Research on Russian troll activity during the 2016 US presidential campaign largely focused on divisive partisan messaging. Here, we document the use of apolitical content—content that could counteract mobilization efforts and escape detection in future campaigns. We argue this resembled techniques used by autocratic regimes domestically, in “flooding” social media with entertainment content to distract from and displace mobilizing messaging. Using automated text analysis and hand coding to construct a timeline of IRA messaging on Twitter, we find left-leaning trolls posted large volumes of entertainment content in their artificial liberal community and shifted away from political content late in the campaign. Simultaneously, conservative trolls were targeting their community with increases in political content. This suggests the use of apolitical content might be an overlooked strategy to selectively manipulate levels of attention to politics.

Substantial evidence exists that members of the US Congress vary in their lawmaking effectiveness. Less known, however, is whether constituents are sufficiently informed and inclined to hold their representatives accountable, based on their effectiveness. We conduct two separate survey experiments, informing some constituents about lawmakers' effectiveness and comparing their responses to those with the baseline level of information. We find that voters demonstrate little knowledge of their elected officials' lawmaking effectiveness. When presented with objective and credible information about lawmaking effectiveness, however, respondents express greater approval of more effective lawmakers. Effects are strongest among ideological moderates, but are even pronounced among partisans, who approve of effective representatives of the opposing party, and disapprove of ineffective representatives from their own party.

Voters use salient issues to inform their vote choice. Using 2020 Cooperative Election Study (CES) data, we analyze how short-, medium-, and long-term issues informed the vote for president in the 2020 election, which witnessed record-setting participation. To explain the dynamics of presidential vote choice, we employ a voter typology advanced by Key (1966). Specifically, compared to standpatters, who in 2020 registered the same major party vote as in 2016, we find that new voters in 2020 and voters switching their preferences from 2016 cast their ballots in favor of Democrat Joe Biden. In the end, President Donald Trump was denied reelection by new voters and vote switchers principally because certain issues had a notable effect in moving their presidential preferences in the Democratic direction.

Although covert warfare does not readily lend itself to scientific inquiry, new technologies are increasingly providing scholars with tools that enable such research. In this note, we examine the effects of drone strikes on patterns of communication in Yemen using big data and anomaly detection methods. The combination of these analytic tools allows us to not only quantify some of the effects of drone strikes, but also to compare them to other shocks. We find that on average drone strikes leave a footprint in their aftermath, spurring significant but localized spikes in communication. This suggests that drone strikes are not a purely surgical intervention, but rather have a disruptive impact on the local population.

Grant and Lebo (2016) and Keele et al. (2016) clarify the conditions under which the popular general error correction model (GECM) can be used and interpreted easily: In a bivariate GECM the data must be integrated in order to rely on the error correction coefficient, $\alpha _1^\ast$, to test cointegration and measure the rate of error correction between a single exogenous x and a dependent variable, y. Here we demonstrate that even if the data are all integrated, the test on $\alpha _1^\ast$ is misunderstood when there is more than a single independent variable. The null hypothesis is that there is no cointegration between y and any x but the correct alternative hypothesis is that y is cointegrated with at least one—but not necessarily more than one—of the x's. A significant $\alpha _1^\ast$ can occur when some I(1) regressors are not cointegrated and the equation is not balanced. Thus, the correct limiting distributions of the right-hand-side long-run coefficients may be unknown. We use simulations to demonstrate the problem and then discuss implications for applied examples.

Members and parties have electoral incentives to address issues on the congressional agenda to satisfy public demand. When determining which issues to address, majorities seek to minimize their uncertainty about the costs and electoral benefits of legislating by revisiting policy areas previously addressed. This theory is tested using error-correction models that demonstrate that policy activity within each chamber is in a long-term equilibrium and that the passage of legislation, even important bills, promotes future policymaking in the same policy area. This relationship is stronger when the majority has less information about the costs of lawmaking—specifically, when it faces a chamber controlled by the opposite party and when it is a new majority.

