Effects of Spatial Characteristics on Non-Standard Employment for Canada’s Immigrant Population

Waad Ali (), Boadi Agyekum, Noura Al Nasiri, Ammar Abulibdeh and Shekhar Chauhan
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Waad Ali: Department of Geography, College of Arts & Social Sciences, Sultan Qaboos University, Muscat 112, Oman
Boadi Agyekum: School of Continuing and Distance Education, University of Ghana, Accra GA184, Ghana
Noura Al Nasiri: Department of Geography, College of Arts & Social Sciences, Sultan Qaboos University, Muscat 112, Oman
Ammar Abulibdeh: Applied Geography and GIS Program, Department of Humanities, College of Arts and Sciences, Qatar University, Doha P.O. Box 2713, Qatar
Shekhar Chauhan: International Institute for Population Sciences (IIPS), Mumbai 400029, India

Economies, 2023, vol. 11, issue 4, 1-17

Abstract: Using microdata from Statistics Canada’s Labour Force Survey (LFS) and Population Census, this paper explores how spatial characteristics are correlated with temporary employment outcomes for Canada’s immigrant population. Results from ordinary least square regression models suggest that census metropolitan areas and census agglomerations (CMAs/CAs) characterized by a high share of racialized immigrants, immigrants in low-income, young, aged immigrants, unemployed immigrants, and immigrants employed in health and service occupations were positively associated with an increase in temporary employment for immigrants. Furthermore, findings from principal component regression models revealed that a combination of spatial characteristics, namely CMAs/CAs characterized by both a high share of unemployed immigrants and immigrants in poverty, had a greater likelihood of immigrants being employed temporarily. The significance of this study lies in the spatial conceptualization of temporary employment for immigrants that could better inform spatially targeted employment policies, especially in the wake of the structural shift in the nature of work brought about by the COVID-19 pandemic.

Keywords: spatial characteristics; immigration; race; non-standard employment; temporary employment (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2023
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