We examine the causal effect of legislative activity on private benefits, which have been largely neglected by previous research in legislative studies. By relying on a natural experiment in New Zealand, where randomly selected Members of Parliament (MPs) are given the opportunity to propose legislation, we find evidence for a causal relation between proposing a (successful) bill and the private benefits MPs receive, in terms of gifts and payments for services. We conclude that the allocation of private benefits depends on legislative performance.

While presidents frequently create new policies through unilateral power, empirical scholarship generally focuses on executive orders and overlooks other categories of directives. We introduce data on more than 50,000 unilateral directives issued between 1877 and 2020 and use machine learning techniques to characterize their substantive importance and issue areas. Our measures reveal significant increases in unilateral activity over time, driven largely by increases in foreign affairs and through the substitution of memoranda for executive orders. We use our measures to formally evaluate the historical development of the unilateral presidency and reassess theoretical claims about public opinion and unilateral power. Our research provides new evidence about variation in the use of presidential authority and opens new avenues for empirical inquiry.

Across a series of experiments, I show that racial threat from a stereotypically nonthreatening racial minority group, Asian Americans, has a direct impact on white Americans' views of discrimination toward the group. When white Americans learn the group is growing, they feel a distinct racial threat which decreases support for the idea that Asian Americans experience discrimination while simultaneously increasing support for policy which actively discriminates against Asian Americans. I show this concept to be portable over context, examining support for discriminatory policy toward Asians in education policy and COVID-19 policy. I conclude by discussing the implications for how racial threat can drive more racial conflict while simultaneously decreasing the perception that this discrimination is occurring.

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.

When analyzing data, researchers are often less interested in the parameters of statistical models than in functions of these parameters such as predicted values. Here we show that Bayesian simulation with Markov-Chain Monte Carlo tools makes it easy to compute these quantities of interest with their uncertainty. We illustrate how to produce customary and relatively new quantities of interest such as variable importance ranking, posterior predictive data, difficult marginal effects, and model comparison statistics to allow researchers to report more informative results.

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.

Within research on the political influence that social network members exert on one another, some studies rely on information obtained directly from different members in the network separately (self-reported measures), while others rely on information obtained from one key informant within the social network (measures based on perception). We investigate the difference between these self-reported and perceived measures by analyzing the correspondence of voting intentions within the family. On the one hand, we examine this correspondence using information obtained from only one family member. On the other hand, we use the self-reported measures obtained from all family members separately. We use data from the Parent-Child Socialization Study (PCSS), a survey conducted among 2,085 mothers, fathers and children in the Flemish region of Belgium (2012). Our analyses suggest that using perceptual measures could lead researchers to different or even opposite conclusions than using self-reported measures from all individual respondents.

How well do existing survey instruments differentiate between opinions that affect individual behavior and opinions that don't? To answer this question, we randomly assigned U.S. respondents to one of three survey instruments: Likert items (Likert), Likert items followed by personal importance items (Likert+) and Quadratic Voting for Survey Research (QVSR), which gives respondents a fixed budget to buy “favor” or “oppose” votes, with the price for each vote increasing quadratically. We find that, relative to Likert, both Likert+ and QVSR better identify people who care enough about an issue to act in opinion-congruent ways, with QVSR offering the most consistent improvement overall. Building on these results, we show how conclusions regarding the relationship between policy opinions and self-interest can differ across measurement strategies.

Increasing partisan polarization has characterized American politics for decades. On January 6, 2021, both Republicans and Democrats in Congress expressed their horror at the violent invasion of the US Capitol, leading to the popular perception—emphasized by media accounts—that the attack generated a rare moment of bipartisan unity. We argue that while members of both parties condemned the attack, a marked partisan divide characterized their messaging even as events unfolded. We analyze all 1861 tweets by members of Congress on January 6th and find that Republicans were significantly more likely to characterize the invasion as a protest grown out of hand, while Democrats described it as an attack on democracy. The results strongly indicate that partisan polarization was alive and well on January 6th and may help to account for Republicans’ shift toward normatively positive portrayals of the day in subsequent months.

In recent years, anti-refugee hate crimes have soared across Europe. We know this violence has spread fear among refugees, but we know less about its effects on the non-refugee population. This is an oversight, as research suggests political violence often has effects on the broader population. Those effects can range from increased solidarity with the targets of the violence to reduced pro-social behavior and less support for the targets of the violence. In this research note, we examine the effects of exposure to anti-refugee hate crimes in Germany. Our results suggest no direct effect of exposure to anti-refugee hate crimes on support for refugees. These results have several implications for our understanding of political divides over refugees in Europe.

This study contributes to understanding mainstream parties' room for maneuver in the immigration domain by exploring the impact of moralization as a rhetorical strategy. Research has found anti-immigrant messages to be more effective than pro-immigrant messages in shaping public opinion. However, a pre-registered survey experiment with Danish respondents reveals that moral rhetoric enhances policy support for pro-immigrant communication, rendering it as effective as anti-immigrant messages. Partisan-motivated reasoning influences reactions to all messages except the non-moral anti-immigrant message, suggesting that when appealing to out-party supporters, mainstream parties still meet least resistance with an exclusive platform.

