To estimate the causal effect of refugee migration on voting outcomes in parliamentary and municipal elections in Denmark, our study is the first that addresses the key problem of immigrant sorting by exploiting a policy that assigned refugee immigrants to municipalities on a quasi-random basis. We find that in all but the most urban municipalities, allocation of larger refugee shares between electoral cycles leads to an increase in the vote share for right-leaning parties with an anti-immigration agenda, and we show large differences in voters’ responses to refugee allocation according to pre-policy municipal characteristics. However, in the largest and urban municipalities, refugee allocation has—if anything—the opposite effect on vote shares for anti-immigration parties. This coincides with a sharp divide in attitudes to refugees between urban and rural populations, which may be partly explained by distinctive interactions between natives and those with different background in cities and rural areas. Refugee allocation also has a large impact on the anti-immigration parties’ choice of where to stand for municipal election, and we provide some evidence that it influences voter turnout.

This article develops and estimates a dynamic model where individuals differ in ability and location preference to evaluate the mechanisms that affect the evolution of immigrants’ careers in conjunction with their re-migration plans. Our analysis highlights a novel form of selective return migration where those who plan to stay longer invest more into skill acquisition, with important implications for the assessment of immigrants’ career paths and the estimation of their earnings profiles. Our study also explains the willingness of immigrants to accept jobs at wages that seem unacceptable to natives. Finally, our model provides important insight for the design of migration policies, showing that policies that initially restrict residence or condition residence on achievement shape not only immigrants’ career profiles through their impact on human capital investment but also determine the selection of arrivals and leavers.

This article derives novel testable implications of referral-based job search networks in which employees provide employers with information about potential new hires that they otherwise would not have. Using comprehensive matched employer–employee data covering the entire workforce in one large metropolitan labour market combined with unique survey data linked to administrative records, we provide evidence that workers earn higher wages and are less inclined to leave their firms if they have obtained their job through a referral. These effects are particularly strong at the beginning of the employment relationship and decline with tenure in the firm, suggesting that firms and workers learn about workers' productivity over time. Overall, our findings imply that job search networks help to reduce informational deficiencies in the labour market and lead to productivity gains for workers and firms.