Do immigrant nurses in Canada see a wage penalty? An empirical study.
Business Economics (2010) 45, 210-223.
Keywords: immigrant wages, nurses, economic discrimination
The issue of whether immigrants face wage penalties compared with domestically trained workers is an important one for many industries since it bears directly on the ability of firms and governments to attract qualified workers to positions in which there are shortages.
The purpose of this paper is to analyse the labour market for immigrant nurses in Canada and examine if there is an earnings penalty associated with being a foreign born and educated nurse. If there is a difference in the recognition or market valuation of educational credentials for nurses trained in Canada and in other countries, then it is hypothesized that individuals with foreign nursing degrees will attain lower earnings than those with a Canadian nursing degree. If the educational credentials are equivalent, then there should be no wage differential seen between a Canadian and a foreign nursing degree. This study adds to the literature, as this is a question that is not really answered for this specific occupation in Canada or the United States. Considering that there are currently nursing shortages in both Canada and the United States and that there are large numbers of immigrant nurses to both countries, examining the employment outcomes for this specific group of workers is important. If educational credentials of immigrant nurses and other workers are not readily transferrable to the labour markets in Canada or the United States, perhaps policy can be implemented to assist these workers to attain the credentials needed to become employed in their new country.
The health care professions in Canada and the United States make up a significant part of the economy. In times when health care reform is being debated and escalating health care costs are frequently a concern to government, examination of health human resources can have important implications. The question of educational credentials among health care workers is important. Canada and the United Stated have both experienced increases in the number of immigrants over recent years. These individuals bring with them their skills, education, and experience. However, in many cases they have difficulties in gaining employment in their chosen fields. This is important to the business world since this can result in qualified workers not being adequately used to fill jobs in industries facing labour shortages. On the other hand, barriers to employment may also be important in preventing those with insufficient or inadequate education from gaining employment and potentially resulting in negative outcomes.
Educational credential recognition is an important determinant of the occupations held by people with nursing training. In Canada, nursing is a regulated profession, meaning that no one can practice the profession without a valid Canadian license. Nurse licensing is done by the various provincial and territorial nursing associations that are organized under the umbrella association of the Canadian Nurses Association (CNA). Registered nurses arc those individuals who have successfully completed an approved program for professional nursing, have passed a written Canadian nurse registration examination, have demonstrated a competence in nursing, and have demonstrated a competence in one or both of the official languages. Canadian and immigrant nurses alike must all have a valid license to practice nursing in Canada. However, it is frequently seen that foreign-trained nurses have much lower rates of passing the exams. The number of internationally trained nurses who have attempted to write the licensing exam has been increasing significantly over the past several years as more people with nursing education immigrate to Canada [Canadian Nurses Association 2004].
An internationally trained nurse who wishes to work as a nurse in Canada must apply to the Canadian provincial regulatory bodies. The regulatory bodies assess each applicant's professional qualifications, educational credentials, and language proficiency to determine a candidate's eligibility to write the Canadian nursing license exam. This can take up to 18 months to process [Canadian Nurses Association 2004]. Of those who apply to write the licensing exam, about 35 percent met the educational and language requirements to be eligible to write the Canadian Registered Nurse Examination. Between 1998 and 2003, the average passing rate, given that the individual was eligible to write the exam, for foreign applicants was 58 percent as compared with 93 percent for Canadian applicants [CNA 2004].
There is an extensive literature surrounding wages and education for nurses. (1) Most of these studies focus on the returns to education for the various educational paths that can be selected by nurses and do not specifically examine foreign educational credentials. The conclusions that have been made regarding the labour market for nurses in the United States vary. Schumacher  examines the returns to education for nurses who obtain a baccalaureate and finds that they earn a higher wage than those who have a diploma. Mennemeyer and Gaumer , however, examine whether higher credentials for a nurse command a premium in the marketplace in the United States and find that there is no significant premium paid to nurses with higher educational credentials (with the exception of nurses who hold a Masters degree). Botelho, Jones, and Kiker  compare wage profiles of registered nurses in the United States across three educational backgrounds. Their results suggest that the wage equations are sensitive to different specifications of labour market experience.
There is a large Canadian labour economics literature relating to immigrant and native-born earnings differentials and credential recognition. This existing literature shows that immigrants in both Canada, and in other countries, initially have lower employment incomes than native-born and native-educated individuals. (2) Studies by Frenette and Morissette  and Aydemir and Skuterud  examine the deterioration of entry earnings of immigrants in Canada. Aydemir and Skuterud  find that declining returns to foreign education are not fully responsible for the decline in entry earnings of immigrants. They find that declining entry earnings of immigrants are explained by declining wage returns to foreign labour market experience. They also attribute this change to the shift away from the traditional European source countries to nontraditional sources and the resulting difference in the two official Canadian language abilities of new immigrants.
Li  uses the 1996 Canadian Census Public Use Microdata File (PUMF) to compare earnings for a variety of groups of individuals based on where their education was received. He finds that immigrants' educational credentials carry a penalty when compared with Canadians. Ferrer and Riddell , however, find that the credentials of immigrants are valued in the Canadian labour market.
Credential recognition associated with specific professions is often described as a form of discrimination, where restricted access to a trade or profession is frequently seen among those who are foreign born [Basran and Zong 1998; McDade 1988]. It must be recognized, however, that certification requirements are not necessarily discriminatory since certain restrictions can be viewed as essential. For example, in the nursing profession literacy and speaking ability in the official languages of Canada is necessary since their absence can potentially endanger the health and safety of a patient.
This paper will be structured as follows: Section 1 will describe the data that will be used, and it will introduce the theoretical model and the empirical specification that will be used; Section 2 will examine the summary statistics and present the regression results; and Section 3 will conclude with a discussion and implications.
