Although attention to populism is ever-increasing, the concept remains contested. This paper provides a comprehensive overview of populism research and identifies tendencies to a conflation of host ideologies and populism in political science through a two-step analysis. First, we conduct a quantitative review of 884 abstracts from 2004 to 2018 using text-as-data methods. We show that scholars sit at “separate tables,” divided by geographical foci, methods, and host ideologies. Next, our qualitative analysis of 50 articles finds a common conflation of populism with other ideologies, resulting in the analytical neglect of the former. We, therefore, urge researchers to properly distinguish populism from “what it travels with” and engage more strongly with the dynamic interlinkages between thin and thick ideologies.

Decades of research has debated whether women first need to reach a “critical mass” in the legislature before they can effectively influence legislative outcomes. This study contributes to the debate using supervised tree-based machine learning to study the relationship between increasing variation in women's legislative representation and the allocation of government expenditures in three policy areas: education, healthcare, and defense. We find that women's representation predicts spending in all three areas. We also find evidence of critical mass effects as the relationships between women's representation and government spending are nonlinear. However, beyond critical mass, our research points to a potential critical mass interval or critical limit point in women's representation. We offer guidance on how these results can inform future research using standard parametric models.

The expectation that voters behave rationally has been challenged through studies suggesting that “irrelevant events” like natural disasters and sports results change voting behavior. We test the effect of irrelevant events by matching candidate-level election results from Irish general (1922–2020) and local elections (1942–2019) with games in the men's Gaelic football and hurling championships, the most popular sports in Ireland. Although Irish citizens care deeply about sports, we fail to find any relationship between match results and support for incumbents or politicians of government parties. These findings hold when applying an “unexpected event during survey design” to two representative surveys. Our results contribute to the literature on political accountability and point to conditional effects of irrelevant events.

How well do citizens understand the associations between social groups and political divisions in their societies? Previous research has indicated systematic biases in how the demographic composition of party supporters are perceived, but this need not imply that citizens misperceive the likely voting behavior of specific individuals. We report results from two experiments where subjects were provided with randomly selected demographic profiles of respondents to the 2017 British Election Study (BES) and then asked to assess either (1) which party that individual was likely to have voted for in the 2017 UK election or (2) whether that individual was likely to have voted Leave or Remain in the 2016 UK referendum on EU membership. We find that, despite substantial overconfidence in individual responses, on average citizens’ guesses broadly reflect the actual distribution of groups supporting the parties and referendum positions.

How do rebels choose among available tactics during civil war? How do they substitute one tactic for another? Although previous studies address these questions, they narrowly focus on the presence or absence of substitution. Differentiating the varieties of substitution, however, is critical. How rebels respond to their tactical environment—including weather conditions—depends on the type of substitution. I formally derive three types of substitution and test them by exploiting weather-induced exogenous variation in rebels' tactical costs for ground and marine violent activities. The analysis of daily panel data in 31 coastal conflict countries indicates that rebels substitute violent ground activities for maritime piracy but not vice versa. This asymmetry cannot be explained without differentiating substitution types.

There has been a proliferation of research with human participants in violent contexts over the past ten years. Adhering to commonly held ethical principles such as beneficence, justice, and respect for persons is particularly important and challenging in research on violence. This letter argues that practices around research ethics in violent contexts should be reported more transparently in research outputs, and should be seen as a subset of research methods. We offer practical suggestions and empirical evidence from both within and outside of political science around risk assessments, mitigating the risk of distress and negative psychological outcomes, informed consent, and monitoring the incidence of potential harms. An analysis of published research on violence involving human participants from 2008 to 2019 shows that only a small proportion of current publications include any mention of these important dimensions of research ethics.

