Immigrant Wages in the Public and Private Sectors: How do these Compare to the Wages of the Canadian-born?
Researchers: Richard Mueller1, Khuong Truong2, Annabella Ansah1, and Andrew Parkin3
Affiliation: University of Lethbridge1, McMaster University2, and Mowat Centre3
Research Partner: Mowat Centre
Keywords: immigrants, labour market integration, wages, wage gap, public sector, private sector, quantitative research, Labour Force Survey, census data
Objective: This study will document immigrant wage differentials in the public and private sectors using two separate data sets: the Labour Force Survey (LFS) and the 2016 Census; immigrant wages will be compared to those of Canadian-born individuals both within and between the two sectors.
Justification: Immigrants are increasingly important source of labour in Canada. However, research shows that immigrants do not tend to perform well in the labour market in terms of wages. A small amount of evidence to date suggests that the immigrant wage disadvantage is smaller in the public sector than it is in the private sector. However, these studies do not address the wage gap between sectors or at different levels of government.
Practical goal: to advance our knowledge of the wage disparities which immigrants experience in both the public and private sector, compared to Canadian-born counterparts.
Primary audience: academics, policy makers, and the public.
The Labour Force Survey (LFS) spans 3 years on either side of 2015, and the 2016 Census contains data for 2015, allowing for an adequate sample size. Using both datasets allows the researchers to compare immigrant wages to those of Canadian-born individuals, both within and between the two sectors. Data will be disaggregated into federal, provincial, and local levels of government administration, and will include public sector jobs that are not related to public administration (e.g. health care).
Standard wage decomposition techniques (e.g., Blinder 1973; Oaxaca 1973) will be employed to see how changes in the gap can be explained by factors such as higher levels of education. Quantile regressions will be employed along with the decomposition techniques outlined in Fortin et al. (2010) to determine at which points (if any) in the wage distribution we still see wage gaps that cannot be explained by the usual factors that influence wages.
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