1. Data and Methodology
This study uses data from the confidential master files of the 2001 Canadian Census on Individuals and will examine those whose major field of study was nursing. Using a basic human capital model of wage determination, this paper examines the wages of those with a Canadian degree and those with a foreign nursing degree. Using Census data, inferences can be made regarding where an individual likely attained her education. (3) It will be assumed that individuals who are born in Canada will have been educated in Canada. There may be a few cases of people who were born in Canada and attained their nursing education outside Canada, but it is anticipated that this will be a very small number. It will also be assumed that people who immigrate to Canada before the age of 19 will have received their nursing education in Canada, and these individuals will be treated as "domestically educated". Individuals who immigrated to Canada after the age of 30 and hold at least one degree will be assumed to have received their nursing education in a country other than Canada and will be considered to be "internationally educated". Those who immigrated to Canada between the ages of 19 and 30 and have at least one degree are considered to have a mixed education since it cannot be as easily inferred where they received their education. These individuals may have received some of their education in Canada and some in their country of origin, so it is not possible to infer where their education was received. Since their source of education cannot be determined, it will be interesting to examine whether these nurses more closely resemble the Canadian or the internationally educated immigrant groups.
For the purposes of this study immigrants will be grouped into five general groups of origin: the United States, Australia and Western and Northern Europe (which will form the reference group when those not born in Canada are examined); Eastern and Southern Europe; Central and South America; Africa and the Caribbean; and Asia. Within this sample of foreign-educated nurses, 66 percent list themselves as a visible minority and just over half (51 percent) list languages other than English or French as the language used at home. It is plausible that nurses who are fluent in English or French may be more likely to be promoted and therefore will have higher earnings, because individuals holding supervisory positions in particular may be called on to write reports or performance evaluations. Racial discrimination in hiring could possibly result in people who are of United States, Western or Northern European, or Australian descent being more likely to be promoted and therefore to earn higher wages and to have better outcomes than other visible minority groups. Coefficients on visible minority status, which remain statistically significant after controlling for language, education and other explanatory variables, can be interpreted as a measure of the extent of discrimination in the labour market.
Within a unionized environment, which has set pay scales for earnings, one should not expect to see a significant variation in these variables. Any variation that is seen can be partially driven by the locations where these nurses are employed. Those employed at nursing homes will see earnings lower than those in hospitals. Similarly, there will be some variation in pay seen among different nurses working within a hospital. There is expected to be a difference in pay seen by those who are working in various jobs within the same institution. Other factors can also underlie differences in pay seen by various individuals. Potential experience is another variable that can be underestimated since it is derived from someone's age and years of schooling. There is a potential that this value can be overestimated for individuals who may not have been able to enter the nursing labour market as quickly or easily as others. Canadian experience, not foreign experience, is recognized under union agreements so the structure of wage determination in the nursing profession would lead us to expect a lower return to potential experience for foreign born or educated individuals.
It is anticipated that individuals who are educated in the United States, Australia, and Western and Northern Europe will see wages closer to that which is seen in a nurse who is educated in Canada. This result is expected since immigrants from these regions have more similarities to Canadian nurses in terms of language and/or race. Thirty-eight percent of nurses who have emigrated from the United States, Western and Northern Europe, and Australia speak languages other than English or French as the language used at home, and only 2 percent report being a visible minority. Educational quality is deemed to be closely related to that which is seen in Canada, and this should allow for easier credential recognition for immigrants from these regions.
Until recently in Canada, nurses have had two main paths to human capital acquisition; these are the baccalaureate nurse (the BN designation) and community college-based diploma nurse (the RN designation). The education of nurses in the United States, Australia, and Western and Northern Europe is similar to that seen in Canada. Nurses in the United States have three basic paths for human capital accumulation; these include the two-year associate degree program, the three-year diploma program (equivalent to the Canadian RN designation), and the four-year baccalaureate program (equivalent to the Canadian BN designation). The nursing training programs vary across Europe, but mostly they involve either a diploma or baccalaureate nurse-training program.
Individuals from these regions are also similar in terms of broad racial categories as perceived by employees and employers. These countries are also similar in language, with English and French being commonly used languages. Finally, there are historical and cultural ties between Canada and these countries that are also expected to have an influence on perceptions of employees and employers.
It is anticipated that nurses who are educated in Africa and the Caribbean will see somewhat lower wages compared with Canadian educated nurses. In these cases it is expected that language will not be a factor in cases where English or French are commonly spoken. However, self-identified visible minority status will have a negative effect on the wages that will be earned by nurses from these areas of the world. Only 28 percent of nurses who have emigrated from Africa and the Caribbean speak languages other than English or French as their home language, and 92 percent of these immigrants report being a visible minority.
Nurses who are educated in Central and South America and in Asia are also expected to face wage discrimination, since language and self-identified visible minority status may both have potentially negative effects on the earnings of these individuals. Ninety-two percent of nurses who have emigrated from these regions speak languages other than English or French as their home language, and 97 percent report being a visible minority. Nurses educated in the Philippines currently must have a baccalaureate certification, but in the past they also had the option of taking a diploma program. Nurses in China can train though an associate degree program, a diploma program, or a baccalaureate program
The theoretical model
The most common framework in economic literature for the study of wage determination is the human capital model. The human capital earnings function will form the basis for this study. The most commonly used empirical estimation for the human capital model is based on the functional form of the Mincer  earnings equation:
log [w.sub.i] = [beta][X.sub.i] + r[S.sub.i] + [delta][e.sub.i] + [delta][e.sub.i.sup.2] +[u.sub.i], (1)
where [w.sub.i] is a measure of hourly wages for an individual i, [S.sub.i] represents the measure of the individual i's schooling or educational attainment, [e.sub.i] is a measure of potential experience. This is entered as a quadratic term to capture the concavity of the typical earnings profile; [X.sub.i] is a vector of other variables such as marital status, presence of children, province of residence, and native language each of which are assumed to affect earnings, and [u.sub.i] is a disturbance term which is assumed to be independent of [X.sub.i] and [S.sub.i].
