# Analytical Studies Branch Research Paper Series International Students, Immigration and Earnings Growth: The Effect of a Pre-immigration Canadian University Education

by Feng Hou, and Yuqian Lu
Social Analysis and Modelling Division, Statistics Canada

Release date: August 22, 2017

## Acknowledgements

The authors would like to thank Grant Schellenberg, Mikal Skuterud, Arthur Sweetman and analysts at Immigration, Refugees and Citizenship Canada for advice and comments on an earlier version of this paper. Any errors are the responsibility of the authors.

## Abstract

Keywords: international students, immigration, Canadian education, earnings

## Executive summary

The number of international students pursuing education in countries with advanced economies has been rising rapidly over recent decades. International students are often regarded as an important group of young and well‑educated individuals from which to select permanent residents. However, a few studies from Australia, Canada and the United States have shown that the earnings advantage of former international students over other economic immigrants is either small or non‑existent. These empirical findings have been reflected in recent changes to immigrant selection policies in Australia and Canada.

This study compared the earnings trajectories of three groups of young university graduates: former international students in Canada who became permanent residents (Canadian‑educated [CE] immigrants), foreign‑educated (FE) immigrants who arrived at age 25 or over and had a university degree before immigration, and the Canadian‑born population. It asked two questions. First, do university‑educated CE immigrants earn as much as Canadian‑born university graduates both in the initial years after immigration and in the long term, and, if there is a large earnings gap between the two groups, what are the possible determinants? Second, do CE immigrants have a large earnings advantage over FE immigrants in the short and long term?

Three data sources were used in this study. The sample of CE immigrants was drawn from the linkage of three files: the Temporary Residents File (TRF), the Immigrant Landing File (ILF) and the T1 personal tax file. International students were identified among temporary residents as anyone who ever held a study permit in Canada. The sample of FE immigrants was derived from the Longitudinal Immigration Database (IMDB). The sample of Canadian‑born workers was created from the linkage between the 20% sample file of the 1991 Census and the Longitudinal Worker File, which is a 10% random sample of the tax‑filing population, and the linkage between the 20% sample file of the 2006 Census and the T1 personal tax file. Common to all three data sources are the longitudinal earnings data from the tax file.

This study examined the earnings trajectories of university‑educated individuals, by immigration status, in two cohorts: the 1991 cohort and the 2006 cohort. The 1991 cohort included the Canadian‑born population aged 25 to 34 in 1991 (the census year), FE immigrants who arrived in Canada and were aged 25 to 34 in 1991, and CE immigrants who became landed immigrants from 1990 to 1992 and were aged 25 to 34 in the year of landing. Similarly, the 2006 cohort included the Canadian‑born population aged 25 to 34 in 2006, FE immigrants who arrived in Canada and were aged 25 to 34 in 2006, and CE immigrants who became landed immigrants from 2005 to 2007 and were aged 25 to 34 in the year of landing.

Conditional on the earnings level in Canada before immigration, an extra year of Canadian work or education experience before immigration made little difference to post‑immigration earnings for CE immigrants. These results may suggest that what matters to CE immigrants is not the length of Canadian work or study experience, but the realized market value of this experience, as indicated by the earnings level before immigration.

## 1 Introduction

The number of international students pursuing education in countries with advanced economies has been rising rapidly over recent decades. According to statistics for four English‑speaking developed countries compiled by the United Nations Educational, Scientific and Cultural Organization (UNESCO), international students participating in tertiary education increased from 451,900 in 1999 to 784,000 in 2013 in the United States, from 232,500 to 416,700 in the United Kingdom, from 117,500 to 249,900 in Australia and from 32,500 to 135,200 (2012 statistics) in Canada.Note  Major receiving countries are becoming increasingly proactive in recruiting international students as a way to improve the financial health of educational institutions, attract talent and increase campus diversity (Choudaha and Chang 2012). These countries also increasingly regard international students as an important group of young and well‑educated individuals from which to select permanent residents. In Canada, for example, about one‑quarter of international students who arrived in the 1990s and 2000s transitioned into permanent residency within 10 years of obtaining their first study permit (Lu and Hou 2015).

The above possible mechanisms have often been invoked to explain empirical findings that immigrants who received destination‑country education outperform FE immigrants and even perform similarly to native‑born workers in the labour market (e.g., Bratsberg and Terrell 2002; Zeng and Xie 2004). Some recent evidence, however, has raised doubts about the extent to which these mechanisms actually work for international students who become permanent residents. A few studies from Australia, Canada and the United States show that the earnings advantage of former international students over other economic immigrants is either small or non‑existent (Birrell, Hawthorne and Richardson 2006; Hou and Bonikowska 2017; Lowell and Avato 2014).

Given the large and rising number of international students in Western countries and the significant social and policy implications, a more comprehensive understanding of the study–immigration issue is needed (Hawthorne and To 2014; King and Raghuram 2013). This study uses three unique national longitudinal datasets to compare the earnings trajectories of immigrants who are former international students in Canada (CE immigrants), FE immigrants and the Canadian‑born population. The study follows two cohorts of CE immigrants from the year when they became permanent residents. These immigrants had a university degree and were aged 25 to 34 when they became permanent residents. They are matched with the university‑educated Canadian‑born population and FE immigrants in the same age range. The focus on young university graduates allows for a clear comparison by immigration status and is also most relevant for policy issues related to the study‑to‑immigration transition.

This study asks two questions. First, do university‑educated CE immigrants earn as much as Canadian‑born university graduates both in the initial years after immigration and in the long term, and, if there is a large earnings gap between the two groups, what are the possible determinants? Second, do CE immigrants have a large earnings advantage over FE immigrants in the short and long term?

The results suggest that the key factor differentiating the post‑immigration earnings of CE immigrants from the earnings of the Canadian‑born population and FE immigrants is whether international students held a well‑paid job in Canada before becoming permanent residents.

The remainder of this paper is organized in three sections. Section 2 consists of a discussion of the data sources, measures and analytical approaches. Section 3 presents descriptive statistics and multivariate analysis results. Section 4 concludes the paper.

## 2 Data and methods

### 2.1 Data

Three data sources are used to construct the study samples of CE immigrants, FE immigrants and the Canadian‑born population.

The sample of CE immigrants is drawn from the linkage of three files: the Temporary Residents File (TRF), the Immigrant Landing File (ILF), and the T1 personal tax file.Note  The TRF was created by Immigration, Refugees and Citizenship Canada (IRCC) and contains sociodemographic and administrative information on all temporary residents in Canada. Foreign students are identified among temporary residents as anyone who ever held a study permit issued by IRCC. The ILF contains the sociodemographic characteristics of permanent residents at the time of landing, including the highest level of completed education, age at immigration, class of immigration, official language and source country. The TRFILF linkage allows for the identification of former international students who made the transition into permanent residency. The T1 personal tax file includes annual information on income, taxes and some basic demographic characteristics, but it does not contain information on immigration status and education. The tax file covers the period from 1982 to 2013, which is the most recent year available at the time of this study.

The sample of FE immigrants is derived from the Longitudinal Immigration Database (IMDB). The IMDB combines immigrant landing records and annual tax records for all immigrants who have arrived in Canada since 1980 and who have filed at least one tax return since 1982. Those who filed a tax return before landing (i.e., who lived in Canada before becoming permanent residents) and those who arrived before the age of 25 are excluded from the analysis as a way to exclude immigrants who might have acquired education in Canada before becoming permanent residents. Some CE immigrants and FE immigrants may pursue further education in Canada after immigration, and the regression models in this study control for this (see Subsection 2.2).

The sample of Canadian‑born workers is created from the linkage between the 20% sample file of the 1991 Census and the Longitudinal Worker File, which is a 10% random sample of the tax filing population, and the linkage between the 20% sample file of the 2006 Census (a subsample that could be linked to the 2011 National Household Survey [NHS]) and the T1 personal tax file. The census and NHS files allow the Canadian‑born population and their educational attainment to be identified.