When working with panel data, many researchers wish to estimate the direct effects of time-varying factors on future outcomes. However, when a baseline treatment affects both the confounders of further stages of the treatment and the outcome, the estimation of controlled direct effects (CDEs) using traditional regression methods faces a bias trade-off between confounding bias and post-treatment control. Drawing on research from the field of epidemiology, in this article I present a marginal structural modeling (MSM) approach that allows scholars to generate unbiased estimates of CDEs. Further, I detail the characteristics and implementation of MSMs, compare the performance of this approach under different conditions, and discuss and assess practical challenges when conducting them. After presenting the method, I apply MSMs to estimate the effect of wealth in childhood on political participation, highlighting the improvement in terms of bias relative to traditional regression models. The analysis shows that MSMs improve our understanding of causal mechanisms especially when dealing with multi-categorical time-varying treatments and non-continuous outcomes.

The Big-Issue Model predicts election outcomes based on voters’ perceptions of candidates’ ability to handle the most important issue. It provided accurate forecasts of the 2012 US presidential election. The results demonstrate the model's usefulness if one issue clearly dominates the campaign, such as the state of the economy in the 2012 election. It is also particularly valuable if economic fundamentals disagree, a situation in which forecasts from traditional political economy models suggest high uncertainty. The model provides immediate feedback to political candidates and parties on the success of their campaign and can advise them on which issues to assign the highest priority.

This article puts forward an explanation of the resilience of corruption by arguing that this phenomenon offers net gains to a much larger share of the population than just corrupt government officials. Corruption is modeled as a solution to an allocation problem for a generic government good G. The defining features of this solution are the existence of a market for G when it is not supposed to exist, and the fact that, in that market, contracts cannot be enforced by an outside agent and transactions are usually secret. Corruption redistributes welfare toward ‘insiders’ who share some natural connection to the government and to other insiders. Corruption also redistributes welfare toward those who are skilled at imposing negative externalities.

Ethnic movements continue to challenge state governments globally, with many ethnic conflicts revolving around the status of groups’ territories. Yet, politically mobilized ethnic groups vary considerably in their territorial demands: some press for increased autonomy or even outright secession, while others do not make such demands at all and prefer integration in the existing state. What explains this divergence in ethnic group demands with respect to the group's territorial status? We argue that the expected benefits of ethno-regional autonomy or secession compared to integration in a centralized state differ across distinct segments within the group as a function of three structural factors: heterogeneity in the group's income sources, cultural divisions, and territorial fragmentation, leading to disagreement over self-determination demands between different political organizations representing the same ethnic group. We test our argument using an expanded version of the Ethnic Power Relations–Organizations (EPR-O) dataset. Our pre-registered study finds support for one of our hypotheses: heterogeneity in groups’ income sources increases disagreement over self-determination demands. This finding sheds new light on the structural sources of internal divisions within ethno-political movements.

Governments can grant political concessions to induce quasi-voluntary compliance with taxation, yet empirical evidence probing the taxation–representation connection remains inconclusive. We contend that this association remains valid but it is primarily confined to business elites in nondemocratic regimes because the same wealth that exposes them to state predation also incentivizes them to endorse tax policies that offer greater political representation. We test our argument by evaluating preferences for hypothetical tax reforms in separate samples of business elites and ordinary citizens in China. We find that business elites show stronger preference than nonelites for tax policies that include advances in political representation. We explore various mechanisms for our results and find support for government credibility, tax ownership, and tax salience considerations.

What allows autocratic political elites to coordinate with each other and check dictators? Earlier work assumes that elite coordination becomes easier as dictators share more power. I argue that, even when power-sharing is pervasive, a lack of cohesiveness can rob regime members of their influence over dictators. Conflicting interests can leave seemingly powerful elites unable to agree on when or how to challenge the dictator. I develop a measure of elite collective action based on this framework. It documents not only how much power elites have, but also the obstacles they would need to resolve to work together. In doing so, it better describes the relationship between autocrats and their ruling coalition, and its added nuance allows it to recover findings that current measures miss. By paying closer attention to the cohesion of autocratic elites, this paper explains why some dictators can rule tyrannically without retribution, and why weaker elites can still constrain powerful autocrats.

A growing body of evidence indicates the public is less committed to democracy than conventional wisdom long held. One possibility is that many in the public have internalized the norm that democracy is “good” but that such support is not firmly held. An implication of this reasoning is that because there is an expectation to express support for democracy, responses will be influenced by the presence of an interviewer due to social desirability effects. In this note, we examine the 2012 and 2016 American National Election Studies—in each year, a portion of respondents were interviewed via the internet while others were interviewed face-to-face. We identify a politically relevant difference between the two survey modes: those interviewed face-to-face express greater satisfaction with democracy. Indeed, the difference we identify is similar in magnitude to the difference typically observed between electoral winners and electoral losers. Our result is robust to different measurement and estimation strategies. While levels of satisfaction are influenced by the presence of an interviewer, a followup analysis indicates that the relationship between satisfaction and winner–loser status is similar across modes.