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The China Challenge

Huhua Cao
Vivienne Poy

The chinese diaspora and immigration in Canada

Chapter 17. Causes and Consequences: Overeducated Chinese Immigrants in the Canadian Labour Market

Tony Fang

Texte intégral

1More than thirty years have passed since Richard Freeman’s influential book The Overeducated American (1976) described the growing tendency for workers to have more formal education than their jobs require, a tendency that Freeman suggested generated a pattern of declining returns to higher education within the United States. While a similar pattern was initially confirmed for Canada (see Dooley 1986), this trend seems to have been reversed more recently in both countries, and certainly so for younger workers (see Katz and Murphy 1992, Bar-Or et al. 1995 and Card and Lemieux 2001). Nevertheless, the extent of overeducation and its consequences remain of vital policy interest. It has been estimated at different periods that forty-one percent of workers in the United States are overeducated (see Sicherman 1991), that thirty-one percent of British workers are overeducated (see Sloane, Battu and Seaman 1999), and that twenty-seven percent of Canadian workers are overeducated (see Ying 2003), while comparative data on seventeen countries in Europe and North America put the Canadian rate of overeducation at second only to that of the United States (see Brisbois 2003). The overeducated are known to have lower earnings, lower job satisfaction and higher job turnover (see Allen and van der Velden 2001). Overeducation represents labour market mismatch, signals wasted public resources and gives rise to inefficient churning and job search (see Bender and Heywood 2006 and Wald 2005). Indeed, the variation in overeducation by degree programme has been used to suggest reallocations within Canadian higher education (see Frenette 2004).

2While recent data confirm the impressions articulated above, the situation is even worse for disadvantaged workers in the labour market, such as immigrants, and especially recent immigrants to Canada. For example, in 2001 twenty-five percent of university-educated male immigrants and thirty-eight percent of university-educated female immigrants were working in jobs that required, at most, a high school education (see Galarneau and Morissette 2004). This compared with twelve percent of Canadian-born men and thirteen percent of Canadian-born women. Data from the Survey of Labour and Income Dynamics reveal that fifty-two percent of recent immigrants with university degrees worked in jobs requiring only high school education at some point during the period 1993–2001, nearly double the proportion among the Canadian-born (see Li, Gervais and Duval 2006). Data from the Longitudinal Survey of Immigrants to Canada also indicate substantial job mismatch for immigrants to Canada. For example, among working-age immigrants who arrived in Canada between April 2001 and May 2002, only forty-two percent found work in their intended occupations during their first two years in Canada (see Statistics Canada 2003).

3While the study of racial and ethnic minorities deserves scrutiny, the imperative for Canada is to focus on the distribution of overeducation among immigrants. The education of immigrants has become a central labour market issue in Canada for a number of reasons. First, Canada selects economic immigrants on the basis of a system that heavily rewards educational attainment. In the most recent version of the “Point System,” which came into effect in 2002, applicants in the “Skilled Worker” category can earn twenty-five of the sixty-seven points necessary for admission into Canada through their educational attainment. Given the policy emphasis on skill-based immigration, it becomes critical to measure the extent to which the education of immigrants is both used and rewarded.

4Second, demographic projections show that the growth of the Canadian population will increasingly rely on immigration. According to one forecast, immigration is expected to account for all net labour force growth by 2011 (see Human Resources Development Canada 2002). Third, and more importantly, immigrants, particularly the recent cohort, suffer increasing difficulties in the Canadian labour market in the following three dimensions. The relative educational standing of immigrants has been falling compared to native-born Canadians; the return that immigrants earn on their education appears to be significantly lower (see Reitz 2001 and Aydemir and Skuterud 2005); and immigrants are less likely to be employed in the most highly skilled professions (see Reitz 2006). The second and third outcomes might well be expected if overeducation is more common among immigrants. Lack of information and failures in signalling make it likely that foreign credentials will be undervalued in the Canadian labour market. At the same time, lack of language fluency may make it genuinely difficult for immigrants to gain a return even on valuable education and credentials. While these points argue that immigrants are more likely to be overeducated (mismatched), they may also indicate that the economic consequences of overeducation may be smaller than anticipated if one controls for language ability. Further, since a very large share of Canada’s visible minorities is comprised of immigrants, one might anticipate that discrimination by employers makes immigrants more willing to compromise in the job search process, resulting in mismatch. Similar concerns in Australia have resulted in at least one major study of the extent of overeducation among immigrants (see Green, Kler and Leeves 2004).

5Although a variety of aspects of overeducation have been studied by labour market economists (see Belfield 2000 for a review of the literature), the distribution of overeducation and the differential consequences of overeducation have received much less study. Early work from the United States suggested that African Americans were more likely to be overeducated (see Duncan and Hoffman 1981). More recent work from the United Kingdom also indicates that members of ethnic minorities are more likely to be overeducated (see Alpin, Shackleton and Walsh 1998), although there is heterogeneity among those minorities (see Battu and Sloane 2002). There have been a number of studies examining returns to immigrants’ education in the Canadian context (see Reitz 2001, Ferrer and Riddell 2008 and Sweetman 2004), but to my knowledge only two studies have directly considered the impact of overeducation (see Galarneau and Morissette 2004 and Wald and Fang 2008). This lack of attention is somewhat surprising, given the prevalence of immigrant overeducation as described above, as well as the well-developed body of literature that examines the earnings consequences of overeducation (see McGuinness 2006 for an up-to-date and thorough review). On the other hand, there were no published studies examining the relationship between educational mismatch and wages in Canada until quite recently (see Vahey 2000). Most Canadian studies of overeducation neglect the immigrant population, either because the focus of the particular research is on other issues, such as literacy or the Canadian post-secondary education system, or because there are unacceptably small numbers of immigrant observations, or even none at all, within the data sets employed (see Boothby 1999, Frenette 2001 and Green and Riddell 2001).

6In this chapter I examine the impacts of overeducation on the earnings of immigrants, particularly Chinese immigrants, in the Canadian labour market from a slightly different perspective. Specifically, I use the framework most commonly appearing in the overeducation literature that enables one to examine returns to school contingent upon job requirements. In more precise terms, a decomposition of respondents’ years of education permits the estimation of returns to schooling according to whether those years of education: are required for the job, exceed job requirements or are in deficit of job requirements. I also use a categorical version of mismatch measurement that contrasts overeducated and undereducated workers to those who are properly matched. Further, whereas Diane Galarneau and René Morissette (2004) examined one particular type of overeducation, albeit probably the most important type, the data set used here captures many different magnitudes of educational mismatch.

Explaining Overeducation

7Why might recent immigrants face a heightened incidence of overeducation? A number of hypotheses have been developed. The first possible explanation, which renders the existence of overeducation consistent with the assumptions of human capital theory, is that, while immigrants may be categorized as overeducated, their “surplus” education compensates for education of inferior quality or other human capital “deficiencies.” For example, a study for Statistics Canada examining the employment of immigrants four years after arrival concludes that there is a significantly positive relationship between the ability to speak English and the likelihood of having an “appropriate” job (see Statistics Canada 2007). Employed immigrants with the highest levels of spoken English (on a five-point self-reported scale) were more likely to have high-skill jobs, jobs in the intended field, jobs similar to the ones they had before migrating, jobs related to their training or education, and higher hourly wages.

8The high incidences of overeducation among Asian immigrants can also be explained by the fact that Asians, especially Chinese, have historically placed a great emphasis on higher education as a stepping stone to social, political and economic advancement (see Stevenson and Stigler 1992). For example, according to one study comparing elementary school children and their families in mainland China, Taiwan and Japan with counterparts in Chicago, Illinois (see Stevenson 1992), the Chinese, Taiwanese and Japanese families were more likely to attribute success in school to the quality of teaching and the hard work of students, whereas the families in Chicago contended that innate talents and abilities beyond students’ control had a greater influence. The families in Chicago tended to regard childhood as a time for a variety of activities, but in East Asia school work was seen as a child’s primary task. When asked to fantasize about what they would like if they could have any wish, more than two thirds of the children in this study from mainland China, Taiwan and Japan wished for something related to education and educational success, while only one in ten of the students in Chicago did so, and the majority instead chose wealth, material objects or fun fantasies such as a trip to the Moon. The lives of the children in East Asia were clearly much more centred on school than those of the children in Chicago were, and the parents were much more involved in, and critical of, their local schools than the parents in Chicago were. These contrasts go a long way toward explaining why students in East Asia have more success in school than American children do. However, attitudes do not exist in a vacuum. There are structures in the societies and educational systems of East Asia that support and encourage them. For example, historically, individuals who excelled in the educational system in China were much more likely to be recruited and promoted into the higher ranks of government or industry even if they did not possess superior management or practical skills. (Nevertheless, the system of recruitment and promotion mainly based on educational attainment has been in transition since China adopted open-door and market reform policies, starting in 1978.) In theory, then, it is because immigrants from East Asia are more educated than Americans or Canadians that they are likely to experience a higher incidence of overeducation.

9Third, if visible-minority immigrants are discriminated against by Canadian employers, they will find it harder to gain employment and will therefore become willing to make greater compromises in terms of job match (an argument advanced in relation to immigrants in Britain by Battu and Sloane 2002). Indeed, a case before the Canadian Human Rights Tribunal in 2006 focused squarely on this issue: the complainant, an immigrant from India with a PhD, argued that refusal to hire overqualified immigrants amounted to discrimination, since members of visible minorities face barriers at their appropriate levels of employment that force them to seek lower-skilled jobs instead (see Canadian Human Rights Tribunal 2006). Third, given their status as new labour market entrants, mismatches might be more prevalent as newcomers learn about the labour market, although overeducation among immigrants cannot be dismissed as a temporary phenomenon, but may persist even ten years after immigrants arrive in Canada (see Galarneau and Morissette 2004). Fourth, it might simply be that the quality of the job match is secondary to more pressing concerns. While it is not surprising that immigrants escaping political persecution would put a somewhat low priority on the quality of job match, survey responses reveal that even principal applicants in the “Economic Class” of immigrants cited reasons other than job prospects as the most important determinant behind their settlement location decision (Statistics Canada 2003, p. 15). Among principal applicant economic immigrants who settled in Vancouver, a number of reasons outranked “job prospects” as the most important, including family or friends, climate, lifestyle; and education prospects. In Toronto “family or friends” was cited by 49.7 percent of respondents, compared to 23.4 percent citing “job prospects.” Finally, immigrant skills may not be fully used when Canadian licensing bodies or employers fail to recognize foreign credentials or work experience (see Reitz 2001).

Returns to Immigrant Education

10As mentioned above, there have been a number of studies examining the returns to immigrants’ education in the Canadian labour market. A finding common to most research is that immigrants receive a smaller earnings premium for formal education compared to the Canadian-born (see Reitz 2001 and Ferrer, Green and Riddell 2006). According to Jeffrey Reitz (2001), a generalization that can be drawn from this research is that the estimated return to an additional year of schooling for immigrants is about half what it is for the native-born. Why should immigrants’ education be rewarded less than that of other Canadians? Again, one strand in the literature hypothesizes that the skills embodied in the education of immigrants are, in some respects, inferior to those of the native-born population and that the observed inferior returns are reflective of this. Research testing this hypothesis has examined heterogeneity in school quality and literacy skills (see Sweetman 2004 and Alboim, Finnie and Meng 2005).

11Arthur Sweetman (2004), using data from multiple Censuses and school quality measures for eighty-seven countries, has explored the role of educational quality in immigrants’ source countries in returns to schooling. He concludes that there is substantial correlation between average source country school quality and Canadian labour market earnings. For instance, parameter estimates implied that moving up from the twenty-fifth to the seventy-fifth percentile of the school quality index is associated with a ten percent increase in annual earnings.

12Ana Ferrer, David Green, and Craig Riddell (2006), using the Ontario Immigrant Literacy Survey to examine the impact of literacy skills on immigrant earnings, find that differences in literacy account for a large amount of the higher earnings of Canadian-born workers. For example, among the university-educated literacy differences account for about two thirds of the earnings gap between immigrants and the Canadian-born. Naomi Alboim, Ross Finnie and Ronald Meng (2005) use the Survey of Literacy Skills Used in Daily Activities, conducted in 1989, and similarly find that an important factor related to the discounting of immigrants’ foreign education is language ability.

Data and Methodological Approach

13Data for this study are drawn from the Canadian Workplace and Employee Survey (WES), conducted by Statistics Canada in 2003. The WES is a linked file consisting of both employer and employee components, and covers a broad range of topics from both the demand and the supply sides of the labour market. Employers are sampled by physical location and employees are then sampled within each location from employer-provided lists. The survey excluded business locations in the Yukon, Nunavut and the Northwest Territories, along with agriculture, fishing, road, bridge and highway maintenance, government services and religious organizations. Responses were received from 6,565 business locations and 20,834 employees.

14For the present study, the key WES data include information on earnings, workers’ educational attainments, perceptions of job requirements, ethnic backgrounds and dates of immigration. Information pertaining to immigrants’ countries of origin and measures of literacy—which, as discussed above are generally found to be important determinants of immigrant labour market earnings—is unfortunately absent from the WES data, but there is information on ethnicity and foreign language usage at home, which will serve as proxy measures.

15The WES contains certain data that render it particularly well-suited for studying the impacts of overeducation on earnings. For instance, it contains a direct measure of individuals’ total work experience in addition to a measure of job tenure with current firms. This is unavailable in most data sets, for which years of experience must be estimated (using the formula: experience = years of age – years of schooling – 5). The WES also contains detailed information on the incidence and amount of workplace training. These high-quality measures of work experience and training are particularly important in light of the hypothesis that overeducated workers possess lower levels of other forms of human capital, namely work experience and training.

16The sample of interest consists of paid workers who were between the ages of eighteen and sixty-four in 2003. This results in a sample of 20,558 workers from 5,267 workplaces, among whom 17,270 were born in Canada and 3,288 were immigrants (including twelve percent Chinese). For this analysis I focus on the economic performance of those who immigrated after 1989. Of the 3,288 immigrants, 963 are what may be termed “recent” immigrants, having immigrated between 1990 and 2003. Chinese immigrants consist of 18.5 percent of these recent immigrant workers (see Table 17.1).

Key Variables and Measures

17Four approaches are typically used in the overeducation literature to ascertain the match between a job’s entry and/or performance requirements and an individual’s educational attainment (see Wald 2005): (1) comparison of a worker’s educational attainment with the education level that the worker believes is necessary for either job entry or performance; (2) the respondent’s perception of being overeducated or overqualified; (3) comparison of a worker’s educational attainment to the educational requirements for the position as specified by job analysts; and (4) deviation from the average level of educational attainment within a narrowly defined occupation. The third and fourth of these approaches cannot be used here, since WES data available to researchers via remote access are not coded with sufficiently detailed occupational information, but the first of these approaches can be used.

18Specifically, an individual’s educational attainment can be compared with responses to the following question: “What is the minimum level of education required for this job?” This question can be reasonably interpreted as asking either about the requirements for being hired or about those for job performance. However, Séamus McGuinness (2006) has pointed out that both interpretations have elicited similar responses. McGuinness cites results from a study using a data set of alumni of the University of Newcastle in the United Kingdom (Green, McIntosh and Vignoles 1999), which found that in the “vast majority of cases, the assessment of education levels needed to do the job tended to match those needed to get the job.”

19Based on the comparison between survey respondents’ educational attainments and the perceived minimum levels of education required for their jobs, I derive a set of three dichotomous variables, characterizing the fit as either overeducated, matched or undereducated. The analysis focuses on the overeducated population, due to its policy relevance. I also derive a continuous version whereby years of schooling (Sa) are separated into three components: years of schooling required for the job (Sr); years of surplus education or overschooling (So); and years of deficit or underschooling (Su), so that Sa = Sr + So - Su.

20For example, a PhD graduate assumed to have twenty years of schooling and driving a taxi would have twelve years of required schooling and eight years of surplus schooling if he/she responded that in order to drive a taxi; a high school education was required. On the other hand, a high school graduate working in a job perceived to require a college diploma would have fourteen years of required schooling and two years of deficit schooling.

21While the self-assessed overeducation measure adopted here can reasonably be criticized for its subjectivity, I feel that it confers two major advantages over external measures. First, it is a job-specific measure rather than an occupation-specific measure, and thus avoids the risk of misclassification solely due to heterogeneity within an occupation. Second, external assessments often rely on occupational taxonomies that are infrequently updated by government analysts. According to analysis of Canadian policies aimed at developing skilled workers (see Baygan 2004), “occupational classifications are slow to incorporate newly emerging fields, particularly in science and technology, or changing skill requirements within occupations.” Given the high number of recent immigrants in Canada employed in computer-related occupations, and the likely rapidity of change within these occupations, relying on respondents’ assessments of the skill requirements of their jobs seems to be the preferable measurement approach.

Sample Characteristics

22If one tabulates weighted sample means according to immigration status (see Table 17.1), one finds, consistent with other data sets, that the earnings of recent immigrants, at $17.81, were well below those of Canadian-born workers, at $20.73. However, recent Chinese immigrants made even less, at $16.49, despite being the most educated in terms of years of education, at 15.0 years versus 13.4 years for the entire population. These inferior wages cannot be attributed to lower amounts of educational attainment, as recent immigrants were a very well-educated group. For example, 31.2 percent of recent immigrants were university graduates, compared to 13.7 percent of Canadian-born workers, and recent immigrants brought one more year of education to the labour market than the Canadian-born did (14.4 years versus 13.2 years). Strikingly, 50.9 percent of recent immigrants were labelled as overeducated according to the dichotomous measure of overeducation, compared to about one third of the Canadian-born. The proportion of the overeducated was even higher for the Chinese immigrant sample, at 55.9 percent. Recent immigrants had one additional year of overeducation compared to Canadian-born workers (2.4 years versus 1.4 years). In fact, despite their significantly higher levels of educational attainment, the jobs of recent immigrants were perceived to require levels of education almost identical to those of the Canadian-born (12.3 years compared to 12.2 years).

Table 17.1 Weighted Means by Immigration Status

Table 17.1 Weighted Means by Immigration Status

Note: The total sample size (23,296) does not equal the sum of categories (23,252) due to the exclusion of forty-four immigrants from the “most recent immigrant” category (those who entered Canada in 1998 or 1999).
Source: Statistics Canada, Workplace and Employee Survey, 2003

23If one tabulates the sample according to education–job matches (see Table 17.2), the data once again indicate that recent immigrants were more likely to be overeducated than non-recent immigrants or the Canadian-born. Recent immigrants comprised 8.9 percent of the overeducated sample, in contrast to only 4.3 percent of workers who were matched. (Note that recent immigrants in this table include forty-four immigrants who entered Canada in 1998 and 1999, whereas these are excluded from the data sample for the purpose of regression analysis.) Individuals of Chinese descent (4.4 percent, compared to 2.8 percent of the overall sample) and individuals of other non-European descent (22.5 percent versus 20.0 percent) are overrepresented in the sample of overeducated workers.

24Overeducated workers earned somewhat less than matched workers or undereducated workers. Compared to workers who were educationally matched, overeducated workers earned $2.27 less per hour on average, in spite of their higher levels of educational attainment, at 14.2 years compared to 12.9 years for matched workers. The positive relationship between the hourly wage rate and years of required education hints at the efficacy of decomposing years of education in this manner.

25The argument that higher levels of education compensate for lower levels of experience and training seems plausible when examining these mean differences. For example, overeducated workers were younger than matched workers (38.6 years compared to 40.5 years), had fewer years of full-time work experience before the current job (9.0 years compared to 9.1 years), and had lower levels of firm-specific job tenure (6.9 years compared to 9.0 years). Additionally, overeducated workers were employed in firms with lower training expenditures per capita ($281 compared to $318).

Table 17.2 Weighted Means by Educational Match

Table 17.2 Weighted Means by Educational Match

Source: Statistics Canada, Workplace and Employee Survey, 2003

26Overeducated workers do not appear to differ in a substantial manner from matched workers either along gender lines or according to the presence of children. Personal employment history does seem to affect the likelihood of over-education, as those with higher levels of unemployment and those who involuntarily left their previous jobs had heightened incidence of overeducation.

27A number of other variables appear to have increased the likelihood of overeducation. For example, a higher proportion of workers in part-time positions were overeducated compared to those who were educationally matched (29.2 percent compared to 25.2 percent), as were workers in firms with a higher incidence of part-time work. Workers with post-secondary educational credentials comprised a relatively large share of the overeducated. For example, while 9.8 percent of the total sample of workers had undergraduate degrees (see Table 17.1), 21.2 percent of overeducated workers had them.


28I use a multinomial logit model to investigate the probability of overeducation and undereducation. The multinomial logit estimation technique is appropriate where the discrete dependent variable covers two or more outcomes that do not have a natural ordering. I am particularly interested in whether the negative relationship between overeducation and time spent in Canada is statistically significant when the other potential determinants discussed above are considered.

29I use survey estimation commands with the employee survey weights provided in the WES in all the estimations to account for the fact that, once an establishment has been selected in the survey, the assumption that a given worker is randomly sampled from the overall population of workers is no longer appropriate. In Stata Version 9, I use the “svyreg” and “svymlogit” commands, the counterparts to “reg” and “mlogit,” which are inappropriate in the presence of complex survey data. That is, the errors generated are corrected for the common components associated with a cluster of workers from a given workplace. These estimation commands also return representative results and provide heteroskedasticity-robust standard errors.

30If one tabulates coefficients and marginal effects (evaluated at the means) from the multinomial logit model (see Table 17.3), one finds, consistent with the bivariate relationships, that the likelihood of over-education was higher for recent immigrants, the marginal effect being 0.126. Being of Chinese descent increased the likelihood of overeducation by a slightly larger magnitude (0.147). Therefore it would be safe to conclude that recent immigrants from Chinese background were highly prone to overeducation.

31Results from the multinomial logit are consistent with the hypothesis that overeducated workers may have been substituting formal education for work experience and workplace training. Higher level of job tenure significantly decreased the likelihood of overeducation. None of the demographic variables related to potential household constraints—such as marriage, the presence of children or gender interactions—were statistically significant. Despite the bivariate relationships between overeducation and a worker’s previous job separation and unemployment history, the estimates from the multinomial logit failed to find a significant relationship. Working in establishments with higher part-time rates heightened the incidence of overeducation (marginal effect of 0.099).

32To analyze the effect of educational mismatch on earnings, I rely on a standard Mincerian semi-logarithmic wage equation, with the modification that years of educational attainment are decomposed:

lnWij = α + β1Srij + β2 Soij + β3Suij + Xijγ + Yijδ + εij (1)


  • ln Wij = the natural logarithm of the observed hourly wage of the ith worker in the jth workplace,

  • Srij = years of required schooling of the ith worker in the jth workplace,

  • Soij = years of surplus schooling of the ith worker in the jth workplace (overeducation),

  • Suij = years of deficit schooling of the ith worker in the jth workplace (undereducation),

  • Xij = a vector of (other) personal characteristics for the ith worker in the jth workplace,

  • γ = a vector of estimated slope coefficients for worker characteristics,

  • Yji = a set of characteristics of the jth workplace for worker i,

  • δ = a vector of estimated slope coefficients for workplace characteristics, and

  • εij = an error term.

Table 17.3 Determinants of Mismatch (Multinomial Logit)

Table 17.3 Determinants of Mismatch (Multinomial Logit)

Notes: N = 20,558, F-Statistic: 5.49***
Also included are dummy variables for six regions
*significant at 10%; **significant at 5%; *** significant at 1%
Source: Statistics Canada, Workplace and Employee Survey, 2003

33If the results from the earnings regressions are tabulated with separate estimations for the Canadian-born, recent immigrants and recent immigrants of Chinese ethnicity (see Table 17.4), one finds that returns to years of overeducation were positive in all three samples, but were smaller than those to years of required education. Both returns to required education and returns to overeducation were smaller for Chinese recent immigrants and for all recent immigrants than for the Canadian-born (4.6 percent, 7.5 percent, 8.9 percent, 3.9 percent, 5.7 percent, 6.6 percent).

34The estimates for the relative returns to overeducation, as compared with returns to required education, are at the high end of the range of typical results, whereas the estimates for recent immigrants are at the low end of the range. An analysis of forty-five studies from numerous countries covering various time periods found that returns to overeducation averaged about half to two thirds of the returns to required education (see Hartog 2000). In all estimates based on equation 1, the implicit assumption within human capital theory that returns to education are not contingent on job requirements (i.e. β1 = β2 = β3) is rejected. For the three equations the relevant F statistics corresponding to the Wald tests are F(2,5024) = 157.97, Prob>F = 0.0000, F(2,706) = 16.36, Prob>F = 0.0000, and F(2, 117) = 7.99 and Prob>F = 0.0006.

35There were significant earnings differences among recent immigrants according to ethnic background. Relative to those of European descent, Chinese immigrants earned significantly less (12.7 percent, 15.3 percent for the dummy variable approach), followed by other non-Europeans (5.7 percent, 7.8 percent for the dummy variable approach). The impact of having a foreign language as the main language spoken within the household was significantly negative for other non-Europeans (15.5 percent), and was also negative for Chinese immigrants (7.2 percent), but was not significant. The returns to prior work experience differed across the three subsets: the Canadian-born reaped significant returns for their years of work experience, whereas recent immigrants, and especially recent Chinese immigrants, did not (returns per year were 0.8 percent, 0.5 percent and 0.3 percent for Canadian-born, recent immigrants and recent Chinese immigrants respectively). In other words, the prior work experience of recent immigrants, which is typically comprised largely of foreign work experience, was seriously discounted by employers. Unfortunately, due to the nature of the data, it was not possible to partition prior work experience into that specifically obtained in Canada and that obtained abroad. Specifically, while there are data of immigration and years of total work experience, there are no complete work histories of time spent in Canada. Accordingly, it is not known, for example, what part of the years since immigration was spent not in the labour force or in unemployment. However, I define prior work experience to exclude experience obtained in the current job (job tenure), which is by definition Canadian experience, thus partially rectifying this problem.


36Analysis with the WES data supports findings from other data sets, as well as substantial anecdotal evidence, that recent Chinese immigrants have faced heightened levels of overducation in the Canadian labour market. Of all recent immigrants arriving between 1990 and 2003, fifty-one percent were overeducated in 2003, according to data from the WES, which was higher than the figure for 1999 (forty-eight percent). Among recent immigrants, the Chinese experienced a heightened level of overeducation, at fifty-six percent. Multivariate analysis confirmed the significance of this relationship when many other potential determinants of overeducation were considered.

37This study has shown that, in addition to the high incidence of overeducation, recent immigrants suffered a larger earnings disadvantage from overeducation than the Canadian-born did, and that this was particularly the case for recent Chinese immigrants. This supports findings based on Canadian Census data (see Galarneau and Morissette 2004). The wage impact of overeducation was assessed in two ways. First, recent immigrants were found to receive lower economic returns both to years of required education (8.9 percent for the Canadian-born, 7.5 percent for recent immigrants and 4.6 percent for recent Chinese immigrants) and to years of surplus schooling (6.6 percent, 5.7 percent and 3.9 percent, respectively), compared to the Canadian-born. Second, it was found that immigrants had a larger earnings penalty associated with overeducation in an estimation approach that measured the incidence, rather than the magnitude, of overeducation (-0.144 for the Canadian-born, -0.184 for recent immigrants and -0.280 for recent Chinese immigrants). Thus, with respect to earnings a proper job match was relatively more important for recent Chinese immigrants than for other recent immigrants and the Canadian-born. This is consistent with the evidence that, compared with recent immigrants from European background, Chinese immigrants earned 15.3 percent less, after controlling for other wage determinants.

Table 17.4 Wage Impacts of Educational Mismatch (Continuous Variable Approach)

Table 17.4 Wage Impacts of Educational Mismatch (Continuous Variable Approach)

Notes: Also included are dummy variables for six regions and fourteen industry sectors.
*significant at 10%; **significant at 5%; *** significant at 1%
Source: Statistics Canada, Workplace and Employee Survey, 2003

38The most plausible explanations for the earnings consequences of overeducation for recent Chinese immigrants are either non-recognition of foreign credentials, employment discrimination or, most likely, both. Although they are somewhat correlated, in this study I cannot disentangle these two types of effects. There might well be a disconnection between foreign education or training and the Canadian labour market, and/or genuine concerns about the quality of foreign education or training, which supports initiatives such as bridge programmes, especially in the medical and engineering fields, or language and skill training specific to the Canadian labour market, including job search skills. However, it is also possible that some employers simply used this possibility as an excuse to discriminate against recent immigrants in employment and/or earnings. Certainly, we cannot rule out this possibility of employer discrimination, including discrimination against foreign education and credentials. Fresh and convincing evidence supports this argument through a carefully designed field experiment (see Oreopoulos 2009): all qualifications being equal, job applicants with Chinese, Indian or Pakistani names were found to be forty percent less likely to be called for a job interview than otherwise equivalent applicants with English-sounding names (eleven percent versus sixteen percent).

39Depending on the interpretations of the empirical findings—non-recognition of credentials or quality of education, which is again hard to measure and validate, or employment discrimination—there can be various different policy responses. If we are concerned about the quality of education, then the government may wish to develop a more vigorous selection system to validate the value of credentials, and add language proficiency test requirements in the selection process, rather than providing various bridge programmes or language training programmes after the immigrants have arrived. On the other hand, if the job–education mismatch is attributable to non-recognition of foreign education and experience, then it appears to be appropriate to provide skilled immigrants with bridge programmes, especially for those in the medical and engineering fields, and language and skill training specific to the Canadian labour market, including job search skills. In the case of employment discrimination, the government may want to tighten human rights legislation, employment equity legislation and other anti-discrimination laws, and make the enforcement more proactive, rather than mainly complaint-driven. There also appears to be a need to educate employers, especially small and medium-sized employers, about the benefits of hiring and rewarding skilled immigrants, such as population and labour force growth, creativity and innovation through workforce diversity, knowledge of emerging markets and links to international trade.

40There is even a possibility that highly educated, highly skilled immigrants may be oversupplied in the Canadian labour market. If this is proved to be true through a thorough labour market analysis, then a shift from highly educated to relatively less educated immigrants or temporary foreign workers can be a reasonable policy option. In fact, such a policy change is occurring. The number of immigrant intakes from the Temporary Foreign Workers programme has increased dramatically in recent years, while the number of landed immigrants remains stable (see Citizenship and Immigration Canada 2009a and 2009b). However, the effect of such programmes on overeducation and job–education match remains to be seen.

41Future studies should do a better job of teasing out the two potential causes of earnings penalty associated with overeducation of Chinese immigrants, that is, employment discrimination and non-recognition of foreign credentials, possibly by using Census data. For example, employment discrimination could be investigated by comparing Chinese and Caucasians with the same Canadian education and other qualifications in job–education match. Alternatively, non-recognition of foreign credentials could be examined by studying differences in job–education match between Canadian- born Chinese with Canadian education and immigrant Chinese with Chinese education. Although somewhat outside the scope of this chapter, these are certainly areas of research that are worth further exploration.

42Given the greater rewards for proficiency in one or other of the official languages, and for work experience in Canada, potential immigration applicants should expose themselves to Canadian or equivalent experience as much as possible. They should also acquire skills and training that are unique to the Canadian market, including language and job search training, as well as targeting specific organizations for pre-arranged employment. In doing so, future immigrants from China may be able to expedite their assimilation into the Canadian labour market and maximize their career success in Canada.



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Table des illustrations

Titre Table 17.1 Weighted Means by Immigration Status
Légende Note: The total sample size (23,296) does not equal the sum of categories (23,252) due to the exclusion of forty-four immigrants from the “most recent immigrant” category (those who entered Canada in 1998 or 1999).Source: Statistics Canada, Workplace and Employee Survey, 2003
Fichier image/jpeg, 420k
Titre Table 17.2 Weighted Means by Educational Match
Légende Source: Statistics Canada, Workplace and Employee Survey, 2003
Fichier image/jpeg, 360k
Titre Table 17.3 Determinants of Mismatch (Multinomial Logit)
Légende Notes: N = 20,558, F-Statistic: 5.49***Also included are dummy variables for six regions*significant at 10%; **significant at 5%; *** significant at 1%Source: Statistics Canada, Workplace and Employee Survey, 2003
Fichier image/jpeg, 548k
Titre Table 17.4 Wage Impacts of Educational Mismatch (Continuous Variable Approach)
Légende Notes: Also included are dummy variables for six regions and fourteen industry sectors.*significant at 10%; **significant at 5%; *** significant at 1%Source: Statistics Canada, Workplace and Employee Survey, 2003
Fichier image/jpeg, 526k


Associate Professor of Human Resources Management and Industrial Relations at York University and a research associate with the Centre for Industrial Relations and Human Resources Management at University of Toronto. Currently he also serves as the Domain Leader in Economic and Labour market Integration at CERIS – Ontario Metropolis Centre and a past Board Member of the Chinese Economists Society. He is also a visiting professor at Fudan University, Southwest University of Finance and Economics, and China University of Geosciences, all in China. In 2010, he received the tile of “Chutian Scholar” of Hubei Province.
Professor Fang has a PhD in Industrial Relations and Human Resource Management from the University of Toronto, a MA in Economics from Memorial University of Newfoundland, and B.A. in economics from Shandong University. His areas of research interest encompass issues of compensation and benefits, high performance workplace practices, pension, retirement policy and the ageing workforce, education, immigration, and minimum wages, union impact on wages, innovation and firm growth, pay equity and employment equity. He has published in such journals as Industrial Relations (Berkeley), Canadian Journal of Economics, Canadian Public Policy, British Journal of Industrial Relations, Journal of Labor Research, International Journal of Manpower, Journal of Management History, Social Indictors Research, and Perspectives on Labour and Income. He also received numerous research grants and awards from Social Sciences and Humanities Research Council and Human Resources and Social Development Canada

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