A straightforward method utilizing the human capital framework can be used to examine the relative earnings of Canadian-born and educated nurses compared with nurses who have been trained in countries other than Canada. To answer the question about relative earnings of nurses in Canada, those who are trained as nurses and who are actively working as registered nurses will be included in the sample. (4) This allows me to focus explicitly on a very specific group of individuals to determine if there is any variation in the relative earnings of people with differing educational credentials who are working in the same profession. Much of the literature related to immigrant labour market outcomes show that immigrants face wage penalties compared with domestic workers. This study will test if this general result holds for individuals with nursing credentials.
The simplest method will look at two specifications. The first will include four dummy variables: one for the reference group of Canadian-born and educated nurses, one for the foreign born and educated nurses, a third for those who have a mixed education, and a final group for those who are foreign born but Canadian educated. This will be done within a pooled regression equation that includes all individuals in the data set who trained as nurses and who are working as nurses in Canada.
The second specification will include a series of dummy variables for the various country groups of origin (those from the United States, Western and Northern Europe, and Australia; those from Eastern and Southern Europe; those from Central and South America; those from the Caribbean and Africa; and those from Asia), with those born in Canada being the reference group. The level of wage advantage or disadvantage can then be measured by the coefficients on these dummy variables. These specifications will allow for an easy identification of a wage penalty associated with having a foreign nursing credential and for the identification of which specific regions of origin may be facing wage penalties compared with Canadians. If the hypothesis that foreign educated nurses suffer wage penalties is supported, one expects to find a statistically significant and negative coefficient on that independent variable.
The variables of interest
The dependent variable for this study is natural logarithm of hourly wages. In the 2001 Census on Individuals, employment income refers to total income received by persons 15 years of age and over during calendar year 2000 as wages and salaries. Since the standard Mincer equation uses the log of hourly wages as the dependent variable, the total income reported in the Census is divided by the average number of weeks worked and the average number of hours per week worked for each individual to derive hourly wage. (5)
An individual's age and potential experience are also characteristics that are, in general, expected to be positively related to wages. The standard Mincer equation using each person's age minus the years of schooling they have minus six is used to obtain an individual's potential work experience. Potential experience squared is also included in the regressions to capture the concavity of the typical earnings profile. One problem with this measure of potential experience is that it may overestimate the actual experience for people who have taken time out of the labour force for various reasons and thus lead to a bias in the results. However, because of the nature of the sample being used, this cannot be eliminated easily. For the foreign-educated nurses, their experience is composed of two aspects: their foreign and their Canadian work experience. Numerous existing studies including, for example, Reitz , Frenette and Morissette , Aydemir and Skuterud , and Alboim, Finnie, and Meng , show that an immigrant's foreign experience is penalized and not fully recognized once the immigrant begins working in Canada. This study will examine if this result holds for the specific occupation of nursing.
Finally, numerous individuals are omitted from the sample. Nurses who reported zero income or zero hours of work in the reference year are removed from the sample. Nurses who immigrated to Canada in 2000 or 2001 are also removed from the sample since there is a potential for these people to have arrived and begun work, but not have worked a full year yet. This number of people is quite small.
3. Data Description
The summary statistics for those who trained as registered nurses are found in Table 1. The proportion of nurses who have different educational credentials shows some variation. Sixty-six percent of Canadian born and 63 percent of the Canadian educated immigrant nurses have an RN designation, while only 55 percent of those with mixed education and 54 percent of the foreign educated nurses have the same designation. A somewhat higher proportion of the foreign born and educated nurses and the mixed education group (27 percent for each group) have a BN designation compared with the Canadian-born nurses (21 percent) and Canadian educated immigrants (24 percent). It is also to be noted that those who are working as nurses have a higher proportion in each group who have a BN designation.
