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Offshorability and wages in the service sector

By Yuqian Lu and René Morissette

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In the early 1980s, the notion that manufacturing jobs in advanced economies were being lost to developing countries gained attention. According to one popular hypothesis, 'de-industrialization' would leave the service sector polarized into high-wage 'knowledge' jobs and low-wage personal service jobs (Bluestone and Harrison 1982).

A new version of the de-industrialization hypothesis emerged recently. Some authors noted that employers had started using offshoring-outsourcing abroad-not only for manufacturing goods, but also for jobs in the service sector that had high skill requirements (Businessweek 2003 and 2004). According to this view, the rise in information and communication technologies (ICTs) and the availability of relatively skilled workers in fast-growing countries were making service offshoring feasible. These factors were assumed to enable firms to move highly paid jobs like engineering and informatics to China, India and Eastern European countries with the skilled workforce required for these jobs.1

Like any form of international trade, service offshoring may affect both employment and domestic wages.2 Service-producing jobs that are offshorable that can technically be moved abroad even though they have not been relocated yet-might be subject to greater downward wage pressure than other service-sector jobs due to competition from workers in emerging economies with lower wages. As a result, the wages for offshorable jobs might grow more slowly than for other jobs.

On the other hand, offshoring is just one of many factors that contribute to occupational wage trends and even its effect may not be simple and direct. If the offshoring of some jobs yields a competitive advantage to a firm, it may expand and increase employment in closely related occupations, resulting in upward wage pressure. In addition, demand for some service-producing occupations that could be moved abroad could be growing in Canada, for reasons unrelated to offshoring. If so, there would also be upward wage pressures in these occupations.3 

Whether wages in offshorable service occupations grew more or less than wages in other service jobs is an empirical question this article examines.

Several studies have examined the association between offshoring and wages in manufacturing. Using the share of intermediate inputs that are imported as a measure of offshoring, many studies find that foreign outsourcing increased the relative wages of nonproduction workers in manufacturing over the past few decades (Feenstra and Hanson 1996 and 1999; Hijzen et al. 2004; and Yan 2006).

Other studies have assessed the impact of trade and offshoring on wages in the service sector and across certain industries. Liu and Trefler (2008) link U.S. trade data on imports and exports of private-sector services to workers' earnings data. They find service offshoring to China and India has little impact on earnings of American service-sector workers. Ebenstein et al. (2009) show that one channel through which trade and offshoring put downward pressure on aggregate U.S. wages is the displacement of some manufacturing workers to lower-paying jobs in service industries.

To date, no Canadian study has examined the association between offshorability and the evolution of wages in the service sector. This article fills this gap by tracking wage growth in offshorable and non-offshorable service occupations over the past decade. Following Organisation for Economic Co-operation and Development (OECD) work from van Welsum and Reif (2005), offshorable service-producing occupations are defined as those that satisfy four criteria (see Data sources and definitions). They make intensive use of ICTs, produce an output that can be traded or transmitted by ICTs, require no face-to-face contact, and their knowledge content is highly codifiable.

Offshorable service-producing occupations

Of all jobs held in the private service sector, about one-quarter are potentially subject to service offshoring (Table 1).4 This pattern is observed in most provinces. Service-sector jobs most susceptible to offshoring are held by workers employed in business, finance and administrative occupations (e.g., secretaries, clerks and telephone operators) or in natural and applied sciences (e.g., computer programmers, engineers and architects): more than one-half of these workers are in offshorable positions. Because they generally require face-to-face contact or involve a service that cannot be transmitted by ICTs, jobs in sales and service occupations and those in retail trade, accommodation and food services are the least likely to be relocated to another country. At most 6% of the jobs in these categories are offshorable.5 

Service-sector jobs held by low-educated workers are not the most susceptible to offshoring. In fact, the opposite is true. Overall, about 40% of service-sector jobs held by university graduates were at risk of being relocated in 2009, more than twice the rate of 16% observed for jobs held by individuals having a high school education or less.

Because of their overrepresentation in clerical jobs, many of which are offshorable, women are more likely than men to be in offshorable service-producing occupations. Women in all age groups are more likely to be in offshorable jobs, but there is some variation in gender patterns across education levels. While women with a high school education or less are at least three times more likely than their male counterparts to be in jobs subject to service offshoring, female university graduates are no more likely than male university graduates to be in such jobs.

