In this paper we analyze the long-run impact of immigration on employment, productivity, and its skill bias. We use the existence of immigrant communities across U.S. states before 1960 and the distance from the Mexican border as instruments for immigration flows. We find no evidence that immigrants crowded out employment. At the same time, we find that immigration had a strong, positive association with total factor productivity and a negative association with the high skill bias of production technologies. The results are consistent with the idea that immigrants promoted efficient task specialization, thus increasing TFP, and also promoted the adoption of unskilled-efficient technologies.

Knowledge flows within and across countries may have important consequences for both productivity and innovation. We use data on 1.5 million patents and 4.5 million citations to estimate knowledge flows at the frontier of technology across 147 subnational regions during 1975-1996 within the frame of a gravity-like equation. We estimate that only 20% of average knowledge is learned outside the average region of origin, and only 9% is learned outside the country of origin. However, knowledge in the computer sector flows substantially farther, as does knowledge generated by technological leaders. In comparison with trade flows, we see that knowledge flows reach much farther. External accessible R&D gained through these flows has a strong positive effect on innovative activity for a panel of 113 European and North American regions over 22 years.

The literature on schooling externalities in U.S. cities and states is rather mixed: positive external effects of average education levels are hardly found while positive externalities from the share of college graduates are more often identified. We propose a simple model to reconcile this mixed evidence. Our model predicts positive externalities from increased college education and negligible external effects from high school education. Using compulsory attendance/child labor laws, push-driven immigration of highly educated workers, and the location of land-grant colleges as instruments for schooling attainments, we test and confirm the model predictions with data on U.S. states for the period 1960–2000.

Positive assortative matching increases both the wages of more productive workers and wage dispersion. We study the effect of immigration on positive assortative matching using French employer-employee data from 1995 to 2005. We find that increases in the share of immigrants, driven by historical networks across local labor markets, generated stronger positive assortative matching between workers and firms. We present evidence suggesting that this effect was associated to higher wages for more productive workers and that the findings are consistent with increased workers' screening by firms.

We estimate the aggregate long-run elasticity of substitution between more educated workers and less educated workers (the slope of the inverse demand curve for more relative to less educated workers) at the U.S. state level. Our data come from the (five) 1950–1990 decennial censuses. Our empirical approach allows for state and time fixed effects and relies on time- and state-dependent child labor and compulsory school attendance laws as instruments for (endogenous) changes in the relative supply of more educated workers. We find the aggregate long-run elasticity of substitution between more and less educated workers to be around 1.5.

We evaluate a Danish reform focused on improving language training for those granted refugee status on or after January 1, 1999. Using a Regression Discontinuity Design, we find a significant, permanent, positive effect on earnings. This effect emerged after completion of language classes and was accompanied by additional schooling and a higher probability of working in complex jobs, consistent with language training, rather than other minor aspects of the reform, producing the results.