Anti-black prejudice affects how some citizens evaluate black candidates. What does it take to reduce the role of prejudice in these evaluations? Using logical implications of relevant psychological phenomena, this article shows that repeated exposure to counter-stereotypical information is insufficient to reduce evaluative prejudice. Instead, citizens must associate this prejudice with adverse effects for themselves in contexts that induce them to rethink their existing racial beliefs. These findings explain important disagreements in empirical prejudice research, as only some empirical research designs supply the conditions for prejudice reduction predicted here. This study also clarifies why similarly situated citizens react so differently to counter-stereotypical information. In sum, we find that prejudice change is possible, but in a far narrower set of circumstances than many scholars claim.

This article develops a game-theoretic model that reconciles three facts: (1) fraud is pervasive in non-competitive elections, (2) domestic and international monitoring of elections have become nearly universal and (3) incumbent regimes often invite monitoring and still cheat. The incumbent regime commits fraud to manipulate the information generated by a non-competitive election before a political interaction with some audience. The audience expects fraud, so the incumbent commits fraud because she would appear weak if not doing so. Increasing the visibility of fraud with monitoring is valuable because it lowers the equilibrium level of costly fraud without changing how popular the incumbent appears. The core results hold under multiple extensions, which produce a rich set of comparative static results.

The nonverbal display of confidence is strongly associated with leadership and power. However, its importance for the persuasiveness of campaign messages has not been explored. How important is showing confidence for a political candidate’s ratings? How does confidence condition the effect of the quality of a candidate’s arguments? This article addresses these questions using an innovative experimental approach that makes it possible to better isolate the impact of the candidate’s nonverbal confidence and the quality of his message. While both of these aspects influence voters’ perceptions of the candidate’s electability and qualifications, the nonverbal dimension matters more when it comes to electability. This research contributes to the study of nonverbal communication in elections by expanding the focus of inquiry beyond the effect of pure emotions (happiness or anger) and facial traits.

Many political scientists and economists have argued that coalition governments tend to accumulate more debt than single-party governments do, but the evidence for this proposition is mixed. This article argues that only some coalition governments are more likely to increase public debt than single-party governments: those in which parties are unable to make credible promises to their partners about future policy. It introduces the concept of ‘commitment potential’ within coalitions and proposes a way of measuring it. The study evaluates its theoretical claims using data on 20 advanced democracies observed over a period of almost 50 years. It finds that multiparty governments with high commitment potential do not, on average, accumulate more debt than single-party governments, but that governments with low commitment potential do.

Given similar economic distress indicators, why do some states enter into International Monetary Fund (IMF) programs while others do not? Building on extant studies of IMF program participation that highlight the importance of various economic and political determinants, this article proposes an argument focusing on the political incentives of the IMF and a borrowing country when they engage in IMF program negotiations. Specifically, the study develops a domestic politics argument to highlight the interactions among sovereignty costs, competence costs, economic conditions and domestic regime types, and tests the argument using a cross-national time-series dataset of all IMF agreements between 1970 and 2006. It finds that when the economic crisis is mild, democracies are less likely than non-democracies to enter IMF programs, but that when the economic crisis is severe, democracies are more likely to do so than their autocratic counterparts. The article attributes this tendency to democratic leaders’ electoral vulnerability and shows that these patterns become more pronounced as elections draw near.

Empirical political science is not simply about reporting evidence; it is also about coming to conclusions on the basis of that evidence and acting on those conclusions. But whether a result is substantively significant––strong and certain enough to justify acting upon the belief that the null hypothesis is false––is difficult to objectively pin down, in part because different researchers have different standards for interpreting evidence. Instead, this article advocates judging results according to their “substantive robustness,” the degree to which a community with heterogeneous standards for interpreting evidence would agree that the result is substantively significant. This study illustrates how this can be done using Bayesian statistical decision techniques. Judging results in this way yields a tangible benefit: false positives are reduced without decreasing the power of the test, thus decreasing the error rate in published results.

A small but growing social science literature examines the correspondence between experimental results obtained in lab and field settings. This article reviews this literature and reanalyzes a set of recent experiments carried out in parallel in both the lab and field. Using a standardized format that calls attention to both the experimental estimates and the statistical uncertainty surrounding them, the study analyzes the overall pattern of lab-field correspondence, which is found to be quite strong (Spearman's ρ = 0.73). Recognizing that this correlation may be distorted by the ad hoc manner in which lab-field comparisons are constructed (as well as the selective manner in which results are reported and published), the article concludes by suggesting directions for future research, stressing in particular the need for more systematic investigation of treatment effect heterogeneity.

This article challenges Fixed Effects (FE) modeling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within and between effects is crucial when choosing modeling strategies. The downside of Random Effects (RE) modeling—correlated lower-level covariates and higher-level residuals—is omitted-variable bias, solvable with Mundlak's (1978a) formulation. Consequently, RE can provide everything that FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plümper and Troeger's FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions and complex variance functions. We argue not simply for technical solutions to endogeneity, but for the substantive importance of context/heterogeneity, modeled using RE. The implications extend beyond political science to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.