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An important goal of immigration policy is to facilitate the entry of foreignborn workers whose skills are in short supply in national labor markets. In recent decades, information and communication technology [ICT] has fueled the demand for highly educated workers at the expense of lower educated groups. Exploiting the fact that different regions in Switzerland have been differentially exposed to ICT due to their pre-ICT industrial composition, we present evidence suggesting that more exposed regions experienced stronger ICT adoption, accompanied by considerably stronger growth in relative employment and wage-premia for college-educated workers. Following this change in the landscape of relative economic opportunities, we find robust evidence that these regions experienced a much stronger in ux of highly educated immigrants in absolute terms as well as relative to lower educated groups. Our results suggest that immigrants' location decisions respond strongly to these long-run, technology-driven changes in their economic opportunities.

Many applied settings in empirical economics require estimation of a large number of individual effects, like teacher effects or location effects; in health economics, prominent examples include patient effects, doctor effects or hospital effects. Increasingly, these effects are the object of interest of the estimation, and predicted effects are often used for further descriptive and regression analyses. To avoid imposing distributional assumptions on these effects, they are typically estimated via fixed effects methods. In short panels, the conventional maximum likelihood estimator for fixed effects binary response models provides poor estimates of these individual effects since the finite sample bias is typically substantial. We present a bias-reduced fixed effects estimator that provides better estimates of the individual effects in these models by removing the first-order asymptotic bias. An additional, practical advantage of the estimator is that it provides finite predictions for all individual effects in the sample, including those for which the corresponding dependent variable has identical outcomes in all time periods over time (either all zeros or ones); for these, the maximum likelihood prediction is infinite. We illustrate the approach in simulation experiments and in an application to health care utilization.

This paper investigates the intergenerational effect of communication barriers on child health at birth using a natural experiment in Switzerland. We leverage the fact that refugees arriving in Switzerland originate from places that have large shares of French (or Italian) speakers for historical reasons and upon arrival are by law randomly allocated across states that are dominated by different languages but subject to the same jurisdiction. Our findings based on administrative records of all refugee arrivals and birth events between 2010 and 2017 show that children born to mothers who were exogenously allocated to an environment that matched their linguistic heritage are on average 72 gram heavier (or 2.2%) than those that were allocated to an unfamiliar language environment. The differences are driven by growth rather than gestation and manifest in a 2.9 percentage point difference in low birth weight incidence. We find substantial dose-response relationships in terms of language exposure in both, the origin country and the destination region. Moreover, French (Italian) exposed refugees only benefit from French-(Italian-) speaking destinations, but not vice versa. Contrasting the language match with co-ethnic networks, we find that high quality networks are acting as a substitute rather than a complement.

The maximum likelihood estimator for the regression coefficients, β, in a panel binary response model with fixed effects can be severely biased if N is large and T is small, a consequence of the incidental parameters problem. This has led to the development of conditional maximum likelihood estimators and, more recently, to estimators that remove the O(T–1) bias in β We add to this literature in two important ways. First, we focus on estimation of the fixed effects proper, as these have become increasingly important in applied work. Second, we build on a bias-reduction approach originally developed by Kosmidis and Firth (2009) for cross-section data, and show that in contrast to other proposals, the new estimator ensures finiteness of the fixed effects even in the absence of within-unit variation in the outcome. Results from a simulation study document favourable small sample properties. In an application to hospital data on patient readmission rates under the 2010 Affordable Care Act, we find that hospital fixed effects are strongly correlated across different treatment categories and on average higher for privately owned hospitals.

From 2004 to 2012, the German social health insurance levied a co-payment for the first doctor visit in a calendar quarter. We develop a new model for estimating the effect of such a co-payment on the individual number of visits per quarter. The model allows for a one time increase in the otherwise constant hazard rate determining the timing of doctor visits, and uses a difference-in-differences strategy to identify the reform effect. The model can be adapted to a situation where the reporting period and the calendar quarter differ. Using data from the German Socio-Economic Panel, we do not find an effect of the co-payment on demand for doctor visits.

In this study, I provide evidence that the educational achievement of second- generation immigrants in German-speaking Switzerland is greater than in Germany. The impact of the first-generation immigrants’ destination decision on their offspring’s educational achievement seems to be much more important than has been recognized by the existing literature. I identify the test score gap between these students that cannot be explained by differences in individual and family characteristics. Moreover, I show how this gap evolves over the test score distribution and how the least favorably endowed students fare. My results suggest that the educational system of Switzerland, relative to the German system, enhances the performance of immigrants’ children substantially. This disparity is largest when conditioning on the language spoken at home, and prevails even when comparing only students whose parents migrated from the same country of origin.