Higher Education Incentives for Economic Development
Education Incentives 1
Higher Education Incentives for Economic Development
Dr. Emanuel Carvalho
LED 613: Regional Development
University of Waterloo
April 8, 2004
Education Incentives 2
Higher Education Incentives for Economic Development
A common mantra among Atlantic Canada’s post-secondary student leaders is that
graduates must leave the region if they wish to increase their earnings and repay their
student debt. But what does this mean for regional economic development? Since an
educated population is vital to endogenous growth, government has developed a variety of
interventions to encourage participation in post-secondary education (PSE). The key
intervention has been the student loan. This paper establishes that while government has
been encouraging participation it has unwittingly been encouraging out-migration from
Canada’s poorest provinces. Sky-rocketing tuition has been met by increases in student debt
levels. Many university and college graduates are forced to leave the least-opportune
provinces to earn wages that are sufficient to service their debt loads. Is there an appropriate
policy response that encourages participation in post-secondary education without
encouraging out-migration? Seven funding sources were examined to determine their effect
on migration. The analysis reveals that few existing government interventions meet both of
the criteria identified. The best strategy to encourage participation without encouraging out-
migration appears to be direct reductions in tuition fees, creating a competitive advantage
over fees in other provinces. Tax incentives to encourage parental support also show promise.
Why encourage PSE?
Government policy in Canada is often informed by neoclassical economic theory
(Carvalho, 2005). This theory states quite simply that regional output of a commodity (in the
Education Incentives 3
case of the one sector model) is a function of the capital and labour employed in its
production (see Equation 1). By modifying this formula, it can be shown that an increase in
productivity (defined as output per unit of labour) is the result of an increase in the ratio of
capital to labour (see Equation 2). Therefore, increases in productivity can only be achieved
two ways: labour must remain constant while capital increases, or capital must increase faster
than labour. Unfortunately this simplistic version of the theory suggests that technological
progress has no qualitative effect on productivity. Technology can only manifest as
additional capital inputs and reduced labour inputs.
Acs and Varga (2002) compare neo-classical and endogenous growth theories and
explain that the latter allows for “the modeling of technological change as a result of profit-
motivated investments in knowledge creation by private economic agents” (p. 137). They
argue that the former is limited by assumptions of perfect competition and constant returns
to scale. In fact, technology is not a purely ‘public good’ since knowledge can be “sticky”
(Bourgeois and LeBlanc, 2002) in time and space. Patents and tacit knowledge can create
disparity in technological diffusion. Firms and regions that can develop “sticky” innovations
gain market power and fixed-term monopoly profits (Bourgeois and LeBlanc, 2002).
Endogenous growth theory attributes productivity growth above and beyond a
change in the capital-labour ratio to “innovations”. These can take the form of product or
Equation 1 Equation 2
Q= f (k , L ) Q
= f k
Education Incentives 4
service innovations, process innovations, and organizational innovations (Morgan, 1997;
Bourgeois and LeBlanc, 2002; and Betts, 1998). Product or service innovations can be
incremental changes to existing products or services, or entirely new ones. Process
innovations can either reduce the costs or improve the quality of production (for example,
just-in-time inventory systems). Organizational innovations involve some form of structural
advantage, such as the way Walmart coordinates its distribution chain through computerized
inventory systems. Even when experiencing equal capital and labour growth, firms that
successfully implement innovations will see growth in output over those which do not
innovate (Carvalho, 2005). This revelation has encouraged governments to divert resources
from expensive capital-mobilization strategies to innovation catalyzing ones. However,
innovation defies simple government intervention.
A typical government initiative might involve encouraging research and
development. When discussing the downfalls of typical job-creation strategies for declining
regions, Hall (1984) suggests using an existing or “deliberately implanted” research and
development tradition to create an entrepreneurial tradition. He is cautious, and notes, “such
bold strategies may succeed, but they are likely to take a long time to produce substantial
results…no single strategy, but rather a combination of different approaches, will be
appropriate” (p. 35). Despite this hesitation, and the tradition of peer-juried awarding of
university research grants, Hall concludes with a call for “the establishment of regional
quotas to the Research Councils” (in the UK, USA and Canada). Indeed, there is evidence
that the Canadian government’s university research grants neglect disadvantaged regions.
