The Flow of
Post-Secondary Graduates into the Knowledge Economy: Evidence from the National Graduate Survey
Walter Sudmant, and
Colleen Hawkey,
May 2000
Introduction
The importance of
a well educated labour force to the well being of a nation’s economy is
supported by a wealth of statistical evidence, both in Canada and world-wide (e.g.,
OECD, 1987, 1992, 1996; Allen, R., 1998, 1999).
A parallel and related development has been the changing structure of the economy: output growth, employment, and productivity gains have shifted away from some of the more traditional manufacturing and resource based industries toward high knowledge, service versus product oriented, and highly technical industries. The phenomenon of structural change in the economy over the past 20 years has been referred to, sometimes very imprecisely, by a variety of often confusing terms: “new (world) economy,” “global economy,” “information age,” “hi-tech economy,” “knowledge economy.” The overwhelmingly most prominent feature of this structural change, both from the point of view of the individual participating in the economy, and the statistical evidence, is the demand for higher levels of education, skills, and cognitive abilities, hence “knowledge economy” has emerged as best characterizing the phenomenon.
One policy
response to the knowledge economy has been to emphasize the need for
scientific, engineering, and technical training. “The justification for such policies lies in
the critical dependence on the economies and societies of OECD countries on
science and technology and on the skills of scientists and engineers”
Another
response, recently most eloquently put by Robert Allen (1998) and based on a variety
of rich Statistics Canada data sources, states that “the economy consists of
more than new technologies. The rapidly
changing economy will require people to manage it and to think of creative
solutions to new problems. Perhaps those
solutions will require imaginations beyond the technological” (p. 4). Allen provides evidence that universities in
the humanities and social sciences have fared well in the labour market, and
that continuing economic growth and structural change will result in increased
demand for the more general, broadly educated graduate. Advocates for this position cite studies of
employers (Conference Board of Canada, 1998) who demand graduates with
management skills, the ability to solve complex people problems creatively,
lifelong learning skills, and a very broad social, political, and psychological
understanding of a changing world (see Figure 1). Senior executives and policy
makers themselves often refer to non-technical aspects of their university
education as seminal to their own success in the labour market and beyond:
CEO of 30 mostly high-tech
companies…noted that many of their technology workers began their higher
education in the humanities and are stronger for it … . They have increased
their value to our companies, our economy, and our culture and themselves, by
acquiring the level of cultural and civic literacy that the humanities offer.
(Globe and Mail, April 8, 2000).
Figure
1: Employability Skills Profile
|
Canadian employers need a person who can: Communicate
Think
Learn
|
Canadian employers need a person who can demonstrate: Positive Attitudes and Behaviours
Responsibility
Adaptability
|
Canadian employers need a person who can: Work with Others
|
Opponents
to Allen’s (1998) conclusions (e.g., some provincial governments) argue,
however, that the current mix of degrees and college credentials is the not result
of market forces, but of historical and cultural forces which have shaped our
institutions. The argument is that students take the programs that are offered
by institutions which are not responsive to demand, and the labour market in
turn, is forced to absorb whatever is provided by an unresponsive public
post-secondary system. This reasoning suggests that even though there is good
evidence that non-technical graduates are successful, the important growth
sectors of the economy - the knowledge economy - does not need these graduates,
that the "knowledge economy" is starved for high tech graduates, and
a shift in educational output is required to stoke the growth of the new, high
growth, knowledge economy. A naïve economic view of the labour market would
reject this claim outright. Allen (1998,
1999) and others have already shown that non-technical graduates work in high
level (managerial, professional) jobs and earn relatively high salaries, hence
they must be making a commensurate contribution to the economy. Non-economists are less convinced - having
perhaps observed widespread inconsistencies between occupations, earnings, and
the contribution to the total economic good.
To fully
address the argument we must also have evidence that graduates from a wide
variety of disciplines, and in particular the very numerous graduates of
humanities and social sciences are indeed flowing into the high knowledge
sector in numbers and proportions comparable to highly technical graduates and
those with very specific training (college and vocational graduates). We suggest that a tool for planning
post-secondary education in
This paper
provides some evidence and conclusions for the analysis of the fundamental
question: What mix of post-secondary outputs (i.e., degrees,
credentials) should the education system produce in response to the emergence
of the knowledge economy?
The
analysis proceeds in several stages:
1.
