Does it Matter if Canadian Immigrants Work in Jobs Related to Their Education? Canadian Research Data Center Network (CRDCN) Conference Toronto, Ontario November 5, 2015
Motivation Immigrants endure substantial wage disadvantages upon arrival. Disadvantages persist over their entire working career. - (Baker and Benjamin, 1994; Bloom, Gunderson, Grenier, 1994; Grant, 1999; Hum and Simpson, 1994; Picot and Sweetman, 2005; Aydemir and Skuterud, 2005; Skuterud and Su, 2011; Campolieti and Gunderson, 2013). Immigrants are also highly educated. Evidence suggests that human capital, especially foreign work experience is discounted. - (Aydemir and Skuterud, 2005; Ferrer and Riddell, 2008; Schaafsma and Sweetman, 2001; Skuterud and Su, 2009).
Purpose of Paper Are Canadian immigrants mismatched relative to the Canadian-born? Do education-job mismatches have an effect on earnings? Are immigrant disadvantages associated with mismatching? - What is the percentage of the immigrant-canadian-born entry wage gap due to mismatching? - Does matching improve the returns to foreign education and experience?
Vast literature on education-job matches that is quantity-based. - Hartog (2000) provides a summary. In the context of immigration: - Chiswick and Miller (2008)(2009a,b) - 2/3 of the lower returns to foreign schooling is due to different payoffs to under- and over-education. - Sharaf (2013) - High incidence of over-education among Canadian immigrants and these mismatches are associated with significant wage penalties.
Qualitative Matches Alternative notion of matching: - Qualitative matches - arise when the qualifications of workers are different from the qualifications required or specified for their jobs (Sattinger, 2012). - Quantity-based measures fail to capture if education-related skills match those required in employment. Yuen(2010) and Robst(2007) - U.S. and Canadian workers, respectively, endure significant wage penalties when in jobs unrelated to their field of study. No studies have investigated the role of qualitative mismatches in explaining immigrant disadvantages in Canada.
Survey of Labour and Income Dynamics (SLID) 2001-2010. Males and females 18-64 with at least one post-secondary education credential. Child immigrants (before 10 years of age) where removed. (Schaafsma and Sweetman, 2001) Removed immigrants with invalid/missing responses for: - Age at migration and birthplace. Analysis stratified by gender and by traditional and non-traditional source regions: - Traditional: U.K., U.S, Europe, Australia and New Zealand. - Traditional: Middle-East, Asia, Caribbean, Mexico, Southern and Central America.
Education-Job Match Measure Ordinal response variable on job relatedness - Records, for both immigrants and the Canadian-born, on how related a worker s current job is to their education. - Survey respondents are directly asked: How closely was this job related to your education? a) Not at all related b) Somewhat related c) Closely related
Empirical Model 1 ln (w it ) = β 0 + β 1 exp it + β 2 expit 2 + β 3s it + β 4 some it + β 5 close it + ) I (α 0 + α 1 ysm it + α 2 ysmit 2 + α 3some it + α 4 close it + X it λ + ε it, (1) Where: - w it is an individual s composite wage in year t - exp is potential work experience, s is years of schooling, ysm is years of schooling, I denotes an immigrant indicator - X contains controls for socio-demographic variables including indicators for marital status, non-english (Ontario and Québec) or non-french (Québec) mother tongue, region (British Columbia, Prairies, Ontario, Québec, Maritimes), major cities (Toronto, Montréal, Vancouver) and the panel and year observed. - some and close are indicator variables for respondents in a somewhat related and closely related job. - Pooled OLS - standard errors are adjusted for clustering at the individual level.
Empirical Model 1 - Results for Males
Empirical Model 1 - Results for Females
Percent of Entry Wage Gap Explained by Mismatch
Percent of Entry Wage Gap Explained by Mismatch
Percent of Entry Wage Gap Explained by Mismatch
Empirical Model 2 ln(w it ) = β 0 + β 1 canexp it + β 2 cans it + β 3 some it + β 4 close it + I(α 0 + α 1 canexp it + α 2 forexp it + α 3 cans it + α 4 fors + α 5 some it + α 6 close it + α 7 fors it some it + α 8 fors it close it + α 9 forexp it some it + α 10 forexp it close it )+ X it λ + ε it, (2) - The foreign and Canadian components of schooling and experience are identified using information on a continuous measure of age at migration (Friedberg, 2000). - Use SLID s actual measure of work experience. - Pooled OLS - standard errors are adjusted for clustering at the individual level.
Matching and the returns to Foreign Human Capital
Matching and the returns to Foreign Human Capital
Matching and the returns to Foreign Human Capital
Severe wage penalties associated with being mismatched Immigrants are more likely to be mismatched upon arrival Immigrant mismatches are partly responsible for immigrant wage disadvantages upon arrival. - Traditional Males/Females - 17.3/21.6 percent. - Non-Traditional Males/Females - 38.9/33.3 percent. Matching increases the returns immigrants receive for foreign schooling and work experience. Evidence suggests that boosting resources dedicated to help immigrants secure related jobs could significantly reduce wage disparities.