Research " ECONOMETRIC STUDY OF THE DEMAND FOR HIGHER EDUCATION IN CANADA, 1976-1995 " pot

Using Canadian time series data from the years of 1976 — 1995, the thesis empirically tests the hypotheses that the demand for higher education is responsive to labour market movement as

Yuanyuan Zhang

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The undersigned hereby certify that they have read and recommended to the Faculty of Graduate Studies for acceptance a thesis entitled “Econometric Study of the

Demand for Higher Education in Canada, 1976 - 1995” by Yuanyuan Zhang in partial

fulfillment of the requirements for the degree Master of Arts in Economics

Dated: Apre! LÍ í LOO

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DALHOUSIE UNIVERSITY

Title: Econometric Study of the Demand for Higher Education in

Canada, 1976 - 1995 Department: Department of Economics

Degree: Master of Arts in Economics

Permission is herewith granted to Dalhousie University to circulate and to have copied for non-commercial purposes, at its discretion, the above title upon the request of

The author attests that permission has been obtained for the use of any copyrighted

material appearing in the thesis (other than brief exerts requiring only proper

acknowledgement in scholarly writing), and that all such use in clearly acknowledged

2.1.1 Education as both consumption and Investment 8

2.1.2 Some theoretical models in the human capital theory LŨ

2.2 Empirical Studies on the Returns to Education in the Ù S 11 2.3 Some Empirical Studies on Returns to Education in Canada 13

CHAPTER II DATA SELCTION AND DESCREITPTION 18

3.1 Selection of Dependent Variable .- -c sàn nen 18 3.2 Selection of Independent Variables . -. cào sàn 20

3.2.1 Unemployment rat€ . - con HH nh nen 20 3.2.2 Wage differentlal -< Ăn Ăn nen se 25 3.2.3 Disposable personal Income .- -. - sec se 27 3.2.4 Private costs of higher education .- .- - 28

3.2.6 Other variables .-. - << nh nh nh nen 31

3.3 Diffculty in Data ConsIst€nCy . - nen nh nh nen he 33 3.4 Trends ofthe Main Varlables .-. - sec ŸS Sàn se 36 3.5 Relationship between Dependent Variable and

Key Independent Variables - - sành ren s 41

iv

CHAPTER IV ECONOMETRIC METHODOLOGY AND MODEL

k)32®013/0.00/9)1-125555 47

4.3 Analysis of Regressions .22cceee cere cece ence eee ence eee ee cere eee eeeee teen nees 51

4.3.1 Sigmiicance ofthe whole r€BỹT€SSIONS . - 51

4.3.2 Significance of the regression cOefÍicienfS .-. .- - 52

4.4 Limitation of the Study .- -. SH HH HH nh n nh hen 56 4.5 Another Possible Explanation . - << sen sen 59

In UMIversity 38 Average Real Wages by Educatlon Level_ - 39 Average Real Wage Differential between University and

High School Graduates In Canada, 1976-1996 39

% of Aged 19-14 in University and High School Graduate Unemployrment Rafe -. - {cà 42 Growth Rate of % of Aged 19-24 in University and of

Wage for High School Graduafes . - 43 Growth Rate of % of Aged 19-24 in University

and of Wage Differential . -. - << se «+ 44 Growth Rate of % Aged 19-24 in University and University

Tuition Fees in Canada .- - -.-.« 45

Table 1.1

Table 4.1

Table 4.2

Table Al

Table A2

Table A3

Table A4

Table AS

Table A6

Table Cl

Table C2

Population Aged 15-24 and Unemployment Rates by

Age Group m Canada, 1976 — 1997 - -

Comparison of Dickey-Fuller & Phillips-Perron Unit Root Tests for the Wages Differential between University and High School Graduates Aged 25-34, and Real Interest Rate

4 +2š-319055ãì 2 ".e—

Dickey-Fuller Unit Root Test Results, 1976-1995

Phillips-Perron Unit Root Test Results, 1976-1995

Engle-Granger Test (Dickey-Fuller Test on Residual)

Dickey-Fuller Unit Root Test Results (After differencing)

Phillips-Perron Unit Root Test Results (After differencing)

