Recent work has pioneered the use of expert surveys to estimate cross-national party positions in a common ideological space. In this paper, we report findings from an original dataset designed to evaluate bridging strategies between European and American party placements. Specifically, we compare the use of “anchoring vignettes” (fictional party platforms) with an alternative approach that asks comparativist scholars who live in the US (whom we call transatlantic or TA experts) to place parties and parties in their country of expertise on a series of issues scales. The results provide an optimistic assessment of the ability of TA experts to serve as valid bridges across the Atlantic. The resulting cross-comparable estimates of party positions show instances of both convergence and divergence between American and European party systems, including parallels between systems on the cross-cutting issue of international economic integration.

Although politicians’ personal attributes are an important component of elections and representation, few studies have rigorously investigated which attributes are most relevant in shaping voters’ preferences for politicians, or whether these preferences vary across different electoral system contexts. We investigate these questions with a conjoint survey experiment using the case of Japan’s mixed-member bicameral system. We find that the attributes preferred by voters are not entirely consistent with the observed attributes of actual politicians. Moreover, voters’ preferences do not vary when asked to consider representation under different electoral system contexts, whereas the observed attributes of politicians do vary across these contexts. These findings point to the role of factors beyond voters’ sincere preferences, such as parties’ recruitment strategies, the effect of electoral rules on the salience of the personal vote, and the availability of different types of politicians, in determining the nature of representation.

This paper examines how a party’s decision to enter a coalition government affects voter perceptions of the party’s policy position. We argue that, for the decision to change voter beliefs, it must be at odds with voters’ prior opinions about the party. Specifically, the party must join a coalition that is not the one voters perceive as the ideologically closest option. Otherwise, the party’s action simply confirms voters’ pre-existing beliefs. Hence, whether or not joining a coalition alters voter attitudes depends on the type of alternative coalitions the party could enter. We test the hypothesis using three complementary empirical strategies: a cross-country analysis of party reputations in five coalition-prone European countries, individual panel data, and a quasi-experimental test. All three empirical tests provide support for our claim. This paper contributes to our understanding of voter information processing, coalition politics, and party competition.

The striking under-representation of women in Japan has been partly attributed to gender stereotypes and prejudice toward female leadership among voters. We examine whether and to what extent candidates get rewarded or punished when they deviate from the behavioral expectations associated with their gender roles and images. Our conjoint experiment results in Japan demonstrate that not only are female candidates disadvantaged compared to their male counterparts, but also that they could lose support when they diverge from gender-based behavioral expectations. Our findings suggest that female candidates face a difficult dilemma in that they must weigh the cost of losing support for failing to conform to gender-based expectations, against the general loss of support they would incur for conforming to these expectations.

In comparative studies, causal evaluations attempt to improve our understanding of the effectiveness of structural reforms by counterfactually inspecting post-treatment effects. Yet, even if comparative scholars find similar treatment and comparison units, the interpretation of the post-treatment trajectory is difficult as short-term estimates can be subject to strategic timing of reform implementation, while long-term effects are likely affected by further interventions. To illustrate these difficulties we apply the generalized synthetic control method to evaluate the introduction of a British national minimum wage. We find a short-term decreasing effect on youth unemployment that turns into an increasing effect over time. This suggests the presence of an upward biased selection effect from strategic timing. We also inspect two post-treatment interventions and find that they differ in their general and country-specific implications for the long-term trajectory.

In this study we focus on party organizational characteristics as key determinants of party congruence. We examine how the horizontal and vertical integration of parties is linked to representation in comparative perspective. We further focus on how congruence is achieved by detailing our expectation regarding effects on the uncertainty versus bias in the estimates of party constituents' opinion. Exploiting a comparative database on political parties and data from Comparative Studies of Electoral Systems, we show that having a complex organizational structure and being leadership dominated makes parties less representative of their constituencies. These findings carry important implications for the study of political representation but also for the literature on political parties in crisis.

Most agree that models of binary time-series-cross-sectional data in political science often possess unobserved unit-level heterogeneity. Despite this, there is no clear consensus on how best to account for these potential unit effects, with many of the issues confronted seemingly misunderstood. For example, one oft-discussed concern with rare events data is the elimination of no-event units from the sample when estimating fixed effects models. Many argue that this is a reason to eschew fixed effects in favor of pooled or random effects models. We revisit this issue and clarify that the main concern with fixed effects models of rare events data is not inaccurate or inefficient coefficient estimation, but instead biased marginal effects. In short, only evaluating event-experiencing units gives an inaccurate estimate of the baseline risk, yielding inaccurate (often inflated) estimates of predictor effects. As a solution, we propose a penalized maximum likelihood fixed effects (PML-FE) estimator, which retains the complete sample by providing finite estimates of the fixed effects for each unit. We explore the small sample performance of PML-FE versus common alternatives via Monte Carlo simulations, evaluating the accuracy of both parameter and effects estimates. Finally, we illustrate our method with a model of civil war onset.