It is fairly well-known that proper time series analysis requires that estimated equations be balanced. Numerous scholars mistake this to mean that one cannot mix orders of integration. Previous studies have clarified the distinction between equation balance and having different orders of integration, and shown that mixing orders of integration does not increase the risk of type I error when using the general error correction/autoregressive distributed lag (GECM/ADL) models, that is, so long as equations are balanced (and other modeling assumptions are met). This paper builds on that research to assess the consequences for type II error when employing those models. Specifically, we consider cases where a true relationship exists, the left- and right-hand sides of the equation mix orders of integration, and the equation still is balanced. Using the asymptotic case, we find that the different orders of integration do not preclude identification of the true relationship using the GECM/ADL. We then highlight that estimation is trickier in practice, over finite time, as data sometimes do not reveal the underlying process. But, simulations show that even in these cases, researchers will typically draw accurate inferences as long as they select their models based on the observed characteristics of the data and test to be sure that standard model assumptions are met. We conclude by considering the implications for researchers analyzing or conducting simulations with time series data.

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.

Many, especially low-skilled workers, blame globalization for their economic woes. Robots and machines, which have led to job market polarization, rising income inequality, and labor displacement, are often viewed much more forgivingly. This paper argues that citizens have a tendency to misattribute blame for economic dislocations toward immigrants and workers abroad, while discounting the effects of technology. Using the 2016 American National Elections Studies, a nationally representative survey, I show that workers facing higher risks of automation are more likely to oppose free trade agreements and favor immigration restrictions, even controlling for standard explanations for these attitudes. Although pocket-book concerns do influence attitudes toward globalization, this study calls into question the standard assumption that individuals understand and can correctly identify the sources of their economic anxieties. Accelerated automation may have intensified attempts to resist globalization.

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.

Twitter is a prominent communication tool for politicians with two potential uses: as a “substitute” channel to circumvent constraints from other political arenas, or as an “amplifier” that reinforces party messages. Using a novel dataset containing tweets and parliamentary speeches by members of parliament (MPs) in seven countries, we estimate politicians’ positions and intra-party dissent on European integration. We find that MPs’ sentiment about Europe on Twitter is a valid measure of their party's position, while also uncovering intra-party disagreements. Our results suggest that most MPs amplify the partisan message, but MPs who participate less in parliamentary debate tend to have larger differences with their party on Twitter. Social media thus can free politicians from their party's grip.

Security forces are one of the main targets of political violence. This paper examines the effect of their casualties on electoral outcomes. Between two general elections in 2015, Turkey experienced a series of attacks that killed 153 members of its security forces. Based on the as-if random assignment of their funerals across the country, I estimate that government vote share increases in the funeral places of security force terror victims. However, in the localities with recurring funerals, it decreases by a similar percentage. These non-linear changes provide strong evidence for the rally theory.

A robust economy is assumed to bolster leaders' standing. This ignores how benefits of growth are distributed. Extending the partisan models of economic voting, we theorize executives are more likely rewarded when gains from growth go to their constituents. Analyses of presidential approval in 18 Latin American countries support our pro-constituency model of accountability. When economic inequality is high, growth concentrates among the rich, and approval of right-of-center presidents is higher. Leftist presidents benefit from growth when gains are more equally distributed. Further analyses show growth and inequality inform perceptions of personal finances differently based on wealth, providing a micro-mechanism behind the aggregate findings. Study results imply that the economy is not purely a valence issue, but also a position issue.

Do agencies implement the president's particularistic goals uniformly? This paper clarifies the presidential particularism literature by explicitly considering the mechanism through which the president pursues their policy goals: executive agencies. The constellation of bureaucratic agencies responsible for allocating grants plays a key role in facilitating or frustrating presidential policy priorities. Using a dataset of 21 agencies over 14 years, I find that only agencies ideologically proximate to the president engage in particularism benefiting the president. I find no evidence that politicization influences agency implementation of particularism. Critically, the moderating effect of the bureaucracy on particularism only occurs for distributive programs over which agencies have discretion. When disbursing formula grants written by Congress but administered by the bureaucracy with little or no discretion, ideological distance between agencies and presidents has no effect on particularism.

A flurry of current interest in time series has focused on clarifying equation balance, fractional integration, and cointegration testing. Despite this, a number of recent suggestions may continue to lead scholars toward incorrect inferences. In this comment, I investigate the likelihood of drawing both correct and incorrect inferences under a variety of stationary and non-stationary data-generating processes. I extend previous work in this area by focusing on both short- and long-run effects using several popular model specifications. Given these findings, I conclude by offering a variety of recommendations to practitioners about how they can best specify their model.