Engle-Granger Test (Dickey-Fuller Test on Residual) (A fer differencing) .-. - sàn se Correlation Matrix of Variables in Wage Differential Aged 25 ẽn Correlation Matrix of Variables in Wage Differential PC sìtaaaầaiÝ(đắŸÝŸ4ẢỀẢÊẢỶÝÝẢÝỶÝ

University enrollment in Canada has witnessed ups and downs in the last two

decades What factors play roles behind these movements of university enrollment in Canada? This question motivates the work of this thesis

Education is a product, a special product Both human capital theory and demand theory try to explain the factors that affect the demand for higher education Especially

since the debut of human capital theory in the late 1950’s and early 1960’s, the motivation for receiving higher education and the expected returns to education have

been widely studied The role that the expected returns to education plays in the demand

for higher education is widely recognized Besides these economic factors, some studies

have also focused on the responsiveness of the demand for higher education to movements in the labour market

Using Canadian time series data from the years of 1976 — 1995, the thesis empirically tests the hypotheses that the demand for higher education is responsive to

labour market movement as well as to personal income and university tuition fee in the observed period

Due to the limitations of the data, the results of this study could not prove what theory suggests

ACKNOWLEDGEMENT

Though this thesis is of my own, it reflects collectively the swpport,

encouragement and help from many people My heartiest thanks go to my supervisor, Shelley Phipps for her encouragement, guidance and support throughout the work I

would like to thank my readers, Kuan Xu and Peter Burton for their valuable comaments and advice My sincere thanks also go to Lars Osberg for his academic guidance I would like to give my acknowledgement to Lynn Lethbridge who has helped me programm some unpublished data Her help is invaluable Phyllis Bailey Ross has provided the codebooks

for the Survey of Consumer Finance I am very grateful to them all

Finally, I would thank my husband, Jinfa, my little son, Yue and my parents Though they are far away from Canada, they always shower me with their- love,

encouragement and support To them this thesis is dedicated.

INTRODUCTION

On May 3, 1999, in an article in the Globe and Mail, Bruce Little noticed that a

huge proportion of Canadian young people dropped out of the labour market in the 1990s

and that there was a huge increase in school enrolment rates.' He conciuded that the two

were obviously linked for the two reasons that: (1) the young stayed in school because they wanted to improve their long-terms odds of getting a good job and (2) a sluggish

economy offered them little chance of finding immediate work Although Little did not

distinguish between higher education and secondary education, his conclusion suggested

a popular perception which provides a motivation for this thesis

Is there any relation between labour market conditions and university enrolment? Did labour market movements play a role in the vicissitudes of university

enrolments in Canada in the 1990s? What factors make youth decide to join the labour force instead of entering universities, that is what factors affect young people’s decision- making about whether or not to study at university? Specifically, this thesis asks: whether

the demand for higher education in Canada is responsive to current labour market

conditions?

' Bruce Little, “The case of the crowded class” in the column of “AMAZING FACTS” in Globe and Mail,

May 3, 1999

Since the debut of human capital theory, the factors that affect the demand for higher education have been widely studied One of the most important incentives for

individuals to continue to higher education is that more years of schooling can bring a higher lifetime income stream For example, Squires (1979), and Rumberger and Thomas

(1993) confirm that education do increase income streams

Besides the incentive of higher earnings, some economists have also analyzed

the incentives from the perspective of the relationship between education and the

probability of employment For example, Kaun (1974) and Zsigmond (1978) observe that the demand for higher education responds to movements in the labour market These authors contend that with reduced or non-existent job opportunities (or with higher

unemployment rates), many job seekers will adopt alternative educational strategies to

improve their employment prospects Some job seekers will enter or continue in

university rather than remain or enter the workforce since the increase in their years of

schooling will improve their chances of being employed Betcherman (1991) more explicitly states, “unemployment experiences are also closely linked to educational attainment.” In general, the probability of being unemployed declines as the level of educational attainment increases The rate will be the lowest for those with the most

schooling and rises in steps as educational attainment diminishes Therefore, “there is a strong relationship between education and success in the labour market, and the evidence

we have presented suggests that this link is becoming stronger over time.” Martijn de

individual but, even more important, provides an individual in a society full of risks with

a certain amount of protection against insecurity and unemployment The role of education and training in resisting unemployment is more a protector of young people than as a guarantor of entry of employment” [Martijn de Goede et al 1996, p 2]

