Education is widely believed to predict attitudes toward immigration, but what causal relationship underlies this descriptive pattern? This research employs three distinct natural experiments and considers genetic factors to triangulate this relationship: Study 1 analyses discordant monozygotic twins; Study 2 assesses the impact of a Swedish education reform; and Study 3 analyses dizygotic twins with the use of a polygenic index for education, a DNA-based measure for genetic predispositions toward education. The results indicate that education does modestly promote open views toward immigration (Study 1), yet the reform’s effect remains uncertain (Study 2). Study 3 offers direct evidence of the effects of genetic predispositions and suggests that genetics related to education may influence attitudes beyond achieved educational attainment. These findings confirm the positive impact of education while pointing to the combined influence of genetic and social pathways in shaping immigration attitudes.

A pioneering study by Loewen et al. made use of the Canadian legislature's newly instituted lottery, which enabled non-cabinet Members of Parliament (MPs) to propose a bill or motion. Their study used this lottery in order to identify the causal effect of proposal power on incumbents' vote share in the next election. Analyzing the first two parliaments to use the lottery, Loewen et al. found that proposal power benefits incumbents, but only incumbents who belong to the governing party. Our study builds on these initial results by adding data from four subsequent parliaments. The pooled results no longer support the hypothesis that MPs—even those who belong to the governing party—benefit appreciably from proposal power. These updated findings resolve a theoretical puzzle noted by Loewen et al., as proposal power would not ordinarily be expected to confer electoral benefits in strong party systems, such as Canada's.

Numerous studies have shown associations between maternal stress and poor birth outcomes, but evidence is unclear for causal inference. Natural disasters provide an opportunity to study effects of quasi-randomized hardship with an accurate measure of onset and duration. In a population-based quasi-experimental study, we examined the effect of maternal exposure to the January 1998 Québec ice storm on birth outcomes by comparing pregnant mothers who lived in an area hard hit by the ice storm with those in two unaffected regions. In a total of 147,349 singleton births between 1995 and 2001, we used a difference-in-differences method to estimate the effects of the ice storm on gestational age at delivery (GA), preterm birth (PTB), weight-for-gestational-age z-scores (BWZ), large for gestational age (LGA), and small for gestational age (SGA). After adjusting for maternal and sociodemographic characteristics, there were no differences between the exposed and the unexposed mothers for birth outcomes. The estimated differences (exposed vs. unexposed) were 0.01 SDs (95% CI: −0.02, 0.05) for BWZ; 0.10% point (95% CI: −0.95%, 1.16%) for SGA; 0.25% point (95% CI: −0.78%, 1.28%) for LGA; −0.01 week (95% CI: −0.07, 0.05) for GA; and 0.16% point (95% CI: −0.66%, 0.97%) for PTB. Neither trimester-specific nor dose–response associations were observed. Overall, exposure to the 1998 Québec ice storm as a proxy for acute maternal stress in pregnancy was not associated with poor birth outcomes. Our results suggest that acute maternal hardship may not have a substantial effect on adverse birth outcomes.

An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper, we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Survey Design. In particular, we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey, we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens’ satisfaction with their national government.

Does exposure to the refugee crisis fuel support for extreme-right parties? Despite heated debates about the political repercussions of the refugee crisis in Europe, there exists very little—and sometimes conflicting—evidence with which to assess the impact of a large influx of refugees on natives’ political attitudes and behavior. We provide causal evidence from a natural experiment in Greece, where some Aegean islands close to the Turkish border experienced sudden and drastic increases in the number of Syrian refugees while other islands slightly farther away—but with otherwise similar institutional and socioeconomic characteristics—did not. Placebo tests suggest that precrisis trends in vote shares for exposed and nonexposed islands were virtually identical. This allows us to obtain unbiased estimates of the electoral consequences of the refugee crisis. Our study shows that among islands that faced a massive but transient inflow of refugees passing through just before the September 2015 election, vote shares for Golden Dawn, the most extreme-right party in Europe, moderately increased by 2 percentage points (a 44 percent increase at the average). The finding that mere exposure to the refugee crisis is sufficient to fuel support for extreme-right parties has important implications for our theoretical understanding of the drivers of antirefugee backlash.

There is an enormous interest in identifying the causes of psychiatric disorders but there are considerable challenges in identifying which risks are genuinely causal. Traditionally risk factors have been inferred from observational designs. However, association with psychiatric outcome does not equate to causation. There are a number of threats that clinicians and researchers face in making causal inferences from traditional observational designs because adversities or exposures are not randomly allocated to individuals. Natural experiments provide an alternative strategy to randomized controlled trials as they take advantage of situations whereby links between exposure and other variables are separated by naturally occurring events or situations. In this review, we describe a growing range of different types of natural experiment and highlight that there is a greater confidence about findings where there is a convergence of findings across different designs. For example, exposure to hostile parenting is consistently found to be associated with conduct problems using different natural experiment designs providing support for this being a causal risk factor. Different genetically informative designs have repeatedly found that exposure to negative life events and being bullied are linked to later depression. However, for exposure to prenatal cigarette smoking, while findings from natural experiment designs are consistent with a causal effect on offspring lower birth weight, they do not support the hypothesis that intra-uterine cigarette smoking has a causal effect on attention-deficit/hyperactivity disorder and conduct problems and emerging findings highlight caution about inferring causal effects on bipolar disorder and schizophrenia.

Survey experiments often manipulate the description of attributes in a hypothetical scenario, with the goal of learning about those attributes’ real-world effects. Such inferences rely on an underappreciated assumption: experimental conditions must be information equivalent (IE) with respect to background features of the scenario. IE is often violated because subjects, when presented with information about one attribute, update their beliefs about others too. Labeling a country “a democracy,” for example, affects subjects’ beliefs about the country’s geographic location. When IE is violated, the effect of the manipulation need not correspond to the quantity of interest (the effect of beliefs about the focal attribute). We formally define the IE assumption, relating it to the exclusion restriction in instrumental-variable analysis. We show how to predict IE violations ex ante and diagnose them ex post with placebo tests. We evaluate three strategies for achieving IE. Abstract encouragement is ineffective. Specifying background details reduces imbalance on the specified details and highly correlated details, but not others. Embedding a natural experiment in the scenario can reduce imbalance on all background beliefs, but raises other issues. We illustrate with four survey experiments, focusing on an extension of a prominent study of the democratic peace.

This note offers an introduction to electromagnetic signal propagation models, which can be used to model terrestrial radio and television signal strength across space. Such data are useful to social scientists interested in identifying the effects of mass media broadcasts when (i) individual-level data on media exposure do not exist or when (ii) media exposure, while observed, is not exogenous. We illustrate the use of electromagnetic signal propagation models by creating a signal strength measure of military-controlled radio stations during the 2012 coup in Mali.

This study uses historical data from the 1965 Voting Rights Act (VRA) to examine the effect of strategic policy making on policy outcomes. Strategic policy making refers to the exploitation of future policy resources by an incumbent government when it anticipates the policy change by a future government. In the South, the segregationist governments immediately after the enactment of the VRA still stayed in office but anticipated the future policy change that would result from minority voters acquiring the right to franchise. This political context provides an ideal setting for testing the theory of strategic policy making. Through analysis of county panel data analysis from the 1960s, this study finds that segregationist governments with large budgets increased long-term debts, education spending, and highway spending significantly when compared with the rest of the country. This finding supports a version of strategic policy making, namely, strategic use of debts, and is consistent with anecdotal evidence indicating that resistance to school integration through the creation of all-white suburban schools is one of the primary motives for bond issues.