Other gender differences are worth noting. In 2009, men employed in large firms (those with 500 employees or more) were roughly twice as likely to be in offshorable jobs as their counterparts employed in small firms (those with less than 20 employees). For women, the difference was less pronounced.

Some of the attention focused on service offshoring stems from the likelihood that many offshorable service-sector jobs are well-paid. The data support this notion. In 2009, 38% of service-sector jobs susceptible to service offshoring paid $25.00 or more per hour (in 2009 dollars), up from 29% in 1999 (Table 2).6 In both years, very few of these jobs (at most 7%) paid less than $10.00 per hour.

In 2009, two-thirds of offshorable jobs were held in business, finance and administrative occupations. Close to three-quarters were held by workers with postsecondary education or a university degree or by those employed in high-skill services. More than 90% of employees in these jobs were not unionized and about two-thirds were women.

Offshorability and wage growth

Overall, wages in offshorable service-sector jobs and in other service-sector jobs grew at a similar pace in recent years. Between 1998 and 2009, real wages in offshorable occupations and other service-producing occupations grew roughly 15% (Chart A).7 Notable differences in wage growth were observed only in two broad occupational groups: management occupations and natural and applied sciences and related occupations.8 In management occupations, wages in offshorable jobs grew 12 percentage points slower than in other jobs. The reverse was true in natural and applied sciences, where wage growth in offshorable jobs exceeded that in other jobs by 6 percentage points. So within broad occupational groups, wages in offshorable jobs did not systematically grow less than wages in jobs not susceptible to offshoring.9

Some of the observed differences in wage growth might result from changes in workers' characteristics. For instance, workers' average labour market experience, seniority and education levels may have risen faster in some occupations than others, which could result in differing wage growth between offshorable and other jobs.

To control for the influence of these factors, multivariate analyses were conducted for each of the five occupational groups shown in Chart A. The question asked was: controlling for workers' characteristics such as age, seniority and education levels, did wages in offshorable jobs grow at the same rate as wages in other jobs?10 

Whether wages grew less among offshorable occupations than among other occupations between the 1998 to 2000 period and the most recent period (2006 to 2009) depended on the occupational group considered.11 Wages in offshorable jobs in natural and applied sciences occupations grew 5 percentage points faster than those in broadly comparable jobs (Table 3).12,13 There is no evidence of differentiated and statistically significant wage growth in other occupational groupings.

The higher wage growth among offshorable natural and applied sciences occupations may partly reflect movements of offshorable jobs across industries or firms of different sizes. If offshorable jobs in natural and applied sciences occupations became increasingly concentrated in high-paying industries or in large firms over the past decade, they would tend to exhibit stronger wage growth than other jobs as a result of this change. To assess whether wage growth in offshorable occupations located in a given industry and in firms of a given size differed from that in other comparable occupations, controls for industry and firm size were needed.14 After these controls were added, wages in offshorable jobs in natural and applied sciences occupations still grew faster than those in other broadly comparable jobs: the difference in wage growth dropped from 5 percentage points to 4 percentage points. Thus, the relatively strong wage growth observed in offshorable natural and applied sciences occupations did not result from compositional effects related to industry or firm size.

The numbers shown in Table 3 indicate that wages in offshorable and non-offshorable business, finance and administrative occupations grew at the same pace for the periods from 1998 to 2000 and from 2006 to 2009. Yet these numbers measure average wage growth across a diverse set of occupations. Offshorable positions in business, finance and administrative occupations include both professional occupations (e.g., financial auditors and accountants, and financial and investment analysts) and clerical jobs (e.g., secretaries, data entry clerks and telephone operators) whose wages may have evolved differently over the past decade.

When offshorable business, finance and administrative occupations are disaggregated into professional and clerical occupations, interesting patterns emerge. Compared to non-offshorable jobs in this grouping, offshorable professional occupations displayed faster wage growth (3 percentage points), while offshorable clerical occupations experienced slower wage growth (-2 percentage points) for the periods from 1998 to 2000 and from 2006 to 2009 (Table 4). The slower wage growth experienced by the clerical group is not recent: it was also observed from 1998 to 2000 and from 2001 to 2005. This implies that wages in offshorable and non-offshorable clerical occupations diverged early in the decade and then grew apace in the second half of the decade.

It is possible that increases in competition from workers in emerging countries predominantly affect wages of less-skilled workers. This could happen if, say, demand for telephone operators or data entry clerks grew at a slower pace than demand for computer programmers. If so, offshorable jobs held by less-educated employees would tend-to a greater degree than would be observed among highly educated workers-to display slower wage growth than those held by their counterparts em­­ployed in non-offshorable positions. This might be true especially in non-unionized firms, where wage concessions from workers might be easier to obtain.

