Evaluations of Immigration- and Integration Policies


In this project, we investigate the (sometimes unintended) consequences of policies that have been implemented to regulate immigration and to subsequently facilitate the socio-economic integration of newly arrived immigrants.

(1) Networks: First, we exploit a natural experiment in Switzerland, where asylum seekers are randomly assigned to cantons. This immigration policy can be regarded as a transparent and neutral way of distributing refugees across a country to “share a burden”. At the same time, such restrictions regarding free movement within a country come with hefty consequences for the persons affected. On the one hand, a large share of jobs are found through referrals within social networks: in the US, for instance, around 30-60% (Bewley, 2007). At least since Granovetter (1973), a rich theoretical literature has rationalized this fact by modelling networks as non-market institutions that help overcome information frictions inherent in the labor market. From workers' perspective, networks grant their members preferential access to information on high-quality job openings, e.g. as in Calvo-Armengol and Jackson (2004). On the firm side, networks may help alleviate the asymmetric information problem in hiring leading potentially to a better job-match, e.g. as in Beaman and Magruder (2012). In our study, we focus on the value of social networks from the perspective of workers. Swiss asylum policy provides a unique natural experiment to study the effects of social networks on labor market outcomes. Because of the truly exogenous placement, long horizon over which the policy was in place and the large sample size, we can delve deeper into the mechanisms of how social networks affect labor market integration than previous studies have done and look at network structure beyond simply its size. Our findings will enable us to distinguish among a large set of theoretical models of the value of networks from the point of view of individual job seekers.

(2) Maternity: At the same time, such immigration policies also affect the social integration of immigrants and, in our case, individual health and wellbeing. Specifically, we exploit the same unique setting to assess the relevance of information on infants' health. Random allocation of asylum seekers in Switzerland allows us to first, study the spatial differences in health care provision across the country. Further, by exploiting that French-speaking refugees are randomly placed in French- or non-French-speaking regions, we can credibly identify the language-match-health-gap, based on refugees that do not speak French as a control group and placed on either side of the language border (in a Difference in Differences framework). By extending the language to a novel (continuous) measure of language distance, we are able to factor out country of origin effects using bi-lateral regressions.

A second strand of policies targets the (economic) integration of immigrants and generally of persons outside the labor market. A common approach is to provide measures, so-called Active Labor Market Programs (ALMP) that enhance a jobseeker’s employability (e.g., through additional human capital) or that keep a person close to the labor market through occupational programs.

(3) Access Bias: Some measures, however, can negatively affect labor market outcomes, such as unemployment duration and post-unemployment wages, because of factors such as human capital deprivation or lock-in effects. Based on encompassing registry data that allow researchers to control for usually unobserved employability variables, we find evidence of a systematic access bias whereby caseworkers in Switzerland assign unemployed immigrants to activation measures based on what we call a competition logic that is mainly driven by and conforms to an economic rationale and the job center’s performance evaluation. From the perspective of immigrants’ labor market integration, this may be problematic because it results in an overrepresentation of immigrants in measures with little efficacy rather than in measures that could compensate for (some of) their employability disadvantages. Conversely, we find that Swiss citizens are relatively advantaged in the ability to access more measures that promote human capital enhancement (compensation logic) and that have been shown to be successful tools for labor market reintegration. It is plausible that a stronger reliance on the competition logic by caseworkers and the consequential overrepresentation of migrants in low-efficacy measures amplifies migrants’ general labor market disadvantages.

(4) Priming: This rather negative stance on integration measures in the form of ALMPs is further advanced by a study where we present indications that ALMP participants are pushed into lower paying jobs compared to equally qualified non-participants. In this study on the effect of subjective beliefs  on employment outcomes we find that the employment chances one year after the start of unemployment increase for both ALMP participants and non-participants when self-control and employment beliefs are high. In contrast, higher initial reservation wages increase employment chances for non-participants but substantially reduce them for ALMP participants. Previous studies have shown that beneficial effects of activation measures are often abrogated by lock-in effects, human capital deprivation, and/or negative signals to prospective employers, all of which are particularly harmful for highly skilled workers and higher-paying jobs. We argue that these detrimental effects ultimately push ALMP participants into jobs below their expected salary, where the negative consequences of activation measures are less pronounced.

(5) Heterogeneity: A related aspect that is crucial from an integration perspective is whether such effects of ALMPs differ across groups, that is, whether the participation of “natives” turns out to have different consequences for their labor market performance compared to participating immigrants. In this study, we argue that effect heterogeneity between native and migrant participants can provide information about the type of discrimination that migrants face in the labor market. Using encompassing administrative data from Switzerland, we observe all registered jobseekers in 2004 and follow their monthly labor market trajectories over 10 subsequent years. Our findings are consistent with earlier evaluations of ALMPs in Switzerland and elsewhere, which find that participation effects of ALMPs are limited and sometimes even negative. However, findings show that employers value the additional productivity-related information of ALMP participation more if participants have a foreign nationality. We infer that labor market discrimination against migrants is dominated by statistical reasoning on the part of prospective employers.

(6) LM-Index: Eventually, we provide a meta-analytical study where we argue that comparative assessments of integration policies fail to properly take confounding factors into account. That is, immigrant groups exposed to integration policies in different countries differ in their characteristics because immigration policies and migrants’ destination choice induce an ex-ante bias. To circumvent this limit to comparative analyses, we aspire to collect and generate data on all existing policy dimensions and subsequently provide a comparative analysis of immigrants’ labor market integration in industrialized countries.

Main content

Selected Publications

Auer, Daniel (2018): "Language Roulette – The Effect of Random Placement on Refugees' Labour Market Integration." In: Journal of Ethnic and Migration Studies, Vol. 44, No. 3, p. 341-362.

Liechti, Fabienne/Fossati, Flavia/Bonoli, Giuliano/Auer, Daniel (2017): "The Signalling Value of Labor Market Programs".  In: European Sociological Review, Vol. 33, No. 2, p. 257-274.

Project Management
Prof. Dr. Flavia Fossati (University of Vienna), Prof. Dr. Carlos Vargs-Silva (Oxford University), Prof. Dr. Stefanie Kurt (HES-SO Valais), Dennis Egger (Berkeley University), Dr. Johannes Kunz (Monash University), Dr. Damaris Rose (Uni Cologne)
2018 -
Swiss National Science Foundation