Identify an operational definition for that sector of
economy which is the “knowledge economy”;
2.
Provide evidence that the definition selects the
sectors of the economy which indeed are desirable. It is clear that the labour force is becoming
increasingly better educated, and that university graduates are easily absorbed
into the labour market, but to suggest that this is evidence for the kind of
workers required by the knowledge economy is circular.
3.
Develop the “Educational Input-Output Matrix” (EIOM) to
show the flows from post-secondary education into the various sectors of the
labour market.
4.
Develop and test hypotheses about the structure of the
EIOM which suggest excess supply or demand.
Steps one and
two have been done by Industry
1.
R&D Expenditures by industry
2.
Proportion of R&D personnel
3.
Proportion of professional R&D personnel
4.
Ratio of workers with post-secondary education
5.
Ratio of knowledge workers to total employment
6.
Ratio of employed scientists and engineers
Figure 2: High knowledge industries
High Knowledge Industries:
Scientific and Professional
Equipment
Communications & Other
Electronic Equipment
Aircraft & Parts
Business Services
Business Machines
Electrical power
Other chemical products
Machinery
Refined Petroleum and Coal
Educational Services
Health & Social Services
Pipeline Transportation
Source: Gera & Mang, 1997, p. 15.
The data
used to produce the EIOM are from the 1997 National Graduate Survey (NGS) of
Graduates from Canadian Post secondary institutions. One of the major purposes
of the NGS is:
To extend available
information required to improve occupational supply and demand projection
models for various occupational categories and to conduct related studies of
supply-demand imbalances in the labour market;
hence the
data are well suited to our purposes. They provide a snapshot for the late
1990's of the flow of post secondary graduates into the labour market.
The population frame consisted of 325,000 post-secondary graduates, from
which a stratified (by level, province, and fields of study) random sample of
62,000 was taken. A telephone survey
resulted in 43,000 completed responses, for a response rate of 69 percent, and
with a refusal rate of 2.6%.
The stratified random sampling scheme used by
Statistics Canada results in weights for each of the strata. In the tables that
follow, the totals and percentages are all based on the use of these weights in
the calculations, hence the tables depict the best estimates for the entire
country, not just the sample. Statistics
The advantage of using data from the NGS is that it provides current data on the movement of graduates into the labour market, hence the flow reflects the current demand for graduates, as new labour is hired, as opposed to the more static picture provided by surveys of the entire labour market. Since we are investigating the adequacy of the mix of post-secondary graduates in meeting the demands of a changing market, and especially meeting the demands of a future which will clearly be more knowledge intensive, it is imperative that we do not confuse the labour market destinations of graduates from the past 30 years with what is required today. It has become a truism that the post-secondary graduates of the baby-boom generation (or at least the leading edge of that generation) entered the economy more easily, and less discriminantly with respect to their particular subject of study.
There are, however some very important
shortcomings in the NGS data, and some critical cautions which must be observed
when using the data. First, and by far
most important, the data set used here is based on 1995 graduates two years
after graduation. Two years is
insufficient time for most university graduates to achieve stable careers, or
long term tenure within industrial sectors.
Evidence from the NGS and other graduate surveys shows a great deal of
movement within the first five years after graduation: graduates enter and leave the labour force (usually
for further education), change jobs, and spend time in job search. Furthermore, the instability within the first
five years increases as education becomes less specific. Graduates from Education, and Health
professions move into more permanent stable career-like jobs than do social science
graduates whose transition is more difficult given the non-specific nature of
their education. Hence we would not
expect the findings for these non-specific graduates to be as favorable in the
short run. Second, evidence on the lifetime earnings and careers/occupations of
university graduates shows that there is a great deal of growth in earnings
over the lifetime (Allen, 1999); much more so
than vocational/technical graduates who tend to reach a stable permanent wage
level much earlier. Therefore any
conclusions arrived at from the NGS must be taken as very conservative,
understating the results for university education, and in particular the
non-career fields. A final caution in
the use of NGS data is in the use of unemployment rates. There is evidence that the NGS rates are not
comparable to the familiar unemployment rates calculated from the Labour Force
Survey, or the census. Partly the lack
of comparability comes from the looking at unemployment during the transitory
phase two years after graduation, but this is discussed in more detail below.