Table 5 provides limited support for this hypothesis. For the periods from 1998 to 2000 and from 2006 to 2009, wages of workers with a high school education or less and who were employed in non-unionized offshorable jobs grew 5 to 6 percentage points less than those of their counterparts employed in non-offshorable positions. In contrast, wages of non-unionized university graduates employed in offshorable positions and those holding other jobs did not differ significantly. The same patterns were observed for 1998 to 2000 and for 2001 to 2005. This implies that among non-unionized employees with a high school education or less, offshorable jobs and other jobs displayed the same wage growth between the periods from 2001 to 2005 and from 2006 to 2009.

Another scenario is that growing competition from abroad might operate mainly by putting downward pressure on pay rates of workers at the bottom of the wage distribution. If so, wage growth in offshorable jobs would lag behind that of other jobs to a greater degree among low-paid positions than among better-paid positions. This hypothesis is examined in Table 6. It receives limited support from the data: for the periods from 1998 to 2000 and from 2006 to 2009, wage growth in offshorable jobs lagged behind that of other jobs to a greater extent in low-paid positions than in high-paid positions in management occupations and in business, finance and administrative occupations, but not in natural and applied sciences occupations.15 For instance, wages in low-paid offshorable jobs in business, finance and administrative occupations grew 4 percentage points slower than wages in low-paid non-offshorable jobs. At the same time, wages in high-paid offshorable jobs in that occupational group grew 4 percentage points faster than wages in high-paid non-offshorable jobs. However, the opposite pattern is found in natural and applied sciences occupations. In other occupational groups, differences in wage growth between offshorable and non-offshorable jobs were not statistically significant.

Offshorability and wage growth among newly hired employees

Analyses that include all workers in selected sectors are not well-suited for detecting changes in the wages employers offer workers when new positions become available (as a result of quits and/or firm expansions). Analyzing the evolution of wages of newly hired employees can help identify channels through which Canadian firms may respond to growing competition within industries and from abroad. More intense competition on the product market could induce some companies to reduce their labour costs by lowering the wages offered to new hires, while maintaining or increasing wages of workers with greater seniority. Under this scenario, differences in wage growth between offshorable and non-offshorable jobs would be bigger among newly hired employees than among their counterparts with greater seniority.

Table 7 provides some mixed evidence for this hypothesis. Between the periods from 1998 to 2000 and from 2006 to 2009, wage growth in offshorable jobs appears to lag behind that of other jobs to a greater degree among newly hired employees than among other employees in management occupations and business, finance and administrative occupations. Yet the opposite pattern was observed in natural and applied sciences occupations. In other occupational groups, wage growth parameters are imprecisely estimated.

Together, the numbers presented in tables 3 to 7 highlight two facts. First, whatever potential factors are considered, wages in offshorable service-sector jobs did not grow systematically more or less than those in other service-sector positions over the past decade. Second, in some cases, offshorable jobs displayed weaker wage growth than other jobs for the periods from 1998 to 2000 and from 2001 to 2005, but similar wage growth afterwards. Since there is no clear reason why the effect of offshoring would be limited to one time period, the slower wage growth observed in some offshorable jobs from 1998 to 2000 and from 2001 to 2005 might well be driven by factors other than service offshoring.16 

Conclusion

In recent years, the emergence of ICTs and the growing availability of highly skilled workers in fast-growing countries like China and India have allowed Canadian firms to move some service-sector jobs offshore. Such a change in service employment patterns could affect wages and wage growth in offshorable jobs.

This article examined whether offshorable service-sector occupations have displayed similar wage growth to comparable occupations since the late 1990s. It found no evidence that wages in offshorable service-producing occupations grew systematicallyless than those in other occupations. Some offshorable occupations, namely those involving clerical work, exhibited weaker wage growth while those in natural and applied sciences occupations displayed stronger wage growth than broadly comparable non-offshorable occupations.

These results suggest that if service offshoring has affected wages of Canadian workers so far, the impact is unlikely to have been uniform across occupations. To test this hypothesis, subsequent research should link Canadian trade data on imports and exports of services and commodities to worker-level wage data from the Labour Force Survey. Such a link would enable an empirical evaluation of the assumed offshorability of jobs, as well as the associated wage effects of offshoring or inshoring.