Education Incentives 5
Over its first five years, the Canada Foundation for Innovation invested only 3.2% of its total
contributions in Atlantic Canada (Beaudin and Breau, 2001, p. 133). But only measuring
innovation in terms of gross expenditures on research and development is inappropriate.
GERD is “meant to reflect the degree of innovative effort and intent, not necessarily
innovative potential and success” (Bourgeois and LeBlanc, 2002, p. 170). Despite a low level
of government R&D funding grants, Bourgeois and LeBlanc found that Atlantic Canada firms
in knowledge intensive industries (computer services, engineering consultant services, and
other scientific and computer services) have innovation rates near the national average
(2002, p. 71). However, this innovation is much less likely to involve the introduction of
new capital intensive technologies than elsewhere in Canada (financial capital is lacking).
They say that, “studies in the last ten years are increasingly rejecting R&D as a master key
that unlocks a linear innovation process, seeing it instead as one of several pieces to the
innovation puzzle” (p. 170).
There is a myth that innovation is unique to high-technology industries and only
happens in R&D laboratories. Bourgeois and LeBlanc, as well as Beaudin and Breau, note the
importance of innovation to firms in the primary sector. For example, in the Atlantic fish
processing sector between 1988 and 1996, the number of labour-hours declined 40% but the
value-added per hour rose 35% (Beaudin and Breau, 2001, p. 89). These industries “acquire
ideas not from in-house R&D but by tapping into the knowledge and ingenuity of their
workers, suppliers and customers – by networking with research institutions, universities,
competitors, governments, and other stakeholders” (Bourgeois and LeBlanc, 2002, p. 18).
Education Incentives 6
Indeed, there is a burgeoning volume of research on the social-embeddedness of innovation.
Noted academics like Saxenian (1994) argue that community networks encourage the free-
flow of ideas and therefore foster continuous innovation. Saxenian is critical of science parks
and other strategies that aim to create replica Silicon Valleys. She concludes that, “ultimately
regions are best served by policies that help companies to learn and respond quickly to
changing conditions – rather than policies that either protect or isolate them from
competition or external change” (p. 166).
All of this is not to diminish the importance of both publicly and privately funded
research and development. Rather, this discussion has demonstrated that there is no simple
solution to the problem of regional disparity. A region’s absorptive capacity is as important as
its ability to develop new technologies. While government might fund and encourage new
technology development in many ways, it cannot neglect the need for a broadly educated
population. Human capital is requisite to both the creation and absorption of innovations.
And social networks are the fabric that enables collaborative innovation. Those regions that
are best able to mobilize the innovativeness of their residents will prosper over the long
term. A basic key to innovation is therefore post-secondary education.
Is there really a problem?
Fenton, Gardner and Singh (2001) recently published an econometric model to
predict the outcome of cuts to PSE in the state of New York. The model demonstrates that
when participation rates fall in response to rising tuition prices, personal income and
personal tax receipts decline. Using a net-present-value accounting model, the authors
Education Incentives 7
conclude that “potential revenue losses quickly dwarf the short-run savings of funding cuts”
(Fenton, Gardner and Singh, 2001, p. 54). However, in the Canadian context there is a
fundamental flaw in this model. As tuition has nearly doubled in Canada over the past
decade, participation rates have also been climbing. More students are paying more money to
attend university and college. This is possible because Canada has a comprehensive system of
government sponsored student loans. This loan system effectively defers the impact of
tuition price hikes so far into the future that the elasticity of demand for PSE is significantly
altered. The PSE consumption decision may not be entirely rational in an economic sense.
Logically, however, the labour market should correct for these higher debt levels. It
appears to be adjusting in two significant ways. First, post-secondary graduates garner a
significant wage premium over their counterparts who did not attend PSE. The Maritime
Provinces Higher Education Commission found that the wage-premium for graduates who
stayed in the Maritimes was 26% (MPHEC, 2002, p. 6). However, the MPHEC also found
that graduates who left the Maritimes saw a 78% wage premium (Ibid.). This appears to be
the second labour-market correction. Graduates migrate in search of higher wages. In the
general population of Canadians, men typically migrate for economic reasons (Finnie, 1998)
while women are more likely to migrate for family reasons (Lin, 1995). However, there is
some indication that post-secondary graduates are different in this regard. Male and female
graduates in the Maritime Provinces are equally likely to cite job-related economic reasons
for migration (MPHEC, 2002). Of all Canadians, young post-secondary graduates are the
most mobile (Looker, 2001, p. 32). Nearly half (45%) of Prince Edward Island residents, one-
Education Incentives 8
in-seven New Brunswickers, and one-in-fifteen Nova Scotians left their home provinces to
go to university (MPHEC, 2002). Those graduates who had attended university outside their
home province were 16% more likely to move at least once after graduation, and nearly one-
in-seven left the region completely. Twenty-eight percent of engineering graduates leave the
region within one year of graduation. They are followed by graduates of math and physical
sciences (20%), information technology (15%), health professions (13.4%) and fine and
applied arts (12.1%).