Table 1 shows the data we are working with, and gives a sense of the raw numbers of graduates of 1995 working full-time in the Canadian economy. Data from the NGS estimates the industrial classification of over 84,000 graduates in the 18 broad industry classifications. At the broadest level this is the EIOM, and it is easy to see how projections in the differential growth in the economy could be crudely translated into required changes in university degree output. Note the vast numbers of university graduates employed in three sectors: Educational Services, Business Services, and Health and Social Services; this will be a recurring theme in the analysis of the data. Though the growth in the “service economy” is often cited in the media, there is still considerable misunderstanding about both the scale of the service economy as well as the level of education, skills, and earnings in these sectors.
Table 1 also highlights that by far the largest numbers flowing into the workforce are those in Commerce, Social Sciences, and Education. What is sometimes missing from the policy debate regarding the supposed need for high tech skills is a sense of the scale, or absolute numbers of university graduates being absorbed into the economy each year. Table 1 highlights some of the largest cells, arbitrarily chosen as cells with over 2,000 graduates. Clearly education and the social sciences are currently providing the economy with vast numbers of graduates in key areas, and given the size of these numbers governments must be extremely cautious in prescribing large scale shifts in the types of educational outputs from Canadian universities. Conversely, note that numbers of graduates entering some of the more "high-tech" industrial sectors are relatively small - not to suggest that these are in any way unimportant, but that labour market shortages in some areas might be small problems in a fiscal/funding sense.
Table 2 shows the labour market destinations for graduates of 1995 two years after graduation by industry, divided into two groups: low/medium knowledge industries, and high knowledge industries. Low/medium industries are all grouped together, while the high knowledge industries are displayed in the categories used by Lee and Has. When an entire major grouping of industries (e.g. Educational services) has been designated high knowledge, the broad SIC name is shown, whereas when a minor grouping has been deemed high knowledge, only that grouping is shown (e.g. Aircraft and parts is one of the few sub-groupings within manufacturing which is designated high knowledge).
Over half, 55 percent, of university graduates are destined for the high knowledge economy. It is important to realize that employment in the low/medium knowledge sector for a university graduate does not mean underemployment. Educational analysts are much more familiar with the grouping of university graduates’ employment outcomes by occupation, where non-professional or non-managerial employment is sometimes viewed as underemployment, or at least a less than optimal economic outcome. When viewing graduate outcomes by industry, this is not so. Many high knowledge occupations are to be found in the low/medium knowledge sector, and these areas will continue to be important to the economy. The important point is that policy makers focus analysis and planning on the high knowledge sector since that is the source of greater economic growth and the direction for the future.
Table 2 now
shows very clearly the nature of the knowledge economy in terms of the flow of
graduates into the labour market: three
sectors dominate in the extreme:
Educational services, business services, and health and social
services. Of all university graduates
entering the knowledge sector, 95% of them are employed in one of these three
broad sectors. Those sectors which
typify “high tech” industries such aircraft, business machines, and
pharmaceutical products absorb only 3 percent of undergraduate and first
professional degrees. This is not to say
that these are not important drivers in the economy. Enormous wealth and productivity increases
have been generated by these sectors (especially of course “business machines”
which refers to the manufacture of computers), but several factors must be taken
into account when considering these typically high tech areas of the
economy. First, a relatively small
number of workers are actually involved in the invention and development of
these products in the private sector (much of the research is done by the
university sector, within educational services); second, once these products are in mass
production, relatively less knowledge intensive labour is required for their
manufacture (as compared say with health and education which are very intensive
in high-knowledge labour), and finally, the major productivity gains will
usually accrue to industries in other sectors;
computer developments increase the output in the business services
sector; pharmaceutical developments
increase the productivity in the health sector.
The bottom row of the matrix shows the proportion of graduates from various degree categories going into the high knowledge sector. It is not surprising that education and health graduates tend to be employed in education and health. What may be surprising to some is the very large numbers involved. Given that these two sectors are projected to grow rapidly, and given the large numbers of graduates already being employed in these fields, clearly the economy will need very large increases in these graduates. Without teachers there is no knowledge economy, and the majority of teachers are graduates from the humanities and social sciences. University teachers are well reminded that a very large fraction of most classes they teach will eventually become teachers.