Common to all three data sources are the longitudinal earnings data from the tax file. The rate of tax filing in Canada is very high, and the T1 personal tax file covers up to 95% of the Canadian working age population (Finnie 2007). Most working age individuals file tax returns every year, so attrition over time is quite low relative to longitudinal survey data. Therefore, the T1 personal tax file is representative both cross‑sectionally and longitudinally.

This study compares the earnings trajectories of university‑educated individuals, by immigration status, in two “entry” cohorts: the 1991 cohort and the 2006 cohort.Note  The 1991 cohort includes the Canadian‑born population aged 25 to 34 in 1991 (the census year), FE immigrants who arrived in Canada and were aged 25 to 34 in 1991, and CE immigrants who became landed immigrants from 1990 to 1992 and were aged 25 to 34 in the year of landing. Three landing years are used for CE immigrants rather than one to increase the sample size. To ensure that CE immigrants who landed in different years are comparable with each other and with the Canadian‑born population and FE immigrants, the study is restricted to a maximum of 20 years of follow‑up, and regional economic conditions in each year when earnings were observed are controlled for, as are individual‑level sociodemographic characteristics. Similarly, the 2006 cohort includes the Canadian‑born population aged 25 to 34 in 2006, FE immigrants who arrived in Canada and were aged 25 to 34 in 2006, and CE immigrants who became landed immigrants from 2005 to 2007 and were aged 25 to 34 in the year of landing. This cohort is restricted to a maximum of six years of follow‑up. All annual earnings are adjusted to 2013 constant dollars. In any given year, only people with at least $1,000 in annual earnings are included in regression model estimations. ### 2.2 Measures The outcome variable is annual employment earnings, which include total wages or salaries and positive net self‑employment income. The tax file does not contain information on working time (weeks or hours worked), so it is not possible to derive wage rates. Real annual earnings are top‑coded at$300,000. The natural logarithm of real annual earnings is used in multivariate models. Since most immigrants cannot have a full year of employment in the calendar year when they first arrive, the earnings trajectories of all immigrants begin from the first full calendar year after immigration (e.g., for those who landed in 1991, 1992 was their first full year).

Three sets of explanatory variables are considered in accounting for group differences in earnings. One set is common to all three groups. The second set is specific to the Canadian‑born population and CE immigrants, and the third is specific to CE and FE immigrants.

The first set includes age in the base year and its squared term, years since the base year and their squared term, months of full‑time school attendance in each tax yearNote  and educational level (bachelor’s degree and graduate degree). It also includes official language (English, French and others), visible minority status (visible minority and non‑visible minority)Note  and geographic region of residence in each tax year (Atlantic region, Quebec, Ontario, Manitoba and Saskatchewan, Alberta, and British Columbia). And, it includes macroeconomic conditions as measured by regional unemployment rates among the population of prime working ages in the year when earnings are observed.

The variables that are applicable only to the Canadian‑born population and CE immigrants include years with positive earnings in Canada prior to the base year and the earnings level in Canada prior to the base year. The former is a conventional indicator of labour market work experience, while the latter represents the realized market value of individuals’ job skills. The years with prior positive earnings are top‑coded at 10, since information before 1982 is not available in the tax file. The level of prior earnings is measured as the maximum annual earnings prior to the base year in 2013 constant dollars, and it is coded into four categories: no prior earnings, low annual earnings ($20,000 or less), medium earnings ($20,000 to $50,000) and high earnings (over$50,000).

The variables that are applicable to both CE immigrants and FE immigrants include immigration class and several source‑country characteristics. Immigration class is coded as skilled worker class, other economic class, family class, refugees and others. Previous Canadian studies have shown that labour market outcomes vary considerably by immigration class even after commonly measured human capital variables are controlled for (Hou and Picot 2014; Abbott and Beach 2011). Source‑country characteristics include log gross domestic product (GDP) per capita (adjusted for purchasing power parity and measured in 2011 constant U.S. dollars),Note  quality of tertiary education (with scores ranging from 33 to 100),Note  whether English is an official language and whether French is an official language.

Finally, the TRF contains a variable that is specific to CE immigrants—years of Canadian study—which is measured as the number of years in which a valid study permit was held in the 10 years prior to landing. This variable is used to capture the general acculturation effect. CE immigrants in this study all had a Canadian university education. When the educational level is controlled for (i.e., bachelor’s degree versus graduate degree), more years of studying in Canada are likely associated with a high degree of acculturation in terms of mastering one or both of the official languages, establishing social networks, and gaining knowledge about the Canadian labour market and society.

### 2.3 Methods

Descriptive statistics are first produced to show the overall differences among the Canadian‑born population, CE immigrants and FE immigrants in earnings trajectories and sociodemographic characteristics. Multivariate regression models are estimated to examine the extent to which the observed group differences in earnings can be accounted for by group differences in sociodemographic characteristics. To simplify the presentation, separate models are estimated to compare CE immigrants with the Canadian‑born population and to compare CE immigrants with FE immigrants, since some key explanatory variables are not available for all three groups.

Three sequential models are constructed to compare CE immigrants with Canadian‑born workers:

Model 1 replicates the observed differences in log earnings trajectories between CE immigrants and the Canadian‑born population, with the assumption that the earnings growth takes a quadratic function of years since the base year ( $YS$ ) and the quadratic function is different between the two groups. $CE$ is a dummy variable (CE immigrants = 1, and the Canadian‑born population = 0). Model 2 adds in sociodemographic and macroeconomic conditions ( $X$ ) as discussed above in Subsection 2.2. Model 3 adds in years of work experience and the earnings level ( $P$ ) in Canada prior to the base year.

Similarly, three models are estimated to compare CE and FE immigrants, with two differences. Model 2 also includes immigration class and source‑country characteristics, which are specific to immigrants. In Model 3, years of work experience, the earnings level in Canada prior to the base year and years of Canadian study are added. These variables are not available for FE immigrants and thus should be interpreted as conditional interaction terms.

