Hostility toward Immigrants

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.

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.

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.

Immigrant Integration

The successful integration of refugees into the local economy has become a major policy challenge for European countries in light of the global displacement crisis. One of the key challenges is to support refugees to learn the language of their host country. Several European countries provide publicly funded language training for asylum seekers and refugees shortly after arrival, but there is scant evidence on the impact of these early training programs on subsequent economic integration. We examine the impact of two such programs policymakers in Germany used in response to the large increase in the number of asylum seekers in 2015: a rapidly developed, ad hoc program that offered basic language training to over 230,000 newly arrived refugees and a smaller, preexisting program that offered refugees comprehensive language training. We leverage register data on the entire population of asylum seekers who arrived in 2015-2016 and exploit program eligibility and temporal participation variation using regression discontinuity and difference-in-differences designs to evaluate and contrast the effectiveness of both programs. We find that the ad hoc program had no discernible effect on refugee employment over the following 24 months. In contrast, the more comprehensive, preexisting program increased refugee employment by about 13 percentage points. These findings have implications for how policymakers can design effective language training programs to foster the integration of refugees.

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.

Migration Choice

How do economic opportunities abroad affect citizens’ ability to exit an authoritarian regime? We theorize the conditions under which authoritarian leaders will perceive emigration as a threat and will 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, we show that as economic opportunities in West Germany increased, the number of East German exit prisoners—political prisoners arrested for attempting to illegally cross the border illegally—also increased. Our causal identification strategy exploits occupation-specific differences in the changing economic opportunities between East and West Germany. Using differential access to West German television, we also shed light on the informational mechanism underlying our main finding, and we leverage cross-national data to present evidence for the external validity of our estimates. Our results highlight how global economic interdependence affects politics within authoritarian regimes.

To what extent does the generosity of local welfare benefits shape the residential choices of immigrants? From a theoretical perspective the expectation is well-established: as rational actors, migrants should relocate to municipalities with higher benefits, given sufficient information and low transaction costs. However the empirical evidence is mixed, largely because existing approaches lack individual-level data and exogeneous variation in local welfare benefits. In this study, we draw on registry data from Switzerland, which cover movement patterns for the full population of foreign residents. By leveraging widespread municipal variation in the generosity of cash transfers and exogenous shocks to benefit rates resulting from cantonal legislation, our design permits us to concretely identify the extent to which changes in benefit rates shape immigrants’ relocation decisions. Our findings have important implications in the European setting, where municipalities often possess discretion over welfare programs and where right-wing parties have been mobilizing voters around the issue of benefit tourism.

Political Methodology

Instrumental Variables

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.

Aggregation Problems

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.

Measurement Problems

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.

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.

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.

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.