What is much more surprising, is that leaving aside health and education graduates, where the proportions are naturally high, the proportion of graduates entering the knowledge economy is surprisingly similar across all fields. 45 percent of social science graduates, 45% of humanities graduates, 42% of commerce and management graduates, and 52 percent of engineering graduates enter the high knowledge economy. There is very little evidence that humanities, social sciences, or fine arts graduates are not required in the knowledge economy. In fact, the smallest fraction of graduates entering the high knowledge sector is for agriculture and biological sciences, where only 39 percent enter the high knowledge sector.
What is also perhaps somewhat surprising when the data are viewed from this point of view is the fraction of Social Sciences, Humanities, and Fine Arts graduates employed in business services (20%, 16%, and 21%). After removing the enormous influence of health and education on the matrix, the fractions of graduates employed in this field are remarkably similar, with certainly no disadvantage for Arts graduates. Business services is a very broad category and includes many computer related businesses, as well as scientific and technical business services, hence the high proportion from engineering working in business services. This is the sector of the economy which has been truly revolutionized by information technology, and warrants further investigation.
Another interesting way to view the EIOM is to calculate the percentages across rows instead of columns, as in table 3. Though the data and conclusions are the same as above, it may be useful in educational policy discussions, to know that 63% graduates entering full-time employment in the knowledge economy come from education, fine arts, humanities, and social sciences. While there may be skill shortages and imbalances, there is clearly a huge labour market demand behind met by the graduates from these fields. Viewed in this way, we can see that by far the largest group of graduates entering the pharmaceutical and medical products industry are graduates from commerce, 39 percent, compared with the second largest group, agriculture and biological sciences, who make up only 18% of the new entrants into the sector. Again, this tells us a great deal about the actual types of skills and jobs which make up many of the industries in the new economy - they are not necessary related to the specific nature of the product - but comprise more general skills.
Another claim which can be investigated with the data on full-time employed graduates from the NGS is that economy, and in particular the knowledge economy requires the more specific skills-oriented graduates of vocational and career training programs offered by colleges. Table 4 investigates this claim by showing the percentage distribution of graduates across sectors of the economy. The bottom row, showing the proportion in the knowledge economy, shows a clear and dramatic relationship between university education and participation in the knowledge economy. It might be argued that this comparison is unfair, since vocational and college graduates are obviously not usually qualified to become teachers, and hence educational services biases the university graduates toward the knowledge sector. However, the business services sector shows much the same result. Both in terms of absolute numbers and percentage of total graduates, university graduates are much more likely than college graduates to enter the business services sector.
Tables 1-4 complete the Robert Allen argument that social sciences and humanities do indeed provide the economy with the knowledge workers that are required, by showing that as recently as 1997, these graduates flowed, in enormous numbers, into the knowledge economy. However, there is much more of relevance to post-secondary educational planning that can be gleaned from the NGS data. In particular, the NGS collected information on earnings, unemployment, occupation, and labour market transitions, all of which, with appropriate context, can provide policy directions.
Salary
If the sectors of the knowledge economy identified by (Lee and Hass check back to see if this is the right pair) are indeed the areas of high growth and productivity, then at least intuitively, earnings for similarly qualified workers should be higher in those sectors, if there are shortages. [1] Table 5 shows that this is the case - that earnings for full-time workers, controlling for length of time out of school, and degree, are indeed about 6 percent higher in the knowledge sector. Of more interest is the analysis of the differential between high-knowledge sectors and other sectors by field of study and within sectors. Table 6 shows this detail.
Of course, salaries and wages are determined by many other factors than industrial sector and field of study. We can dismiss immediately the differential in the education and health sector, where unions or professional monopolies have a major impact on salaries. For example, the relatively high salaries of education graduates employed in the education sector probably tell us nothing about supply and demand for teachers - the key information in this sector is the number employed, and projected growth, from the EIOM.
The most interesting sector is then the business services sector. This sector is rapidly growing, and to a large extent reflects "contracting out", the growing practice of industries using the specialized business service sector as a substitute for in-house expertise, and many believe that this trend is closely related to the revolution in communications and information technology. Earnings in this sector are also much more a result of market forces than of institutional factors.