Data sources and definitions

The data used in this article are drawn from the March and September files of the Labour Force Survey. For tables 1 and 2, the sample consists of private-sector17 employees age 15 to 64, who are not full-time students and are employed outside manufacturing, primary industries and construction. The restriction that workers be employed in one of the five occupational groups shown in Table 3 is added for the discussion of the model results.

Offshoring, outsourcing and offshorability are three distinct concepts. Blinder and Krueger (2009) point out that "offshoring refers to the movement of home-country jobs to another country¯whether or not those jobs go to another company." It is different from outsourcing, "which refers to moving jobs out of the company, regardless of whether those jobs leave the country." Finally, "offshoring, which is an observable action, must also be distinguished from offshorability, which is a job characteristic." A job is offshorable if the underlying tasks can "be moved overseas in principle, even if that movement has not actually occurred." This article examines whether wages in offshorable service-producing occupations have displayed different trends since the late 1990s, compared to other service-producing jobs.

Van Welsum and Reif (2005) argue that occupations that are potentially affected by service offshoring share many characteristics. First, they make intensive use of information and communication technologies (ICTs). Second, they produce an output that can be traded or transmitted by ICTs. Third, their knowledge content is highly codifiable. Fourth, they require no face-to-face contact.

Using these four criteria, van Welsum and Reif (2005) select a subset of Canadian occupations, based on the 1991 Standard Occupational Classification (SOC), that are potentially affected by service offshoring. Because the occupation-level data in the Labour Force Survey are based on the 2001 National Occupational Classification for  Statistics (NOC-S), our subset of occupations is, with minor exceptions, identical to that of van Welsum and Reif (2005).18 

Offshorable service-producing occupations

Management Occupations

A121 Engineering Managers
A122 Computer and Information Systems Managers
A123 Architecture and Science Managers
A301 Insurance, Real Estate and Financial Brokerage Managers
A302 Banking, Credit and Other Investment Managers
A303 Other Business Services Managers
A311 Telecommunication Carriers Managers
A312 Postal and Courier Services Managers
A392 Utilities Managers

Business, Finance and Administrative Occupations

B011 Financial Auditors and Accountants
B012 Financial and Investment Analysts
B013 Securities Agents, Investment Dealers and Brokers
B014 Other Financial Officers
B022 Professional Occupations in Business Services to Management
B111 Bookkeepers
B112 Loan Officers
B114 Insurance Underwriters
*B211 Secretaries (Except Legal and Medical)
*B212 Legal Secretaries
*B213 Medical Secretaries
*B214 Court Recorders and Medical Transcriptionists
*B311 Administrative Officers
*B312 Executive Assistants
*B412 Supervisors, Finance and Insurance Clerks
*B511 General Office Clerks
*B513 Records Management and Filing Clerks
*B514 Receptionists and Switchboard Operators
*B522 Data Entry Clerks
*B524 Telephone Operators
*B531 Accounting and Related Clerks
*B532 Payroll Clerks
*B533 Customer Service Representatives – Financial Services
*B534 Banking, Insurance and Other Financial Clerks
*B553 Customer Service, Information and Related Clerks
*B554 Survey Interviewers and Statistical Clerks
B523 Desktop Publishing Operators and Related Occupations

Natural and Applied Sciences and Related Occupations

C181 Computer and Network Operators and Web Technicians
C011 Physicists and Astronomers
C012 Chemists
C013 Geologists, Geochemists and Geophysicists
C014 Meteorologists
C015 Other Professional Occupations in Physical Sciences
C021 Biologists and Related Scientists
C031 Civil Engineers
C032 Mechanical Engineers
C033 Electrical and Electronics Engineers
C034 Chemical Engineers
C041 Industrial and Manufacturing Engineers
C042 Metallurgical and Materials Engineers
C043 Mining Engineers
C044 Geological Engineers
C045 Petroleum Engineers
C046 Aerospace Engineers
C047 Computer Engineers (Except Software Engineers)
C048 Other Professional Engineers, not elsewhere classified
C051 Architects
C052 Landscape Architects
C053 Urban and Land Use Planners
C054 Land Surveyors
C061 Mathematicians, Statisticians and Actuaries
C071 Information Systems Analysts and Consultants
C072 Database Analysts and Data Administrators
C074 Computer Programmers and Interactive Media Developers
C152 Industrial Designers
C172 Air Traffic Control and Related Occupations