Indeed, each progressive level of education results in greater proportions of graduates
leaving their home province. MacNeil (2004) found that Canadian graduates at the Ph.D.
level show the greatest propensity for leaving their province of origin. Nearly one-third of
them (29.7%) become leavers, versus 17.0% of masters graduates, 10.9% of undergraduates,
5.8% of college graduates, and 3.4% of trade and vocational graduates. Looker (2001, p. 30)
disputes this link by saying, “…it is not always clear from the data whether those with
higher education are more likely to move, or if those who are more likely to move obtain
higher levels of education”. Since higher levels of education are centralized at larger
universities it is conceivable that master’s and Ph.D. degrees are only attained by those
willing to move.
Three pieces of evidence suggest that Looker’s critique is unfounded. First, the
propensity among graduates to migrate is not geographically consistent with this logic (see
Figure 1). Atlantic graduates are nearly twice as likely to leave their home provinces as
Education Incentives 9
graduates from anywhere else in the country1. Nineteen-point-five percent of Atlantic
Canadians leave their province of origin at some point either before or after their graduation.
This is trend extends not only to those who originate in Atlantic Canada, but also to all those
who studied2 or were interviewed3 in an Atlantic Province. Therefore, the region of Canada
with the greatest provincial out-migration (Atlantic Canada) has the highest per-capita
number of post-secondary institutions. It also has the weakest economy. This suggests that
migration is more closely linked to economic circumstances than access to higher education.
Origin Study Interview
Figure 1. Percent of graduates who became leavers by region of origin, study and interview (MacNeil, 2004).
Second, tuition is correlated with out-migration rates among 20-24 year olds (see
1 The effect of “region of residence pre-1995” on interprovincial migrant class is statistically significant, L2 = 9,374.229, df =
8, p = .000 (MacNeil, 2004).
2 The effect of “region of institution” on interprovincial migrant class is statistically significant, L2 = 10,525.658, df = 6, p =
.000 (MacNeil, 2004).
3 The effect of “region of interview” on interprovincial migrant class is statistically significant, L2 = 10,126.103, df = 6, p =
.000 (MacNeil, 2004).
Education Incentives 10
Tuition vs. Out-Migration in the Atlantic Provinces
Out-Migration of 20-24 year olds (%)
4.00% Linear (PE)
2.00% Linear (NB)
$- $1,000 $2,000 $3,000 $4,000 $5,000 $6,000
Average Tuition ($)
Figure 2. Linear regression of average tuition prices vs. out-migration rates among 20-24 year olds, Atlantic
Provinces (Prepared by R. MacNeil with data from CANSIM Tables 051-0001 and 051-0012).
Note: Pearson’s Product Moment Correlation Coefficients (r): NL = +0.88, PE = +0.63, NS = +0.38, NB = +0.85.
Tuition vs. Out-Migration in the Central Provinces
Out-Migration of 20-24 year olds (%)
0.80% Linear (ON)
0.60% Linear (PQ)
$- $1,000 $2,000 $3,000 $4,000 $5,000 $6,000
Average Tuition ($)
Figure 3. Linear regression of average tuition prices vs. out-migration rates among 20-24 year olds, Ontario and
Quebec (Prepared by R. MacNeil with data from CANSIM Tables 051-0001 and 051-0012).
Note: Pearson’s Product Moment Correlation Coefficients (r): ON = -0.71, PQ = -0.72.
Education Incentives 11
In the Atlantic Provinces there is a strong positive association between higher out-
migration rates and higher tuition levels since 1992 (with the exception of Nova Scotia
which has a weaker association). This is not simply a time effect. Tuition in Newfoundland
and Labrador has declined over the past four years and so have migration rates. In Atlantic
Canada higher tuition levels are in some way associated with higher out-migration rates.