Table 1. Summary Statistics tor the Sample of All Women Whose Major Field of Study was Nursing and Who are Either Currently Working as Registered Nurses or Not Working as Registered Nurses Canadian Born and Foreign Born and Educated Canadian Educated Working as Not Working Not an RN working as as an RN working an RN as an RN N = 26,905 N = 13,073 N = 1,758 N = 905 Age 42.5663 44.4369 40.8544 41.6641 Employment income 41,281.91 32,672.29 41,843.66 31,640.71 Hourly wages 28.62 29.21 27.95 31.03 Weeks 50.0488 48.2934 49.4226 46.8519 Hours 35.1974 34.7070 37.1200 35.3680 Potential experience 20.8310 23.0784 18.9283 20.3017 Potential Canadian experience Potential foreign experience Nonuniversity 0.6529 0.6813 0.6206 0.6674 certification Other certification below 0.0995 0.0822 0.0910 0.0873 Bachelors Bachelors degree 0.2217 0.1849 0.2520 0.1967 Higher degree 0.0259 0.0516 0.0364 0.0486 English 0.7014 0.7704 0.5199 0.4895 French 0.2610 0.1784 0.0301 0.0110 Other 0.0376 0.0512 0.4499 0.4994 Hospitals 0.6946 0.2366 0.7133 0.2586 Nursing and residential 0.1053 0.1161 0.1143 0.1392 care facilities Offices 0.0148 0.0270 0.0193 0.0276 Other health care 0.1149 0.0969 0.0956 0.0884 facilities Nonhealth care jobs 0.0703 0.5234 0.0575 0.4862 Separated, divorced or 0.1574 0.1627 0.1507 0.1657 widowed Married or common law 0.6542 0.6626 0.6257 0.6155 Single 0.1883 0.1747 0.2235 0.2188 No dependent children 0.4205 0.4801 0.4135 0.4442 Dependent children 0.5795 0.5199 0.5865 0.5558 Visible minority 0.0311 0.0449 0.4022 0.3856 Not a visible minority 0.9689 0.9551 0.5978 0.6144 United States, Western 0.4681 0.5138 and Northern Europe, and Australia Eastern and Southern 0.1212 0.0862 Europe Central and South 0.0478 0.0431 America Caribbean and Africa 0.1735 0.1370 Asia 0.1894 0.2188 Rural (less than 1,000) 0.2219 0.2568 0.1064 0.1238 Town (between 1,000 and 0.2594 0.2545 0.1268 0.1536 100,000) City (over 100,000) 0.5186 0.4887 0.7668 0.7227 The Atlantic Provinces 0.1088 0.0874 0.0233 0.0232 Montreal 0.0997 0.0625 0.0870 0.0541 Rest of Quebec 0.1324 0.0788 0.0108 0.0022 Toronto 0.0716 0.0844 0.3032 0.2552 Rest of Ontario 0.2842 0.3238 0.2776 0.2696 Manitoba 0.0472 0.0488 0.0370 0.0398 Saskatchewan 0.0405 0.0454 0.0119 0.0199 Alberta 0.1018 0.1212 0.0796 0.1006 Vancouver 0.0426 0.0549 0.1069 0.1315 Rest of BC 0 0596 0.0801 0.0557 0.0939 The Territories 0.0116 0.0129 0.0068 0.0099 Mixed Education Foreign Born and Educated Working as Not Working Not an RN working as an RN working as an RN as an RN N = 2,236 N = 1,132 N = 982 N = 1,699 Age 47.4812 47.8993 48.7546 45.0983 Employment income 44,277.74 25,525.72 41,568.86 29,437.68 Hourly wages 29.92 30.52 30.53 25.41 Weeks 49.6418 46.2792 49.0560 47.5468 Hours 37.6132 36.1405 37.8340 35.7157 Potential experience 25.0729 25.9488 26.3198 23.3508 Potential Canadian 10.4919 5.6716 experience Potential foreign 16.4471 19.7440 experience Nonuniversity 0.5456 0.5822 0.5346 0.6133 certification Other certification below 0.1400 0.1352 0.1365 0.1242 Bachelors Bachelors degree 0.2728 0.2261 0.2770 0.2166 Higher degree 0.0416 0.0565 0.0519 0.0459 English 0.4231 0.2898 0.4012 0.4044 French 0.0300 0.0133 0.0224 0.0200 Other 0.5470 0.6970 0.5764 0.5756 Hospitals 0.7035 0.1263 0.5947 0.1848 Nursing and residential 0.1453 0.1890 0.1986 0.1677 care facilities Offices 0.0161 0.0300 0.0316 0.0277 Other health care 0.0733 0.0883 0.0957 0.0836 facilities Nonhealth care jobs 0.0617 0.5663 0.0794 0.5362 Separated, divorced or 0.1637 0.1546 0.1864 0.1413 widowed Married or common law 0.7017 0.7482 0.6792 0.7404 Single 0.1346 0.0972 0.1344 0.1183 No dependent children 0.4852 0.4982 0.4929 0.4838 Dependent children 0.5148 0.5018 0.5071 0.5162 Visible minority 0.6453 0.6440 0.6660 0.5486 Not a visible minority 0.3547 0.3560 0.3340 0.4514 United States, Western and 0.2648 0.2076 0.2179 0.3384 Northern Europe, and Australia Eastern and Southern 0.0742 0.1237 0.0906 0.0977 Europe Central and South America 0.0344 0.0601 0.0458 0.0400 Caribbean and Africa 0.2428 0.1272 0.2342 0.1424 Asia 0.3828 0.4814 0.4084 0.3802 Rural (less than 1,000) 0.0604 0.0786 0.0540 0.0954 Town (between 1,000 and 0.0868 0.0751 0.0743 0.1101 100,000) City (over 100,000) 0.8529 0.8463 0.8717 0.7946 The Atlantic Provinces 0.0174 0.0062 0.0285 0.0224 Montreal 0.1199 0.0751 0.0733 0.0677 Rest of Quebec 0.0112 0.0053 0.0092 0.0047 Toronto 0.3640 0.3560 0.4145 0.3014 Rest of Ontario 0.1749 0.1413 0.1344 0.1913 Manitoba 0.0264 0.0336 0.0214 0.0359 Saskatchewan 0.0121 0.0150 0.0143 0.0106 Alberta 0.0966 0.1307 0.1059 0.1301 Vancouver 0.1234 0.1705 0.1517 0.1624 Rest of BC 0.0470 0.0557 0.0377 0.0636 The Territories 0.0072 0.0106 0.0092 0.0100
In terms of place of employment, the individuals with a mixed education appear to be more like the two Canadian educated groups. More Canadian-born nurses (72 percent), Canadian educated immigrants (74 percent) and mixed education (72 percent) work in hospitals compared with only 63 percent of the immigrant nurses, while 20 percent of the immigrant nurses work in nursing homes, compared with only 11 percent of Canadian nurses, 12 percent of the Canadian educated immigrants, and 15 percent of the mixed education nurses. It can also be seen that many individuals who are not working as nurses are still working in hospitals, nursing homes, and other health care industries. In many cases, these are individuals who are potentially working as nursing assistants or other jobs such as those within health care.
One final interesting difference to be seen in the three samples relates to where these nurses live. Fifty-one percent of Canadian nurses live in cities with a population over 100,000, while 77 percent of Canadian educated immigrant nurses, 85 percent of the mixed educated nurses, and 87 percent of foreign educated nurses live in cities. A larger proportion of Canadian nurses live in either a rural area or small town (22 and 26 percent respectively), while fewer of the immigrant nurses live in rural areas or towns (10 percent, and 13 percent for Canadian-educated immigrants, 6 and 9 percent for the mixed-educated nurses and 5 and 8 percent for foreign-educated nurses, respectively). There is also a distinction between the samples when one considers the three largest Census Metropolitan Areas of Montreal, Toronto and Vancouver. Forty-one percent of foreign educated nurses, 36 percent of mixed education nurses, and 30 percent of Canadian educated immigrant nurses live in Toronto, while only 7 percent of the Canadian-born nurses live there. Similarly, more immigrant nurses live in Vancouver (11 percent of Canadian-educated immigrant nurses, 13 percent of mixed-education nurses, and 16 percent of foreign-educated nurses--compared with only 5 percent of Canadian nurses).