Liberalization is a perennial topic in politics and political science. We first review a broad scholarly debate, showing that the mainstream theories make rival and contradictory claims regarding the role of political parties in (de)liberalization reforms. We then develop a framework of conditional partisan influence, arguing that and under what conditions parties matter. We test our (and rival) propositions with a new dataset on (de)liberalization reforms in 23 democracies since 1973 covering several policy areas. Methodologically, we argue that existing quantitative studies are problematic: They rely on time-series cross-section models using country-year observations; but governments do not change annually, so that the number of observations is artificially inflated, resulting in incorrect estimates. We propose mixed-effects models instead, with country-year observations nested in cabinets, which are nested in countries and years. The results show under what conditions parties matter for (de)liberalization. More generally, the paper argues that mixed-effects models should become the new standard for studying partisan influences.

Can data on government coercion and violence be trusted when the data are generated by state itself? In this paper, we investigate the extent to which data from the California Department of Corrections and Rehabilitation (CDCR) regarding the use of force by corrections officers against prison inmates between 2008 and 2017 conform to Benford's Law. Following a growing data forensics literature, we expect misreporting of the use-of-force in California state prisons to cause the observed data to deviate from Benford's distribution. Statistical hypothesis tests and further investigation of CDCR data—which show both temporal and cross-sectional variance in conformity with Benford's Law—are consistent with misreporting of the use-of-force by the CDCR. Our results suggest that data on government coercion generated by the state should be inspected carefully before being used to test hypotheses or make policy.

Despite considerable progress, inequality between countries remains at staggering levels. However, we know surprisingly little about demand for international redistribution in the Global South. This is unfortunate as it hinders our understanding of the pressures governments experience to cooperate internationally. Therefore, this paper studies perceptions of international inequality and attitudes toward international aid, an important instrument for redistribution, in Kenya, a major recipient of aid. It features an SMS-based survey experiment, in which respondents are treated with information about international income differences. It is found that most respondents underestimate these differences and that providing accurate information lowers inequality acceptance. However, this does not translate into demand for aid. The findings question often-made assumptions about the popularity of aid and call for further investigation of other internationally redistributive policies.

This article evaluates the reliability of sensitivity tests. Using Monte Carlo methods we show that, first, the definition of robustness exerts a large influence on the robustness of variables. Second and more importantly, our results also demonstrate that inferences based on sensitivity tests are most likely to be valid if determinants and confounders are almost uncorrelated and if the variables included in the true model exert a strong influence on outcomes. Third, no definition of robustness reliably avoids both false positives and false negatives. We find that for a wide variety of data-generating processes, rarely used definitions of robustness perform better than the frequently used model averaging rule suggested by Sala-i-Martin. Fourth, our results also suggest that Leamer’s extreme bounds analysis and Bayesian model averaging are extremely unlikely to generate false positives. Thus, if based on these inferential criteria a variable is robust, it is almost certain to belong into the empirical model. Fifth and finally, we also show that researchers should avoid drawing inferences based on lack of robustness.

When separation is a problem in binary dependent variable models, many researchers use Firth's penalized maximum likelihood in order to obtain finite estimates (Firth, 1993; Zorn, 2005; Rainey, 2016). In this paper, I show that this approach can lead to inferences in the opposite direction of the separation when the number of observations are sufficiently large and both the dependent and independent variables are rare events. As large datasets with rare events are frequently used in political science, such as dyadic data measuring interstate relations, a lack of awareness of this problem may lead to inferential issues. Simulations and an empirical illustration show that the use of independent “weakly-informative” prior distributions centered at zero, for example, the Cauchy prior suggested by Gelman et al. (2008), can avoid this issue. More generally, the results caution researchers to be aware of how the choice of prior interacts with the structure of their data, when estimating models in the presence of separation.

What is the effect of external economic intervention on political support and economic evaluations? We argue that economic interventions systematically worsen support for governing institutions and much of this is mediated through updating economic perceptions, at least during the Eurozone crisis. We evidence this with two analyses. First, we provide the first quasi-experimental evidence to show that intervention worsened both political support and economic evaluations. Second, we conduct a mediation analysis using Eurobarometer data to quantify how much of the effect of intervention is mediated by economic evaluations. This has broader implications for understanding how citizens react to international integration, international cues, and the process of forming judgements of political support.