Although individuals are followed longitudinally starting from the base year in the study data, these data are not a balanced panel consisting of individuals who were employed in all years. The advantage of using this unbalanced panel is that the analysis can capture all individuals who ever worked in any given year, thus providing a fuller picture of the economic performance of immigrants. This is particularly important for CE immigrants, who are more likely to pursue further studies after the base year than FE immigrants and the Canadian‑born population (as shown below in Tables 1 and 2). To check the robustness of the results, the analyses are also conducted for a more restricted sample: individuals who had non‑trivial annual earnings (i.e., over $1,000) in at least 15 years (out of a possible 20 total years of observation) for the 1991 cohort and in at least 4 years (out of a maximum of 6 years) for the 2006 cohort. The conclusions on group differences in earnings trajectories from these restrictive samples are essentially the same as those from the unbalanced sample. In regression models, cluster‑robust standard errors are estimated to correct the independence among multiple observations of the same individual. Alternatively, random effects models are estimated and the results are broadly similar.Note All models are estimated separately for men and women. ## 3 Empirical results ### 3.1 Group differences in explanatory factors and earnings Table 1 presents descriptive statistics that show differences in explanatory variables between university‑educated Canadian‑born men, CE immigrant men and FE immigrant men for the 1991 and 2006 cohorts. Table 2 is for women. Compared with the other two groups, CE immigrants tended to be slightly younger by half a year to one and a half years, depending on cohort and gender. A much higher share of them had a graduate degree, and they were more likely to undertake further education after the base year. CE immigrants were also more likely to belong to visible minority groups. For instance, in the 2006 cohort, 85% of CE immigrant men belonged to a visible minority, while the corresponding share was 10% for Canadian‑born men and 79% for FE immigrants. These group differences were similar in the 1991 and 2006 cohorts. 1991 cohort 2006 cohort Canadian-born men Canadian-educated immigrants Foreign-educated immigrants Canadian-born men 60,303 31,025 24,294 63,099 36,730 31,343 10.77 9.98 9.74 10.80 10.14 10.05 10.36 9.46 10.12 3.50 3.43 3.52 29.66 29.10 29.51 29.41 28.42 30.23 7.29 7.06 6.82 5.96 5.98 5.99 7.04 2.97 Note ...: not applicable 7.34 3.16 Note ...: not applicable Note ...: not applicable 3.96 Note ...: not applicable Note ...: not applicable 3.84 Note ...: not applicable Note ...: not applicable 50.15 47.16 Note ...: not applicable 46.27 43.89 Note ...: not applicable 8.00 7.77 Note ...: not applicable 7.63 7.44 0.25 0.49 0.21 0.24 0.45 0.33 0.08 0.29 0.12 0.58 1.62 0.60 0.33 0.06 0.05 0.25 0.04 0.04 Note ...: not applicable 0.03 0.23 Note ...: not applicable 0.01 0.08 0.04 0.91 0.76 0.10 0.85 0.79 0.07 0.03 0.01 0.06 0.03 0.01 0.28 0.19 0.16 0.23 0.25 0.23 0.06 0.04 0.02 0.06 0.04 0.04 0.11 0.10 0.08 0.11 0.15 0.13 0.09 0.17 0.18 0.11 0.13 0.13 Note ...: not applicable 0.62 0.29 Note ...: not applicable 0.77 0.69 Note ...: not applicable 0.03 0.06 Note ...: not applicable 0.05 0.10 Note ...: not applicable 0.25 0.43 Note ...: not applicable 0.14 0.19 Note ...: not applicable 0.10 0.21 Note ...: not applicable 0.04 0.02 Note ...: not applicable 0.29 0.51 Note ...: not applicable 0.30 0.41 Note ...: not applicable 0.08 0.03 Note ...: not applicable 0.15 0.07 0.01 0.09 Note ...: not applicable 0.00 0.12 Note ...: not applicable 0.08 0.40 Note ...: not applicable 0.11 0.40 Note ...: not applicable 0.29 0.37 Note ...: not applicable 0.32 0.35 Note ...: not applicable 0.62 0.14 Note ...: not applicable 0.57 0.14 Note ...: not applicable 4,523 3,176 4,191 7,714 7,730 9,615 79,574 37,872 56,836 43,788 37,660 48,265 ... not applicable Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. 1991 cohort 2006 cohort Canadian-born women Canadian-educated immigrants Foreign-educated immigrants Canadian-born women 44,506 26,086 19,130 47,677 30,677 20,855 10.45 9.78 9.50 10.52 9.97 9.58 10.45 9.81 10.55 3.50 3.41 3.54 29.49 28.57 29.15 29.36 28.03 29.37 7.25 6.94 6.66 6.07 5.99 5.95 6.97 2.59 Note ...: not applicable 7.48 3.09 Note ...: not applicable Note ...: not applicable 3.55 Note ...: not applicable Note ...: not applicable 3.92 Note ...: not applicable Note ...: not applicable 54.19 48.51 Note ...: not applicable 49.85 44.55 Note ...: not applicable 8.42 7.93 Note ...: not applicable 8.07 7.53 0.24 0.34 0.17 0.26 0.40 0.30 0.10 0.23 0.14 0.51 1.39 0.62 0.30 0.05 0.04 0.28 0.03 0.04 0.00 0.04 0.24 0.00 0.01 0.11 0.04 0.85 0.71 0.09 0.80 0.75 0.08 0.02 0.01 0.08 0.02 0.01 0.26 0.16 0.13 0.26 0.24 0.21 0.06 0.04 0.04 0.05 0.04 0.05 0.10 0.07 0.07 0.10 0.11 0.13 0.09 0.19 0.18 0.11 0.18 0.15 Note ...: not applicable 0.43 0.15 Note ...: not applicable 0.58 0.35 Note ...: not applicable 0.16 0.20 Note ...: not applicable 0.10 0.33 Note ...: not applicable 0.33 0.48 Note ...: not applicable 0.28 0.31 Note ...: not applicable 0.08 0.18 Note ...: not applicable 0.04 0.02 Note ...: not applicable 0.36 0.54 Note ...: not applicable 0.18 0.41 Note ...: not applicable 0.06 0.02 Note ...: not applicable 0.13 0.05 0.01 0.14 Note ...: not applicable 0.00 0.16 Note ...: not applicable 0.09 0.43 Note ...: not applicable 0.11 0.42 Note ...: not applicable 0.41 0.35 Note ...: not applicable 0.41 0.33 Note ...: not applicable 0.48 0.08 Note ...: not applicable 0.47 0.09 Note ...: not applicable 4,716 1,661 3,353 11,564 5,912 9,629 80,635 20,005 44,300 64,446 27,304 42,614 ... not applicable Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. The average months of study in the earnings year increased for all three groups from the 1991 cohort to the 2006 cohort. This increase was due to two factors. First, the latter cohort was followed for only 6 years, while the former was followed for 20 years. The likelihood of undertaking additional study was higher in the first few years in the follow‑up.Note Second, there was an increase in the average months of study for a given follow‑up year between the 1991 and 2006 cohorts. For instance, in the first follow‑up year, the average months of study increased from 0.15 to 0.92 for Canadian‑born men, from 0.81 to 3.12 for CE immigrants and from 0.15 to 0.65 for FE immigrants. Relative to the Canadian‑born population, proportionally more CE immigrants did not work or had low earnings in Canada. For instance, in the 2006 cohort, about 14% of CE immigrant men had high earnings in Canada before the base year, compared with 62% of Canadian‑born men. About 12% of CE immigrant men never worked in Canada before the base year, while almost all Canadian‑born men had positive earnings in at least one year. CE immigrants also had about four fewer years of work experience in Canada than the Canadian‑born population. These gaps in work history could result from a variety of factors: pursuing education beyond the bachelor’s level at a higher rate, starting Canadian university education at a later age and having more difficulties in finding a job after graduation. Relative to FE immigrants, CE immigrants were more likely to be admitted in the skilled worker class, particularly in the 1991 cohort. CE immigrants tended to come from countries with higher‑quality tertiary education and a higher GDP per capita, but they were less likely to come from countries with English as an official language. Essentially all CE immigrants could speak an official language of Canada, but 8% of FE immigrant men and 11% of FE immigrant women could not in the 2006 cohort. Charts 1 to 4 present earnings trajectories among individuals with only a bachelor’s degree by immigration status, sex and cohort. Since a much higher share of CE immigrants have a graduate degree, comparing earnings at the same educational level could take into account group differences in educational level. Charts for individuals with a graduate degree showed similar patterns and are not reproduced here. Data table for Chart 1 Data table for Chart 1 Table summary This table displays the results of Data table