Meanwhile, in the central provinces of Ontario and Quebec there is a strong negative
association between tuition and out-migration (see Figure 3). Here, higher tuition levels are
in some way associated with lower out-migration rates. The pattern is simple: when tuition
increases, more young people leave the poor provinces and more stay in the rich provinces.
Since debt is likely the real causal factor, the relationship identified above is not perfect.
Unfortunately average student debt data is not readily available.
The third and final reason for rejecting Looker’s chicken-and-egg argument is that
graduates with greater debt are more likely to become leavers (see Figure 4). The incidence
of leavers is lowest among graduates who borrowed a government student loan but had paid
it off by graduation (0.8%). It is highest (5.9%) among those who borrowed the most (over
It is now clear that an educated population is a vital component to economic growth,
but migration rates are related to student debt. Government must therefore attempt to
encourage post-secondary participation without losing new graduates to out-migration.
These two criteria should factor into any higher education incentive policy.
Education Incentives 12
Figure 4. Percentage of leavers among graduates in each loan value grouping (MacNeil, 2004).
Note. The effect of government student loan value (at graduation) on migrant class is statistically significant, L2 = 719.391, df
= 16, p = .000.
This study used a public-use micro data file provided by the Government of Canada
under the Data Liberation Initiative. The file contains all records resulting from Statistics
Canada’s Survey of 1995 Graduates in 1997. It is the latest public release in a series of cohort
surveys conducted since 1978. The primary objective of the survey was to collect data on
labour market trends among post-secondary graduates. The sample size is sufficiently large to
support generalization of the findings over the entire population of the class of 1995. This
current study should, however, be considered only an exploratory analysis because the data
is from a cohort that graduated ten years ago.
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Population and Sample
The survey's population is all graduates from Canadian public post-secondary
education institutions who completed the requirements for degrees, diplomas, or certificates
during the 1995 calendar year (298,154 individuals). It does not include graduates of private
career/trade colleges and training institutes. With the exception of three small institutions,
all 402 public post-secondary institutions supplied graduation lists. A sample was drawn from
these lists first by stratifying the population into five levels:
- skilled trades
- undergraduate (degrees, diplomas, and certificates)
- masters level (degrees, diplomas, and certificates)
The population was further stratified into nine fields of study for university and
career/technical programs and eight fields of study for the trade/vocational programs. An
independent systematic random sample was subsequently selected from each stratum. The
resulting sample size is 61,759 graduates. Of that sample, 43,040 graduates responded to the
survey (Statistics Canada, 1999). Statistics Canada includes weighting values for all records in
the data file (see the survey documentation, pp. 28 and 61 – 66). These weights have been
used to calculate estimates throughout the course of the study.
Collection and Format
The Survey of 1995 Graduates in 1997 was conducted from May to July, 1997, using a
computer-assisted telephone interview (CATI) methodology (Statistics Canada, 1999). A
conversion script for the SPSS 9.0® file format is provided by the Data Liberation Initiative.
Education Incentives 14
The Survey of 1995 Graduates in 1997 data file was analyzed in SPSS 12.0®. The
analysis included the use of basic descriptive statistics, but the primary tool of inquiry was
Pearson’s Chi-Square (denoted as L2 throughout the text). This non-parametric method was
necessary because most of the variables are nominal in nature. Variables in the dataset that
would otherwise be useful in a parametric analysis (such as loan value) are grouped such that
they could not be reorganized into ordinal sets. Violations of the assumption of homogeneity
of variance precluded the use of other non-parametric tests on the data set. It was possible to
calculate the significance of variations in the sample with the chi-squared statistic for two
and three way cross tabulations. A confidence level of 95% was used to interpret all
The three youth migrant classes presented in Rural Youth : Stayers, Leavers and
Return Migrants (Dupuy et al, 2000) were used. For the purposes of this study, migration was
defined as the movement between provinces over the two year study period. To this end, the
values found in the “interprovincial migration for education” variable were recoded. Table 1
is a comparison of the original and new migration variables. Hypothesis testing compared the
post-secondary graduates who fall into the three migrant classes.
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Table 1. Recoding of Migration Data into the Three Migrant Classes
Interprovincial Migrant Class (new Interprovincial Migration for Education (old variable)
Stayers (Value = 0) Non-migrant (Value = 1)
Leavers (Value = 1) Migrant before graduation, not returning to province of origin after
graduation (Value = 3)
Migrant after graduation, not before (Value = 4)
Migrant before and after graduation, not returning to province of
origin (Value = 5)
Return Migrants (Value = 2) Migrant before graduation, returning to the province of origin after
graduation (Value = 2)
Note. The SPSS conversion file provided by the Data Liberation Initiative erroneously switched the definitions for values 2
and 3 in the old variable. This error was corrected using the data codebook.