Conventional OLS fixed-effects and GLS random-effects estimators of dynamic models that control for individual-effects are known to be biased when applied to short panel data (T ≤ 10). GMM estimators are the most used alternative but are known to have drawbacks. Transformed-likelihood estimators are unused in political science. Of these, orthogonal reparameterization estimators are only tangentially referred to in any discipline. We introduce these estimators and test their performance, demonstrating that the unused orthogonal reparameterization estimator in particular performs very well and is an improvement on the commonly used GMM estimators. When T and/or N are small, it provides efficiency gains and overcomes the issues GMM estimators encounter in the estimation of long-run effects when the coefficient on the lagged dependent variable is close to one.

Previous scholarship has provided ample evidence that non-spatial considerations can trump voters’ policy preferences in candidate selections. The literature has been less successful, however, in providing a sense of the factors that raise candidates’ non-policy appeal. Faced with the challenging task of separating policy and non-policy aspects of individual vote choices, empirical research has frequently relied on shorthand measures like candidate incumbency. This paper separates the valence component from policy-based candidate selections by explicitly supplying voters with information on the policy agreement between themselves and their district candidates. Relying on the distinction between campaign valence and character valence by Stone and Simas, it is shown that candidate valence is driven by candidate visibility in a party-dominated political system.

Inequalities in voter participation between groups of the population pose a problem for democratic representation. We use administrative data on 6.7 million registered voters to show that a previously-ignored characteristic of voters—access to a personal automobile—creates large disparities in in-person voting rates. Lack of access to a car depresses election day voter turnout by substantively large amounts across a variety of fixed-effects models that account for other environmental and voter characteristics. Car access creates the largest hindrance to voting for those people who live farther from the polls. These effects do not appear for absentee voting, suggesting a simple policy solution to solve large disparities in political participation. This study contributes to the theoretic understanding of political participation as well as the impact of potential policy reforms to solve participatory gaps.

Research from the United States has shown that the 9/11 terrorist attacks activated individuals’ ethnocentric predispositions to structure public opinion toward several political and social issues. Beyond this overall finding, several aspects of the activation hypothesis remain unexplored, including its geographical and substantive scope. Using the quasi-random timing of terrorist attacks during the collection of the 2016 GGSS, we demonstrate the terrorism-induced activation of ethnocentrism in Germany. Specifically, a cascade of terrorist attacks involving immigrants in the summer of 2016 activated ethnocentrism among native Germans to predict (lower) support for civil liberties relative to security concerns after its influence had been absent just a month before. Further, we show that the activation of ethnocentrism holds up in a series of robustness checks and is not explained by alternative factors, including other predispositions.

A central challenge in understanding public opinion shifts is identifying whose opinions change. Political economists try to uncover this by exploring voters’ economic vulnerability, particularly the relationship between labor-market risk and redistribution preferences. Predominantly, however, such work imputes risk from occupational or sectoral characteristics. Due to within-occupational inequality in exposure to risk, considerable variation remains unexplored. I propose an individual-level, dynamic account of risk inferred from job tenure, contract type, and expectations of job security. These aspects, importantly, account for individual variation in risk and the possibility that one's experience of risk may change across time. The results indicate the usefulness of this approach to risk in understanding changes in social spending preferences.

In light of important political events that go beyond the nation state (e.g., migration, climate change, and the coronavirus pandemic), domestic politicians are increasingly pressured to scrutinize and speak out on European policy-making. This creates a potential trade-off between allocating effort to domestic and supranational affairs, respectively. We examine how citizens perceive legislator involvement in European Union (EU) politics with a pre-registered conjoint experiment in Germany. Our results show that Members of Parliament (MPs) are not disadvantaged when allocating effort to European affairs as compared to local and national affairs. In addition, voters tend to prefer MPs who engage in EU policy reform over those who do not. As demand for legislator involvement in European politics is on the rise, we provide empirical evidence that MPs can fulfill this demand without being disadvantaged by the electorate.

Firms in the USA rely on highly skilled immigrants, particularly in the science and engineering sectors. Yet, the recent politics of immigration marks a substantial change to US immigration policy. We implement a conjoint experiment that isolates the causal effect of nativist, anti-immigrant, pronouncements on where skilled potential-migrants choose to immigrate to. While these policies have a significantly negative effect on the destination choices of Chilean and UK student subjects, they have little effect on the choices of Indian and Chinese student subjects. These results are confirmed through an unobtrusive test of subjects’ general immigration destination preferences. Moreover, there is some evidence that the negative effect of these nativist policies are particularly salient for those who self-identify with the Left.