nonprofit interest communities, they seem to have not affected the structuring of for-profit interest communities or interest communities as a whole.
(with Eric McGhee, Seth Masket, Steven Rogers, and Nolan McCarty)
Published in the American Journal of Political Science (April 2014)
Abstract: Many supporters of political reform advocate opening party nominations to non-members as a way of increasing the number of moderate elected officials. This presumes that the composition of the primary electorate is, in fact, a significant cause of polarization, an idea that has rarely been tested empirically. We marry a unique new data set of state legislator ideal points to a detailed accounting of primary systems to gauge the effect of primary systems on polarization. The results of this analysis suggest that the openness of a primary election has little effect, if any, on the partisanship of the politicians it produces. We speculate on why the effect is so inconsistent and weak, and discuss the implications of our study for the theoretical literature on parties in American political life.
(with Avi Feller and Andrew Gelman)
Published February 2013 in The Forum
The so-called “red/blue paradox” is that rich individuals are more likely to vote Republican but rich states are more likely to support the Democrats. Previous research argued that this seeming paradox could be explained by comparing rich and poor voters within each state – the difference in the Republican vote share between rich and poor voters was much larger in low-income, conservative, middle-American states like Mississippi than in high-income, liberal, coastal states like Connecticut. We use exit poll and other survey data to assess whether this was still the case for the 2012 Presidential election. Based on this preliminary analysis, we find that, while the red/blue paradox is still strong, the explanation offered by Gelman et al. no longer appears to hold. We explore several empirical patterns from this election and suggest possible avenues for resolving the questions posed by the new data.
Published in the American Political Science Review (August 2011), 105:3, pp. 530-551.
(with Nolan McCarty)
Abstract: The development and elaboration of the spatial theory of voting has contributed greatly to the study of legislative decision making and elections. Statistical models that estimate the spatial locations of individual legislators have been a key contributor to this success (Poole and Rosenthal 1997, Clinton et al 2004). In addition to applications to the U.S. Congress, spatial models have been estimated for the Supreme Court, U.S. presidents, a large number of non-U.S. legislatures, and supranational organizations. But, unfortunately, a potentially fruitful laboratory for testing spatial theories of policymaking and elections, the American states, has remained relatively unexploited. Two problems have limited the empirical application of spatial theory to the states. The first is that state legislative roll call data has not yet been systematically collected for all states over time. Second, because ideal point models are based on latent scales, comparisons of ideal points across states or chambers within a state are difficult. This paper reports substantial progress on both fronts. First, we have obtained the roll call voting data for all state legislatures from the mid-1990s onward. Second, we exploit a recurring survey of state legislative candidates to enable comparisons across time, chambers, and states as well as with the U.S. Congress. The resulting mapping of America’s state legislatures has tremendous potential to address numerous questions not only about state politics and policymaking, but legislative politics in general.
A Bridge to Somewhere: Mapping State and Congressional Ideology on a Cross-Institutional Common Space
Published in the August 2010 issue of the Legislative Studies Quarterly
Researchers face two major problems when applying ideal point estimation techniques to state legislatures. First, longitudinal roll-call data are scarce. Second, even when such data exist, scaling ideal points within a single state is an inadequate approach. No comparisons can be made between these estimates and those for other state legislatures or for Congress. Our project provides a solution. We exploit a new comparative dataset of state legislative roll calls to generate ideal points for legislators. Taking advantage of the fact that state legislators sometimes go on to serve in Congress, we create a common ideological scale. Using these bridge actors, we estimate state legislative ideal points in congressional common space for 11 states. We present our results and illustrate how these scores can be used to address important topics in state and legislative politics.
(with Andrew Gelman, Joseph Bafumi, and David Park)
Published in the Quarterly Journal of Political Science, November 2007
Abstract: For decades, the Democrats have been viewed as the party of the poor, with the Republicans representing the rich. Recent presidential elections, however, have shown a reverse pattern, with Democrats performing well in the richer blue states in the northeast and coasts, and Republicans dominating in the red states in the middle of the country and the south. Through multilevel modeling of individuallevel survey data and county- and state-level demographic and electoral data, we reconcile these patterns.
Furthermore, we find that income matters more in red America than in blue America. In poor states, rich people are much more likely than poor people to vote for the Republican presidential candidate, but in rich states (such as Connecticut), income has a very low correlation with vote preference.
Key methods used in this research are: (1) plots of repeated cross-sectional analyses, (2) varying-intercept, varying-slope multilevel models, and (3) a graph that simultaneously shows within-group and between-group patterns in a multilevel model. These statistical tools help us understand patterns of variation within and between states in a way that would not be possible from classical regressions or by looking at tables of coefficient estimates.
(with Joseph Bafumi, Luke Keele, and David Park)
Published in Political Analysis, Spring 2007
Abstract: The analysis of time series cross-sectional (TSCS) data has become increasingly popular in political science. Meanwhile, political scientists are also becoming more interested in the use of multilevel models. However, little work exists to understand the benefits of multilevel modeling when applied to TSCS data. We employ Monte Carlo simulations to benchmark the performance of a Bayesian multilevel model (BML) for TSCS data against popular models used in the literature. We use various diagnostics to analyze the performance of our approach relative to these techniques. Compared to the most commonly employed estimators for such data, we find that the Bayesian multilevel model is (1) equally unbiased on average, (2) considerably more efficient, and (3) reports higher quality standard errors. Moreover, the BML is more general and flexible, which offers researchers additional advantages for TSCS data.