The results of this study were limited by the data available. Unfortunately Statistics
Canada has yet to release the responses collected from a five-year post-graduation follow-up
with this sample in the year 2000. Access to the extra three years of labour market and
migration information would add significantly to the value of this study’s findings. Also, data
from a more recent cohort of graduates would provide more reliable and actionable results.
This study’s definition of migration is also limited by the data available. Detailed
migration information has been suppressed in the public release of this data. Typically
migration is defined in terms of relocation over a specific measured distance, between
communities, or between rural and urban settings. This data set identifies graduates based
only on their region of origin, study, and interview. Despite the focus on regional data there
is one variable that identifies respondents by their inter-provincial migration patterns.
Therefore, this study must define migration as relocation between provinces.
Education Incentives 16
Government Sponsored Student Loans
Surprisingly, graduates who used government student loan programs were less likely
to become leavers than those who did not (see Table 2). While the difference is only 0.7%, it
is statistically significant. This only confirms that government student loan programs, in and
of themselves, do not encourage migration. In fact, the effect of loan programs on migration
is so negligible that, when used as one of two main funding sources, it is insignificant4.
Table 2. Incidence of the Three Migrant Classes by Use of Government Loans.
Interprovincial Migrant Class
Stayers Leavers Migrants Total
Use government Yes Count 113,423 10,082 473 123,978
Percentage 91.5% 8.1% .4% 100.0%
program? No Count 153,151 14,775 698 168,624
Percentage 90.8% 8.8% .4% 100.0%
Total Count 266,574 24,857 1,171 292,602
Percentage 91.1% 8.5% .4% 100.0%
Note. The effect of using a government student loan program on interprovincial migrant class is statistically significant, L2 =
38.700, df = 2, p = .000.
Other Funding Sources
Government student loans are not the only funding source graduates used to finance
their education. Respondents to the Statistics Canada survey were asked to identify their two
main funding sources. Fully half of the major funding sources cited had no statistically
4The effect of government student loans as one of two main funding sources is not statistically significant, L2 = 7.292, df = 2,
p = .026.
Education Incentives 17
significant effect on interprovincial migrant class. These sources were: spouse/partner5,
student loans4, other loans6, and employment earnings7. Conversely, migrant class was
affected by those funding sources that did not place a direct financial burden on the
graduate. Those who used scholarships, awards and fellowships as one of two main funding
sources were the most likely graduates to be leavers (see Table 3). Graduates who did not use
parents and worker’s compensation as their funding sources were more likely to be leavers.
Table 3. The Incidence (%) of Leavers by Main Funding Sources.
Used as one of two main
Funding Source Yes No
Parentsa 8.0% 8.7%
Scholarships / awards / fellowshipsb 14.5% 8.1%
Grants / bursariesc 9.0% 8.5%
Worker’s compensationd 2.5% 8.6%
Note. Those funding sources that had an insignificant effect on migrant class have been excluded.
aThe effect of financial support from parents (as one of two main funding sources) on interprovincial migrant class is
statistically significant, L2 = 49.865, df = 2, p = .000.
bThe effect of financial support from scholarships / awards / fellowships (as one of two main funding sources) on
interprovincial migrant class is statistically significant, L2 = 866.532, df = 2, p = .000.
cThe effect of financial support from grants / bursaries (as one of two main funding sources) on interprovincial migrant class
is statistically significant, L2 = 58.875, df = 2, p = .000.
dThe effect of financial support from worker’s compensation premiums (as one of two main funding sources) on
interprovincial migrant class is statistically significant, L2 = 140.156, df = 2, p = .000.
Repayment Assistance versus Needs-based Grants
An important sideline to the relationship between student debt and migration is the
remedial effect of debt relief programs. The results indicate that loan repayment assistance
5 The effect of financial support from a spouse/partner (as one of two main funding sources) on interprovincial migrant class
is not statistically significant, L2 = 6.819, df = 2, p = .033.
6 The effect of borrowing “other” non-government loans (as one of two main funding sources) on interprovincial migrant
class is not statistically significant, L2 = 2.009, df = 2, p = .366.