The literature on autocracies has argued that repression of protest is either a result of the political environment in which protest occurs, or depends on particular characteristics of the protest events themselves. We argue that the interaction of both matters. Authoritarian regimes vary in how they legitimize their rule, and they should be particularly thin-skinned if protesters challenge the basis of their legitimacy. Using event-level data on mass mobilization in autocracies between 2003 and 2015, we use text classification methods to extract protest issues from newspaper reports. Our analysis shows that dictators are more likely to repress protest against incumbents when they claim legitimacy based on the person of the leader. Overall, our study shows that protest issues are not universal in triggering repression; rather, they need to be considered together with the political context in which they are raised.

Individuals' attitudes about gender roles have been shown to be associated with a wide range of political outcomes. It is therefore crucial to better understand what shapes these attitudes. This note takes advantage of a randomized survey experiment embedded in the 2018 wave of the European Social Survey (ESS) to investigate how differences in education levels between partners influence the “gender childcare bias”—the extent to which individuals disapprove more of women working full time with children under three than men. Although male and female respondents exhibit an equally strong gender childcare bias on average, we find clear-cut evidence that the bias varies asymmetrically across the household education gap for women and men. In particular, positive household education gaps lead to a smaller gender childcare bias for female respondents, whereas the opposite holds for male respondents. Our findings are more in line with a resource-bargaining approach than a gender identity approach to the formation of gender role attitudes.

In the absence of a complete voting record, decision records are an important data source to analyze committee decision-making in various institutions. Despite the ubiquity of decision records, we know surprisingly little about how to analyze them. This paper highlights the costs in terms of bias, inefficiency, or inestimable effects when using decision instead of voting records and introduces a Bayesian structural model for the analysis of decision-record data. I construct an exact likelihood function that can be tailored to many institutional contexts, discuss identification, and present a Gibbs sampler on the data-augmented posterior density. I illustrate the application of the model using data from US state supreme court abortion decisions and UN Security Council deployment decisions.

In small samples, maximum likelihood (ML) estimates of logit model coefficients have substantial bias away from zero. As a solution, we remind political scientists of Firth's (1993, Biometrika, 80, 27–38) penalized maximum likelihood (PML) estimator. Prior research has described and used PML, especially in the context of separation, but its small sample properties remain under-appreciated. The PML estimator eliminates most of the bias and, perhaps more importantly, greatly reduces the variance of the usual ML estimator. Thus, researchers do not face a bias-variance tradeoff when choosing between the ML and PML estimators—the PML estimator has a smaller bias and a smaller variance. We use Monte Carlo simulations and a re-analysis of George and Epstein (1992, American Political Science Review, 86, 323–337) to show that the PML estimator offers a substantial improvement in small samples (e.g., 50 observations) and noticeable improvement even in larger samples (e.g., 1000 observations).

The COVID-19 pandemic is an unparalleled global crisis. Yet, despite the grave adversity faced by citizens, incumbents around the world experienced a boost in popularity during the onset of the outbreak. In this study, we examine how the response to the COVID-19 outbreak in one country affected incumbent support in other countries. Specifically, we leverage the fact that the first country-wide lockdown on European soil, in Italy on 9 March 2020, happened during the fieldwork of surveys conducted in four other European countries, France, Germany, Poland and Spain. This allows us to examine how an event abroad that alerted citizens to an imminent crisis—prior to a similar domestic government response—influenced incumbent support. Our results indicate a crisis signal effect of Italy's COVID-19 lockdown, as support for the incumbent increased domestically in other European countries after the lockdown. Importantly, these findings suggest that incumbents can benefit from a crisis unfolding in other countries, even when their own performance in response to the same crisis is not yet fully clear. They illustrate the importance of developments abroad for incumbent approval and the difficulty facing citizens seeking to disentangle performance signals from exogenous shocks.