Table 6 shows a significant earnings differential between the low/medium knowledge sector and the business services sector for graduates from programs in Fine Arts, Humanities, Social Sciences, Agriculture and Biological Sciences, and Math and Physical Sciences. Commerce, Education, Engineering, and the Health professions show negative differentials. This is consistent with the hypothesis that business services, as its demand for workers grows, is meeting the demand by attracting graduates from the "non high-tech" fields, the more broadly educated social science graduates in particular, and it is doing so by drawing the graduates out of the low/medium knowledge economy. To put this into concrete terms, for example, engineers command roughly the same salary whether they work in the low-knowledge resource industry, or the high knowledge business sector, but a social sciences graduate can command a salary of, on average, 27 percent higher, in the business services sector. Clearly the market values the skills of social science graduates, and pays a premium to attract them into the high knowledge industries. The salary differential is evidence of an increased and more productive use of their skills in the knowledge sector.
Further evidence of this point is given by looking at the relationship between levels of post-secondary education and average salary, for the high knowledge sectors and the low-medium knowledge sectors. The statistics are shown graphically in figure 3. Two observations are evident. First, the clear increasing relationship between level of education and average salary, a relationship which has been demonstrated many times, and becomes more dramatic as time since graduation increases (i.e. At 2 years out we are looking at a relationship which will steepen with time). Second, is that in general there is no salary differential for the knowledge economy, except for the relatively small 6 percent differential for bachelor's and first professional degrees; the only differential of any significant size is within fields of study, as shown above. This would indicate that there is no particular shortage at any level of education of workers in the high knowledge sector, but taken together with table 5, would indicate that the demands are being met by the hiring of university graduates from the humanities and social sciences.
So far we have shown that university graduates from all disciplines are employed in the knowledge economy, and that in an overall educational planning sense (ie. Excluding very specific skills shortages), there is no evidence that the current system is unbalanced, producing too many of any one discipline (with the possible exception of biological sciences and agriculture). One further argument which must be addressed is the argument that while we are counting the numbers of graduates entering the labour force, we are neglecting to take into account large numbers of unemployed graduates with the “wrong education” for the knowledge economy. To examine this, we look at unemployment rates.
As an indicator of macro economic performance the unemployment rate often sufficient, but in the analysis of specific labour markets, or labour market planning, the unemployment rate is much less satisfactory tool for making policy decisions. This is because the unemployment rate is very much influenced by at least three factors. First, it is influenced by the level of supply and demand in the economy for workers; this is the component we actually wish to measure. Second it is influenced by the rate of movement between jobs. In occupations, or economies where people change jobs often, the unemployment rate will be higher, though not necessarily a bad thing if people are using job change to gain find a more appropriate place in the economy, or to gain further education. Third, the unemployment rate is influenced by the rate and timing at which people are leaving and entering the workforce. People are much more likely to unemployed shortly after entering the labour force, or shortly before leaving the labour force, given the standard definition of unemployment. Each of the second and third points is very relevant to the data from the NGS. University graduates, particularily those from bachelor's programs, are in a period of transition in the first five years after graduation (Sudmant & Heslop, 1997). The broader and less occupation specific their degrees are, the more likely they are to be feeling their way in the labour market - searching longer, gathering information from jobs and job search, changing jobs, and returning for further education. Table 7 shows this to be the case: in those fields of study which are directly related to specific employment, the rate of unemployment is lower. Table 7 also shows a high negative correlation between unemployment and labour force participation – the higher the labour force participation, the lower the rate of unemployment – supporting the hypothesis that labour force participation (mediated perhaps by further education) is related to the unemployment rate. But the most remarkable feature of table 7 is the overall level of unemployment for bacherlor’s graduates two years after graduation. The labour force survey for 1997 shows the unemployment rate for university degree holders to be about 5%. The NGS shows the unemployment rate to be almost double that rate, and above the unemployment rate in the general population. Why do recent graduates have such high unemployment? The general answer, of course, is that we are looking at group which is still in transition, as described above; graduate surveys typically show that unemployment decreases over time, and that the labour market transition period can last many years.
At a more detailed level, other the British Columbia Graduate Follow-up survey also sheds some light on this question. The NGS questionnaire asks graduates whether they are employed. If they are not employed it goes on to ask whether they are looking for employment. Graduates are defined as unemployed if they are not employed, and seeking employment. The B.C. survey asks one additional question: “are you currently enrolled in school”? Based on the results of the B.C. survey, it appears that many graduates who are classified as unemployed by the NGS are actually attending school while reporting that they are searching for employment as well – resulting in a higher rate of unemployment than would be calculated if those in school (or at least full-time students) were excluded. Unfortunately, the NGS does not ask specifically whether respondents are in school during the reference week.