for Chart 1. The information is grouped by Years since the base year (appearing as row headers), Canadian-born population, Canadian-educated immigrants and Foreign-educated immigrants, calculated using log annual earnings (2013 dollars) units of measure (appearing as column headers). Years since the base year Canadian-born population Canadian-educated immigrants Foreign-educated immigrants log annual earnings (2013 dollars) 1 10.75 9.90 9.72 2 10.81 10.01 9.88 3 10.85 10.16 10.01 4 10.93 10.28 10.14 5 10.96 10.37 10.23 6 11.02 10.47 10.34 7 11.08 10.54 10.45 8 11.15 10.66 10.51 9 11.18 10.72 10.58 10 11.24 10.76 10.60 11 11.26 10.77 10.62 12 11.26 10.74 10.61 13 11.25 10.79 10.64 14 11.28 10.84 10.68 15 11.32 10.90 10.70 16 11.36 10.89 10.73 17 11.38 10.93 10.74 18 11.39 10.86 10.69 19 11.37 10.88 10.70 20 11.36 10.95 10.71 Data table for Chart 2 Data table for Chart 2 Table summary This table displays the results of Data table for Chart 2. The information is grouped by Years since the base year (appearing as row headers), Canadian-born population, Canadian-educated immigrants and Foreign-educated immigrants, calculated using log annual earnings (2013 dollars) units of measure (appearing as column headers). Years since the base year Canadian-born population Canadian-educated immigrants Foreign-educated immigrants log annual earnings (2013 dollars) 1 10.40 9.73 9.49 2 10.43 9.88 9.63 3 10.48 9.94 9.73 4 10.50 10.04 9.85 5 10.48 10.09 9.92 6 10.53 10.27 9.98 7 10.59 10.34 10.08 8 10.65 10.45 10.17 9 10.70 10.48 10.24 10 10.72 10.45 10.27 11 10.74 10.48 10.30 12 10.75 10.51 10.33 13 10.77 10.53 10.38 14 10.81 10.57 10.40 15 10.84 10.64 10.42 16 10.87 10.68 10.48 17 10.91 10.76 10.50 18 10.92 10.74 10.49 19 10.94 10.71 10.52 20 10.95 10.73 10.51 Data table for Chart 3 Data table for Chart 3 Table summary This table displays the results of Data table for Chart 3. The information is grouped by Years since the base year (appearing as row headers), Canadian-born population, Canadian-educated immigrants and Foreign-educated immigrants, calculated using log annual earnings (2013 dollars) units of measure (appearing as column headers). Years since the base year Canadian-born population Canadian-educated immigrants Foreign-educated immigrants log annual earnings (2013 dollars) 1 10.88 10.23 10.06 2 10.98 10.41 10.24 3 11.05 10.50 10.27 4 11.10 10.59 10.37 5 11.14 10.67 10.45 6 11.18 10.76 10.54 Data table for Chart 4 Data table for Chart 4 Table summary This table displays the results of Data table for Chart 4. The information is grouped by Years since the base year (appearing as row headers), Canadian-born population, Canadian-educated immigrants and Foreign-educated immigrants, calculated using log annual earnings (2013 dollars) units of measure (appearing as column headers). Years since the base year Canadian-born population Canadian-educated immigrants Foreign-educated immigrants log annual earnings (2013 dollars) 1 10.51 10.01 9.58 2 10.54 10.13 9.73 3 10.59 10.18 9.81 4 10.64 10.23 9.86 5 10.67 10.30 9.97 6 10.72 10.34 10.04 In Chart 1, CE immigrant men with a bachelor’s degree in the 1991 cohort had a very large earnings gap, at -0.84 log point, relative to Canadian‑born men with the same level of education (i.e., CE immigrants earned 43% of the average earnings of Canadian‑born men $\left[exp\left(-0.84\right)=43%\right]$ ) in the first year after the base year. The gap narrowed to -0.37 log point 10 years after the base year (i.e., CE immigrants earned 69% of the average earnings of Canadian‑born men); the gap stabilized afterwards. Relative to FE immigrants, CE immigrant men had higher initial earnings, by 0.19 log point (or about 21%), and the advantage barely changed over the 20‑year follow‑up period. Similar patterns of group differences were observed for women in Chart 2. Relative to their male counterparts, CE immigrant women had a smaller gap in earnings with the Canadian‑born population, while their advantage over FE immigrants in earnings was somewhat larger. CE immigrant women had a large earnings gap, at -0.67 log point, relative to Canadian‑born women with the same education level (or 49% lower than the average for Canadian‑born women) in the first year. This gap narrowed to -0.27 log point (or 20% lower than the average for Canadian‑born women) by the 10th year and remained stable afterwards. The patterns of group differences in earnings trajectories for the 2006 cohort (Charts 3 and 4) are broadly similar to those for the 1991 cohort. One discernible change is that the advantage of CE immigrant women relative to FE immigrant women was larger in the 2006 cohort than in the 1991 cohort. This is because CE immigrants experienced a much larger increase in earnings between the 1991 and 2006 cohorts than FE immigrant women. ### 3.2 Comparing Canadian‑educated immigrants with the Canadian‑born population Table 3 presents the results of multivariate regression models that compare the earnings of university‑educated CE immigrant men and Canadian‑born men and factors associated with their earnings gaps for the 1991 and 2006 cohorts. Table 4 presents the same models for women. The first three models in Table 3 were estimated for the 1991 cohort. Model 1 shows that there was a very large initial earnings gap between CE immigrant men and Canadian‑born men (-0.760 log point, or CE immigrants earned about 46% of what Canadian‑born men earned). The earnings of CE immigrant men grew more rapidly, as indicated by the positive interaction term between CE immigrants and years since the base year. However, they could not catch up with those of the Canadian‑born population because their growth rate started to level off after about 10 years, as indicated by the negative interaction term between CE immigrants and squared years since the base year. When the sociodemographic control variables were added for Model 2, the initial earnings gap of CE immigrants decreased from -0.760 to -0.549 log point. This decrease in the estimated earnings gap was mostly attributable to the high share of visible minorities among CE immigrants; visible minorities had a large earnings gap (-0.193 log point) with the white group. When variables representing work history before the base year were added for Model 3, the initial earnings gap of CE immigrants was further reduced to -0.245 log point. Having high earnings before the base year was associated with a very large earnings advantage (0.800 log point), while having medium earnings before the base year was associated with a moderate earnings advantage (0.241 log point). In contrast, having low earnings before the base year was not associated with any significant earnings advantage after the base year. One year of Canadian work experience before the base year was associated with higher earnings of 0.030 log point in the years after the base year. The effect of the earnings level in Canada before immigration was about three times as large as the effect of years of prior work experience, in terms of the contribution to the decrease in the earnings gap of CE immigrants from Model 2 to Model 3.Note In addition, the large and significant coefficient of visible minority status in Model 2 became non‑significant in Model 3. This change suggests that a lower share of people who belong to a visible minority had high earnings in the early stage of their careers. The three models in the right panel were estimated for CE immigrant men and Canadian‑born men in the 2006 cohort. As with the 1991 cohort, the earnings gap of CE immigrants became smaller from Model 1 to Model 2 and was further reduced from Model 2 to Model 3, becoming not statistically significant. The reduction in the gap from Model 1 to Model 2 was mostly attributable to the inclusion of visible minority status and months of study, as most CE immigrants belonged to a visible minority, and they spent more months studying after the base year than the Canadian‑born population. The decrease in the earnings gap from Model 2 to Model 3 was almost entirely attributable to the earnings level before immigration. Years of prior work experience were not a significant predictor of earnings for the 2006 cohort. Compared with the results for the 1991 cohort, the effect of the earnings level before immigration became much stronger for the 2006 