Social Science, Education, Government Service and Religion

E012 Lawyers and Quebec Notaries
E031 Natural and Applied Science Policy Researchers, Consultants and Program Officers
E032 Economists and Economic Policy Researchers and Analysts
E033 Business Development Officers and Marketing Researchers and Consultants

Occupations in Art, Culture, Recreation and Sport

F011 Librarians
F013 Archivists
F021 Authors and Writers
F022 Editors
F023 Journalists
F025 Translators, Terminologists and Interpreters

Sales and Service Occupations

G131 Insurance Agents and Brokers

Morissette and Johnson (2007) disaggregate offshorable service-producing occupations into two groups: professional occupations and clerical occupations (* denoted above by an asterisk). The former group includes jobs held by highly skilled workers such as engineers, architects, computer programmers, translators and journalists. The latter includes occupations (requiring a lower skill level) such as secretaries, data entry clerks and telephone operators. Natural and applied sciences and related occupations will be denoted as "natural and applied sciences occupations" while occupations in social science, education, government service and religion will be denoted as "social sciences occupations."

Several non-standard industry groupings are used in the article. High-skill service industries include finance, insurance, real estate and leasing, professional, scientific, and technical services, business, building, and other support services. Public service industries include education services, health care and social assistance, and public administration. Other service-producing industries include wholesale trade, transportation and warehousing, performing arts and heritage, and amusement.

There are several limitations. The analyses are based on a single definition of offshorability. Alternative definitions could yield different results. Since no firm-level data on the intensity of service offshoring are currently available, the evidence presented here may reflect demand-side factors other than service offshoring that cannot be measured with the Labour Force Survey (LFS). Finally, no distinction is made between service offshoring to low-wage countries and service offshoring to high-wage countries. These two types of offshoring may have quite different impacts on the Canadian labour market.

Multivariate models

Multivariate analyses are used to estimate whether offshorable service-sector occupations and other service-sector occupations displayed similar wage growth between the late 1990s and the late 2000s. The following wage equation is estimated using the ordinary least squares (OLS) method:

ln(HOURLY WAGE)it = β0 + β1OFFSHOREit + β2PERIOD_0105it + β3PERIOD_0609it

4OFFSHOREit*PERIOD_0105it + β5OFFSHOREi*PERIOD_0609it

+ β6Xit + β7 Zit + ε it

where the dependent variable is the natural logarithm of hourly wages of worker i in year t, and where εit is an error term uncorrelated across individuals and years. Controls for workers' characteristics, Xit, include education, gender, a quadratic term in age and seniority, and interaction terms between gender and age, and gender and seniority, as well as province indicators. Also included are a constant term, an offshorability indicator (OFFSHOREit, equal to 1 if a job is offshorable, 0 otherwise), two indicators for the periods from 2001 to 2005 and from 2006 to 2009 (PERIOD_0105it and PERIOD_0609it,) and interaction terms between period indicators and the offshorability indicator. Apart from these variables, the full set of controls includes the following job-related characteristics, Zit: 69 industry categories, 4 firm-size categories (1 to 19, 20 to 99, 100 to 499, and 500 employees or more), 10 occupation groups, union status and full-time status.

When separate analyses are conducted by education level and union status, controls for education levels and union status are omitted. In all analyses, the period from 1998 to 2000 is the reference (or omitted) period.

The numbers shown in tables 3 to 7 are the estimated values of β4 and β5. They measure the degree to which wages in offshorable service-sector jobs and those in other service-sector jobs grew at a different pace between the period from 1998 to 2000 and the periods from 2001 to 2005 and from 2006 to 2009. For instance, an estimated value of 0.10 for β4 (β5) implies that, for the periods from 1998 to 2000 and from 2001 to 2005 (2006 to 2009), wages in offshorable service-producing occupations grew 11 percentage points faster than wages in other service-producing occupations. The 11 percentage-point figure is obtained by taking the antilog of 0.10 minus 1.

All t-values shown in tables 3 to 7 take the Labour Force Survey (LFS) complex survey design into account.