7 The effect of employment earnings (as one of two main funding sources) on interprovincial migrant class is not statistically
significant, L2 = 6.590, df = 2, p = .037.
Education Incentives 18
has an insignificant effect on interprovincial migrant class8. This is a discouraging statistic for
those provinces that currently have debt relief programs. Although, debt relief programs
with specific residency requirements (ie. bonus relief for stayers) are only a recent
government strategy. The graduates of 1995 did not benefit from repayment assistance
programs with stayer-targeted rewards. Regardless, the fact that repayment assistance had an
insignificant effect on migration in the mid-nineties begs for an investigation of such
strategies today. More recent evidence is required.
Many post-secondary student leaders would respond to the previous finding by
trumpeting a need-based grant strategy. However, the evidence for such a program is even
more discouraging. Graduates who received need-based grants or bursaries were 1.1% more
likely to have become leavers than those who did not (see Table 4). The grants had no effect
on return migration. This is surprising given that such grants serve to reduce the debt loads
that have been found to encourage migration. Since those who received such grants were the
neediest, it may be that the grants are simply not reducing the debt to a point where these
graduates can become stayers. Perhaps an exploration of the mechanics of grant and bursary
programs is required. Unfortunately the necessary data is not available in this dataset.
8 The effect of “assistance from government/lenders to repay student loans” on interprovincial migrant class is not
statistically significant, L2 = 1.972, df = 2, p = .373.
Education Incentives 19
Table 4. Incidence of Stayers, Leavers and Return Migrants by Receipt of Need-Based Grants / Bursaries.
Interprovincial Migrant Class
Stayers Leavers Migrants Total
Receive Yes Count 40,394 4,205 165 44,764
need-based Percentage 90.2% 9.4% .4% 100.0%
grants / No Count 225,760 20,559 1,005 247,324
Percentage 91.3% 8.3% .4% 100.0%
Total Count 266,154 24,764 1,170 292,088
Percentage 91.1% 8.5% .4% 100.0%
Note. The effect of “need-based grants/bursaries” on self-employment is statistically significant, L2 = 58.132, df = 2, p = .000.
One of the many challenges facing governments in Canada is this issue of post-
secondary education. Government should encourage PSE participation as an economic
development strategy. But it is evident that some incentives encourage graduates to leave
disadvantaged provinces. Few existing interventions meet both of the criteria identified.
Scholarships, award and fellowships facilitate migration, as do grants and bursaries. The best
strategy appears to be direct reductions in tuition fees. A province that undertakes this
strategy would create a competitive pricing advantage over other provinces while reducing
the debt-servicing burden. Tax incentives to encourage parental support also show promise.
Surprisingly, debt repayment assistance does not appear to have a significant effect on
migration. This is discouraging news for those provinces whose debt-relief programs are
specifically targeted at reducing out-migration, but more research is required.
The evidence presented here does little to support existing government strategies.
Education Incentives 20
Most provincial governments continue to cut PSE funding, increasing tuition9. To counteract
these increases, provinces like Saskatchewan are providing scholarship and bursary
programs. Scholarships and bursaries may make PSE more accessible, but they exacerbate the
problem of out-migration. Perhaps the worst strategy in this regard was a measure in the
2004 federal budget to increase the maximum allowable student loan. More student debt will
undoubtedly push graduates out of the poorest provinces.
Three provinces have strategies that hold up well under these findings. Manitoba
reduced tuition by 10% in 2000 and has since maintained a tuition fee freeze. Quebec has
deliberately maintained the lowest university tuition in the country (and free college tuition)
for Quebecers. University tuition fees in Quebec have been frozen for 15 of the past 20 years.
Finally, Newfoundland and Labrador now has the second lowest tuition fees in the country
following 10% reductions in 2000 and 2001. Newfoundland and Labrador was the first
province to introduce a loan repayment assistance program tied to a stay-at-home incentive.
The territories have used a similar repayment incentive for some time to address the fact that
all territorial residents must leave to obtain a post-secondary education.
Clearly more research is needed on grant size and more recent data is needed on stay-
at-home debt relief programs. Also, it must be noted that even though some of the
interventions identified had negative or negligible effect on migration their effect on
improving accessibility for low-income earners could be very significant.
9 Details of government programs obtained from CFS, 2005 and provincial government websites.
Education Incentives 21
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Education Incentives 22
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