Abstract: Although Europe has experienced unprecedented numbers of refugee arrivals since 2015, there exists almost no causal evidence regarding the impact of the refugee crisis on natives’ attitudes, policy preferences, or political engagement. We provide evidence from a natural experiment in the Aegean Sea, where Greek islands close to the Turkish coast experienced a sudden and massive increase in refugee arrivals while similar islands slightly farther away did not. Leveraging distance as an instrument for between-island variation in exposure to the refugee crisis allows us to obtain causal estimates of its impact. In our targeted survey of 2,070 islands residents, we find that immediate exposure to large-scale refugee arrivals induces sizable and lasting increases in natives' hostility toward refugee, immigrant and Muslim minorities; support for restrictive asylum and immigration policies; and political engagement to effect such policies.

Abstract: Recent years have seen a surge of politicians campaigning on policies that aim to deter asylum applicants. We present a game-theoretic model in which foreign nationals consider applying for asylum and bureaucrats decide their case if they apply. We show that while policies that make the asylum application less attractive decrease the probability that foreign nationals apply, they also endogenously raise the credibility of applicants’ claims to political persecution and, therefore, may not decrease the number of admitted refugees. Investigating how these competing effects shape asylum policy-making, we show how policy choices depend on bureaucrats’ leniency and politicians’ objectives. Our analysis speaks to the causes of restrictive asylum policies and their limited effectiveness in reducing immigration.

Abstract: Governments across Europe are restricting labor market access for asylum seekers, with often detrimental consequences for the livelihood of refugees and the public finances of host societies. This raises the following questions: Are the benefits of restrictive immigrant policies political rather than economic, and do incumbent governments receive an electoral edge by implementing such policies? In this paper, we exploit a natural experiment in Germany, where, following a deterministic assignment rule, certain regions were exempted from a reform that liberalized labor market access for refugees. Using difference-in-difference and regression discontinuity designs, we find that the incumbent vote share sharply increases in regions with restrictive labor market access. Exploring different mechanisms, our results suggest that this effect is primarily driven by differential candidate entry: In regions with restrictive labor market access, fewer conservative and populist challengers are running for office. Our results suggest that not only do immigration inflows have direct electoral repercussions, but immigrant policies do also.

Abstract: While far-right parties profit electorally from rising immigration, we know very little about how increases in immigration mobilize opposition outside the electoral arena. Using fine-grained, classified data from the Federal Criminal Office in Germany, we estimate the causal effect of a sizable increase in asylum-seekers in a community on the probability of xenophobic hate crimes. Exploiting county-level quota regimes governing the allocation of asylum-seekers in Germany, we find that when immigration levels rise nationally, an increase in asylum-seeker arrivals in a community causes an increase in xenophobic hate crimes. We also document that these crimes are directed against asylum-seekers and not other non-natives, which suggests that they are instrumental actions intended to dispel and deter asylum-seekers from local communities.

Abstract: Amidst the Ukrainian displacement crisis, private hosting of refugees in Europe has surged, yet its impact on integration remains understudied. This research examines the short- to medium-term effects of private hosting on Ukrainian refugee integration in Germany. Using data from one of the largest non-profit platforms that matches private hosts with refugees, we compare the multidimensional integration outcomes of refugees who were matched with private hosts to those of observably similar refugees who applied for private hosting but were not matched (N = 1,700).Our findings show significant improvements in the social, psychological, and navigational integration of privately hosted refugees, with no discernible effects on linguistic, economic, or political integration. This study provides causal evidence on the effectiveness of private hosting in enhancing refugee integration, underscoring its potential to complement traditional public asylum reception and housing systems, and to harness civil society engagement for refugee integration during humanitarian crises.

Abstract: Given the global displacement crisis, the integration of refugees has emerged as a critical policy issue for many host countries. A key challenge involves supporting refugees in learning the language of their host country. While several European nations have instituted publicly funded language training for asylum seekers and refugees soon after their arrival, evidence on the efficacy of these early language programmes in promoting economic integration remains limited. This study examines the impact of a pioneering, large-scale ad hoc programme introduced by German policymakers, which provided basic language training to over 230,000 refugees arriving in 2015–2016. Utilizing register data on the population of asylum seekers and exploiting a cut-off date in programme eligibility, we assess the programme’s effectiveness using a regression discontinuity design. Our findings reveal no discernible effect on refugee employment over the subsequent 2 years. To explore whether language programmes are generally ineffective during refugee crises, we contrast these results with the impacts of a more comprehensive, preexisting, yet smaller-scale programme. Using a variety of difference-in-differences estimators, we find that this programme considerably increased refugee employment. These contrasting findings offer important insights for policymakers on designing effective language training programmes for refugees.

Abstract: The welfare magnet hypothesis holds that immigrants are likely to relocate to regions with generous welfare benefits. Although this assumption has motivated extensive reforms to immigration policy and social programs, the empirical evidence remains contested. In this study, we assess detailed administrative records from Switzerland covering the full population of social assistance recipients between 2005 and 2015. By leveraging local variations in cash transfers and exogenous shocks to benefit levels, we identify how benefits shape intracountry residential decisions. We find limited evidence that immigrants systematically move to localities with higher benefits. The lack of significant welfare migration within a context characterized by high variance in benefits and low barriers to movement suggests that the prevalence of this phenomenon may be overstated. These findings have important implications in the European setting where subnational governments often possess discretion over welfare and parties frequently mobilize voters around the issue of “benefit tourism.