Behavioral economists and social psychologists have shown that extrinsic motivations can crowd out intrinsic motivations to act. This study examines this crowding out effect in the context of legislative behavior. By exploiting the federal nature of Swiss elections, we examine if response rates to requests of voters residing inside or outside a candidate's district vary based on the electoral competition candidate legislators face. We report two main findings. First, we find a high response rate among Swiss candidates (66 percent) which remains high for voters who reside outside a candidate's district (59 percent) suggesting that intrinsic motivations are a key driver of constituency effort. Second, the response to voters who reside inside a candidate's district is more pronounced for candidates confronted with a high degree of electoral competition. This suggests that extrinsic motivations are important for constituency work, but at the same time their presence might crowd out intrinsic motivations. This evidence suggests that the relationship between electoral competition and responsiveness might be less straightforward than assumed.

Scholars often use voting data to estimate central bankers’ policy preferences but consensus voting is commonplace. To get around this, we combine topic-based text analysis and scaling methods to generate theoretically motivated comparative measures of central bank preferences on the US Federal Open Market Committee (FOMC) leading up to the financial crisis in a way that does not depend on voting behavior. We apply these measures to a number of applications in the literature. For example, we find that FOMC members that are Federal Reserve Bank Presidents from districts experiencing higher unemployment are also more likely to emphasize unemployment in their speech. We also confirm that committee members on schedule to vote are more likely to express consensus opinion than their off schedule voting counterparts.

In many elections around the world, voters choose between politicians who differ not only in personal background and policy promises, but also in their history of dishonest electoral conduct. While recent literature has begun to investigate the conditions under which voters punish electoral malfeasance, we know relatively little about whether they penalize different forms of illicit activities carried out by politicians differently. In this paper, we present the results of a candidate choice experiment embedded in a survey fielded prior to the 2016 Romanian local election. We asked voters to choose between two hypothetical candidates, randomly varying several attributes, including different illicit electoral activities. We find that citizens tolerate some forms of political malfeasance less than others depending on how much that malfeasance infringes on voters' autonomy. Informational campaigns carried out by prosecutorial agencies also affect how much voters punish different illicit exchanges.

Models testing interactive and quadratic hypotheses are common in Political Science but control strategies for these models have received little attention. Common practice is to simply include additive control variables, without relevant product terms, into models with interaction or quadratic terms. In this paper, we show in Monte Carlos that interaction terms can absorb the effects of other un-modeled interaction and non-linear effects and analogously, that included quadratic terms can reflect omitted interactions and non-linearities. This problem even occurs when included and omitted product terms do not share any constitutive terms. We show with Monte Carlo experiments that regularized estimators, the adaptive Lasso, Kernel Regularized Least Squares (KRLS), and Bayesian Additive Regression Trees (BART) can prevent the misattribution of interactive/quadratic effects, minimize the problems of efficiency loss and overfitting, and have low false-positive rates. We illustrate how inferences drawn can change when relevant product terms are used in the control strategy using a recent paper. Implementing the recommendations of this paper would increase the reliability of conditional and non-linear relationships estimated in many papers in the literature.

Globalization has been one of the biggest driving forces of the last half century. There has been substantial disagreement about the impact that increased international integration has on income inequality. Though most agree that globalization positively affects economic output, it is no surprise that it leads to relative winners and losers within nations. The question that remains is where in the income distribution are these relative gains and losses occurring? We offer a broader picture of globalization's effects on inequality by using a dynamic compositional approach to test the impact of globalization and relative factor endowments on the composition of income. Using data from four countries, we model the effects of globalization on quantiles of the income distribution. Our findings suggest that globalization has substantial (and divergent) effects across income strata, and that these effects differ across nations based on relative factor endowments.

Measuring networks in the field—usually by asking individuals systematically about their networks–entails complex design choices, with large consequences for the resulting data. Because observations in a network are interconnected, well-established practices from non-network survey settings can lead researchers astray. Despite the increasing focus on networks in political science, little guidance is available for researchers facing high-stakes decisions when designing a study to elicit networks. This paper serves as a practical guide. It offers a simple framework for constructing a network theory, illuminates tradeoffs like measuring more nodes versus more ties per node or asking for names versus selections from a list, and proposes a new technique for cleaning relational data.