Over the last three decades, the unemployment rate in Canada has been consistently high The youth” cohort in Canada has always been a more vulnerable group

in the labour market The youth unemployment rate was high despite the fact that fewer young people aged 15 — 24 entered into the labour market Table 1.1 shows that the percentage of youth in the total labour force’ decreased slightly from 1976 - 1997 In spite of all measures taken in the last twenty years to help young people find employment, the unemployment situation for youth has not improved much

> According to Statistics Canada, the definition of “youth” is referred to the group aged 15-24 Since a large percentage of students enrolled in universities are the group within this age range, this thesis concerns this age group

3 The related definitions in this thesis are listed in Appendix B

Table 1.1 Population Aged 15-24 and Unemployment Rates by Age Group

in Canada, 1976 — 1997

15 and over labour force

Source: CANSIIM database The series for population aged 15 and over is D984550 and for the total labour

force aged 15 and over is D984551 The series for unemployment rate for 15-year-old and over is D980745,

for 15 —24 age group is D980746, and for 25 years and over is D980749

Note: ' Computed from CANSIM database

? The national total labour force.

why does university enrolment fluctuate? Does it really respond to current labour market situations? Besides labour market situations, are there other factors that play roles in

individuals’ decision about whether or not to study at university? These questions constitute the topic of this thesis

This thesis uses time series data in Canada for the years from 1976 to 1995 to test two hypotheses: 1) university enrolment increases as returns to education increase (i.e., as

the earning differentials between those with university degrees and those with high school

education increases.); 2) university enrolment increases as i) unemployment for youth increases; and/or ii) the unemployment difference between high school graduates and university graduates increases

Unemployment and wage differences between university graduates and high school graduates are not the only factors that affect demand for higher education Other important factors such as current family/personal income, university tuition fees and other education costs play roles We expect that the higher is current personal income, the

higher will be the demand for higher education as families can afford to purchase more education On the other hand, the higher are university tuition fees (price for higher education), the lower will be the quantity of demand for higher education

The organization of the rest of the thesis is as follows The second chapter reviews

the related literature The third chapter discusses the data and variable selection The

fourth chapter cites the regressions based on a variety of specifications and the inference from these regressions The fifth chapter presents conclusions.

LITERATURE SURVEY

Human capital theory examines the relationship between investment in human

capital and returns to education It explains individuals’ motivations to receive higher

education; and thus is the cornerstone of this study Hence, this chapter briefly introduces some key ideas of human capital theory Also this chapter surveys some earlier empirical

research relevant to the topic of this thesis

2.1 Human Capital Theory

Human capital theory emerged in economic studies in the late 1950s The essence

of the idea is that investments are made in human resources so as to improve their productivity and therefore their earnings Costs are incurred in the expectation of future benefits Like all investments, the key question becomes: is it economically worthwhile? The answer to this question depends on whether or not benefits exceed costs by a

sufficient amount Focusing on this, many studies have been published of the demand for higher education, which explore the relationship between higher education and lifetime

income stream (or individual welfare) The most influential one is Becker’s Human Capital in 1964, because this is the first work to develop a complete price theoretic

analysis of the individual’s investment in education and to derive the implications for

supply of labour, salary determination, and the path of salaries over the life cycle It is the

foundation on which all succeeding work has been based In the last four decades, human

capital theory has argued that the lifetime income stream is positively related to years of schooling Indirectly, this suggests that the incentive to pursue a higher education will

increase as it improves the probability of being employed and having a better job, though few papers have directly addressed the responsiveness of university enroliment to labour

market conditions

2.1.1 Education as both consumption and investment

From a general perspective, education is both consumption and an investment good Thus, an empirical analysis of the demand for education must be based upon a theory of how people make decisions concerning the type and amount of education to acquire These decisions are influenced mainly by economic factors, such as family/personal income, university tuition fees, etc., although they are also affected by non-economic factors, such as personal preferences

Handa and Slolnik (1972) note that there are two principal economic theories of

the demand for education, corresponding to two different hypotheses about students’ motivation for acquiring education

“The consumption motive is present when the good or service in question

generates satisfaction of primary or secondary wants in the current period,

such as an ice cream cone The investment motive is present when the item

goods and services contribute to an individual’s satisfaction in more than

one of these ways and the choice of labeling a purchase as consumption or

investment have always been somewhat arbitrary.””

