Research

Does immigration change support for redistribution? We design and conduct large-scale surveys and experiments in six countries to investigate how people perceive immigrants and how these perceptions influence their support for redistribution. We find striking misperceptions about the number and characteristics of immigrants. In all countries, respondents greatly overestimate the total number of immigrants, think immigrants are culturally and religiously more distant from them, and economically weaker–less educated, more unemployed, and more reliant on and favored by government transfers–than they actually are. In the experimental part of our paper, we show that simply making respondents think about immigration before asking questions about redistribution makes them support less redistribution, including actual donations to charities. The perception that immigrants are economically weaker and more likely to take advantage of the welfare system is strongly correlated with lower support for redistribution, much more so than the perceived cultural distance or the perceived share of immigrants. These findings are confirmed by further experimental evidence. Information about the true shares and origins of immigrants does not change support for redistribution. An anecdote about a “hard working” immigrant has somewhat stronger effects, but is unable to counteract the negative priming effect of making people think about immigration. Our results further suggest that narratives shape people’s views on immigration more deeply than hard facts.

Americans are polarized not only in their views on policy issues and attitudes toward government and society but also in their perceptions of the same factual reality. We conceptualize how to think about the “polarization of reality” and review recent papers that show that Republicans and Democrats view the same reality through a different lens. Perhaps as a result, they hold different views about policies and what should be done to address economic and social issues. We also show that providing information leads to different reassessments of reality and different responses along the policy support margin, depending on one's political leaning.

Using data from 16 OECD countries from 1981 to 2014 we study the effects on output of fiscal adjustments as a function of the composition of the adjustment—that is, whether the adjustment is mostly based on spending cuts or on tax hikes—and of the state of the business cycle when the adjustment is implemented. We find that both the “how” and the “when” matter, but the heterogeneity related to the composition is more robust across different specifications. Adjustments based upon permanent spending cuts are consistently much less costly than those based upon permanent tax increases. Our results are generally not explained by different reactions of monetary policy. However, when the domestic central bank can set interest rates—that is outside of a currency union—it appears to be able to dampen the recessionary effects of consolidations implemented during a recession.

I study how beliefs about search costs, returns to search effort, and outside options relate to the job mobility decisions of employed workers. I design an online survey and administer it to a representative sample of wage and salaried workers in the US. In the survey, I directly measure employed workers’ perceptions of search costs—time, money, stress—and the perceived returns to their job search effort—the expected success rate of their job applications. I also elicit workers’ beliefs about their opportunities outside of their current job and measure their knowledge of the wage distribution in their occupation. I document significant heterogeneity in expectations across demographic groups. Women expect higher costs and lower returns to effort. I find that beliefs about outside options, returns to search effort and search costs are significant predictors of job search intentions. Respondents who expect to spend more time looking for job openings have a lower propensity to search, consistent with the relevance of information frictions. Using two information experiments, I show that accurate information about the median wage does not affect search intentions, whereas shifting perceived search costs improves women’s willingness to search.

We investigate how coworkers shape job mobility decisions by influencing workers’ perceptions of their outside options. Using novel survey data from a representative sample of U.S. wage and salaried workers, we identify two distinct channels through which current and former coworkers affect mobility. First, having more current coworkers with prior experience in an industry enhances both the accuracy of workers’ wage beliefs and their perceived probability of receiving a job offer from that industry. Second, having more past coworkers currently employed in a sector raises the perceived likelihood of receiving an offer from that sector. At the firm level, personal connections increase the perceived probability of receiving an offer from that specific firm, as shown in a survey experiment eliciting subjective job-offer probabilities. We incorporate these findings into a job choice model featuring coworker-based learning and referral effects. Relative to standard models that assume perfect information about wages and job opportunities, our framework demonstrates that coworker networks facilitate labor reallocation and mitigate the welfare losses associated with information frictions.

Technological change is reshaping labor market dynamics at an increasingly rapid pace, making it crucial to understand the interaction between workers’ skills and job requirements. Mismatch between the two plays a key role in shaping wages, productivity, career mobility, and unemployment. This paper provides an up-to-date survey of the theoretical and empirical literature on the sources, measurement, and consequences of worker–job mismatch. We classify the theoretical drivers of mismatch into two main categories—search frictions and incomplete information—and empirical measures into three groups, depending on whether they rely on (i) observed matches and/or expert evaluations, (ii) workers’ subjective assessments, or (iii) a combination of the two. We review recent contributions emphasizing the importance of multidimensional skills and the use of machine-learning techniques to construct measures of occupational skill mismatch from employer–employee data when direct skill measures are unavailable. We then survey the evidence on the impact of financial constraints, employment protection legislation, managerial practices, and recent technological changes on mismatch and its consequences for workers’ careers and firm productivity. Finally, we discuss policy interventions aimed at reducing mismatch and outline directions for future research.

We study how employed workers perceive and respond to opportunities for occupational mobility. Using a large-scale online survey of 4,500 full-time workers in Germany, linked with administrative employment data, we measure workers’ beliefs about the transferability of their skills, the similarity of alternative occupations to theirs, the benefits---potential earnings---and costs---retraining and licensing requirements---of moving to other occupations. We also capture respondents’ beliefs about exposure of theirs and alternative occupations to automation, AI, and the green transition.  The results reveal that workers are imperfectly informed about opportunities in other occupations: they systematically underestimate task similarity and wages in alternative occupations while overestimating the need for retraining or licensing. These misperceptions are strongly correlated with intentions to seek jobs in other occupations. Randomized information treatments providing data on wages, retraining requirements, and displacement risk meaningfully alter workers’ beliefs and mobility intentions. These findings suggest that information gaps may hinder efficient labor reallocation, especially during periods of structural transformations, and that targeted informational interventions can help improve occupational mobility decisions.

We study the factors shaping the supply and demand of “good politicians” in Italian local politics and how these interact with the local presence of organized crime. We conduct two large-scale surveys of 12,000 respondents across all Italian provinces to study both sides of the political market. On the supply side, we measure individuals’ propensity to run for mayor and relate it to traits such as honesty (elicited via an incentivized dice-guessing game), tolerance for organized crime, risk aversion, and professional background. We find that those more likely to consider running for office are younger, more skilled, and risk-loving, but also more dishonest and more tolerant of criminal organizations. Selection patterns are similar across provinces with high and low risk of organized crime infiltration, yet due to differing underlying population traits, likely candidates in high-risk areas exhibit lower honesty and greater tolerance of criminal organizations. On the demand side, we use a conjoint experiment to measure voters’ preferences for candidates’ traits. Voters place substantial value on honesty and the absence of ties to organized criminality, and this valuation is higher in high-risk areas. Combining both surveys, we find evidence of a mismatch between voters’ preferences and the pool of likely candidates, particularly in provinces more exposed to organized crime.