Table 2 reports information about the various occupations in which the different individuals who trained as nurses are working. In terms of occupations, it can be seen that those who are Canadian-born and the immigrants who are Canadian educated show nearly the same proportion (close to 65 percent for each group) of those who trained as nurses and are actually working as registered nurses. In contrast, 55 and 45 percent of those with a mixed education and foreign education, respectively, are working as registered nurses. It can also be noted that there is a relatively large proportion of those with foreign and mixed educations who are working in other health care occupations (around 14 and 17 percent respectively) compared with 9 percent for those born in Canada. The next largest group of occupations where those trained as nurses are found are in sales and service occupations. Here we see 9 percent of the mixed-education nurses and 14 percent of the foreign-trained nurses, compared with only about 5 percent of the other two groups.
Table 2. Detailed Description of the Various Occupational Groupings where Those Who Trained as Nurses are Working and Separated by the Different Educational Source Location All Nurses Canadian Born Foreign Born and Canadian and Canadian Educated Educated Freq. Percent Freq. Percent Freq. Percent Working as a nurse Nurse Supervisor 1134 2.33 1017 2.54 41 1.54 Registered Nurse 30747 63.15 25888 64.76 1717 64.48 Not working as a nurse Other health 5009 10.27 3757 9.44 334 12.57 occupations Management 2314 4.74 1903 4.8 120 4.53 occupations Business, finance and 3548 7.24 2834 7.17 175 6.64 administrative occupations Sales and service 2885 5.91 2075 5.27 140 5.28 occupations Other (a) 1275 2.44 964 2.43 55 2.13 Total 48691 100 39978 100 2663 100 Foreign Born Mixed Education and Foreign Educated Freq. Percent Freq. Percent Working as a nurse Nurse Supervisor 26 1.23 50 1.27 Registered Nurse 956 45.22 2186 55.55 Not working as a nurse Other health occupations 365 17.25 553 14.08 Management occupations 112 5.32 179 4.57 Business, finance and administrative 181 8.56 358 9.15 occupations Sales and service occupations 304 14.39 365 9.34 Other (a) 119 5.69 137 3.61 Total 2114 100 3935 100 (a) This group includes: Natural & Applied Sciences and Related Occupations, Occupations in Social Science, Education, Government Service & Religion, Occupations in Art, Culture, Recreation and Sport, Trades, Transport and Equipment Operators and Related Occupations, Occupations Unique to Primary Industry, Occupations Unique to Processing, Manufacturing and Utilities.
Table 3 reports information about various industries in which the different individuals who trained as nurses are working. As was seen with the different occupations where those trained as nurses are found, the same trend is seen in the various industries as well. Both Canadian-born women and immigrants who trained as nurses in Canada show very similar outcomes, but a difference can be seen between these two groups and those educated outside Canada. Around 55-56 percent of those born in Canada and immigrants educated in Canada work in hospitals, while about 11-12 percent work in nursing homes. Alternatively, only 34 percent of those educated outside of Canada work in hospitals but a larger proportion tend to work in nursing homes (19 percent).
Table 3. Detailed Description of the Various Industry Groupings where Those Who Trained as Nurses are Working and Separated by the Different Educational Source Location All Nurses Canadian Born Foreign Born and Canadian and Canadian Educated Educated Freq. Percent Freq. Percent Freq. Percent Offices 2606 5.35 2082 5.21 140 5.26 Hospitals 25884 53.16 21782 54.48 1488 55.88 Nursing homes 5697 11.7 4351 10.88 327 12.28 Other health Industries 5514 11.31 4683 11.73 264 9.92 Retail trade 1103 2.27 851 2.16 50 1.91 Educational services 1485 3.05 1266 3.17 70 2.64 Other (a) 6402 13.12 4963 12.59 324 12.32 Total 48691 100 39978 100 2663 100 Foreign Born Mixed Education and Foreign Educated Freq. Percent Freq. Percent Offices 155 7.33 229 5.82 Hospitals 727 34.39 1887 47.95 Nursing homes 409 19.35 610 15.5 Other health Industries 234 11.08 332 8.43 Retail trade 75 3.55 127 3.25 Educational services 44 2.09 98 2.5 Other (a) 470 22.23 645 16.67 Total 2114 100 3935 100 (a) This group includes: Agriculture, Forestry, Fishing and Hunting, Mining and Oil and Gas Extraction, Utilities, Construction, Manufacturing, Wholesale Trade, Transportation and Warehousing, Information and Cultural Industries, Finance and Insurance, Real Estate and Rental and Leasing, Professional, Scientific and Technical Services, Management of Companies and Enterprises, Administrative and Support, Waste Management and Remediation Services, Arts, Entertainment and Recreation, Accommodation and Food Services, Other Services (except Public Administration) and Public Administration.
In the first set of regression results the focus is only on individuals who have qualified to work as a nurse in Canada. There exists the possibility that a sample selection bias problem may be present, in that the sample includes only those immigrant nurses who qualified to write and pass the licensing exam to enter the nursing profession in Canada. These individuals may be more able, and this will tend to bias the results toward the finding of no penalty to foreign birth/education.
The regression results for the first exercise, which examines earnings of women who trained as nurses and who are working as a registered nurse, are found in Table 4. The first column controls for the four basic educational groupings, which include the reference group of Canadian-born, Canadian-educated immigrants, mixed-educated nurses, and foreign-educated nurses. The second column controls for the various general country regions.