A another approach to the labour market behavior is shown in table 8 from the BC GFS, using follow up data on individuals at two points in time: 2 years after graduation and five years after graduation. While there is a rich source of information provided by such longitudinal tracking, for the purposes of this paper we draw attention only to three cells in the lower right hand corner: those who are not working and not in school, first in 1995 (7.1%), then in 1998 (6.6%), and finally those who were in that state at both points in time (1.7%). Further investigation of a third dimension to the table – labour force participation – shows that a significant majority of graduates who are both not working and not in school are not in the labour force. The only way to reconcile these statistics with the unemployment rate from the NGS is that many “unemployed” graduates are actually attending school while “unemployed. The “traditional” path after graduation, of leaving school, working full-time, and continuing to work full time, is taken by only 40 percent of graduates. The first five years are a period of transition for university graduates from all disciplines.
Table 9 show rates of unemployment and labour force participation by highest level of schooling in 1995. Further evidence for the hypothesis above, that university graduates tend toward unemployment due to further schooling, is provided by the statistics for trade and vocational graduates, who show both very high rates of unemployment and high rates of labour force participation. The high rate of unemployment is explained partly by labour market supply and demand, and partly by the transition factor. However, since these graduates tend not to continue on for further education at the same rate as university graduates, we see both a higher labour force participation rate, and a higher unemployment rate as a result.
Another way to view unemployment can be calculated from the NGS data: table 10 shows, for those graduates who were ever unemployed, the average number of months of unemployment, less the number of unemployed months spent in school. The general pattern is similar to table 7, but the table clearly shows that on average, over a period of 30 months (the lag between graduation and the survey), the number of truly unemployed months is relatively small. The worst case, that of fine arts graduates, shows that on average those who were ever unemployed spend about 5 months out of 30 searching for work while not in school. Statistics from Allen (1999) and the Census data show that as graduates age, not only do their unemployment rates decrease, but the differences between disciplines tend to disappear.
It is difficult to make conclusions about labour market supply and demand imbalances from calculated unemployment rates from the NGS, but a few general conclusions are relevant to educational planning. 1., that university graduates have, in general, lower rates of unemployment than trade/vocational graduates, and despite transition difficulties, they are absorbed into the labour market much more quickly than those with vocational/technical skills; 2. that the disciplines which are associated with specific occupations have lower rates on unemployment, and 3. that some graduates (humanities, biological sciences, fine arts, and social sciences) experience a more difficult labour market transition. Hence there is some evidence that the overall labour market is unbalanced, with too few teachers and engineers, there is no evidence of the existence of large pools of university graduates with inappropriate skills for the knowledge economy; Spells of unemployment for all graduates are relatively short, and chronic unemployment is almost non-existent.
Conclusions
and Policy Recommendations
To summarize the argument: there is sufficient research to show that university graduates from a wide range of disciplines succeed in the labour market; they command relatively high salaries, progress to managerial and professional occupations, and are relatively unlikely to be unemployed. Nevertheless, some educational policy in recent years has been directed at changing the mix of disciplines of university graduates, as well as changing the mix of vocational/technical training versus university education, with the objective of better serving the “knowledge economy”. According to this argument, the emerging knowledge economy is starved for technical skills, and the current mix of broadly educated university graduates is absorbed into the labour market with some reluctance. This hypothesis implies that some disciplines are disproportionately in demand in the knowledge economy, that there is an earnings premium for these skills, and that graduates in the low demand disciplines are unable to meet the requirements of the economy, and hence are more likely to be unemployed. This paper addresses the validity of that policy direction by looking at the flows of recent graduates into the labour force by sector, and in particular, by adopting an existing robust definition of the “knowledge sector”, and observing the flow of university graduates into the knowledge sector via the EIOM.
In terms of the absolute numbers of university graduates entering the knowledge economy, three sectors predominate: education, health, and business services, and the matrix is dominated by a small number of very large transition cells: the discipline of education into the education sector, health disciplines into the health sector, and social sciences into business services. The very magnitude of these transitions should give policy makers some perspective on the overall picture; broadly educated university graduates currently meet a huge demand, and tampering with the mix is not to be taken lightly. The labour market connections are also quite obvious.
