Returns to migration after job loss—The importance of job match

Abstract

Loss of specific human capital is often identified as a mechanism through which displaced workers might experience permanent drops in earnings after job loss. Research has shown that displaced workers who migrate out of their region of origin have lower earnings than those who do not. This paper extends the discussion on returns to migration by accounting for the type of jobs people get and how related they are to their skills. Using an endogenous treatment model to control for selection bias in migration and career change, we compare displaced stayers with displaced movers in Sweden. Results show that migrants who get a job that matches their occupation- and industry-specific skills display the highest earnings among all displaced workers. If migration is combined with a job mismatch, earning losses are instead observed. This group experiences the lowest earnings among all displaced workers.

Identify social and job disparities in the relationship between job‐housing balance and urban commuting using Baidu trajectory big data

“…In the era of big data, more nuanced depictions of people's commuting behaviors and socioeconomic statuses are available, offering insights into their interrelationship. As the basic assumptions of spatial mismatch regarding housing affordability and job accessibility weaken in complex urban contexts, skill mismatch emerges as a critical research focus in future studies on job‐housing relationships and commuting (Kekezi & Boschma, 2021; L'Horty & Sari, 2019; Xiao et al., 2021, 2023).…”

“…(2023) found that skill mismatch significantly influences the long‐distance commuting of low‐income individuals. The skill mismatch index has also been used to explain commuting distances (L'Horty & Sari, 2019), and the unemployment rate, a key factor in the spatial mismatch hypothesis, is strongly linked to people's working skills (Kekezi & Boschma, 2021).…”

“…There are two main strands of literature linking commuting and job‐housing balance to job types. Economists typically concentrate on the impacts of job matching on work efficiency, examining if individuals can find jobs that suit their skills and the outcomes thereof (Barmby et al., 2012; Belfield & Harris, 2002; Kekezi & Boschma, 2021), but often overlook the costs of accessing job opportunities, like commuting distance. Transportation and planning researchers, on the contrary, investigate job accessibility by analyzing the relationship between people's commuting distance and various determinants, including the built environment and socio‐demographic factors like income, education, and car ownership (Manaugh et al., 2010; Sandow & Westin, 2010; Xiao et al., 2023; Zhu et al., 2020).…”

“…In this study, we integrate the concept of geographical skill mismatch, instead of spatial mismatch, to explain the relationship between job‐housing balance and urban commuting. Geographical skill mismatch highlights social disparities, such as those between individuals' education and income, and the educational and salary requirements of jobs (Kekezi & Boschma, 2021; Stoll, 2005; Zhou, Yeh, & Yue, 2018). Skill mismatch extends the job‐housing relationship by considering the skills of labor forces and jobs, rather than solely their volume.…”

Agriculture 4.0? Studying the evidence for automation in Chilean agriculture

“…However, technological changes affecting the labor market could not only produce changes in the structure of agricultural employment. Workers not only have the option to be employed in other jobs within agriculture, but can migrate to other sectors of the economy or migrate geographically to other parts of the country where such changes occur less quickly (Kekezi & Boschma, 2021).…”