Table 4. Regression Results for the Mincer Earnings Equation for the Sample of All Women Working as Nurses (Robust Standard Errors in Parenthesis) (1) (2) Constant 2.8334 *** (0.0217) 2.8409 *** (0.0217) Potential experience 0.0247 *** (0.0018) 0.0245 *** (0.0018) Potential experience -0.0004 *** (0.0000) -0.0004 *** (0.0000) squared Other certification below 0.0202 * (0.0132) 0.0174 * (0.0132) Bachelors Bachelors degree 0.1229 *** (0.0095) 0.1191 *** (0.0095) Higher degree 0.0912 *** (0.0267) 0.0876 *** (0.0267) Canadian educated -0.0446 ** (0.0207) immigrant Foreign educated -0.0916 *** (0.0286) immigrant Mixed education -0.0328 * (0.0202) United States, Western and Northern Europe, and Australia -0.0354 ** (0.0178) Eastern and Southern -0.0903 ** (0.0386) Europe Central and South -0.0229 (0.0458) America Caribbean and Africa -0.0874 *** (0.0360) Asia 0.0314 (0.0332) Dependent children 0.0076 (0.0087) 0.0087 (0.0087) French 0.0468 *** (0.0159) 0.0414 *** (0.0160) Other language 0.0473 *** (0.0168) 0.0286 * (0.0187) Separated, divorced or -0.0169 (0.0150) -0.0150 (0.0149) widowed Married or common law 0.0449 *** (0.0122) 0.0437 *** (0.0122) Nursing and residential -0.1614 *** (0.0136) -0.1619 *** (0.0135) care facilities Offices -0.1848 *** (0.0199) -0.1859 *** (0.0199) Other health care -0.0913 *** (0.0121) -0.0907 *** (0.0121) facilities Visible minority -0.1110 *** (0.0184) -0.1284 *** (0.0250) N 33,207 33,207 [R.sup.2] 0.0370 0.0375 Dependent variable is the natural log of hourly wages Significance indicated by *** for 1 percent, ** for 5 percent and * for 10 percent. Reference groups are RN certification, Canadian-born and educated, Canadian-born, English, No childcare, Single, Hospitals, Nonvisible minority status. Urban and rural dummies and provincial dummies are also included but not presented.
The interesting thing to notice is that the coefficient on foreign education is negative and statistically significant. This supports the hypothesis that nurses who obtain their education in a country other than Canada face a wage penalty, given that they are working as a nurse in Canada. Nurses who were educated outside of Canada face 9 percent lower wages compared with Canadian-born nurses. Canadian-educated immigrant nurses and the group of nurses who have a mixed education see wage penalties as well, but only about half of what the internationally trained nurses observe. When region of origin is controlled for, it is seen that nurses from the United States, Western and Northern Europe, and Australia see nearly a 4 percent wage penalty, while nurses from Eastern and Southern Europe see a 9 percent penalty. Those from Africa and the Caribbean see a 9 percent wage penalty. The effect is not statistically significant for those from Asia or from Central and South America. It was anticipated that nurses from Africa and the Caribbean would see larger wage penalties compared with nurses from the United States, Western and Northern Europe, and Australia.
There are several other variables that are of interest. In this sample, being a self-identified visible minority results in a significant earnings penalty of roughly 11-13 percent, depending on which variables are controlled for. This result is also expected and it is consistent with numerous existing studies that examine earnings for immigrants. The various levels of education have statistically significant effects for most of the regressions. Having a Bachelors degree results in an earnings benefit of around 12 percent compared with an RN certification. A higher degree (having additional education beyond the first nursing degree or certification) has a significant wage benefit of around 9 percent for this nursing sample. Similarly, the premiums associated with the various educational levels for nurses are consistent with the results found in studies examining American nurses.
Since international education and countries of origin both show a statistically significant effect in the initial regressions, the second exercise allows for a closer examination of this. The second exercise will consider each of the four origins of nursing education, Canadian-born, Canadian-educated immigrants, mixed-educated immigrants, and foreign-educated immigrants, separately. The results are presented in Tables 5 and 6. For each of the immigrant samples, two regressions will be analyzed. In the first regression, a dummy variable will be included for visible minority status in Table 5; and in the second regression for each sample, the country of origin groupings will be controlled for in Table 6.
Table 5. Regression Results for the Mincer Earnings Equation for the Sample of All Women Working as Nurses (Robust Standard Errors in Parenthesis) Canadian Born and Foreign Born and Canadian Educated Canadian Educated Constant 2.8318 *** (0.0243) 2.6751 *** (0.0970) Potential Canadian 0.0250 *** (0.0018) 0.0329 *** (0.0103) experience Potential Canadian -0.0004 *** (0.0000) -0.0006 *** (0.0003) experience squared Foreign potential experience Foreign potential experience squared Other certification 0.0287 ** (0.0137) -0.0786 (0.0824) below Bachelors Bachelors degree 0.1276 *** (0.0102) 0.1113 *** (0.0411) Higher degree 0.0894 *** (0.0321) 0.0522 (0.0752) Childcare 0.0145 * (0.0093) -0.0289 (0.0406) French 0.0358 ** (0.0170) 0.0918(0.1028) Other language 0.0280 (0.0236) 0.1108 *** (0.0431) Married or common law -0.0046 (0.0152) -0.0422 (0.0863) Separated, divorced or 0.0358 *** (0.0128) 0.1411 ** (0.0640) widowed Nursing homes -0.1446 *** (0.0144) -0.2964 *** (0.0758) Offices -0.1906 *** (0.0205) -0.3537 *** (0.1197) Other health care -0.0787 *** (0.0127) -0.0721 (0.0592) facilities