Estimating Candidates’ Political Orientation in a Polarized Congress

Abstract

Over the past decade, a number of new measures have been developed that attempt to capture the political orientation of both incumbent and nonincumbent candidates for Congress, as well as other offices, on the same scale. These measures pose the possibility of being able to answer a host of fundamental questions about political accountability and representation. In this paper, we examine the properties of six recent measures of candidates’ political orientations in different domains. While these measures are commonly viewed as proxies for ideology, each involves very different choices, incentives, and contexts. Indeed, we show that there is only a weak relationship between these measures within party. This suggests that these measures are capturing domain-specific factors rather than just candidates’ ideology. Moreover, these measures do poorly at distinguishing between moderate and extreme roll call voting records within each party. As a result, they fall short when it comes to facilitating empirical analysis of theories of accountability and representation in Congress. Overall, our findings suggest that future research should leverage the conceptual and empirical variation across these measures and avoid assuming they are synonymous with candidates’ ideology.

How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data

“…More technically, the model is similar to an item-response model in which the probability that a user follows a political actor's Twitter account is a function of the latent (ideological) spatial distance between the user and that political actor. The method has been used in recent work to examine selective exposure (Barberá, Jost, Nagler, Tucker, & Bonneau, 2015;Vaccari et al, 2016), to compare ideological estimates of political actors derived from social media to those from other data sources (Tausanovitch & Warshaw, 2017), and to examine the link between journalists' social media networks and the content they produce (Wihbey, Coleman, Joseph, & Lazer, 2017).…”

Who Punishes Extremist Nominees? Candidate Ideology and Turning Out the Base in US Elections

“…Recent literature has raised questions about what exactly contribution-based scalings reveal about candidate positions 12 . In particular, Tausanovitch and Warshaw (2017) shows that the CFScores developed in Bonica (2014) do not correlate well with estimates of candidate ideology built from roll-call votes (like the Nominate scalings from Poole and Rosenthal (1985)). The most important point for us to make is that the Hall–Snyder scalings we use actually correlate fairly well with Nominate within party; as Hall and Snyder (2014) shows, the Hall–Snyder scores correlate at 0.61 with Nominate scores for Democrats and at 0.53 for Republican Nominate scores.…”

“…No other measure is available for studying questions about incumbents and challengers at scale. That said, recent work, focusing primarily on the CFScore scalings from Bonica (2014), raises questions about what the scalings actually measure (Hill and Huber 2017; Tausanovitch and Warshaw 2017). Tausanovitch and Warshaw (2017), in particular, shows that CFScores do not correlate well with DW-NOMINATE scores—a conventional measure of roll-call-based ideology for sitting legislators from Poole and Rosenthal (1985)—within party.…”

Inferring Roll-Call Scores from Campaign Contributions Using Supervised Machine Learning

“…A well-known limitation of roll-call-based measures of ideology is that they are confined to voting bodies. This precludes estimating scores for nonincumbent candidates prior to taking office, which is arguably where such predictions would be most valuable (Tausanovitch and Warshaw 2017). Only recently has the focus on scaling Congress begun to give way as political scientists Adam Bonica is Assistant Professor, Department of Political Science, Stanford University,Encina Hall West,Office Number 307,616 Serra Street,Stanford,CA 94305 (bonica@stanford.edu). have sought to extend ideal point estimation to a wider set of institutions and contexts.…”

“…In a recent article, Tausanovitch and Warshaw (2017) evaluate several alternative measures of ideology recovered from survey data, campaign contributions, and social media data based on comparisons with DW-NOMINATE. They find that most measures successfully sort legislators by party but are less successful in distinguishing between members of the same party.…”