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

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 metr...

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Bibliographic Details
Published inEconomies Vol. 11; no. 4; p. 114
Main Authors Ali, Waad, Agyekum, Boadi, Al Nasiri, Noura, Abulibdeh, Ammar, Chauhan, Shekhar
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.04.2023
Subjects
Alien labor
Analysis
Cultural capital
Economic aspects
Education
Employers
Employment
Evaluation
Habitus
Hypotheses
Immigrants
Immigration
Labor market
Labor supply
non-standard employment
Part time employment
Population
race
Self employment
spatial characteristics
Statistics
Surveys
Temporary employment
Canada
Ontario
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Summary: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.
ISSN:2227-7099
2227-7099
DOI:10.3390/economies11040114