Notes

  1. Evidence that Canadian firms started contracting out some service-producing jobs to non-OECD countries like China and India can be found in data produced by Statistics Canada's Balance of Payments Division. These data consist of a series of business surveys that measure the imports and exports of commercial services and contain information about 48 types of commercial services (e.g., telecommunications, accounting, architectural and engineering services, and information-related services). Statistics can be broken down by industry and by country of origin or destination, thereby allowing analysts to distinguish imports from OECD countries from those originating from non-OECD countries like China and India. Morissette and Johnson (2007) use these data and find that, in 2004, imports of computer, information and other business services (such as management services, advertising and related services, research and development, architectural, engineering, and other technical services) from non-OECD countries amounted to roughly $1 billion, compared to $17 billion for those from OECD countries.
  2. The net effect of offshoring on employment need not be negative. One reason is that domestic firms might reduce their production costs by offshoring low-skilled tasks, which in turn might increase their profit-maximizing output and increase the demand for (and employment of) some types of workers (Cheung et al. 2008). Morissette and Johnson (2007) use several data sets to examine the relationship between service offshoring and employment. They find little evidence of a correlation between service offshoring and the evolution of employment and layoff rates.
  3. So far, the discussion has been framed solely in terms of imports of services. However, exports of services (termed inshoring by Liu and Trefler [2008]) are another factor that may stimulate demand for some types of workers and thus increase wages.
  4. About 1.4 million and 1.7 million service-sector jobs were subject to offshoring in 1999 and 2009, respectively. In both years, they accounted for about 21% of all paid jobs in the economy. Although they refer to offshorable jobs in the service sector only, these estimates are in line with those of Blinder (2009) who, when combining the goods sector and the service sector, estimates that between 22% and 29% of all paid jobs in the United States were potentially offshorable in 2004.
  5. Since the sample used in tables 1 and 2 consists of private-sector employees (15 to 64, who are not full-time students, and who are employed outside manufacturing, primary industries and construction), readers might wonder why numbers for public services are shown in these tables. The reason is that some workers, e.g., nurses in privately owned residences for seniors, are private-sector employees operating in sub-sectors (e.g., health) of public services.
  6. Multivariate analyses indicate that close to one-half of the increase (from 29% to 38%) observed between 1999 and 2009 is due to the growing proportion of offshorable jobs held by older and highly educated workers.
  7. Although the wage data used in this article start in 1997, information on firm size is available only starting in 1998. Since firm size is subsequently used as a control variable in multivariate analyses of wage growth, the focus in this section is on wage growth between 1998 and 2009.
  8. Since they account for less than 2% of jobs in sales and service occupations (group G), offshorable jobs held by insurance agents and brokers are not considered in the remainder of the article.
  9. Chart A also shows relatively high wage volatility among offshorable jobs in social science and art, culture, recreation and sport. Part of it might be related to the relatively small sample sizes for these jobs.
  10. Calendar years are grouped into three periods to increase the precision of the estimates. The initial period starts with the year 1998 since subsequent multivariate analyses require controlling for firm size, a variable for which data are not available in the LFS prior to 1998. Workers' characteristics also include control for gender and province (see Multivariate models).
  11. The same conclusion is obtained when wage growth is measured between the periods from 1998 to 2000 and from 2006 to 2008.
  12. Differences in wage growth, measured in percentage points, are obtained by taking the antilog of the coefficients shown in tables 3 to 7, minus one.
  13. The difference is statistically significant at the 1% level (two-tailed test).
  14. Conversely, if movements of offshorable jobs across industries or companies of different sizes actually result from factors related to offshoring, controls for industry and firm size are best avoided.
  15. For each year, occupational group and value of the offshorability indicator (1 for offshorable jobs, 0 otherwise), jobs in the bottom (top) third of the (cell-specific) wage distribution are selected. Data for the years from 1998 to 2009 are pooled. For each occupational group and each tier, separate regression models are estimated as described in Multivariate models.
  16. For instance, if labour-saving technological changes were more prominent among offshorable jobs held by non-unionized low-educated workers than other jobs held by their counterparts, wages could grow less among the former group than the latter, thereby potentially accounting for the slower wage growth observed among the former group between 1998 and 2000 and 2001 and 2005.
  17. The private sector includes all self-employed workers and business owners and all employees except those in public administration at the federal, provincial, territorial, municipal, First Nations and other Aboriginal levels as well as in Crown corporations, liquor control boards, and other government institutions such as schools (including universities), hospitals and public libraries.
  18. For instance, the "computer operators" category, used by van Welsum and Reif (2005), is replaced by "computer and network operators and web technicians."

References

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Authors

Yuqian Lu and René Morissette are with the Social Analysis Division. Yuqian Lu can be reached at 613-951-3833. René Morissette can be reached at 613-951-3608 or both at perspectives@statcan.gc.ca.