cohort. Even individuals with low earnings had a significant earnings advantage over those who did not work before the base year. 1991 cohort 2006 cohort Model 1 Model 2 Model 3 Model 1 -0.760Note *** -0.549Note *** -0.245Note *** -0.660Note *** -0.324Note *** 0.003 0.074Note *** 0.066Note *** 0.068Note *** 0.101Note *** 0.089Note *** 0.098Note *** -0.002Note *** -0.002Note *** -0.002Note *** -0.007Note *** -0.006Note *** -0.007Note *** 0.071Note *** 0.056Note *** 0.062Note *** 0.105Note *** 0.032Note *** 0.055Note *** -0.003Note *** -0.002Note *** -0.002Note *** -0.007Note ** -0.002 -0.004Note * Note ...: not applicable 0.183Note ** -0.070 Note ...: not applicable 0.103 -0.105 Note ...: not applicable -0.003Note ** 0.001 Note ...: not applicable -0.001 0.002 Note ...: not applicable 0.227Note *** 0.218Note *** Note ...: not applicable 0.144Note *** 0.149Note *** Note ...: not applicable -0.180Note *** -0.157Note *** Note ...: not applicable -0.101Note *** -0.084Note *** Note ...: not applicable 0.006 0.007 Note ...: not applicable 0.099Note ** 0.059Note * Note ...: not applicable -0.273Note ** -0.211Note ** Note ...: not applicable -0.379Note *** -0.207Note * Note ...: not applicable -0.193Note *** -0.036 Note ...: not applicable -0.125Note ** -0.057 Note ...: not applicable -0.193Note *** -0.122Note *** Note ...: not applicable -0.107Note ** -0.051Note * Note ...: not applicable -0.219Note *** -0.129Note *** Note ...: not applicable -0.287Note ** -0.143Note *** Note ...: not applicable -0.247Note *** -0.186Note *** Note ...: not applicable -0.040 0.004 Note ...: not applicable -0.017 0.005 Note ...: not applicable 0.216Note *** 0.194Note *** Note ...: not applicable -0.207Note *** -0.157Note *** Note ...: not applicable -0.116Note *** -0.081Note *** Note ...: not applicable -0.010Note ** -0.009Note * Note ...: not applicable -0.007 -0.014Note *** Note ...: not applicable Note ...: not applicable 0.039 Note ...: not applicable Note ...: not applicable 0.181Note *** Note ...: not applicable Note ...: not applicable 0.241Note *** Note ...: not applicable Note ...: not applicable 0.559Note *** Note ...: not applicable Note ...: not applicable 0.800Note *** Note ...: not applicable Note ...: not applicable 1.130Note *** Note ...: not applicable Note ...: not applicable 0.030Note *** Note ...: not applicable Note ...: not applicable 0.010 10.758Note *** 8.099Note *** 11.438Note *** 10.807Note *** 9.114Note *** 11.631Note *** ... not applicable Note * significantly different from reference category (p < 0.05) Return to note * referrer Note ** significantly different from reference category (p < 0.01) Return to note ** referrer Note *** significantly different from reference category (p < 0.001) Return to note *** referrer Note: The model R‑squared is 0.150, 0.208 and 0.312 in Models 1, 2 and 3, respectively, for the 1991 cohort; it is 0.108, 0.257 and 0.393 in Models 1, 2 and 3, respectively, for the 2006 cohort. Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. The results of the multivariate models comparing CE immigrant women and Canadian‑born women in Table 4 are generally similar to those for men. One noticeable difference for women is that visible minority status was not associated with an earnings disadvantage for either the 1991 cohort or the 2006 cohort. As a result, controlling for visible minority status made very little change in the earnings gap of CE immigrant women from Model 1 to Model 2 in the 1991 cohort. The relatively large decrease in the earnings gap of CE immigrants from Model 1 to Model 2 for the 2006 cohort was due mostly to the group difference in months of study. As with men, the disadvantages in the earnings level before the base year and in the years of work experience before the base year accounted for about one‑half for the 1991 cohort or essentially all for the 2006 cohort of the earnings gap of CE immigrant women. In terms of the contribution to the earnings gap, the effect of the earnings level was about five times that of years of Canadian work experience for both the 1991 cohort and the 2006 cohort. 1991 cohort 2006 cohort Model 1 Model 2 Model 3 Model 1 -0.617Note *** -0.624Note *** -0.343Note *** -0.540Note *** -0.374Note *** -0.021 0.040Note *** 0.038Note *** 0.037Note *** 0.060Note *** 0.046Note *** 0.052Note *** 0.000Note *** 0.000Note ** 0.000Note * -0.002 -0.001 -0.001 0.071Note *** 0.067Note *** 0.070Note *** 0.061Note *** 0.032Note * 0.047Note *** -0.003Note *** -0.003Note *** -0.003Note *** -0.005 -0.004 -0.005Note * Note ...: not applicable -0.054 -0.270Note *** Note ...: not applicable -0.164Note ** -0.290Note *** Note ...: not applicable 0.001 0.004Note *** Note ...: not applicable 0.003Note ** 0.005Note *** Note ...: not applicable 0.276Note *** 0.235Note *** Note ...: not applicable 0.201Note *** 0.170Note *** Note ...: not applicable -0.109Note *** -0.091Note *** Note ...: not applicable -0.087Note *** -0.074Note *** Note ...: not applicable 0.082Note ** 0.093Note *** Note ...: not applicable 0.103Note *** 0.071Note ** Note ...: not applicable -0.178 -0.107 Note ...: not applicable -0.163 0.005 Note ...: not applicable 0.046 0.144Note *** Note ...: not applicable -0.020 0.020 Note ...: not applicable -0.148Note *** -0.086Note * Note ...: not applicable -0.060Note * 0.015 Note ...: not applicable -0.151Note *** -0.065Note * Note ...: not applicable -0.253Note *** -0.125Note *** Note ...: not applicable -0.211Note *** -0.168Note *** Note ...: not applicable -0.057Note * -0.024 Note ...: not applicable -0.067Note * -0.088Note ** Note ...: not applicable 0.066Note * 0.047 Note ...: not applicable -0.167Note *** -0.106Note *** Note ...: not applicable -0.127Note *** -0.071Note ** Note ...: not applicable -0.003 -0.007 Note ...: not applicable -0.007 -0.009Note * Note ...: not applicable Note ...: not applicable 0.078 Note ...: not applicable Note ...: not applicable 0.252Note *** Note ...: not applicable Note ...: not applicable 0.355Note *** Note ...: not applicable Note ...: not applicable 0.573Note *** Note ...: not applicable Note ...: not applicable 0.822Note *** Note ...: not applicable Note ...: not applicable 1.078Note *** Note ...: not applicable Note ...: not applicable 0.015Note * Note ...: not applicable Note ...: not applicable 0.017Note ** 10.448Note *** 11.086Note *** 13.935Note *** 10.522Note *** 12.881Note *** 14.172Note *** ... not applicable Note * significantly different from reference category (p < 0.05) Return to note * referrer Note ** significantly different from reference category (p < 0.01) Return to note ** referrer Note *** significantly different from reference category (p < 0.001) Return to note *** referrer Note: The model R‑squared is 0.077, 0.115, and 0.201 in Models 1, 2 and 3, respectively, for the 1991 cohort; it is 0.066, 0.146, and 0.250 in Models 1, 2 and 3, respectively, for the 2006 cohort. Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. ### 3.3 Comparing Canadian‑educated and foreign‑educated immigrants Table 5 presents the results of multivariate regression models that compare the earnings of university‑educated CE and FE immigrant men and factors associated with their earnings gaps for the 1991 and 2006 cohorts. The three models in the left panel in Table 5 are for the 1991 cohort. CE immigrant men had higher initial earnings (0.210 log point) and a higher growth rate (about 0.012 log point per year) than FE immigrants. After sociodemographic characteristics and source‑country attributes were controlled for in Model 2, the initial earnings advantage of CE immigrants narrowed slightly to 0.177 log point, and they no longer had a higher growth rate relative to FE immigrants. These changes were attributable mostly to the larger share of CE immigrants with a graduate degree and the smaller share not speaking English or French. Although the included source‑country attributes did not contribute much to the earnings differences between CE and FE immigrants, they were significant predictors of the earnings of university‑educated immigrants. In particular, a 10% increase in source‑country GDP per capita (adjusted for purchasing power parity) was associated with a 0.53% increase in immigrant earnings. Immigrants from source countries with English or French as the (or an) official language earned more than