Executive control of government is generally not a long-term job. In such cases, relatively short executive tenure should be expected to play an important role in determining the degree to which policymakers internalize the future costs associated with their current fiscal behavior. The effects of policymaker's expected planning horizons on macroeconomic outcomes, however, have been difficult to model outside of a fixed term limit context due to the unobserved likelihood of remaining in office, along with potential endogeneity problems where re-election campaigns can be enhanced with generous, deficit-financed expenditures in election years. From a globally representative sample of 79 countries over a 32-year period (1980–2012), this paper provides empirical evidence suggesting that incumbent governments who know that will not be in office in the following period with a probability of one, are found to generate significantly higher deficits in a linear discounting model, and are found to produce the least responsible fiscal outcomes where the likelihood of re-election is around fifty percent in quadratic discounting models.

Analyzing audiovisual communication is challenging because its content is highly symbolic and less rule-governed than verbal material. But audiovisual messages are important to understand: they amplify, enrich, and complicate the meaning of textual information. We describe a fully-reproducible approach to analyzing video content using minimally—but systematically—trained online workers. By aggregating the work of multiple coders, we achieve reliability, validity, and costs that equal those of traditional, intensively trained research assistants, with much greater speed, transparency, and replicability. We argue that measurement strategies relying on the “wisdom of the crowd” provide unique advantages for researchers analyzing complex and intricate audiovisual political content.

Coincidence Analysis (CNA) is a configurational comparative method of causal data analysis that is related to Qualitative Comparative Analysis (QCA) but, contrary to the latter, is custom-built for analyzing causal structures with multiple outcomes. So far, however, CNA has only been capable of processing dichotomous variables, which greatly limited its scope of applicability. This paper generalizes CNA for multi-value variables as well as continuous variables whose values are interpreted as membership scores in fuzzy sets. This generalization comes with a major adaptation of CNA’s algorithmic protocol, which, in an extended series of benchmark tests, is shown to give CNA an edge over QCA not only with respect to multi-outcome structures but also with respect to the analysis of non-ideal data stemming from single-outcome structures. The inferential power of multi-value and fuzzy-set CNA is made available to end users in the newest version of the R package cna.

Researchers in political science often estimate linear models of continuous outcomes using least squares. While it is well known that least-squares estimates are sensitive to single, unusual data points, this knowledge has not led to careful practices when using least-squares estimators. Using statistical theory and Monte Carlo simulations, we highlight the importance of using more robust estimators along with variable transformations. We also discuss several approaches to detect, summarize, and communicate the influence of particular data points.

Spatial conditionally autoregressive (CAR) models in a hierarchical Bayesian framework can be informative for understanding state politics, or any similar population of border-defined observations. This article explains how a hierarchical CAR model is specified and estimated and then uses Monte Carlo analyses to show when the CAR model offers efficiency gains. We apply this model to data structures common to state politics: A cross-sectional example replicates Erikson, Wright and McIver’s (1993) Statehouse Democracy model and a multilevel panel model example replicates Margalit’s (2013) study of social welfare policy preferences. The CAR model fits better in each case and some inferences differ from models that ignore geographic correlation.

Mixed-methods designs, especially those in which case selection is regression-based, have become popular across the social sciences. In this paper, we highlight why tools from spatial analysis—which have largely been overlooked in the mixed-methods literature—can be used for case selection and be particularly fruitful for theory development. We discuss two tools for integrating quantitative and qualitative analysis: (1) spatial autocorrelation in the outcome of interest; and (2) spatial autocorrelation in the residuals of a regression model. The case selection strategies presented here enable scholars to systematically use geography to learn more about their data and select cases that help identify scope conditions, evaluate the appropriate unit or level of analysis, examine causal mechanisms, and uncover previously omitted variables.

Why do left parties lose vote shares in times of economic crisis and hardship? Why do right-wing governments implement seemingly left-wing policies, such as labor market activation? Why is representation becoming more and more unequal? And why do workers vote for right-wing populist parties? Several political science theories propose meaningful and important answers to these key questions for comparative politics, focusing on identity politics, programmatic convergence of parties or exogenous constraints. However, there is an additional and distinct approach to all of the questions above, which emphasizes socio-structural transformations in the labor market: most of the processes above can be understood with reference to increasing labor market inequality and its political implications. The relevance and explanatory power of labor market inequality for mass politics have not been fully acknowledged in comparative political science and this is the reason for this symposium. Labor market inequality affects political preferences and behavior, electoral politics, representation, and government strategies. The main purpose of our symposium is to make broader comparative politics research aware of the crucial structural changes that labor markets have undergone in the advanced capitalist democracies of the OECD, and of the tremendous implications these changes have had for politics.