The core of human capital model is the notion that education is an investment of current resources — time and money — for future pay If people spend money on acquiring education and some increase in their lifetime earnings can be attributed to their education, then there is an implied ex post rate of return to that investment in education A student is

assumed to make the decision to continue to receive higher education’ if the expected return from higher education exceeds his or her discount rate The discount rate reflects the opportunity cost of capital and the individual’s time preference between present and

future consumption Many studies have produced estimates of the implied ex post rates of

return on investment in education both to individuals and to the whole society

This thesis will only focus on the theory of private investment, not public

investment, in education and the benefits from education, considering the fact that most

individuals’ decision about whether or not to study at universities is based on private

costs to education

* Handa and Slolnik, 1972, p 11

> Course selection in universities also plays an important role in the expected returns to the investment in higher education This study is to focus the returns from higher education as a whole, so the course

selection will be ignored here

10

2.1.2 Some theoretical models in human capital theory

In human capital theory, in order to analyze the demand for higher education, numerous models, simple or complicated, have been developed for various purposes The implication of all, however, is that the demand for education is a function of the expected rate of return to education

Theoretical models, such as Becker (1964), Kuan (1974), Johnston and DiNardo (1997) and Benjamin et al (1998) relate the lifetime income stream with years of

schooling and show that lifetime earnings are a function of years of schooling Gunderson

and Riddell (1993) more explicitly illustrate the benefits from more education through comparing lifetime income stream and education costs They demonstrate that although more education requires more education costs, such as university tuition fees and foregone earnings, it will bring a higher lifetime income stream later on All these models show that earnings are a function of years of schooling

Groot and Oosterbeek (1992) extend the basic human capital model to incorporate uncertainty and consider the implications of education for the probability of becoming unemployed They analyze the optimal length of schooling given unemployment and

uncertainty, assuming the unemployment probability to be a function of the length of

schooling However, they conclude that theoretically the effects of changes of unemployment probability and wages on the optimal schooling length are ambiguous

2.2 Empirical Studies on the Returns to Education in the U S

In addition to the above theoretical studies of the education-earnings relationship,

a substantial body of empirical research has also appeared since the debut of human capital theory Many studies use U S data and calculate the expected returns to education based on the fact that after the Second World War university enrollment in the

United States exploded These studies demonstrate that the enrollment explosion in the

US at that time primarily reflected students’ perceptions of the economic and social advantages of obtaining education in addition to the other motives for acquiring education

Most of these empirical studies have shown that income is positively related with the number of years of schooling For example, Squires (1979) observes that the major attractions of schooling have been the greater social and economic rewards which are available to the better educated members of society primarily because of the kinds of jobs for which that education qualifies them Rumberger and Thomas (1993) also note in their more recent study that a volume of research conducted over the last 30 years has demonstrated considerable economic benefits from college participation College

graduates earn substantially more than high school graduates and, in the US the

differences have increased noticeably in recent years

From the papers discussed thus far, we can see that most studies, using the human capital framework, specify income streams from education or expected returns to education as the dependent variable while independent variables are years of schooling

and other factors that will affect the income stream or expected return, such as years of

work, rental price of human capital, etc

Campbell and Siegel (1967) use a long time-series of data from the United States from the First World War to mid 1960’s to analyze the demand for higher education from both the investment and consumption perspectives In their study, Campbell and Siegel set university enrollment (the demand for higher education) as the dependent variable while using current income (affordability) and price (university tuition fee) to explain the

movement of demand for higher education They find that these two variables explain 87

per cent of the variation in demand for higher education In addition, they find that demand responds positively to changes in income and negatively to changes in price

Using data from 1946 to 1966 in the United States, Kaun (1974) studies the impact of labour market conditions on the probability of college dropouts Together with

other regressors, included in the right-hand side variables of the equation are two

unemployment variables: change in unemployment rate and weighted unemployment rate over years t through t + 3.° Kaun’s study shows that these variables “explain” 92 percent

of the change in dropout rates over the period and both unemployment variables are significant for at least 10 per cent level