Visible minority -0.1350 **** (0.0291) -0.0653 * (0.0494) N 27.934 1.831 [R.sup.2] 0.0368 0.0758 Mixed Education Foreign Born and Foreign Educated Constant 2.7475 *** (0.0994) 2.6603 *** (0.3373) Potential Canadian 0.0304 *** (0.0086) 0.0356 * (0.0249) experience Potential Canadian -0.0004 *** (0.0002) -0.0005 (0.0004) experience squared Foreign potential experience Foreign potential experience squared Other certification below 0.0492 (0.0459) -0.1133 (0.0923) Bachelors Bachelors degree 0.0817 ** (0.0385) 0.0901 * (0.0607) Higher degree 0.1410 ** (0.0762) 0.1149 * (0.0814) Childcare -0.0101 (0.0357) -0.1111 ** (0.0545) French -0.0509(0.1099) 0.3636 *** (0.1424) Other language 0.0558 * (0.0365) 0.0542 (0.0600) Married or common law -0.0847 (0.0671) -0.1109 (0.1113) Separated, divorced or 0.0854 * (0.0525) -0.0206 (0.0743) widowed Nursing homes -0.2000 *** (0.0492) -0.2091 *** (0.0674) Offices 0.0380 (0.0798) -0.2191 ** (0.1127) Other health care -0.2529 *** (0.0689) -0.2151 *** (0.0712) facilities Visible minority -0.1843 *** (0.0385) -0.0059 (0.0597) N 2.368 1.074 [R.sup.2] 0.0546 0.0505 Foreign Born and Foreign Educated Constant 3.9373 *** (0.2743) Potential Canadian experience -0.0444 ** (0.0251) Potential Canadian experience squared -0.0001 (0.0010) Foreign potential experience -0.0179 * (0.0125) Foreign potential experience squared 0.0000 (0.0003) Other certification below Bachelors -0.1089 (0.0915) Bachelors degree 0.0954 * (0.0616) Higher degree 0.1394 ** (0.0795) Childcare -0.1160 ** (0.0546) French 0.3010 ** (0.1412) Other language 0.0655 (0.0603) Married or common law -0.1052 (0.1098) Separated, divorced or widowed -0.0183 (0.0726) Nursing homes -0.1889 *** (0.0667) Offices -0.1802 * (0.1144) Other health care facilities -0.2001 *** (0.0691) Visible minority 0.0035 (0.0584) N 1.074 [R.sup.2] 0.0720 Dependent variable is the natural log of hourly wages. Significance indicated by *** for 1 percent, ** for 5 percent and * for 10 percent. Reference groups are RN certification, English, No childcare. Single, Hospitals, Nonvisible minority status. Urban and rural dummies and provincial dummies are also included but not presented. Table 6. Regression Results for the Mincer Earnings Equation for the Sample of All Women Working as Nurses (Robust Standard Errors in Parenthesis) Foreign Born and Mixed Education Canadian Educated Constant 2.7076 *** (0.0940) 2.7669 *** (0.1031) Potential Canadian 0.0342 *** (0.0104) 0.0299 *** (0.0086) experience Potential Canadian -0.0007 *** (0.0003) -0.0004 *** (0.0002) experience squared Foreign potential experience Foreign potential experience squared Other certification below -0.0774 (0.0825) 0.0211 (0.0462) Bachelors Bachelors degree 0.1023 *** (0.0414) 0.0545 * (0.0384) Higher degree 0.0432 (0.0734) 0.1167 * (0.0754) Childcare -0.0240 (0.0407) -0.0071 (0.0356) French 0.1110 (0.1035) -0.0510 (0.1137) Other language 0.0760 * (0.0513) 0.0096 (0.0474) Married or common law -0.0413 (0.0857) -0.0659 (0.0669) Separated, divorced or 0.1352 ** (0.0637) 0.0830 * (0.0522) widowed Nursing homes -0.2956 *** (0.0756) -0.1949 *** (0.0495) Offices -0.3548 *** (0.1221) 0.0522 (0.0806) Other health care -0.0708 (0.0590) -0.2463 *** (0.0692) facilities Eastern and Southern -0.0272 (0.0659) -0.0466 (0.0781) Europe Central and South America 0.0256 (0.0713) -0.0976 (0.0792) Caribbean and Africa -0.2052 *** (0.0638) -0.2134 *** (0.0524) Asia -0.0172 (0.0692) -0.0910 ** (0.0545) N 1,831 2,368 [R.sup.2] 0.0815 0.053 Foreign Born and Foreign Born and Foreign Educated Foreign Educated Constant 2.6428 *** (0.3373) 3.9589 *** (0.2831) Potential Canadian 0.0372 * (0.0248) -0.0455 ** (0.0255) experience Potential Canadian -0.0006 * (0.0004) -0.0001 (0.0010) experience squared Foreign potential -0.0174 * (0.0125) experience Foreign potential 0.0000 (0.0003) experience squared Other certification below -0.1139 (0.0928) -0.1140 (0.0921) Bachelors Bachelors degree 0.0900 * (0.0592) 0.0868 * (0.0600) Higher degree 0.1198 * (0.0816) 0.1393 ** (0.0795) Childcare -0.1093 ** (0.0548) -0.1141 ** (0.0548) French 0.3520 *** (0.1441) 0.2877 ** (0.1430) Other language 0.0692 (0.0815) 0.0590 (0.0810) Married or common law -0.1144 (0.1097) -0.1062 (0.1083) Separated, divorced or -0.0247 (0.0743) -0.0240 (0.0725) widowed Nursing homes -0.2052 *** (0.0679) -0.1856 *** (0.0669) Offices -0.2174 ** (0.1129) -0.1777 * (0.1147) Other health care -0.2159 *** (0.0721) -0.1988 *** (0.0701) facilities Eastern and Southern -0.0383 (0.1174) -0.0352 (0.1154) Europe Central and South -0.1244 (0.1177) -0.1208 (0.1177) America Caribbean and Africa 0.0100 (0.0877) -0.0015 (0.0877) Asia -0.0195 (0.0889) 0.0203 (0.0894) N 1,074 1,074 [R.sup.2] 0.0516 0.0733 Dependent variable is the natural log of hourly wages. Significance indicated by *** for 1 percent, ** for 5 percent and * for 10 percent. Reference groups are RN certification, Bora in the United States, Western or Northern Europe, or Australia, English, No childcare, Single, Hospitals, Nonvisible minority status. Urban and rural dummies and provincial dummies are also included but not presented.
The first distinction that becomes apparent when the nurses are separated by the educational source groupings relates to potential experience. We see that there is a penalty associated with potential experience for the foreign born and trained nurses. Both their foreign and Canadian potential experience is penalized. The low or negative returns to potential Canadian experience for those who are foreign born and educated indicates that a difference between actual experience in the Canadian labour market and potential experience may be particularly significant for foreign educated nurses.
