Hitler’s rise to power amidst an unprecedented propaganda campaign initiated scholarly interest in campaign effects. To the surprise of many, empirical studies often found minimal effects. The predominant focus of early work was on U.S. elections, though. Nazi propaganda as the archetypal and, in many ways, most likely case for strong effects has rarely been studied. We collect extensive data about Hitler’s speeches and gauge their impact on voter support at five national elections preceding the dictatorship. We use a semi-parametric difference-in-differences approach to estimate effects in the face of potential confounding due to the deliberate scheduling of events. Our findings suggest that Hitler’s speeches, while rationally targeted, had a negligible impact on the Nazis’ electoral fortunes. Only the 1932 presidential runoff, an election preceded by an extraordinarily short, intense, and one-sided campaign, yielded positive effects. This study questions the importance of charismatic leaders for the success of populist movements.

Repeated measurements of the same countries, people, or groups over time are vital to many fields of political science. These measurements, sometimes called time-series cross-sectional (TSCS) data, allow researchers to estimate a broad set of causal quantities, including contemporaneous effects and direct effects of lagged treatments. Unfortunately, popular methods for TSCS data can only produce valid inferences for lagged effects under some strong assumptions. In this paper, we use potential outcomes to define causal quantities of interest in these settings and clarify how standard models like the autoregressive distributed lag model can produce biased estimates of these quantities due to post-treatment conditioning. We then describe two estimation strategies that avoid these post-treatment biases—inverse probability weighting and structural nested mean models—and show via simulations that they can outperform standard approaches in small sample settings. We illustrate these methods in a study of how welfare spending affects terrorism.

Has government protection of human rights improved? The answer to this and many other research questions is strongly affected by the assumptions we make and the modeling strategy we choose as the basis for creating human rights country scores. Fariss (2014) introduced a statistical model that produced latent scores showing an improving trend in human rights. Consistent with his stringent assumptions, his statistical model heavily weighted rare incidents of mass killings such as genocide, while discounting indicators of lesser and more common violations such as torture and political imprisonment. We replicated his analysis, replacing the actual values of all indicators of lesser human rights violations with randomly generated data, and obtained an identical improving trend. However, when we replicated the analysis, relaxing his assumptions by allowing all indicators to potentially have a similar effect on the latent scores, we find no human rights improvement.

In this article, I introduce a method that uses large-scale event data and latent factor network models to provide a new comparative measure of cooperation and conflict in public relationships among politicians, nonpartisan political actors, and societal actors. The approach has a number of advantages over existing techniques: It captures public relationships in a multitude of venues on a continuous basis, incorporates both partisan and nonpartisan actors, allows quantifying the relationship between any pair of actors, reflects that communication is not unidirectional but rather a back and forth, and can be applied to a large number of countries over time. I apply the method to 13 Western European countries from 2001 to 2014 and demonstrate that party relationships are determined by coalition status as well as policy differences. The measure is publicly available and can be incorporated into standard research designs.

How does ethnoracial demography relate to public goods provision? Many studies find support for the hypothesis that diversity is related to inefficient outcomes by comparing diverse and homogeneous communities. We distinguish between homogeneity of dominant and disadvantaged groups and argue that it is often impossible to identify the effects of diversity due to its collinearity with the share of disadvantaged groups. To disentangle the effects of these variables, we study new data from Brazilian municipalities. While it is possible to interpret the prima facie negative correlation between diversity and public goods as supportive of the prominent “deficit” hypothesis, a closer analysis reveals that, in fact, more homogeneous Afro-descendant communities have lower provision. While we cannot rule out that diversity is consequential in other contexts, our results cast doubt on the reliability of previous findings related to the benefits of local ethnoracial homogeneity for public outcomes.

Taking advantage of a unique event in American history, the Second Great Migration, we explore whether the rapid entry of African Americans into nearly exclusively White contexts triggered “racial threat” in White voting behavior in the state of California. Utilizing historical administrative data, we find that increasing proximity to previously White areas experiencing drastic Black population growth between 1940 to 1960 is associated with significant increases in aggregate White voter support for a highly racially-charged ballot measure, Proposition 14, which legally protected racial discrimination in housing. Importantly, we find that this result holds when restricting the analysis to all-White areas with high rates of residential tenure and low rates of White population growth. These latter findings indicate that this relationship materializes in contexts where a larger share of White voters were present during the treatment and exercised residential-choice before the treatment commenced, which is suggestive of a causal effect.

The objective of this paper is to model the incumbent’s allocation of efforts that maximize his electoral chances in the presence of both vote buying (persuasion) and turnout buying (mobilization). The existing literature on distributive politics concludes that political candidates should concentrate their campaigning efforts either on safe districts or on swing districts. This paper shows that when candidates can use both persuasion and mobilization strategies, and the ideology of voters is unknown to the incumbent party, a third option should be taken into account. In fact, the optimal allocation of resources—rather than focusing on safe or swing districts—should target opposition strongholds, that is, the incumbent should try to sway voters in those districts in which the challenger is favored. The intuition for this result is simple. Since the incumbent does not know individual preferences (he only observes the distribution of preferences in the districts), all voters in a given district look identical to him. Hence, when approaching voters in a district to buy their vote, the incumbent always faces the risk of buying the vote of his supporters (who would have voted for him anyway).

Public reason liberals appeal to public deliberation to ensure that a legal order can be publicly justified to its citizens. I argue that this voice mechanism should be supplemented by exit mechanisms. By allowing citizens to exit legal orders they believe cannot be publicly justified, citizens can pressure states to change their laws. This exit pressure is sometimes more effective than deliberation. I explore federalism as an exit mechanism that can help public deliberation establish a publicly justified polity.