those from countries with another language as the official language. The negative effect of the quality of tertiary education in the source country seemed counterintuitive. This was because of the control of source‑country GDP per capita. Without such a control, the effect of the quality of tertiary education in the source country was positive and moderate.Note When the conditional interaction terms of work history and years of study in Canada among CE immigrants (variables that do not apply to FE immigrants, as mentioned in Subsection 2.3) were included in Model 3 for the 1991 cohort (Table 5), the coefficient for CE immigrants became negative and significant at -0.208 log point. This negative coefficient implies that CE immigrants who did not have any Canadian work history before they became permanent residents earned significantly less than otherwise observably equivalent FE immigrants. This point is further illustrated in Table 7, which presents the estimated earnings gap between FE immigrants and CE immigrants with various combinations of Canadian work history and years of study in Canada, based on the regression coefficients in Model 3. The choice of four years of study in Canada and three years of Canadian work experience before immigration for CE immigrants in the estimation was based on the observed averages for these two variables as reported in Tables 1 and 2. 1991 cohort 2006 cohort Model 1 Model 2 Model 3 Model 1 0.210Note *** 0.177Note *** -0.208Note *** 0.072Note *** 0.250Note *** -0.138Note *** 0.133Note *** 0.114Note *** 0.114Note *** 0.124Note *** 0.176Note *** 0.180Note *** -0.005Note *** -0.004Note *** -0.004Note *** -0.006Note *** -0.016Note *** -0.016Note *** 0.012Note * 0.001 0.004 0.081Note *** -0.020Note * -0.007 0.000 0.000 0.000 -0.008Note *** 0.003 0.002 Note ...: not applicable 0.084 0.076 Note ...: not applicable 0.103Note * 0.091Note * Note ...: not applicable -0.002 -0.001 Note ...: not applicable -0.002Note ** -0.002Note * Note ...: not applicable 0.246Note *** 0.203Note *** Note ...: not applicable 0.070Note *** 0.060Note *** Note ...: not applicable -0.150Note *** -0.141Note *** Note ...: not applicable -0.091Note *** -0.086Note *** Note ...: not applicable -0.161Note ** -0.150Note *** Note ...: not applicable -0.075Note ** -0.072Note ** Note ...: not applicable -0.299Note *** -0.301Note *** Note ...: not applicable -0.265Note *** -0.263Note *** Note ...: not applicable -0.282Note *** -0.276Note *** Note ...: not applicable -0.105Note *** -0.076Note *** Note ...: not applicable 0.111 0.116 Note ...: not applicable 0.154Note *** 0.130Note *** Note ...: not applicable -0.177Note *** -0.162Note *** Note ...: not applicable -0.213Note *** -0.161Note *** Note ...: not applicable -0.103Note ** -0.094Note * Note ...: not applicable 0.007 0.007 Note ...: not applicable -0.018 -0.025 Note ...: not applicable 0.247Note *** 0.228Note *** Note ...: not applicable -0.194Note *** -0.180Note *** Note ...: not applicable -0.036Note * -0.037Note * Note ...: not applicable -0.028Note *** -0.028Note *** Note ...: not applicable -0.032Note *** -0.036Note *** Note ...: not applicable -0.096Note * -0.068 Note ...: not applicable -0.147Note *** -0.117Note *** Note ...: not applicable -0.196Note *** -0.159Note *** Note ...: not applicable -0.233Note *** -0.177Note *** Note ...: not applicable -0.180Note *** -0.183Note *** Note ...: not applicable -0.422Note *** -0.389Note *** Note ...: not applicable -0.004Note ** -0.002Note * Note ...: not applicable 0.000 0.000 Note ...: not applicable 0.053Note *** 0.041Note *** Note ...: not applicable 0.050Note *** 0.044Note *** Note ...: not applicable 0.187Note *** 0.119Note *** Note ...: not applicable 0.139Note *** 0.103Note *** Note ...: not applicable 0.102Note * 0.109Note * Note ...: not applicable 0.039Note * 0.075Note *** Note ...: not applicable Note ...: not applicable 0.110 Note ...: not applicable Note ...: not applicable 0.221Note *** Note ...: not applicable Note ...: not applicable 0.288Note *** Note ...: not applicable Note ...: not applicable 0.539Note *** Note ...: not applicable Note ...: not applicable 0.690Note *** Note ...: not applicable Note ...: not applicable 0.972Note *** Note ...: not applicable Note ...: not applicable 0.023Note * Note ...: not applicable Note ...: not applicable 0.012Note * Note ...: not applicable Note ...: not applicable 0.015Note * Note ...: not applicable Note ...: not applicable -0.020Note *** 9.788Note *** 9.124Note *** 9.319Note *** 10.075Note *** 8.796Note *** 8.956Note *** ... not applicable Note * significantly different from reference category (p < 0.05) Return to note * referrer Note ** significantly different from reference category (p < 0.01) Return to note ** referrer Note *** significantly different from reference category (p < 0.001) Return to note *** referrer Note: The model R‑squared is 0.132, 0.214 and 0.235 in Models 1, 2 and 3, respectively, for the 1991 cohort; it is 0.054, 0.194 and 0.236 in Models 1, 2 and 3, respectively, for the 2006 cohort. Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. 1991 cohort 2006 cohort Model 1 Model 2 Model 3 Model 1 0.290Note *** 0.211Note *** -0.062 0.384Note *** 0.422Note *** 0.049 0.108Note *** 0.098Note *** 0.098Note *** 0.114Note *** 0.148Note *** 0.153Note *** -0.003Note *** -0.002Note *** -0.003Note *** -0.005Note *** -0.011Note *** -0.012Note *** 0.004 -0.002 0.001 0.007 -0.053Note *** -0.042Note *** 0.000 0.000 0.000 -0.002 0.004 0.003 Note ...: not applicable 0.082 0.068 Note ...: not applicable -0.059 -0.045 Note ...: not applicable -0.001 -0.001 Note ...: not applicable 0.001 0.001 Note ...: not applicable 0.188Note *** 0.160Note *** Note ...: not applicable 0.050Note *** 0.037Note ** Note ...: not applicable -0.090Note *** -0.085Note *** Note ...: not applicable -0.077Note *** -0.072Note *** Note ...: not applicable -0.046 -0.040 Note ...: not applicable -0.100Note *** -0.117Note *** Note ...: not applicable -0.323Note *** -0.329Note *** Note ...: not applicable -0.206Note *** -0.204Note *** Note ...: not applicable -0.127Note ** -0.128Note *** Note ...: not applicable -0.073Note *** -0.072Note *** Note ...: not applicable -0.277Note ** -0.219Note * Note ...: not applicable 0.073 0.066 Note ...: not applicable -0.210Note *** -0.188Note *** Note ...: not applicable -0.232Note *** -0.179Note *** Note ...: not applicable -0.223Note *** -0.200Note *** Note ...: not applicable 0.023 0.019 Note ...: not applicable -0.076Note * -0.075Note * Note ...: not applicable 0.173Note *** 0.140Note *** Note ...: not applicable -0.140Note *** -0.125Note *** Note ...: not applicable -0.066Note *** -0.061Note *** Note ...: not applicable -0.019Note *** -0.019Note ** Note ...: not applicable -0.016Note ** -0.020Note *** Note ...: not applicable -0.165Note *** -0.136Note *** Note ...: not applicable -0.317Note *** -0.283Note *** Note ...: not applicable -0.267Note *** -0.241Note *** Note ...: not applicable -0.384Note *** -0.320Note *** Note ...: not applicable -0.248Note *** -0.232Note *** Note ...: not applicable -0.525Note *** -0.457Note *** Note ...: not applicable -0.004Note ** -0.003Note * Note ...: not applicable 0.001 0.000 Note ...: not applicable 0.059Note *** 0.045Note ** Note ...: not applicable 0.052Note *** 0.046Note *** Note ...: not applicable 0.104Note *** 0.066Note * Note ...: not applicable 0.073Note *** 0.055Note *** Note ...: not applicable -0.122Note * -0.121Note * Note ...: not applicable 0.019 0.042 Note ...: not applicable Note ...: not applicable 0.101 Note ...: not applicable Note ...: not applicable 0.245Note *** Note ...: not applicable Note ...: not applicable 0.328Note *** Note ...: not applicable Note ...: not applicable 0.550Note *** Note ...: not applicable Note ...: not applicable 0.756Note *** Note ...: not applicable Note ...: not applicable 0.994Note *** Note ...: not applicable Note ...: not applicable -0.005 Note ...: not applicable Note ...: not applicable -0.001 Note ...: not applicable Note ...: not applicable 0.016Note * Note ...: not applicable Note ...: not applicable -0.002 9.541Note *** 8.565Note *** 8.869Note *** 9.598Note *** 10.545Note *** 10.368Note *** ... not applicable Note * significantly different from reference category (p < 0.05) Return to note * referrer Note ** significantly different from reference category (p < 0.01) Return to note ** referrer Note *** significantly different from reference category (p < 0.001) Return to note *** referrer Note: The model R‑squared is 0.117, 0.171 and 0.184 in Models 1, 2 and 3, respectively, for the 1991 cohort; it is 0.056, 0.151 and 0.178 in Models 1, 2 and 3, respectively, for the 2006 cohort. Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. Table 7 shows that CE immigrant men in the 1991 cohort with four years of study in Canada but no Canadian work experience before immigration earned less than observably equivalent FE immigrants in both the initial years after landing and the long term. CE immigrant men with four years of study in Canada and three years of experience with low earnings performed similarly to FE immigrants in the initial years after immigration but slightly better in the long term. However, CE immigrants with medium or high earnings in Canada before immigration had much higher earnings than FE immigrants in both the short term and the long term. These estimates clearly suggest that having medium or high earnings in Canada before immigration was the key factor that put CE immigrants at an advantage over FE immigrants after immigration. Years of Canadian work experience or years of Canadian education mattered much less. As will be further discussed below, the earnings level before immigration likely reflects the observed and unobserved skills of CE immigrants and the match between skills and labour market demand. The pattern of earnings differences between CE and FE immigrant men in the 2006 cohort is generally similar to that observed in the 1991 cohort. Model 1—in the right panel of Table 5 for the 2006 cohort—shows that CE immigrants on average had higher initial earnings, by 0.072 log point, and more rapid earnings growth than FE immigrants. When sociodemographic factors are controlled for, CE immigrants had an even larger advantage in initial earnings, by 0.250 log point, but a smaller growth rate than FE immigrants. These changes were due to CE immigrants spending more months studying after immigration. Model 3 in Table 5 and the estimated earnings differences in Table 7 between FE immigrants and CE immigrants with various combinations of Canadian work history and years of Canadian study show that only CE immigrants with medium or high earnings in Canada before immigration had a large earnings advantage over FE immigrants after immigration. The effect on post‑immigration earnings of having medium or high earnings before immigration was much stronger in the 2006 cohort than the 1991 cohort, while the effect of years of prior Canadian work experience was smaller. The effect of years of study in Canada was positive in the 1991 cohort but negative in the 2006 cohort. Table 6 presents the multivariate regression for university‑educated CE and FE immigrant women that corresponds to Table 5 for men. The overall patterns of earnings differences between CE and FE immigrant women were similar to those of men, with a few minor differences. The advantage of CE immigrant women in initial earnings was larger than that of men, so they did not have significantly lower earnings than FE immigrant women even without Canadian work history before immigration (see also Table 7 estimates for women). For the 2006 cohort in particular, CE immigrant women who had low earnings in Canada before immigration earned significantly more than FE immigrants (by 0.284 log point, Table 7). The effect of the earnings level before immigration on post‑immigration earnings was much larger for CE immigrant women than for CE immigrant men. More years of Canadian work or study experience were not associated with an extra gain in post‑immigration earnings for CE immigrant women when the earnings level before immigration was controlled for. Years since immigration 1991 cohort 2006 cohort 1 5 -0.148 -0.132 -0.070 -0.220 -0.223 0.031 0.047 0.108 0.035 0.032 0.208 0.225 0.286 0.354 0.351 0.610 0.626 0.688 0.787 0.784 0.564 0.581 0.642 0.764 0.761 0.003 0.004 -0.012 0.040 -0.073 0.089 0.090 0.075 0.284 0.170 0.317 0.318 0.302 0.588 0.475 0.744 0.746 0.730 1.032 0.919 0.754 0.755 0.739 1.033 0.920 Note: Estimated from Model 3 in Tables 5 and 6. Sources: Statistics Canada, 1991 Census and Longitudinal Worker File linkage; 2006 Census and T1 personal tax file linkage; Temporary Residents File, Immigrant Landing File and T1 personal tax file linkage; and Longitudinal Immigration Database. ## 4 Discussion and conclusion This study compared the earnings trajectories of immigrants who are former international students in Canada (Canadian‑educated [CE] immigrants), foreign‑educated (FE) immigrants and the Canadian‑born population. This is the first comprehensive study in Canada and, to the best of the authors’ knowledge, in any major immigrant‑receiving Western country that uses large national longitudinal datasets to examine cross‑cohort trends and within‑cohort changes in the earnings of former international students who became permanent residents relative to FE immigrants and native‑born workers. The analysis followed the earnings trajectories of university graduates who were aged 25 to 34 in the 1991 and 2006 cohorts. The results showed that CE immigrants who graduated from university had a large earnings gap with their Canadian‑born counterparts both in the initial years after immigration and in the long term. In the first full year after becoming permanent residents, CE immigrant workers earned on average about 50% less (for women) to 60% less (for men) than Canadian‑born workers in the 1991 cohort. This gap narrowed in the first 10 years after immigration to 20% among women and 31% among men, but there was no further catching up afterwards. The narrowing of the initial earnings gap was also observed during the six‑year follow‑up period for the 2006 cohort. Part of the earnings gap was related to the fact that most CE immigrants belonged to a visible minority, and they tended to spend more time pursuing additional education. However, most of the gap could be accounted for by differences in Canadian work history. For both the 1991 cohort and the 2006 cohort, about 50% of CE immigrant men had medium or high earnings in Canada before the base year (the year of immigration), compared with about 90% of Canadian‑born men. When group differences in prior Canadian work history were taken into account, the earnings gap of CE immigrants became much smaller in the 1991 cohort and disappeared in the 2006 cohort. The disadvantage of CE immigrants in prior Canadian work history is certainly endogenous and could originate from a variety of sources: pursuing education beyond the bachelor’s level at a higher rate, resulting in fewer years in the labour force; starting Canadian university education at a later age or taking longer to finish a given level of education; and having more difficulties in finding a good job after graduation because of deficiencies in their social network and language abilities. An investigation of these possible factors requires information that is not available in the administrative data used for this study. Nevertheless, these results suggest that many CE immigrants could not overcome this disadvantage in the initial stage of their career even 20 years after immigration. On average, CE immigrants did have some advantages in post‑immigration earnings over FE immigrants. Their earnings advantage in the first full year after immigration was moderate among men (0.19 log point, or 21%, in the 1991 cohort and 0.17 log point, or 18%, in the 2006 cohort) and somewhat larger among women. The earnings advantage of CE immigrants increased slightly over time among men, mostly because they were more likely to pursue additional education in the initial years after immigration and this tended to reduce their relative earnings in those years. The observed earnings advantage of CE immigrants barely changed when group differences in individual‑level sociodemographic characteristics and source‑country attributes were taken into account. However, the earnings advantages of CE immigrants were concentrated among those who had medium or high earnings in Canada before immigration. CE immigrant men without a Canadian work history before immigration, who made up 9% of all