Another distinction that becomes apparent when the nurses are separated by their educational groupings is the varying benefits to the different levels of nursing education. Looking at these samples we see that having a Bachelors degree results in a higher wage premium for Canadian-born nurses. Canadian educated immigrants and foreign educated immigrants see a wage premium of roughly 9-12 percent, while immigrants with a mixed education see a 5-8 percent premium when they have a BN certification. The benefit seen by Canadian-born nurses with a Bachelors degree is seen as a wage premium of nearly 13 percent. Having a higher degree is seen to be beneficial for all of the nurses, with the largest benefit being seen by those with a mixed education or a foreign education, with a benefit of around 14 percent.
Other variables of interest include place of employment. All of the nurses show an earnings penalty compared with those working in a hospital setting. In nearly every case both groups of immigrant nurses see a larger penalty compared with Canadian nurses. This result is potentially driven by the unionization that is common in the nursing profession in Canada. Hospitals employ the largest proportion of nurses in Canada and they also follow a structured pay scale. Nurses who work in nursing homes are also unionized but are covered by different collective bargaining units and see lower earnings than those in hospitals. Nurses working in offices and other health care facilities are less frequently unionized.
Language is not particularly a significant variable in determining wages for nurses. Speaking French at home is beneficial for Canadian-born nurses. It is also seen that speaking French at home is highly beneficial for foreign-educated nurses, but this result is driven by the small sample size of nurses who have this characteristic.
Being a visible minority yields some interesting results. Canadian-born nurses see a 14 percent earnings penalty, those with a mixed-education see an 18 percent penalty, and Canadian-educated immigrant nurses see a 7 percent penalty resulting from being a visible minority. This result is not statistically significant for the nurses who are foreign born and educated. It is interesting to note that Canadian-educated nurses and nurses with a mixed education from Africa and the Caribbean see a 21 percent earnings penalty when compared with nurses from the U.S., Western and Northern Europe, and Australia. The effect of being from Asia is not statistically significant for the foreign born samples of nurses.
4. Discussion, Implications, and Conclusion
The results of this study support the hypothesis that immigrant registered nurses suffer wage penalties in Canada. These results are consistent with findings in the literature regarding immigrant earning outcomes. It is also interesting to note that the same results hold for the specific labour market of nurses. Wage penalties are seen by both the immigrant nurses who arrived in Canada at a young age and the immigrant nurses who come to Canada at a later age with nursing credentials, although the penalty is larger for the older immigrants. Once the various regions of birth are controlled for it is seen that there is a wage penalty to all of them except for those from Asia and from Central and South America, where the results are not statistically significant. The penalty is the smallest for those from the United States, Western and Northern Europe, and Australia. It was hypothesized that immigrants from these regions would see the smallest earnings penalty because of the broad similarities to Canadian-born nurses. The groups from Eastern and Southern Europe as well as those from Africa and the Caribbean see the largest penalty. However, it was also anticipated that those from Asia should see penalties as well.
The nursing shortage in Canada is an important policy area that needs to be examined. Many nurses immigrating to Canada from other countries are bringing their educational skills and experience to the employment market for registered nurses in Canada. This brain gain could be beneficial to the labour market for nurses in Canada since recently there have been shortages of qualified nurses in Canada. The shortage of nurses will likely grow over time as the demographics in Canada shift and as some individuals begin to require additional medical and nursing care as they grow older. The recognition of foreign nursing educational credentials can be an avenue to attempt to alleviate the shortage of nurses in Canada and in other countries as well. The results of this study indicate that this is an important area to examine in the United States as well. In both countries, immigrants, in general, see wage penalties. Since the United States is also seeing a nursing shortage, this is an important question to address there as well. Immigrant nurses can be a source of labour in this field, but credentials are important to consider.
This result applies beyond the health care field and into other business as well. Immigrant workers face wage penalties in general and perhaps policy should be implemented to aide new immigrants in upgrading their qualifications so that they can gain meaningful employment in their new country. This would be beneficial to all parties involved.
Alboim, Naomi, Finnie, Ross, and Meng, Ronald. February 2005. "The Discounting of Immigrants' Skills in Canada: Evidence and Policy Recommendations." IRPP Choices, 11(2): 1-28.
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Basran, G.S., and Zong, L. 1998. "Devaluation of Foreign Credentials as Perceived by Visible Minority Immigrants in Canada." Canadian Ethnic Studies, 30: 6-23.
Botelho, Anabela, Jones, Cheryl Bland, and Kiker, B.F. 1998. "Nursing Wages and Educational Credentials: The Role of Work Experience and Selectivity Bias." Economics of Education Review, 17(3): 297-306.
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--. 2002. "Skilled Immigrant Labour: Country of Origin and the Occupational Locations of Male Engineers." Canadian Studies in Population, 29(1): 71-99.
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McDade, Kathryn. 1988. Barriers to Recognition of the Credentials of Immigrants in Canada. Institute for Research on Public Policy.
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(1) See, for example, Botelho, Jones, and Kiker , Mennemeyer and Gaumer , Nowak and Preston , and Schumacher .
(2) See, for example, Alboim, Finnie, and Meng , Basran and Zong , Boyd and Thomas [2001, 2002], Bratsberg and Ragan , Ferrer and Riddell , Friedberg , McDade , Reitz , and Sweetman .
(3) Only women will be examined in this paper as the sample of male immigrant nurses is relatively small.
(4) The nursing sample is identified by selecting those whose list their major field of study to be nursing and who further identify themselves as working as a registered nurse.
(5) The various exercises and regressions were also executed using annual employment earnings and the results are very similar to that which was found using the derived hourly wages.
KAREN J. BUHR *
* Karen J. Buhr is an assistant professor of Economics at the University of Maine and holds a joint appointment with the School of Economics and the Canadian American Center. Her current research focuses on the labor market for registered nurses in the United States and Canada. She is particularly interested in studying earnings, workplace stress, and job satisfaction among nurses and how this affects retention. She received a BA with honours in economics from the University of Winnipeg, an MA in economics from Queen's University in Ontario, and a Ph.D. in economics from Carleton University.
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|Comment:||Do immigrant nurses in Canada see a wage penalty?|
|Author:||Buhr, Karen J.|
|Date:||Jul 1, 2010|
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