The occupational trajectories and outcomes of forced migrants in Sweden. Entrepreneurship, employment or persistent inactivity?

Abstract

The current surge in forced migration to Europe is probably the largest and most complex since the Second World War. As population aging accelerates and fertility falls below replacement level, immigration may be seen as a key component of human capital to address labor and skill shortages. Receiving countries are, however, hesitant about the contribution that forced migrants can make to the local economy. Coupled with increasing pressure on welfare services, they are associated with increased job competition and crime. Underutilization of immigrants' skills is, however, a waste of resources that countries can scarcely afford. Understanding the labor market integration process of forced migrants is thus critical to develop policies that unleash their full skills potential and ultimately foster local economic productivity. While prior studies have examined the employment and salary outcomes of these immigrants at a particular point in time post-migration, they have failed to capture the temporal dynamics and complexity of this process. Drawing on administrative data from Sweden, we examine the occupational pathways of forced migrants using sequence analysis from their arrival in 1991 through to 2013. Findings reveal polarized pathways of long-term labor market integration with over one-third of refugees experiencing a successful labor market integration pathway and an equally large share facing a less fruitful employment outcomes. Our findings suggest education provision is key to promote a more successful integration into the local labor market by reducing barriers of cultural proximity and increasing the occurrence of entrepreneurship activity.

Entrepreneurial Opportunities of Refugees in Germany, France, and Ireland: Multiple Embeddedness Framework

“…While both public and private sectors have made substantial efforts to facilitate the employment of newly arriving refugees in the European Union (EU), refugees commonly suffer from the socalled "refugee gap" (Bakker et al 2017;Connor 2010;Easton-Calabria and Omata 2016) or "canvas ceiling" (Lee et al 2020), which hypothesizes that labor-market disadvantages exist for refugees. As a result of the lack of vocational opportunities in the host country, several refugees are pushed to self-employment (Backman et al 2020;Van Kooy 2016;Shneikat and Alrawadieh 2019). Furthermore, refugees must handle the psychological burden of career disruption in their home countries and re-establish their lives more or less from scratch in their host countries (Shneikat and Ryan 2018;Wehrle et al 2018).…”

Exploring the occupational lives of Syrians under temporary protection in Turkey

“…The literature supports this finding, describing one reason for these problems as the long processes to obtain work permits and access skills training and higher education, and language programmes and services (e.g., Baban et al, 2017;Bélanger & Saracoglu, 2020;Fincham, 2020;Ilcan et al, 2018;Mencutek, 2019). Backman et al (2021) argue that education can improve integration of immigrants into the local economy and community and that the underutilization of their job skills can negatively impact the host country's economy. The current study participants were grateful for having shelter in Turkey and for the policies that enable countries to provide immediate support for refugees forced from their countries; however, all participants were living day-to-day, until they returned home or were accepted to another country where they could attain refugee status, and those participants looking for work wanted to contribute their skills through employment and feel valued by their host country.…”

Construction of a Visual Saliency Model for Neighborhood Building Landmarks Based on K‐Means Clustering

“…Textures on the building surface in the highresolution images are mainly artificial textural features with human involvement and different from the surface properties of naturally existing objects. It is mainly represented by four angles in mean, homogeneity, standard deviation, heterogeneity, information entropy, correlation, contrast, and angular second-order moments with a total of eight feature parameters [25]. Quantitative expressions are made in terms of the mean and gray size, local variations of gray details in the image, and their degree of variation and homogeneity.…”