While an extensive literature examines the association between immigrants’ characteristics and their earnings in Canada, there is a lack of knowledge regarding the relative importance of various human capital factors, such as language, work experience and education when predicting the earnings of economic immigrants. The decline in immigrant earnings since the 1980s, which was concentrated among economic immigrants, prompted changes to the points system in the early 1990s and in 2002, in large part, to improve immigrant earnings. Knowledge of the relative role of various characteristics in determining immigrant earnings is important when making such changes. This paper addresses two questions. First, what is the relative importance of observable human capital factors when predicting earnings of economic immigrants (principal applicants), who are selected by the points system? Second, does the relative importance of these factors vary between the short, intermediate, and long terms?
This research employs Statistics Canada’s Longitudinal Immigration Database (IMDB). The analysis is restricted to immigrants who are principal applicants in the Economic Class (specifically, federal skilled workers and nominees in the provincial nominee programs), aged 20 to 54 in the year of landing, and with positive earnings in any given year after immigration. Since the Quebec selection system is somewhat unique in Canada, economic immigrants (principal applicants) entering through that system are excluded. To assess the effect of human capital variables on annual earnings in the short term (first 2 full years in Canada) and intermediate term (5 and 6 years after landing), immigrants who landed from 2002 to 2004 are considered. Outcomes of immigrants who landed between 1997 and 1999 are examined to assess the long-term (10 and 11 years after landing) effects on earnings. The results were verified using other cohorts.
The explanatory variables include factors available for use in an immigration selection system, and available in the IMDB. They include age at landing, educational attainment at landing, official-language characteristics at landing, years of Canadian work experience prior to landing, years of study in Canada prior to landing, spouse’s educational attainment at landing, spouse’s years of Canadian work experience prior to landing, and spouse’s years of study in Canada prior to landing.
The study finds that the relative predictive power of various human capital variables varies, depending on the number of years immigrants have spent in Canada. Language at landing is one of the most important variables in predicting earnings in the short term. But this factor becomes less important as an entering cohort increases its tenure in Canada. A similar pattern emerges for the Canadian work experience prior to landing. It is a strong predictor of earnings in the short term, but less so in the longer term. Education and age at landing are the two variables for which predictive power increases with time spent in Canada. While true for all cohorts, this was most evident in the unique situation faced by the entering cohorts of principal applicants during the early 2000s. Those with higher education earned little more than those with less education immediately following landing. But the earnings trajectory of the highly educated is much steeper, so that a significant earnings advantage for higher education developed after 5 to 10 years in Canada. In the longer term, education becomes the best predictor of earnings among the available variables. Generally, the older the economic immigrants at landing, the less well they do in the labour market. This effect increases with time spent in Canada, making age a relatively strong predictor of longer-term earnings, along with education.
Some interaction effects are also important. The predictive power of education and age (in part a proxy for foreign work experience) is influenced by their interaction with official-language skills and Canadian work experience. The earnings advantage for higher education is much larger among principal applicants who have strong rather than weak official-language skills. Immigrants with a mother tongue that is English or French do not experience a significant negative effect of age on earnings. Finally, many factors beyond those studied here affect immigrant earnings. The predictive power could be increased with improved data sources.
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