CE immigrants in the 1991 cohort and 12% in the 2006 cohort, earned significantly less than FE immigrants. CE immigrant men who had worked but had had low earnings in Canada before immigration, who made up about 40% of all CE immigrant men, did not have a significant earnings advantage over FE immigrants. Only CE immigrants who had had medium or high earnings before immigration had much higher earnings than FE immigrants, and this advantage was larger in the 2006 cohort than in the 1991 cohort. The post‑immigration earnings of CE immigrant women without prior Canadian work experience were similar to those of FE immigrant women. However, as long as CE immigrant women had prior Canadian work experience, they surpassed FE immigrant women in post‑immigration earnings by a wide margin, particularly in the 2006 cohort. These results may suggest that the level of pre‑landing Canadian earnings plays an increasing role in differentiating the post‑immigration labour market outcomes of university‑educated immigrants. Over the 1990s and 2000s, the share of immigrants with a university degree more than doubled among men and tripled among women; it reached over 50% among prime‑aged immigrants (Hou and Picot 2016). Meanwhile, the earnings returns to university education declined among immigrants both in absolute terms and relative to lower levels of education (Picot, Hou and Qiu 2016). While education might have become less indicative of the earning potential of immigrants, the level of pre‑landing Canadian earnings, as a proven record of success in the Canadian labour market, might come to be more effective in capturing the unobserved skills of immigrants and the match between their skills and labour market demand. Reasons why some international students could find good jobs and have high earnings before immigration while others could not are likely complicated and cannot be addressed by the data used in this study. Labour market demand and supply in particular fields of study, language ability, concentration in certain types of educational institutions and contact with the receiving society are among the possible factors (Hawthorne and To 2014). It is also possible that certain international students may face a labour market barrier that constrains their chance of finding a high‑paying job after finishing their Canadian education. Further understanding of these underlying factors would help more international students become economically successful immigrants. Finally, this study found that an extra year of Canadian work experience or an extra year of Canadian education experience added only a small or no earnings gain after immigration for CE immigrants when earnings level in Canada before immigration was controlled for. This seems to suggest that general acculturation associated with extended exposure to the receiving society was not a strong predictor of post‑immigration earnings when achieved educational attainment and earnings level before immigration are taken into consideration. What matters to CE immigrants was not years of Canadian work or study experience, but the realized market value of the Canadian work or education experience, as indicated by the earnings level in Canada before immigration. ## References Abbott, M.G., and C.M. Beach. 2011. Do Admission Criteria and Economic Recessions Affect Immigrant Earnings? IRPP Study no. 22. Montréal: Institute for Research on Public Policy. Birrell, B., L. Hawthorne, and S. Richardson. 2006. Evaluation of the General Skilled Migration Categories. Canberra: Commonwealth of Australia. Bleakley, H., and A. Chin. 2004. “Language skills and earnings: Evidence from childhood immigrants.” Review of Economics and Statistics 86 (2): 481–496. Bonikowska, A., F. Hou, and G. Picot. 2015. Which Human Capital Characteristics Best Predict the Earnings of Economic Immigrants? Analytical Studies Branch Research Paper Series, no. 368. Statistics Canada Catalogue no. 11F0019M. Ottawa: Statistics Canada. Bratsberg, B., and J.F. Ragan. 2002. “The impact of host‑country schooling on earnings: A study of male immigrants in the United States.” Journal of Human Resources 37 (1): 63–105. Bratsberg, B., and D. Terrell. 2002. “School quality and returns to education of U.S. immigrants.” Economic Inquiry 40 (2): 177–198. Butcher, K.F. 1994. “Black immigrants in the United States: A comparison with native blacks and other immigrants.” Industrial and Labor Relations Review 47 (2): 265–284. Chiswick, B.R., and P.W. Miller. 1992. “Language in the labor market: The immigrant experience in Canada and the United States.” In Immigration, Language, and Ethnic Issues, ed. B.R. Chiswick, p. 229–296. Washington, D.C.: American Enterprise Institute. Choudaha, R., and L. Chang. 2012. Trends in International Student Mobility. Research Report no. 1. New York: World Education Services. Coulombe, S., G. Grenier, and S. Nadeau. 2014. “Human capital quality and the immigrant wage gap.” IZA Journal of Migration 3 (14): 1–22. Available at: http://www.izajom.com/content/3/1/14. Finnie, R. 2007. International Mobility: A Longitudinal Analysis of the Effects on Individuals’ Earnings. Analytical Studies Branch Research Paper Series, no. 289. Statistics Canada Catalogue no. 11F0019M. Ottawa: Statistics Canada. Hawthorne, L., and A. To. 2014. “Australian employer response to the study‑migration pathway: The quantitative evidence 2007‑2011.” International Migration 52 (3): 99–115. Hou, F. 2014. “A general approach to effect decomposition.” Social Science Quarterly 95 (3): 894–904. Hou, F. and Bonikowska, A. (2016), Selections Before the Selection: Earnings Advantages of Immigrants Who Were Former Skilled Temporary Foreign Workers in Canada. Int Migr Rev. doi:10.1111/imre.12310. Hou, F., and G. Picot. 2014. “Annual levels of immigration and immigrant entry earnings.” Canadian Public Policy 40 (2):166–181. Hou, F., and G. Picot. 2016. “Changing immigrant characteristics and pre‑landing Canadian earnings: Their effect on entry earnings over the 1990s and 2000s.” Canadian Public Policy 42 (3): 308–323. King, R., and P. Raghuram. 2013. “International student migration: Mapping the field and new research agendas.” Population, Space and Place 19 (2): 127–137. Li, Q., and A. Sweetman. 2014. “The quality of immigrant source country educational outcomes: Do they matter in the receiving country?” Labour Economics 26: 81–93. Lowell, L., and J. Avato. 2014. “The wages of skilled temporary migrants: Effects of visa pathways and job portability.” International Migration 52 (3): 85–98. Lu, Y., and F. Hou. 2015. “International students who become permanent residents in Canada.” Insights on Canadian Society (December). Statistics Canada Catalogue no. 75‑006‑X. Oreopoulos, P. 2011. “Why do skilled immigrants struggle in the labor market? A field experiment with thirteen thousand resumes.” American Economic Journal: Economic Policy 3 (4): 148–171. Painter, M.A. 2013. “Immigrant and native financial well‑being: The roles of place of education and race/ethnicity.” Social Science Research 42 (5): 1375–1389. Picot, G., F. Hou, and T. Qiu. 2016. “The human capital model of selection and immigrant economic outcomes.” International Migration 54 (3): 73–88. SJR (Scimago Journal & Country Rank). n.d. Country Rankings. Available at: http://www.scimagojr.com/countryrank.php (accessed March 24, 2017). Tong, Y. 2010. “Place of education, gender disparity, and assimilation of immigrant scientists and engineers earnings.” Social Science Research 39 (4): 610–626. UNESCO (United Nations Educational, Scientific and Cultural Organization). n.d.Welcome to UIS.Stat,” UNESCO Institute for Statistics. Available at: http://data.uis.unesco.org/ (accessed March 24, 2017). Williams, R., A. Leahy, G. de Rassenfosse, and P. Jensen. 2015. U21 Ranking of National Higher Education Systems 2015. Melbourne, Australia: Melbourne Institute of Applied Economic and Social Research, University of Melbourne. The World Bank. 2016. GDP per capita, PPP (constant 2011 international$) (chart and table). Available at: http://data.worldbank.org/indicator/NY.GDP.PCAP.PP.KD (accessed March 27, 2017).

Zeng, Z., and Y. Xie. 2004. “Asian‑Americans’ earnings disadvantage reexamined: The role of place of education.” American Journal of Sociology 109 (5): 1075–1108.

﻿
Date modified: