The Earnings of First and Second Generation Immigrants in Canada

Rudy Sam* Honours Student, Department of Economics The University of British Columbia

Abstract Previous studies have often noted that second generation immigrants receive higher levels of both education and earnings than first or third generation immigrants. Several scholars suggested that this is due to unobservable characteristics within the second generation. Data from the 2001 Canadian census propose that female immigrants do have a marginal advantage due to some unobservable factor if they belong to the second generation. This study also demonstrates that while first generation immigrants of South/South-East Asian origin experience low earnings in the Canadian labour market, their children do not. In particular, low earnings among first generation immigrants are partly due to unobservable (discrimination) factors in the labour market. Earnings of first generation immigrants are also significantly dampened if they are not proficient in at least one of Canada’s official languages. Lastly, past studies often grouped immigrants who were born abroad and arrived in the host country at an early age together with those who were born in the host country and had at least one foreign-born parent. In terms of earnings, our analysis shows that such assumption is quite acceptable.

* I would like to thank Dr. Thomas Lemieux for being providing me with valuable insight for my research. I am also extremely thankful to Dr. Nicole Fortin, who assisted me with economic and econometric theory. Lastly, I am eternally grateful to my parents - whom are first generation immigrants - for coming to Canada so that my future children and I could have better lives.

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Table of Contents

Introduction ....................................................................................................................... 2

Data Source ..................................................................................................................... 12

Data Selection .................................................................................................................. 13

Key Independent Variables ............................................................................................ 17

Empirical Framework .................................................................................................... 20

Estimation Results .......................................................................................................... 23

Conclusion ....................................................................................................................... 29

References ........................................................................................................................ 33

Tables ............................................................................................................................... 35

Appendix .......................................................................................................................... 42

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Introduction

After the Second World War, Canada has been experiencing high rates of

immigration. In the beginning, the majority of immigrants coming to Canada were from

Europe. As time progressed, the number of new European immigrants entering the

country steadily declined while the number of immigrants originating from South and

South-East Asia rose dramatically. By the 1980’s, these Asians became the largest ethnic

group immigrating to Canada (see Illustration A in the appendix). Canadians do not have

the stereotypical American “melting pot” perspective and instead enjoy ethnic diversity.

Canada is a multicultural society which depends on immigration as its key source of

labour force growth (Bloom et al 1995, Baker and Benjamin 1994). Understanding why

some immigrant cohorts succeed while others fail in the workplace can help improve

existing labour, schooling and immigration policies. This study assesses four

assumptions concerning first and second generation immigrants that were held by

previous studies. The next section will explain in further detail the results from previous

publications.

1. Individuals who were born in Canada and have at least one foreign-born parent

have the highest earnings among the immigrant generations, holding all other

relevant factors constant.

If parents can influence their children’s outcomes, then it should not be a surprise that

second generation immigrants have greater success in the labour market. Chiswick

(2003) mentioned that there is evidence of positive selection bias in migration in the

U.S.; that is, individuals who are relatively more able than their peers in their home

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country are more likely to migrate to the U.S. If this positive selection bias is present

among immigrants in the U.S., then one could argue that selection bias should play an

even greater role in Canada. U.S. immigration policy emphasises on family

unification to a greater extent than Canadian immigration policy. While Canada’s

“point system” does take family ties into account, substantial consideration is given

on the amount of human capital attained by applicants (Baker and Benjamin, 1994).

The goal of this stringent evaluation process is to simultaneously minimize racial

discrimination when determining the eligibility of foreigners and to ensure that those

who are entering into Canada can make a positive contribution to the economy.

Therefore the thought that second generation immigrants having higher levels of

ability and motivation relative to third generation (and higher) immigrants is not so

unlikely if first generation immigrants are able parents. Black et al (2005) also

suggested that “unobserved parental characteristics,” such as patience or attitudes,

could influence the development of children.

2. Earnings immigrants receive will depend on their ethnicity. Individuals of

European-Canadian ethnicity have the highest earnings among the ethnic groups

discussed in this study, holding all relevant observable characteristics constant.

Ethnicity may have a positive (or negative) impact on earnings if ethnicity is

correlated with culture. It is possible that immigrants from certain cultures are more

ambitious in school and in the labour force than others. Both Gang and Zimmermann

(2000) and Chiswick (2003) found that ethnic origin has significant effects on

educational attainment among second generation immigrants. In the U.S., some

ethnic groups (i.e. Mexicans, Vietnamese) attain less education than others ethnic

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groups (i.e. European, Chinese) (Chiswick, 2003). Alternatively, ethnicity may be

correlated with language deficiencies or racial discrimination immigrants endure in

the work place (Bloom et al, 1995). In such case, visible minority first generation

immigrants would earn much less than European-Canadian immigrants. This study

will define racial discrimination as the treatment of an individual based on the ethnic

group to which that individual belongs rather than his ability to satisfy his job

requirements. The repertoire of racial discrimination should not be limited to skin

colour because there are many other characteristics that are unobservable in the

labour market but are correlated with ethnicity. For example, an immigrant could

face discrimination in the work place due to his foreign accent or style of clothing.

3. The level of earnings immigrants receive will depend on their familiarity of

Canada’s official languages.

The quality of education received by foreign-born immigrants is likely to be lower

than the quality of education received by immigrants born in Canada. In particular,

many Asian immigrants cannot express themselves in English or French (written and

oral) at same level as Canadian-born immigrants. Thus their earnings are reduced due

to their language skills.

4. Differences between foreign-born and Canadian-born second generation

immigrants are minimal.

Previous studies often considered those foreign-born immigrants who arrive in the

destination country at a young age as second generation. Those who arrived in

Canada at a young age do not suffer the negative wage premiums of their parents.

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They are much less likely to be hindered by language or social differences because

majority of their education was attained in Canada. Moreover, these foreign-born

second generation immigrants should assimilate to a higher degree than their parents

since they are exposed to the same socioeconomic environment as the Canadian-born

during childhood.

Literature Review

Antecol et al (2005) found that first generation immigrants of Asian origin tend to

have lower earnings relative to first generation immigrants of European origin and

Canadian-born immigrants. They used pooled individual-level data from the 1981 and

1991 Canadian censuses for their study. It appears that complete assimilation never

occurs for Asian first generation immigrants. For example, Asian first generation

immigrants who have lived in Canada for 5 years earned 14% less than Canadian

descendents. In comparison, Asian immigrants who have lived in Canada for over 30

years still suffered a negative wage premium of 6%. While Antecol et al (2005)

controlled for experience and education, she did not control for language ability when

comparing the wages of Asian immigrants to those of European and Canadian-born

immigrants. Therefore the lower earnings experienced by Asian immigrants may be due

to differences in quality of schooling. Baker and Benjamin’s (1994) study of first

generation immigrants in the Canadian labour market also had similar results. While

their methodology was like Antecol et al’s (2005), the data they used were from the 1971,

1981 and 1986 Canadian censuses. Estimates showed that the entry earnings for first

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generation immigrants have been falling and the rates of assimilation across successive

immigrant groups were small. While Baker and Benjamin (1994) do mention that there

have been strong increases in proportion of immigrants from Asia, they do not examine

immigrant earnings by ethnicity.

Using data from the 1991 Canadian census, Pendakur and Pendakur (1998)

concluded that both foreign-born (first generation) and Canadian-born (second generation

and higher) visible minorities earned less than Canadian-born Caucasians. They

suggested that this wage discrepancy is due to racial discrimination since it cannot be

fully explained by observable characteristics. After controlling for the usual variables,

Canadian-born visible minority men earn 8.2 percent less than Canadian-born Caucasian

men. Conversely, Hum and Simpson (1999) discovered no evidence of a wage gap

between visible minority and non-visible minority groups. Bloom et al (1995)

established that, using pooled 1971, 1981, and 1986 Canadian census data, assimilation

was particularly slow for immigrant men from Asia, Africa, and Latin America relative to

immigrant men from Europe and the United States. Immigrants from Asia, Africa, and

Latin America require 43 years to assimilate while immigrants from Europe and the U.S.

take only 11 years. He suggested that discrimination may have increased as the

composition of immigrants entering Canada shifted towards visible minorities. Foreign-

born Caucasian men were found to earn almost as much as Canadian-born Caucasian

men while foreign-born visible minority men earned 15.8 percent less than Canadian-

born Caucasian men (Pendakur and Pendakur, 1998).

Neither Pendakur and Pendakur (1998) nor Bloom et al (1995) adequately

controlled for differences in language skills. First generation visible minorities are less

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likely to have a strong grasp of English/French than their Caucasian peers and this will be

reflected in lower earnings. Pendakur and Pendakur (1998) controlled language ability

using the “Knowledge of Official Language” field in the Canadian census.

Unfortunately, this is an inefficiently control because respondents were only required to

indicate whether they were able to conduct a (basic) conversation in English or French.

Bloom et al (1995), on the other hand, acknowledges the importance of language ability

in the Canadian labour market but does not control for it at all. In comparison,

Schaafsma and Sweetman (2001) used the field in the Canadian census which

respondents answered whether if English/French were their “mother tongue” to construct

their language control variable. They established that returns to “English as a mother

tongue” were highest for foreign-born immigrants who arrive at a later age. In

comparison, returns to “English as a mother tongue” were nearly the same among

foreign-born immigrants who arrived at a young age and those who were born in Canada.

Consequently, they concluded that immigrants who arrive at a later age possess weaker

English/French skills. English or French “as a mother tongue” is only a satisfactory

proxy for language ability. This study will argue (later) that “language spoken most often

at home” provides a better approximation for language proficiency.

First generation immigrants are at a significant disadvantage, especially if they

migrate at an older age. Schaafsma and Sweetman’s (2001) empirical findings suggested

that returns to pre-immigration schooling (returns earned by those who immigrated after

19 years old) are only about two-thirds of returns to post-immigration schooling.

Furthermore, labour market experience obtained outside of Canada has no economic

return in Canada. Trejo (2003) came to the same conclusion when analyzing data from

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the Current Population Survey (November 1979 and 1989) to study the earnings of

Mexican immigrants. He argued that low returns to experience for first generation

immigrant men indicated that job training and work experience accumulated in the

foreign countries transfers imperfectly to the U.S. labor market. In comparison, the

returns to experience were similar for U.S.-born workers regardless of ethnicity (Mexican

or Caucasian) and generation status. He also established that returns to education for

Mexicans require three generations to converge towards the mean. In summary, first

generation immigrants are hindered by three factors: discrimination, language deficiency,

and imperfect transfer of existing human capital.

Ethnicity plays an important role on the level of earnings and schooling for all

immigrant cohorts. Antecol et al (2005) found significant wage differences stemming

from ethnic origin within first generation immigrants. Ethnic origin also plays a vital role

in determining the educational outcome of immigrants. Chiswick’s (2003) revealed that

first generation South Asian immigrants attained 3.371 more years of education than 3rd

generation Americans, whereas first generation Mexican immigrants acquired 2.442 less

years of education than 3rd generation Americans. He suggested that individuals from

certain ethnic origins attain less education due to the distance between their home and

host countries. For example, first generation Mexican immigrants in the U.S. attain the

lowest level of schooling because transportation costs between Mexico and the U.S. are

very low, which leads to a lower incentive for them to invest in both origin specific and

destination specific skills. The same consideration would occur when investing in their

children. These Mexican first generation immigrants would be hesitant to make large

educational investments on their children while residing in the U.S. if there is good

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possibility that their families will return to Mexico. While this theory does explain a

majority of the observed differences in educational attainment among ethnic groups, there

are a few exceptions. For example, Vietnam and Southern Europe are quite a distance

away from the U.S., yet immigrants from these areas exhibit low levels of schooling. Yet

immigrants from neighbouring countries (i.e. China and Northern Europe) have relatively

higher levels of education.

First generation immigrants arriving to host country at a young age exhibit similar

traits which are found among second generation immigrants. Gang and Zimmermann

(2000) found that female foreign-born immigrants arriving to Germany by the age of 6

attained the same level of schooling as a second generation female immigrants. Chiswick

(2003) also found that first generation immigrants arriving to the U.S. before age 5

attained 0.352 more years of education than that of the second generation. Furthermore,

those immigrants who arrived in the U.S. between the ages of 5 and 12 attained the same

level of schooling as second generation immigrants. Similar results were attained in

analyzing first generation immigrants in Canada. Immigrants arriving prior to the age of

15 consistently have slightly higher earnings than the Canadian born individuals

(Schaafsma and Sweetman, 2001). There is clearly a negative relationship between level

of earnings and age of immigration; earnings fall as age of immigration rise. However

there seemed to be an anomaly: immigrants arriving in Canada during their mid to late

teens earn much less than those who were slightly younger and those who are slightly

older (Schaafsma and Sweetman, 2001). Chiswick (2003) had identical results when

comparing educational attainment between immigrants groups. Immigrants arriving to

the U.S. between the age of 13 and 19 had significantly lower levels of education relative

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to the remaining first generation immigrants. Therefore both studies suggest that the

young have an easier time acculturating, while immigrants who arrive during their

teenage years have tremendous difficulty adjusting in the host country.

We have seen evidence that first generation immigrants commonly earn less than

the Canadian descendants. Does the level of earnings or education of the first generation

have any effect on their children’s performance in school or in the labour market? Using

a German socioeconomic panel (GSOEP) data set, Gang and Zimmermann (2000) found

that the level of educational attainment of first generation immigrants have no impact on

the educational outcomes of second generation immigrants. After the Second World

War, Germany was in the process of rebuilding and was short on manual labourers. To

increase the supply of unskilled labour, the German government created a “guest worker”

program to invite foreign workers and their families into the country. These first

generation immigrants were from Yugoslavia, Turkey, Italy, Spain and Greece, and have

had very little education. OLS and ordinal probit estimation techniques were used to

approximate the educational outcomes of the second generation. “Total years of

schooling” was the dependent variable for their OLS regressions, whereas “level of

schooling” was the dependent variable for their ordinal probit regressions. Results from

both approaches indicated that there was no significant relationship between the

educational attainment of these first generation immigrant and their children. However,

there may be some evidence that the opposite is true in terms of earnings. Borjas’ (1993)

article on the intergenerational mobility of U.S. immigrants argued that the average

earnings of second generation ethnic groups are influenced by the earnings of first

generation ethnic groups. While there does appear to be some intergenerational

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correlation, wages of the second generation were shown to be regressing towards the

mean. Canadian data shows second generation immigrants of Asian ethnicity perform as

well as third generation European-Canadians in both the labour market and in schooling.

There are abilities and attitudes which can be transferred from parent to child and

cannot be directly measured. These factors may help or hinder second generation

immigrants in both schooling and in the labour market. Chiswick (2003) found that after

controlling for the typical demographic variables (i.e. age, sex, etc), second generation

immigrants attain 0.466 years of schooling more than third generation immigrants. He

suggested that the second generation immigrants are positively influenced by their

parents’ due to “selectivity bias in migration,” which implies that “immigrants tend to be

disproportionately high ability or highly motivated people.” This would be particularly

true in countries that have stringent immigration policies such as Canada. Canada’s

immigration policy is based on a “point system” which attempts to match the skills of

immigrant inflows with perceived shortages in the Canadian labour market (Baker and

Benjamin, 1994). As of 2006, 70 of the 100 points are issued based on the level of

education, work experience, and language (English and French) proficiency of the

applicant. This clearly promotes positive selection bias among immigrants. Gang and

Zimmermann (2000) also suggested that the success of second generation immigrants

may stem from the positive role modeling that they received from their parents. First

generation immigrants are motivated, as seen with their decision to leave their home

countries in an effort to improve their economic status, and perhaps the status of their

children as well. Moreover, first generation immigrants need to possess a certain level of

ability to be able to overcome the difficulty of adjusting to their new environment (i.e.

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learning the host country’s language). Consequently, second generation immigrants

would be more likely to perform well in both school and in the labour market if these

traits can be transmitted across generations.

Data Source

Empirical results for this study were derived using the “2001 Census Public Use

Microdata File (PUMF) on Individuals”. While this survey is officially called the

“Census of Population,” it is commonly known as simply the “Canadian census.” This

census is conducted every 5 years by Statistics Canada. The 2001 public use file was

based on a 2.7% sample of the population, which translates to a total of 801,055

respondents. And clearly, nearly all data present in the 2001 Canadian census was based

on information from the previous year (2000). Information had been collected in

“reduced level of detail” so that the confidentiality of respondents can be preserved to a

much higher degree relative to both the U.S. decennial censuses and Current Population

Surveys. For example, the data on occupation did not indicate “Physician,” but rather the

more general category “Occupations in Medicine and Health.” This category also

included other medical occupations, such as “Nurse.” The Census of Population is a

cross-sectional data source and the unit of observation is at an individual level.

The 2001 Canadian census is the most appropriate data source when researching

wages differences between Asian immigrant generations in Canada. Unlike Canadian

censuses from previous years, the 2001 version inquires the generation status of its

respondents. Individuals were required to indicate whether if they were “First

Generation,” “Second Generation,” or “Third Generation and Over.” “First generation”

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referred to persons 15 years of age and over who were born outside Canada. “Second

generation” referred to persons 15 years of age and over who were born in Canada and

had at least one parent born outside Canada. Finally, “third generation and over” referred

to persons 15 years of age and over who were born in Canada and whose parents were

born in Canada. If the individual answered “Second Generation,” s/he also had to

indicate whether one or both parents were born outside of Canada. The availability of

detailed information on the ethnic origin of respondents is another crucial feature of the

Canadian census. Each respondent were asked: “To which ethnic or cultural group(s) did

this person’s ancestors belong?” The ability to identify respondents by their ethnic

groups allows a more in-depth analysis on the differences in earnings between immigrant

generations.

Data Selection

The actual number of observations dropped when each of the criteria is

implemented is presented on Table 1. The data set will only encompass individuals who

were between the ages of 25-64 and had identified themselves as working mainly full-

time in the year 2000. All remaining respondents who did not fall into this category were

excluded. By the age of 23, most individuals would have finished obtaining their desired

level of education; and by the age of 25, most individuals would be past their frictional

unemployment phase. Thus by restricting the sample by age, it provides a better

representation of wages for all groups than if the data set were to include the adolescence.

Similarly, if the elderly were included in the sample, my estimates would be bias since

most people over the age of 64 generally do not participate in the labour market. While

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there are individuals who enter school during later stages of their lives, people generally

accumulate their desired level of human capital as early as possible so that their net

benefits from schooling are maximized. It is unfortunate that the 2001 Canadian census

data does not provide information on the parents of second generation immigrants or vice

versa. If this information were available, analysis of relationships between the earnings

and education of parents and their children would have been possible. This study is

focused on individuals employed on a full-time basis; therefore those who had worked

less than 40 weeks during the year 2000 were excluded. However, this question in the

census only refers to the number of weeks worked, even if only for a few hours. Thus

respondents who earned less than $10,400 in the year 2000, which averages out to 200

dollars per week, were excluded from the data set as well. Rejecting the extreme (lower)

end of the earnings distribution reduces the “skewness” of estimates and ensures that the

observations used in this study are individuals employed on a full-time basis. “Total

number of hours worked for pay” (during the given reference week) is provided in the

census, but was not used to identify full-time workers because the number of hours

worked is based on the week prior to Census Day (May 15, 2001). There are many

legitimate reasons why respondents may not have worked all of their hours during that

week (i.e. illness, vacation, frictional unemployment, etc) but were employed on a full-

time basis in year 2000. Unfortunately, the 2001 Canadian census does not provide

information on the usual number of hours worked in 2000. Respondents were also asked

whether if they had attended school between September 2000 and May 15, 2001.

Similarly, this information was not used to identify full-time workers. Respondents may

have been working full-time in the year 2000 but decided to return to school in 2001.

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Thus if this study were to have excluded those who identified themselves as attending

school during the mentioned period, the results would have become biased.

The data used for this study only encompassed individuals of “South/South-East

Asian” or “European/Canadian” ethnic origin. Individuals of Asian ethnicity will be

classified into the following 6 categories: East Indian, Chinese (includes Taiwanese),

Filipino, Vietnamese, “Other South Asians” (i.e. Bangladesh, Kashmiri, Pakistani etc)

and “Other South East Asians” (i.e. Korean, Indonesian, Japanese etc). Remaining

persons of Asian origin who did not fit into these 6 categories were rejected from the data

set. “European” ethnicity includes all individuals whose ancestors were from Europe.

While the census was quite specific in cataloguing individuals of European ethnicity by

their ancestral countries, this information is not needed here. The main focus of this

paper is to analyze the earnings of Asian immigrants. Therefore, all respondents whose

ethnicity is European will be grouped together, along with those who identified

themselves as “Canadian.” The majority of individuals who considers their ethnicity as

“Canadian” have either been fully assimilated into “Canadian” culture or is of European

descent. Of the 49,230 individuals who identified themselves as “Canadian” in the

restricted data set, only 114 admitted to speaking a language other than English or French

on a regular basis at home. Individuals of “Australian” and “American” ethnicity were

dropped from the data set due to the lack of detail provided in the census. These

responses were grouped into a generic “Other Single Origins” category in the census

(along with Fijian, Hawaiian and others) which had a total of 954 individuals. All

remaining persons from ethnic groups not already mentioned have been excluded from

the data set as well; which includes individuals of Aboriginal origin. Individuals who

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provided multiple responses when asked of their ethnic origin were excluded from the

study, unless British Isles, French or Canadian was part of their response. In these cases,

the respondents were classified as European-Canadian. While 9,961 observations were

dropped due to this criterion, it was necessary because the Canadian census does not

provide detail on individuals of mixed race.1 These respondents were grouped into a

generic category called “Other (Multiple) Origins.”

The classification of first and second generation status in this study are not the

same as what had been described in the census. First generation immigrants have been

redefined as those who were born outside Canada and had immigrated at the age of 13

and above. Second generation immigrants now includes immigrants who arrive in

Canada between the ages 0-12, and those who were born in Canada and have at least 1

foreign-born parent. Classifying those who arrive in a foreign country at a young age as

second generation immigrants is important for the following 2 reasons: 1) the decision of

relocating were of their parents and not of their own 2) immigrants who arrive at a young

age share the same characteristics – in terms of both the level of earnings and educational

attainment – of the second generation. The first reason is significant because there may

be positive bias in migration among first generation immigrants. Those who chose to

come to Canada may be more ambitious and able than their peers still living in their

home country (more on this later). In addition, immigrants who arrive at a very young

age are exposed to the same socioeconomic conditions during their crucial developmental

years as second generation immigrants. Schaafsma and Sweetman (2001) found that

foreign-born immigrants in Canada who arrive during their early teenage years do not

1 Please refer to the appendix for more information.

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have an earnings deficit relative to their Canadian-born counterparts. In contrast, those

visible minority immigrants who arrive at a later age do suffer an earnings deficit and this

deficit increases with age at migration. The census originally delineated between those

second generation immigrants with 1 foreign-born parent from those with 2 foreign-born

parents. For simplicity, this distinction was ignored and both groups were combined.

Lastly, the classification of “third generation and over” group were left unchanged.

These are the individuals who were born in Canada and both their parents were born in

Canada as well. This group will serve as the base group in our empirical analysis unless

otherwise specified.

The data set used in this study should be large enough to provide fairly accurate

empirical results. After restricting the original data source using the aforementioned

criteria, a total of 202,265 observations were available. For a breakdown on the total

number of observation by generation status and by ethnicity, please refer to Table 2.

Key Independent Variables

Dummy variables were prominently used in evaluating the differences in earnings

between ethnic and generation cohorts. Seven dummy variables were created to

represent each of the ethnic groups present in the restricted data set (East Indian, Chinese,

Filipino, Vietnamese, Other South Asians, Other South East Asians and European-

Canadian). In addition, 3 dummy variables were constructed to represent each of the

immigrant generations (first, second and third). A “Non-Official Language” dummy

variable was used to approximate for English and French skills. This variable indicated

whether respondents spoke a non-official language regularly at home (=1 if yes, =0 if

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no). Individuals who have a deep understanding of English or French are very likely to

speak these languages at home. This assumption is especially reasonable considering the

demographic in data set are adults between ages 25 to 64 and are employed full-time.

These respondents are less likely to be still living with their (if they have any) foreign-

born parents, which in turn are not pressured to speak a foreign language. Secondly, first

generation immigrants would consciously choose to speak English over their foreign

mother tongue if they know English well and are well assimilated.

Other dummy variables that were used include “Female,” “Married,” and “CMA.”

“Female” indicated the sex of the respondent (Female=1 if female, =0 if male).

“Married” indicated whether the respondent is legally married (Married=1 if married, =0

if not married). CMA, or “Census Metropolitan Area”, indicated whether respondents

were living in urban centers (CMA=1 if yes, =0 if no) at the time of the census. Each of

these dummy variables had been reconstructed from the original variables provided in the

census to improve clarity. I will not go into detail as how this was done here because it

was a very straight forward and simple process. An “age,” which is not a dummy but

rather a continuous, variable was provided in the census to specify the age of the

respondents. This variable was used in this study to proxy for work experience. Its

squared form, “Age2,” was also included to account for possible non-linear characteristics

of experience. Previous studies using American data typically constructed a work

experience variable using the following formula: Experience = age - total years of

schooling – 6 (Mincer’s identity). Unfortunately, it is much too difficult to apply this

formula using Canadian data due to reduced level of detail. While the census does

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provide a variable representing the total years of schooling attained, it is not continuous

and is difficult to accurately recode the nine given categories into numerical values.

Descriptive Statistics

The mean and standard deviation of key variables are illustrated in Table 2 and

the results are quite similar to findings from previous journal articles. In Canada, it

appears that second generation immigrants tend to have the highest level of earnings

relative to the other 2 generations. Second generation immigrants earn on average

$47,962 annually, which is about 13% more than the first generation and 8% more than

the third generation. First generation immigrants earn significantly less than second and

third immigrant generations, with average annual earnings of $42,386. Although it is

difficult to see in this table, the second generation attain the most education between the

three immigrant generations. One may be inclined to conclude that the difference in

earnings stem from differences in education. Empirical results will show later that some

of the difference in earnings is attributed to unobservable characteristics. Since this data

set consists of only full-time workers, it is unsurprising that only 42% of each immigrant

generation is female. On average, individuals of the first generation tend to be older (45

years old). This age difference may help explain why 80% of the first generation are

married, compared to 64% and 60% of the second and third generation respectively.

Over 90% of first generation immigrants reside in CMAs. There appears to be a trend:

the higher a person’s generation status the more likely s/he is to reside in a rural area.

More than half of first generation immigrants spoke a foreign language regularly at home.

This number appears to be rapidly regressing towards zero as immigrant generation rises.

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When this analysis was repeated with European-Canadians excluded, the value of the

“Non-Official Language” variable decreased at a much slower rate. This suggests that

Asian immigrants assimilate at a slower pace than European immigrants in Canada.

Finally, first generation immigrants typically choose to immigrate to Canada at the age of

27. Second generation immigrants who were born outside of Canada tend to be 6 years

old at the time they came to Canada with their parents.

Empirical Framework

In summary, the empirical model used in this study is as follows:

Y = βX + θG+ αF + γS + λE, where

Y: Natural logarithm of annual earnings from labour sources

X: Vector of standard human capital determinants of earnings (age, age2, schooling,

language ability) and other control variables (gender, married)

G: Vector of geographical dummy variables (provinces, CMA)

F: Dummy variable representing the first immigrant generation. α is expected to be < 0

S: Dummy variable representing the second immigrant generation. γ is expected to be ≥ 0

E: Vector of dummy variables representing the ethnicities of immigrants. λ is expected to

be ≤ 0

This empirical model is a slightly modified version of the immigrant earnings equation

used by Chiswick (1978), which was later adopted by Bloom et al (1995).

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OLS estimation technique was used to derive all empirical results in this study.

As mentioned previously, most regressions will include the following independent

variables: Age, Age2, CMA, Female, Married, Non-Official Language and most

importantly, immigrant generation and ethnicity dummy variables. With the third

generation serving as the base group, first generation and second generation dummy

variables were shown in each of the regressions to contrast the differences in log earnings

between immigrant generations. It is widely accepted by economists that first generation

immigrants tend to have much lower earnings relative to third generation immigrants.

Therefore the magnitude of the “First Generation” variable is expected to be large, and its

sign is expected to be negative. Second generation immigrants were found by previous

studies to attain the highest level schooling and earnings among the three generation

groups (Chiswick, 1977, Carliner, 1980). However, it would not be surprising if any

wage differential between second and third generation is eliminated when schooling is

controlled for. The second generation may earn more than the third generation simply

due to higher educational attainment and nothing more. Therefore the sign of the

“Second Generation” variable is expected to be greater or equal to zero. However,

controlling for education should not eliminate differences in earnings between first and

third generation immigrants. The quality of education received by the first generation in

their home countries is unlikely to be comparable to the quality of education the third

generation received in Canada. CMA is included because the difference in earnings or

educational attainment may be due to the distance between residence and schools or

commercial zones. In addition, immigrants tend to concentrate themselves in CMAs

because earnings are higher in metropolitan areas. Provinces were also controlled - in all

- 22 -

regressions unless noted otherwise - to account for differences in legislation that affects

immigrants, i.e. labour laws and income redistribution policies. Seven (European-

Canadian, East Indian, Chinese, Filipino, Vietnamese, South Asian, South East Asian)

ethnicity dummy variables were included in most of the regression models, with Euro-

Canadian serving as the base group. These ethnicity dummy variables would capture any

discrimination minority individuals may face in the labour market. They may also

capture language deficiencies immigrants suffer which the education dummies cannot be

account for. For this reason, the Non-Official Language dummy variable is used.

Schooling in a foreign country is unlikely to provide destination specific skills, such as

English skills, to the same degree as schooling in the destination country itself. The

estimated values for each of these ethnic dummy variables - with the exception of Euro-

Canadian since this group is the base group - are expected to be negative for first

generation immigrants even when language ability is controlled for. While the estimated

values for the ethnic dummy variables may be positive or negative for second generation

immigrants, the magnitude of these values is expected to be close to zero or even

insignificant. Antecol et al (2005) found that earnings of first generation immigrants tend

to regress towards the mean as their length of stay in Canada grew longer. The same

logic can arguably be applied across immigrant generations. Due to assimilation, any

wage differential due to cultural differences would be much stronger within the first

immigrant generation than in the second immigrant generation.

- 23 -

Estimation Results

Table 3

The four regression models provided in Table 3 briefly outline any noticeable

differences in weekly earning between the three immigrant generations when controlling

for ethnicity and education. The base group for each regression are third generation

European-Canadians with high school education. At first glance, it appears that second

generation immigrants have higher earnings if and only if education remains

uncontrolled. When education is left uncontrolled as in regression I, second generation

immigrants appear to have 2% higher earnings than the third generation immigrants.

Regression III, which only controls for ethnicity, shows that the second immigrant

generation tend to have earnings are nearly 3% higher than the third immigrant

generation. Moreover, both of these values are significant at a 99% level. Both

regression II and IV show that once education is controlled for, the second generation

variable is no longer significant. Therefore differences in earnings observed between the

second and third generation are attributed to differences in educational attainment.

First generation immigrants have significantly lower earnings relative to second

and third generation immigrants. The four regression models show that they suffer an

earnings deficit of at least a 13% relative to the third immigrant generation ceteris

paribus. Interestingly, the wage gap shrinks once ethnicity is controlled for. The wage

deficit first generation immigrants experience falls from 19% to 13% once ethnicity is

controlled. South and South-East Asian immigrants may have lower earnings than

individuals of European descent due to their ethnicity. Although racial discrimination is

- 24 -

one possible explanation, the ethnicity variables could be capturing the difference in

quality of education. If so, the effects of “ethnicity” on second generation immigrants

would be insignificant since both the second and third generation immigrants receive

their schooling in the same country. By comparing the adjusted R-squared values of each

regression, it is clear that educational attainment explains the models to a much higher

degree than ethnicity.

Table 4

Regression IV from Table 3 is expanded in Table 4. Here, all of the coefficients

for each of the education and ethnicity control variables are shown. Third generation

European-Canadians with high school education remain as the base group in each

regression. Firstly, it is clear that immigrants of all 6 Asian ethnicities experience lower

wages relative to those of Euro-Canadian descent and these estimates are significant at a

99% level. This supports the hypothesis that ethnicity has a negative impact on earnings

for Asian minorities. Among the ethnic groups, the Vietnamese experience the smallest

disadvantage with earnings that are 11% lower than Euro-Canadians, while Filipino

immigrants experience the largest disadvantage with annual earnings that are nearly 26%

lower than Euro-Canadians. Chiswick (1988) had also found that Filipino immigrants

tended to have the lowest earnings among Asian ethnic groups.

When provinces are controlled, the wage gap between first and third generation

immigrants unsurprisingly widens. When arriving to Canada, majority of first generation

immigrants consciously choose to locate to specific provinces. Nearly 77% of the first

generation immigrants in this study resided in either Ontario or British Columbia. In

- 25 -

2000, Ontario and British Columbia had the highest and the third highest average

earnings in Canada.2 Moreover, both these provinces historically have had higher

minimum wages relative to the other provinces in Canada. Unfortunately, testing these

hypotheses is not within scope of this study. Nonetheless, this supports Bloom et al’s

(1995) argument that recent immigrants are more likely to “cluster together in networks

of families and ethnic neighbourhoods, making them feel less pressured to learn a new

language and fit into the Canadian labour market.” Similarly, 71% of second generation

immigrants live in Ontario or British Columbia. This is expected since majority of their

parents live in those two provinces.

Regression III shows that once 25 occupation variables are introduced, the

magnitude of the wage disparity Filipinos experience falls significantly (from 25.7% to

19.4%).3 This is expected since the majority of Filipinos in our restricted data set were

employed in lower paying occupations. Over 39% of the Filipino immigrants working

full-time fall into the following three categories: “machine operators and assemblers in

manufacturing”, “clerical occupations” or “occupations in travel and accommodation.”

While 35% of Filipinos in this study have a bachelor’s degree (see Table 2), none of

these occupations are particularly high paying. Therefore their low earnings may be

attributed to their choice in employment.

2 Ontarians working primarily full time had average earnings of $47,806 while British Columbians had average earnings of $46,015 in 2000.

3 To see the full list of occupation variables used, please refer to the appendix.

- 26 -

Table 5

Table 5 shows separate regressions by gender to allow a comparative study of the

determinants of earnings between the two groups. Second generation female immigrants

appears to enjoy a small (but significant) earnings premium over third generation

females. In contrast, second generation male immigrants do not have such advantage.

This finding substantiates claims that unobservable characteristics exist within at least

some of the second generation. Ethnicity has a larger negative effect on male immigrants

than on female immigrants. This result is in line with previous studies (Hum and

Simpson 1999, Pendakur and Pendakur 1998) which suggests that male immigrants are

more often discriminated against than female immigrants. The female population has

significantly higher returns to university-level education than the male population. Such

observation has been noted previously by Vaillancourt (1995), who found that rates of

returns for bachelor's-level studies are higher for women than for men in Canada.

Table 6

Separate regressions for the first and second generation are provided to further

show the effects of ethnicity on immigrant earnings. Immigrants of European-Canadian

descent with high school education serve as the base group. We can clearly see that both

ethnicity and language plays a more active role in the first generation than in the second

generation. When language is left uncontrolled, all of the ethnicity dummy variables are

significant at a 99% level for the first generation, whereas only “East Indian,” “Chinese”

and “Filipino” are significant at a 95%, 90%, and 90% level respectively for the second

generation. As hypothesized, the effects of ethnicity on wages weaken and wages tend to

- 27 -

regress towards the mean as immigrant generation rises (Borjas, 1993). Once language

ability is controlled, values for each of the ethnic variables decrease dramatically for the

first generation. A sizable portion of the wage gap existing between the first generation

Asian and European-Canadian immigrants is due to differences in language ability. As

for the second generation, all of its ethnicity variables are no longer significant. And as

shown, the “Non-Official Language” variable is significant at a 99% level in all cases.

This contradicts Pendakur and Pendakur’s 1998 conclusion that Canadian-born visible

minorities earn less than Canadian-born non-visible minorities.4 Perhaps the earnings

disadvantage they previously found is due to their poor proxy for language skills.5

First generation immigrants receive significantly lower returns to experience

relative to second generation immigrants. With language ability held constant, an

additional year of experience yields a modest 3% rise in earnings among first generation

immigrants. Conversely, second generation immigrants receive a 7% rise in earnings for

each additional year of experience. This result is in line with Schaafsma and Sweetman`s

(2001) and Trejo`s (2003) suggestion that work experience is unlikely to transfer

perfectly from one country`s labour market to another.

4 Although there is a difference between “visible minorities” and “South/South-East Asian minorities,” the results presented in this study should still be reasonably comparable since majority of foreign immigrants in Canada are from East Asia.

5 Ethnicity dummy variables remained largely unchanged when regression III of Table 6 were repeated using Pendakur and Pendakur’s “Knowledge of Official Language” variable.

- 28 -

Table 7

This study, as well as many others, has classified second generation immigrants as

immigrants who arrived in Canada between the ages 0-12, as well as those who had been

born in Canada and have at least 1 foreign-born parent. The purpose of Table 7 is show

evidence to whether if such classification legitimate. Chiswick (2003) found that, with

schooling, foreign-born immigrants who arrive in a host country at a young age tend to

exhibit the same characteristics as “natively” born second generation immigrants,

whereas Schaafsma and Sweetman (2001) had similar results but in terms of earnings.

Table 7 contains regressions which compares log earnings between these 2 groups to

determine whether such assumptions are valid. As usual, immigrants of European-

Canadian descent with high school education serve as the base group. Ethnicity appears

to have an unsubstantial impact on earnings for both groups. In regression I, only

“Chinese” and “Filipino” are significant at a 99% and 90% level respectively. Similarly,

“East Indian” is the only ethnic variable that is significant – at a 95% level – in regression

III, Canadian-born second generation immigrants have only one ethnicity variable, “East

Indian” that is significant (at a 95% level). Once language is controlled these ethnicity

variables become increasing insignificant.

Foreign-born second generation immigrants enjoy the same level of returns to

education as Canadian-born second generation immigrants. The only two exceptions are

at the elementary and doctorate level of schooling. Foreign-born second generation

immigrants experience lower returns from elementary schooling because the quality of

education outside of Canada is often lower. Education variables barely change when

language ability is controlled for and remain significant at a 99% level. Commonly used

- 29 -

methods to control for education are incapable of accounting for the quality of education.

While foreign-born and Canadian-born second generation immigrants are largely the

same, there are still a few noticeable differences. For example, Canadian-born second

generation receives higher benefits living in CMAs than the foreign-born second

generation.

Conclusion

This study has shown that first generation immigrants of any East Asian ethnicity

earn less than their Caucasian peers, ceteris paribus. Thus discrimination against foreign-

born immigrants in the Canadian labour market is likely to exist. In particular, first

generation immigrants of Asian origin are more likely to be discriminated against if they

are male. It is important to note that discrimination mentioned here does not appear to

stem from differences in skin colour, but rather from other unobservable characteristics

(i.e. foreign accent, lifestyle, etc). While ethnicity affects earnings of the first generation,

no such conclusion can be made for the second generation. In fact, earnings between the

second and third generation are very similar. Since lower earnings were not observed

among Asian second generation immigrants, then skin colour is not an important

component to racial discrimination. Second generation immigrants would not be affected

by discrimination if discrimination stems from characteristics that are not transferable

from the first generation to the next (i.e. foreign accent). Past journal articles (Antecol et

al 2005, Pendakur and Pendakur 1998, Baker and Benjamin 1994, Bloom et al 1995) has

established that first generation immigrants never fully assimilate into the Canadian

- 30 -

society. Here, we illustrated that second generation immigrants earn as much as – if not

more than – third generation immigrants.

Foreign-born and Canadian-born second generation immigrants are essentially

one and the same. Ethnicity does not have significant effects on earnings for either group

and both receive the same level of returns from education. The key characteristic which

differentiates the second generation from the third is that the second generation tend to

attain more education. It is clear that education explains almost the entire wage premium

the second generation enjoys over the other generations. However, second generation

female immigrants still earn slightly more than females from the third generation, ceteris

paribus. It would be most interesting to repeat this analysis using the data from the 2006

Canadian census. Since this difference is statistically significant, it provides some

credence that special characteristics exist within the second generation.

Positive selection bias may exist in the sample since first generation immigrants

made the conscious effort to immigrate to Canada (in hopes to improve their standard of

living). Their willingness to bare the costs of relocation suggests that they are more

ambitious and forward-looking than their peers who are still living in their home

countries. Furthermore, Canada has a point system which evaluates foreign individuals

applying for immigration rights. Those who pass the point system are reasonably adept

since a large portion of this test is based on skills attained (i.e. knowledge of official

languages, highest level of schooling, etc) in their home countries. Carroll et al (1999),

Gang and Zimmermann (2000), and Black et al (2005) all suggested that personal traits

such as work ethics and ambition can be transmitted from the first generation to the next.

These unobservable characteristics may explain the higher educational attainment among

- 31 -

the second generation. Unfortunately, this idea is only speculative and testing for

intergenerational mobility is not within the scope of this study.

While ethnicity does not have a strong direct effect on earnings for the second

generation, there may still be correlation between ethnicity and schooling. This study has

shown that second generation immigrants tend to have higher earnings due to their higher

educational attainment. Carroll et al (1999) found that cultural origin plays a significant

role in the saving behaviour of first generation immigrants, and that Asian immigrants

tend to have a higher savings rate than other ethnic groups. This savings behaviour could

apply to schooling as well, since schooling and saving money are both investments.

Perhaps Asians value future benefits more heavily than other ethnic groups.

- 32 -

Policy Implications

It is clear that those first generation immigrants who are unable to express

themselves in either English or French are at an enormous disadvantage in Canada. Our

empirical analysis has shown that both ethnicity and language variables are very large

and significant among the first generation. For example, first generation Filipinos earn

38% less than first generation European-Canadians. There are three possible ways where

Canadian policymakers could reduce this wage gap. Firstly, it could increase legislation

to protect immigrants from discrimination in the workplace. The Canadian government

could also provide incentives for first generation immigrants to develop better English or

French skills. Alternatively, they could increase emphasis on language ability in their

“100 point system.” Perhaps the system should award more points based on language

skills and less on work experience, especially since our study has shown that returns to

experience among the first generation are less than half of what the second generation

receive. Canadian policymakers should be acknowledged for the success that current

legislation is having on children of foreign-born immigrants. Nonetheless, they must also

focus on helping first generation immigrants integrate into Canadian Society as well.

- 33 -

References

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Quantities? Labor Market Institutions and Immigrant Earnings Growth in Australia, Canada, and the United States.” Journal of Human Resources, (2005), Forthcoming.

Baker, Michael and Dwayne Benjamin. “The Performance of Immigrants in the

Canadian Labor Market.” Journal of Labor Economics, Vol. 12, No. 3. (Jul. 1994), pp. 369-405.

Black, Sandra E., Paul J. Devereux and Kjell G. Salvanes. "Why the Apple Doesn't Fall

Far: Understanding Intergenerational Transmission of Human Capital." American Economic Review, Vol. 95(1), (Mar. 2005), pp. 437-449.

Bloom, David E., Gilles Grenier and Morley Gunderson. “The Changing Labour Market

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Borjas, George J. “Ethnic Capital and Intergenerational Mobility.” The Quarterly

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Chiswick, Barry R. “The effect of Americanization on the earnings of foreign-born

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Gang, Ira N. and Klaus F. Zimmermann. “Is Child like Parent? Educational Attainment

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Hum, Derek. and Wayne Simpson. “Wage Opportunities for Visible Minorities in

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- 35 -

Tables

Table 1. Data Restriction Method Used in Study Original Number of Observations in 2001 Canadian Census: 801,055

Criteria Number of Observations Dropped

Remaining Number of Observations

Keep if between age 25 and 64 360,470 440,585

Keep if mainly worked full-time in year 2000 136,415 304,170

Drop if average weekly earnings were less than $200 in year 2000 52,586 251,584

Drop if worked less than 40 weeks in year 2000 24,255 227,329

Drop if non-permanent resident 875 226,454 Drop if generational status was not

indicated 22 226,432

Keep if 1st, 2nd or 3rd generation immigrant 616 225,816

Drop if age of immigration was indicated but are not of 1st generation 37 225,779

Keep if and only if European-Canadian or South/South-East Asian ethnicity*

Jamaican 1,162 Lebanese 472

African 973 Other Arab origins 765 West Asian origins 847

Latin, Central and South American 972 Caribbean origins 1,587 Aboriginal origins 6,511

Australian, American 264 Other Origins** 9,961

23,514 202,265

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on Individuals Notes: Total number of observations used in study: 202,265 *The census provided 2 variables, "ethnicra" and "ethnicr", to indentify respondents ethnic origin. Both were utilized in this study to provide best results. Please see appendix for more information. **Those who indentified themselves as multiple ethnicities with no components of Canadian, English, Irish, Scottish, Welsh, French, Acadian, Provincial, or Aboriginal origin.

I II III IVFirst Generation -0.192*** -0.211*** -0.128*** -0.134***

(0.003) (0.003) (0.004) (0.004)

Second Generation 0.022*** -0.003 0.027*** 0.004(0.003) (0.003) (0.003) (0.003)

Female -0.287*** -0.307*** -0.287*** -0.306***(0.002) (0.002) (0.002) (0.002)

Married 0.086*** 0.082*** 0.087*** 0.083***(0.002) (0.002) (0.002) (0.002)

CMA 0.144*** 0.090*** 0.148*** 0.095***(0.002) (0.002) (0.002) (0.002)

Age 0.059*** 0.059*** 0.060*** 0.060***(0.001) (0.001) (0.001) (0.001)

Age 2 -0.001*** -0.001*** -0.001*** -0.001***(0.000) (0.000) (0.000) (0.000)

Adjusted R-squared 0.156 0.275 0.160 0.280

Is Education Controlled? NO YES NO YES

Is Ethnicity Controlled? NO NO YES YES

Number of Observations 202,265 202,265 202,265 202,265

Table 3. Estimates of the Log Earnings for Canadian Immigrants: A Comparison using Ordinary Least Squares

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on IndividualsNotes: Standard errors in parentheses. *,**,*** indicates significance level of 90, 95, and 99 percent respectively. Third generation (and higher) of Euro-Canadian descent is the base group in each of the regressions. All estimates were derived using a total of 202,265 observations. Provinces were controlled in all regressions.

I II IIIFirst Generation -0.134*** -0.090*** -0.116***

(0.004) (0.004) (0.004)

Second Generation 0.004 0.045*** 0.001(0.003) (0.003) (0.003)

Female -0.306*** -0.307*** -0.258***(0.002) (0.002) (0.002)

Married 0.083*** 0.096*** 0.065***(0.002) (0.002) (0.002)

CMA 0.095*** 0.109*** 0.083***(0.002) (0.002) (0.002)

Age 0.060*** 0.058*** 0.056***(0.001) (0.001) (0.001)

Age 2 -0.001*** -0.001*** -0.001***(0.000) (0.000) (0.000)

Ethnicity Dummy Variables

East Indian -0.129*** -0.118*** -0.119***(0.007) (0.007) (0.007)

Chinese -0.137*** -0.126*** -0.137***(0.006) (0.006) (0.006)

Filipino -0.257*** -0.260*** -0.194***(0.009) (0.010) (0.009)

Vietnamese -0.110*** -0.121*** -0.110***(0.015) (0.015) (0.014)

Other South Asian -0.245*** -0.237*** -0.225***(0.013) (0.013) (0.012)

Other South East Asian -0.117*** -0.105*** -0.113***(0.014) (0.014) (0.013)

Level of Education Dummy Variables

Elementary -0.161*** -0.184*** -0.111***(0.006) (0.006) (0.006)

Table 4. Estimates of Log Earnings by Immigrant Generation Status, Ethnic Origin and Educational Attainment using Ordinary Least Squares Some High School -0.074*** -0.073*** -0.046***

(0.004) (0.004) (0.003)

Trades Certification 0.064*** 0.058*** 0.047***(0.004) (0.004) (0.003)

College Diploma 0.150*** 0.153*** 0.089***(0.003) (0.003) (0.003)

Some University 0.144*** 0.149*** 0.096***(0.006) (0.006) (0.006)

University Diploma 0.226*** 0.212*** 0.141***(0.004) (0.004) (0.004)

Bachelors Degree 0.410*** 0.406*** 0.287***(0.003) (0.003) (0.003)

Masters Degree 0.504*** 0.502*** 0.369***(0.005) (0.005) (0.005)

Doctorate Degree 0.579*** 0.566*** 0.451***(0.011) (0.011) (0.011)

Adjusted R-squared 0.280 0.263 0.350

Control for Provinces? YES NO YES

Control for Occupation? NO NO YES

Number of Observations 202,265 202,265 202,265

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on IndividualsNotes: Standard errors in parentheses. *,**,*** indicates significance level of 90, 95, and 99 percent respectively. Third generation (or higher) of Euro-Canadian descent with a high school education is the base group in each of the regressions. All estimates were derived using a total of 202,265 observations.

Male FemaleFirst Generation -0.132*** -0.136***

(0.005) (0.006)

Second Generation -0.004 0.016***(0.004) (0.004)

Married 0.148*** 0.004(0.003) (0.003)

CMA 0.073*** 0.128***(0.003) (0.003)

Age 0.060*** 0.061***(0.001) (0.001)

Age 2 -0.001*** -0.001***(0.000) (0.000)

Ethnicity Dummy Variables

East Indian -0.157*** -0.085***(0.010) (0.011)

Chinese -0.205*** -0.051***(0.009) (0.009)

Filipino -0.317*** -0.211***(0.014) (0.012)

Vietnamese -0.137*** -0.059***(0.020) (0.021)

Other South Asian -0.270*** -0.184***(0.016) (0.022)

Other South East Asian -0.135*** -0.088***(0.019) (0.019)

Level of Education Dummy Variables

Elementary -0.150*** -0.200***(0.008) (0.010)

Some High School -0.063*** -0.099***(0.005) (0.005)

Table 5. Comparison of Log Earnings between Male and Female Immigrants Trades Certification 0.076*** 0.001

(0.005) (0.006)

College Diploma 0.155*** 0.142***(0.005) (0.004)

Some University 0.130*** 0.160***(0.008) (0.008)

University Diploma 0.195*** 0.252***(0.006) (0.006)

Bachelors Degree 0.379*** 0.436***(0.005) (0.004)

Masters Degree 0.452*** 0.569***(0.007) (0.008)

Doctorate Degree 0.545*** 0.651***(0.014) (0.020)

Adjusted R-squared 0.217 0.257

Control for Provinces? YES YES

Control for Occupation? NO NO

Number of Observations 117,679 84,586

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on IndividualsNotes: Standard errors in parentheses. *,**,*** indicates significance level of 90, 95, and 99 percent respectively. Third generation (and higher) of Euro-Canadian descent with a high school education is the base group in each of the regressions.

I II III IVFemale -0.276*** -0.281*** -0.280*** -0.280***

(0.006) (0.006) (0.005) (0.005)

Married 0.015** 0.036*** 0.109*** 0.107***(0.007) (0.007) (0.005) (0.005)

CMA 0.020** 0.043*** 0.110*** 0.112***(0.010) (0.010) (0.006) (0.006)

Age 0.032*** 0.030*** 0.070*** 0.070***(0.003) (0.003) (0.002) (0.002)

Age 2 -0.000*** -0.000*** -0.001*** -0.001***(0.000) (0.000) (0.000) (0.000)

Non-Official Language -0.173*** -0.101***(0.006) (0.011)

Ethnicity Dummy VariablesEast Indian -0.138*** -0.110*** -0.037** -0.021

(0.009) (0.009) (0.018) (0.018)

Chinese -0.151*** -0.076*** -0.025* -0.006(0.008) (0.008) (0.013) (0.013)

Filipino -0.266*** -0.213*** -0.054* -0.046(0.011) (0.011) (0.030) (0.030)

Vietnamese -0.116*** -0.034** -0.001 0.047(0.017) (0.017) (0.044) (0.045)

Other South Asian -0.261*** -0.203*** -0.008 0.010(0.015) (0.015) (0.044) (0.044)

Other South East Asian -0.176*** -0.117*** -0.008 0.000(0.018) (0.018) (0.029) (0.029)

Level of Education Dummy Variables

Elementary -0.141*** -0.087*** -0.171*** -0.157***(0.012) (0.012) (0.020) (0.020)

Some High School -0.038*** -0.027*** -0.070*** -0.069***(0.011) (0.011) (0.009) (0.009)

Table 6. Comparison of Log Earnings between the First and Second Immigrant Generation Cohorts

First Generation Second Generation

Trades Certification 0.124*** 0.113*** 0.054*** 0.054***(0.011) (0.011) (0.008) (0.008)

College Diploma 0.192*** 0.174*** 0.132*** 0.131***(0.010) (0.010) (0.007) (0.007)

Some University 0.086*** 0.081*** 0.132*** 0.132***(0.017) (0.017) (0.012) (0.012)

University Diploma 0.208*** 0.193*** 0.202*** 0.202***(0.012) (0.012) (0.010) (0.010)

Bachelors Degree 0.375*** 0.361*** 0.379*** 0.377***(0.009) (0.009) (0.007) (0.007)

Masters Degree 0.469*** 0.460*** 0.488*** 0.486***(0.013) (0.013) (0.012) (0.012)

Doctorate Degree 0.623*** 0.599*** 0.540*** 0.541***(0.020) (0.019) (0.027) (0.027)

Adjusted R-squared 0.252 0.271 0.260 0.261

Number of Observations 28,778 28,778 39,071 39,071

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on IndividualsNotes: Standard errors in parentheses. *,**,*** indicates significance level of 90, 95, and 99 percent respectively. Immigrants of Euro-Canadian descent with high school level education is the base group in each of the regressions. Provinces were controlled in all regressions.

I II III IIIIFemale -0.265*** -0.264*** -0.284*** -0.284***

(0.010) (0.010) (0.005) (0.005)

Married 0.105*** 0.101*** 0.112*** 0.110***(0.011) (0.011) (0.006) (0.006)

CMA 0.073*** 0.079*** 0.120*** 0.121***(0.013) (0.013) (0.006) (0.006)

Age 0.069*** 0.068*** 0.071*** 0.071***(0.005) (0.005) (0.002) (0.002)

Age 2 -0.001*** -0.001*** -0.001*** -0.001***(0.000) (0.000) (0.000) (0.000)

Non-Official Language -0.117*** -0.067***(0.017) (0.016)

Ethnicity Dummy Variables

East Indian -0.013 0.004 -0.071** -0.061**(0.024) (0.024) (0.028) (0.028)

Chinese -0.071*** -0.039* 0.020 0.025(0.020) (0.021) (0.018) (0.018)

Filipino -0.069* -0.056 -0.018 -0.019(0.038) (0.038) (0.050) (0.050)

Vietnamese -0.006 0.049 0.114 0.109(0.047) (0.048) (0.168) (0.168)

Other South Asian 0.020 0.038 -0.066 -0.055(0.052) (0.052) (0.086) (0.086)

Other South East Asian -0.051 -0.031 0.021 0.020(0.046) (0.046) (0.039) (0.039)

Level of Education Dummy Variables

Elementary -0.221*** -0.194*** -0.113*** -0.111***(0.031) (0.031) (0.027) (0.027)

Some High School -0.066*** -0.061*** -0.071*** -0.071***(0.018) (0.018) (0.010) (0.010)

Table 7. Comparison of Log Earnings within the Second Immigrant Generation Cohort

Foreign-Born* Canadian-Born

Trades 0.044** 0.046** 0.056*** 0.056***(0.018) (0.018) (0.010) (0.010)

College Diploma 0.140*** 0.136*** 0.129*** 0.129***(0.016) (0.016) (0.008) (0.008)

Some University 0.142*** 0.138*** 0.129*** 0.130***(0.025) (0.025) (0.013) (0.013)

University Diploma 0.206*** 0.202*** 0.200*** 0.200***(0.020) (0.020) (0.011) (0.011)

Bachelors Degree 0.406*** 0.401*** 0.369*** 0.369***(0.015) (0.015) (0.008) (0.008)

Masters Degree 0.519*** 0.510*** 0.478*** 0.478***(0.025) (0.025) (0.013) (0.013)

Doctorate Degree 0.642*** 0.640*** 0.507*** 0.508***(0.054) (0.054) (0.031) (0.031)

Adjusted R-squared 0.261 0.265 0.261 0.261

Number of Observations 8,846 8,846 30,225 30,225

Source: 2001 (Canadian) Census Public Use Microdata File (PUMF) on IndividualsNotes: Standard errors in parentheses. *,**,*** indicates significance level of 90, 95, and 99 percent respectively. Immigrants of Euro-Canadian descent with high school level education is the base group in each of the regressions. Provinces were controlled in all regressions.*These are immigrants who were born aboard and arrived in Canada before the age of 13

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Appendix

Illustration A

This graph was taken from Michael Baker and Dwayne Benjamin’s 1994 journal article,

The Performance of Immigrants in the Canadian Labor Market (see bibliography).

Table 1

During the data selection process, I wanted to include all the provinces and territories into

the analysis to avoid any selection bias. Unfortunately the level of detail for certain fields

was reduced. In particular, responses concerning the ethnicity of respondents living from

the Atlantic Provinces and the territories were not as detailed as responses from other

provinces. The census data provided two variables, ethnicra and ethnicr, to identify the

ethnicity of respondents. Ethnicra was detailed while ethnicr was less so. An issue that

may arise is that ethnicr grouped individuals who are Chinese, Vietnamese, Filipino, and

“Other South-East Asians” who are from the Atlantic provinces into one group.

Fortunately, there are only 49 respondents that fall into this category after restricting the

data set to only include full-time workers. These 49 observations were classified as

“Other South-East Asian” ethnic group in this study. Similarly, individuals of East

Indian and “Other South Asian” descent from the Atlantic Provinces and territories were

grouped together. The resulting 35 observations belonging to this group were classified

as “Other South Asian” ethnic group in this study. Visible minorities of multiple origins

fell into the “Other Origins” category in the census. Since the census does not go into

further detail, these individuals were excluded from the study.

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Table 2

The number of observations for Non-Official Language (Among Asians Only) was

different than what is listed at the bottom of the table since non-Asians immigrants were

excluded.

Generation Status Number of Observations

First Generation 13980

Second Generation 2554

Third Generation 320

Total # of Asians in this study 16854

Table 3-7

All regressions control for provinces unless noted otherwise, and British Columbia serves

as the base group.

Table 3

Here is the list of occupation dummy variables that were controlled in Regression III,

with “other management occupations” serving as the base group.

1 Senior management occupations 2 Other management occupations 3 Professional occupations in business and finance 4 Financial, secretarial and administrative occupations 5 Clerical occupations and clerical supervisors 6 Occupations in natural and applied sciences 7 Professional occupations in health, registered nurses and supervisors 8 Technical, assisting and related occupations in health 9 Occupations in social science, government services and religion

10 Teachers and professors 11 Occupations in art, culture, recreation and sport 12 Wholesale, technical, insurance, real estate sales specialists, and retail, wholesale and grain buyers 13 Retail trade supervisors, salespersons, sales clerks and cashiers 14 Chefs and cooks, supervisors, and other occupations in food and beverage service 15 Occupations in protective services 16 Childcare and home support workers 17 Service supervisors, occupations in travel and accommodation, attendants in recreation and sport and

sales and service occupations 18 Contractors and supervisors in trades and transportation 19 Construction trades 20 Other trades occupations 21 Transport and equipment operators 22 Trades helpers, construction, and transportation labourers and related occupations 23 Occupations unique to primary industries 24 Supervisors, machine operators and assemblers in manufacturing 25 Labourers in processing, manufacturing and utilities