In terms of proportions, there is not much variation by discipline in terms of the percentage of university graduates entering the knowledge economy. The very large difference is that vocational/technical and college educated graduates are much less likely to enter high knowledge sector. If any adjustment in the mix is indicated, it would be away from specific vocational/technical training and more toward general university education. The graduates of Canadian universities are employed, to a very large extent, in the knowledge economy.
When we look at the business services sector as a subset of the knowledge economy, we see that 35 percent of all new graduates hired are supplied by the social sciences and humanities, as compared with 28 percent from commerce and 13 percent from engineering. This fast growing, largely market based sector of the economy is to a very large extent seeking the broad, general skills of university graduates. Furthermore, the business services sector pays a substantial salary premium to attract these graduates from other, low knowledge sectors. If there is disequilibrium in the economy, it is perhaps most apparent as a shortage of broadly educated university graduates in the business sector. No other cell in the EIOM exhibits such a combination of large numbers employed and a salary differential.
Finally, although the more generally educated university graduates show higher levels of unemployment than more job specific fields, their rate of unemployment is still far below that of vocational/technical graduates, and there is evidence that it is a reflection of a longer transition period for less specifically educated graduates. Certainly there is no evidence of chronic, long term unemployment.
University graduates from all fields do well in the labour market, tend to work in the knowledge economy, and there are no obvious imbalances or oversupplies by discipline. This should not be surprising, given the nature of the high-knowledge economy, and the types of skills that are required. By using a precise definition of the knowledge economy, and noting the skills and abilities developed by a broad, general university education, apparently Canadian universities are serving the economy well.
Policy
Recommendations
1. Support for the increased growth of the knowledge economy implies support for university education. Recent university graduates are flowing into the knowledge sector of the economy in both greater proportion and absolute numbers than other forms of post-secondary education.
2.
Policy decisions must take into account the
absolute numbers in the EIOM; while
there are indeed specific skill shortages in specific industries, there is no
evidence of the need for macro shifts in educational mix to accommodate these
micro problems. Compelling anecdotes for
specific skills must be tempered by the overwhelmingly large numbers of
university graduates who fair well in the knowledge economy, and will be needed
in greater numbers in the future.
3.
University educators, especially in the social
sciences, humanities, and biological sciences need to be aware of the career
destinations of graduates – an enormously large fraction of university
graduates become teachers. While the
EIOM illustrates this, it understates it, as many of the current graduates in
other fields eventually return.
4.
There is evidence that graduates from all
disciplines undergo a transition period, during which they move between various
forms of employment and education. More attention and research into this
transition period, particularly for those with non-specific degrees, might
result in a more efficient transition.
Transition strategies prior to graduation might also be useful.
5.
Analysis of employment data from the NGS should not
be compared with other data sources; the
unemployment rates, in particular reflect the ambiguity of simultaneous
education and unemployment. A useful
addition to the questionnaire would be to add
questions on current educational activity.
6.
There is a link between the employment of social
science and humanities graduates in the business service sector and their
university education, but the description of this link is anecdotal. The broad general abilities espoused by the
universities are similar to the broad general abilities required in the labour
force, but more specific teaching and learning outcomes remain vague.
References
Allen,
R.C. (1998). The employability of university graduates in the humanities,
social sciences, and education: Recent statistical evidence.
Allen, R.C. (1999). Education and technological revolutions: The role of the social sciences and the humanities in the knowledge based economy. Unpublished paper.
Conference
Board of
Lee,
F. & Has, H. (1996). A quantitative assessment of high-knowledge industries
versus low-knowledge industries. In P. Howitt (ed.). The implications for
knowledge based growth for micro-economic policies. The Industry
Organisation
for Economic Cooperation and Development. (1987). Structural adjustment and
economic performance.
Organisation
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explanations. Labour market trends underlying forces of change.
Organisation
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productivity and job creation.
Partridge, J. (2000, April 8). High-tech CEOs endorse funding liberal arts. The Globe and Mail.
Sudmant, W.
& Heslop, J. (1997). Five year graduate follow-up of 1991 baccalaureate
graduates from BC’s public universities. Report of Findings.
[1] Economic theory predicts that in equilibrium,
earnings for similarly productive workers will be equal, other factors being
equal, and that the level of employment in the various sectors will adjust to
achieve this, however few labour market
analysts, economists or otherwise, would argue that equilibrium economic theory
is applicable in this context. The
premise of the debate about post-secondary educational planning is that the
economy is changing, and policy/funding must either respond to, or dictate the
type and rate of change.