Abstract: Many European countries impose employment bans that prevent asylum seekers from entering the local labor market for a certain waiting period upon arrival. We provide evidence on the long-term effects of these employment bans on the subsequent economic integration of refugees. We leverage a natural experiment in Germany, where a court ruling prompted a reduction in the length of the employment ban. We find that, 5 years after the waiting period was reduced, employment rates were about 20 percentage points lower for refugees who, upon arrival, had to wait for an additional 7 months before they were allowed to enter the labor market. It took up to 10 years for this employment gap to disappear. Our findings suggest that longer employment bans considerably slowed down the economic integration of refugees and reduced their motivation to integrate early on after arrival. A marginal social cost analysis for the study sample suggests that this employment ban cost German taxpayers about 40 million euros per year, on average, in terms of welfare expenditures and foregone tax revenues from unemployed refugees.

Abstract: An extensive literature links the rise of populist radical right (PRR) parties to immigration. We argue that another demographic trend is also significant: emigration. The departure of citizens due to internal and international emigration is a major phenomenon affecting elections via two complementary mechanisms. Emigration alters the composition of electorates, but also changes the preferences of the left behind. Empirically, we establish a positive correlation between PRR vote shares and net-migration loss at the subnational level across Europe. A more fine-grained panel analysis of precincts in Sweden demonstrates that the departure of citizens raises PRR vote shares in places of emigration and that the Social Democrats are the principal losers from emigration. Elite interviews and newspaper analyses explore how emigration produces material and psychological grievances on which populists capitalize and that established parties do not effectively address. Emigration and the frustrations it generates emerge as important sources of populist success.

Abstract: How do economic opportunities abroad affect citizens’ ability to exit an authoritarian regime? This article theorizes the conditions under which authoritarian leaders will perceive emigration as a threat and use imprisonment instead of other types of anti-emigration measures to prevent mass emigration. Using data from communist East Germany's secret prisoner database that we reassembled based on archival material, the authors show that as economic opportunities in West Germany increased, the number of East German exit prisoners – political prisoners arrested for attempting to cross the border illegally – also rose. The study's causal identification strategy exploits occupation-specific differences in the changing economic opportunities between East and West Germany. Using differential access to West German television, it also sheds light on the informational mechanism underlying the main finding; cross-national data are leveraged to present evidence of the external validity of the estimates. The results highlight how global economic disparities affect politics within authoritarian regimes.

Abstract: Political scientists have long been interested in the persistent effects of history on contemporary behavior and attitudes. To estimate legacy effects, studies often compare people living in places that were historically exposed to some event and those that were not. Using principal stratification, we provide a formal framework to analyze how migration limits our ability to learn about the persistent effects of history from observed differences between historically exposed and unexposed places. We state the necessary assumptions about movement behavior to causally identify legacy effects. We highlight that these assumptions are strong; therefore, we recommend that legacy studies circumvent bias by collecting data on people's place of residence at the exposure time. Reexamining a study on the persistent effects of U.S. civil rights protests, we show that observed attitudinal differences between residents and nonresidents of historic protest sites are more likely due to migration rather than attitudinal change.

Abstract: Instrumental variable (IV) estimation is an essential method for applied researchers across the social sciences who analyze randomized control trials marred by non-compliance or leverage partially exogenous treatment variation in observational studies. The potential outcomes framework is a popular model to motivate the assumptions underlying the identification of the local average treatment effect (LATE), and to stratify the sample into compliers, always-takers, and never-takers. However, applied research has thus far payed little attention to the characteristics of compliers and non-compliers. Yet profiling compliers and non-compliers is necessary to understand what subpopulation the researcher is making inferences about, and an important first step to discuss the external validity (or lack thereof) of the LATE estimated for compliers. In this letter, we discuss the assumptions necessary for profiling, which are weaker than the assumptions needed to identify the LATE if the instrument is randomly assigned. We introduce a simple and general method to characterize compliers, always- and never-takers in terms of their covariates, and easy-to-use software in R and STATA that implements our estimator. We hope that our method and software facilitate the profiling of compliers and non-compliers as standard practice accompanying any IV analysis.

Abstract: Instrumental variable (IV) analyses are becoming common in health services research and epidemiology. IV analyses can be used both to analyze randomized trials with noncompliance and as a form of natural experiment. In these analyses, investigators often adopt a monotonicity assumption, which implies that the relevant effect only applies to a subset of the study population known as compliers. Since the estimated effect is not the average treatment effect of the study population, it is important to compare the characteristics of compliers and non-compliers. Profiling compliers and non-compliers is necessary to understand what subpopulation the researcher is making inferences about, and an important first step in evaluating the external validity (or lack thereof) of the IV estimate for compliers. Here, we discuss the assumptions necessary for profiling, which are weaker than the assumptions necessary for identifying the local average treatment effect if the instrument is randomly assigned. We then outline a simple and general method to characterize compliers and noncompliers using baseline covariates. Next, we extend current methods by deriving standard errors for these estimates. We demonstrate these methods using an IV known as tendency to operate (TTO) from health services research.

Abstract: Dyadic data from UNHCR on the size of the global refugee population are widely used. However, for a large fraction of the refugee population, these data provide no information about refugees' country of origin, which contributes to a high nominal rate of unreported values in the data. In this article, I demonstrate that two imputation approaches outperform the current standard approach, which assumes that all unreported values are zero. The first approach interpolates the unreported values, while the second predicts them based on trends observed in other dyads. Drawing on different types of information, the two approaches' performance is similar. Replicating a published study on the effect of refugee crises on international war and peace, I demonstrate how both approaches strengthen the author's findings and help to minimize the risk of a null finding.

Abstract: Imputing missing values is an important preprocessing step in data analysis, but the literature offers little guidance on how to choose between imputation models. This letter suggests adopting the imputation model that generates a density of imputed values most similar to those of the observed values for an incomplete variable after balancing all other covariates. We recommend stable balancing weights as a practical approach to balance covariates whose distribution is expected to differ if the values are not missing completely at random. After balancing, discrepancy statistics can be used to compare the density of imputed and observed values. We illustrate the application of the suggested approach using simulated and real-world survey data from the American National Election Study, comparing popular imputation approaches including random forests, hot-deck, predictive mean matching, and multivariate normal imputation. An R package implementing the suggested approach accompanies this letter.

Abstract: 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.

Abstract: This article presents a new method for estimating positions of political parties across country- and time-specific contexts by introducing a latent variable model for manifesto data. We estimate latent positions and exploit bridge observations to make the scales comparable. We also incorporate expert survey data as prior information in the estimation process to avoid ex post facto interpretation of the latent space. To illustrate the empirical contribution of our method, we estimate the left-right positions of 388 parties competing in 238 elections across twenty-five countries and over sixty years. Compared to the puzzling volatility of existing estimates, we find that parties more modestly change their left-right positions over time. We also show that estimates without country- and time-specific bias parameters risk serious, systematic bias in about two-thirds of our data. This suggests that researchers should carefully consider the comparability of party positions across countries and/or time.

Abstract: RILE estimates based on party manifesto data suggest that political parties leapfrog on the left-right scale over time. This implausible finding has raised questions about the efficacy not only of RILE for estimating left-right positions but of coded party manifestos for political science research in general. The recently developed Manifesto Common Space Scores (MCSS), which reduce leapfrogging by accounting for the election-specific character of party manifestos, provide alternative estimates for parties left/right-positions, but little is known about their validity. This study shows that MCSS estimates exhibit greater convergent validity relative to RILE estimates when compared to other measures of parties left/right-positions. It also finds that MCSS has greater construct validity relative to RILE estimates in two prominent cases (Greece and Italy). Overall, the findings underscore the election-specific character of party manifestos and demonstrate that MCSS is a useful alternative measure of parties’ left-right positions.

Abstract: Comparative studies report the rise of left- and right-wing Eurosceptic parties that have transformed national party competition in Europe toward an inverted U-shaped configuration: Peripheral parties at the left and right of the party spectrum oppose while centrist parties support several features of European integration. To describe the tempo and timing of this transformation and the heterogeneity across countries, we develop a Bayesian finite mixture factor analysis that estimates the election-specific probability of a one-dimensional left/right versus a two-dimensional inverted U-shaped national party configuration. The results show a general trend toward 'U' but with significant variation across countries and time, including cases with a reversal of this trend.

Abstract: Authoritarian rulers fend off revolutions by stimulating the economy. However, expanding the economy can also increase environmental pollution. If citizens value clean air and water, worsening pollution has the potential to galvanize large segments of the society against the regime—which increases the risk of a revolution. While the literature has documented how concerns over the environment upend politics in democracies, we know relatively little about the effects of these concerns in authoritarian regimes. We analyze environmental pollution as an overlooked threat to authoritarian rulers. Using unique data from Communist East Germany and exploiting variation in thermal inversions to instrument for pollution levels, we find that pollution causes both individual and collective expressions of regime dissatisfaction. Our findings suggest that rulers face a trade-off between growing the economy and worsening pollution.

Abstract: The spread of COVID-19 has prompted governments to implement restrictions to public life and the economy (broadly, lockdown policies). We evaluate the short- and medium-term impacts of lockdown policies on civic attitudes relevant for the health of democracy. Using survey data collected daily between March and May 2020 in the United States and four European countries from 27,317 respondents and a difference-in-differences design, we document that lockdown policies increase authoritarian values and, to a lesser degree, support for autocracy. We find no effects on satisfaction with democracy and the government, out-group hostility, and generalized trust. Additional analyses reveal that the effects persist for at least seven weeks, that these effects persist after the lifting of lockdowns, and that economic support packages have limited ability to alleviate these effects. We discuss the implications of our findings for how governments might need to accompany lockdowns with measures that strengthen civic culture.