Becker [1964] and Hanoch (1967) have also shown that rates of return to schooling are positive but generally diminish with additional years of schooling Ashenfelter and Layard [1979] point out that although every study of earnings finds that years of schooling have a significant and sizable impact on earnings, at the same time,

every study also finds that by itself, years of schooling explains a relatively small part of

the variance of log earnings, say 3-5 percent at most What gives the theory its empirical power in explaining earnings is the extension to the impact of age/experience on earnings

It should also be mentioned here that Freeman (1976), Dooley (1986) and Katz (1992) show that the “overeducated” phenomenon since the late 1970s reduced the rates

of return to higher education Nonetheless, these studies, which study the US cases, show

that the highly educated individuals are able to find jobs and to get higher income more

easily than less educated individuals

2.3 Some Empirical Studies of Returns to Education in Canada

Studies of returns to education have also been carried out in Canada over the last

thirty years Most of the results of these studies are consistent with the similar studies

conducted in other countries A consultation paper Learning Well Living Well

14

[Ministry of Supply and Service Canada, 1991, p vi] points out “more and better learning means more and better jobs Countless studies confirm this connection between a highly skilled work force and a high-wage economy How well people live be they Germans, Australians, Koreans or Canadians depends on how well they learn.” But the paper further points out that in Canada this connection between jobs and learning is not widely recognized This is because “Canadians have been able to take their prosperity for granted” According to this paper, the Canadian natural resources and Canadian proximity to the U S market seemed to guarantee that Canada would always enjoy one

of the world’s highest living standards.”

Zsigmond et al (1978) find that there has been a strong negative correlation between years of school and unemployment: the higher the level of education, the lower the probability of unemployment They explain this relationship by using another notion:

relative “employability” according to education, i.e, the rate of increase of”

unemployment in each educational group relative to the increase for the labour force as a whole Using data between 1967 and 1977, they find that unemployment among those with secondary school grew more quickly than overall unemployment in the observed years This shows that the relative “employability” for high school graduates declined Meanwhile, this relative “employability” shows that the situation for individuals with higher education did not change, even though individuals with higher education became a

larger proportion of the total labour force.

Handa and Slolnik (1972) in their study Empirical Analysis of the Demand for

Education in Canada observe that formal education has become the most important pre-

requisite for employment in different occupations that has emerged in the second half of

the twentieth century They argue that the expansion of higher education during the

1960’s in Canada reflected the phenomenon that more students realized that with social development the economy needed more educated manpower Thus the students made adjustment accordingly and had more education Thus the authors conclude that from the perspectives of social development only those with more education will be relatively more employable

Freeman and Needels (1993) compare Canada and the United States and find that

in Canada education differentials between university-educated and high school-educated workers increased very modestly for both men and women over the same period

Between 1979 and 1987 the differential increased by 0.16 log points for 25-64-year-old Americans women compared to 0.04 points for Canadian women Among 25-34-year-

olds the increase for Canadian was 0.04 for men and for women versus an increase for Americans of 0.21 (men) and 0.10 for (women)

Vaillancourt (1986) computes the future earnings of males aged 18-year-old in

1981 from five Canadian regions, and faced with the choice of either attending university

or working His regression shows that university education has a private rate of return of

All these studies, differing in focus, design, sampling, and measurement, address

the relationship between schooling and future earnings and the responsiveness of demand for higher education to labour market situations The above lengthy literature survey is helpful to theoretically justify the topic of the thesis and the selection of the core variables in the study

The human capital theory reviewed previously provides a theoretical foundation for this thesis The theory suggests that additional years of schooling increase the lifetime income stream, reduce the possibility of being unemployed, and thus, provide a higher standard of living This is one of the major incentives for individuals to decide to

7 Rates of return by level of schooling are calculated relative to the next lowest level, e.g., the return to

secondary (incomplete) is relative to elementary, and the return to a Master’s degree is relative to a

Bachelor’s degree

continue to study at university In other words, utility maximization makes individual decide to receive additional education if they expect to be better off by doing so, either because more education can increase life-time earnings or decrease the possibility of unemployment, other things being equal “Other things” refer to the price of higher education (costs of higher education) and current family/personal income (affordability) Given this framework, Chapter 3 will discuss the selection of the data.

CHAPTER Ill DATA SELECTION AND DESCRIPTION

3.1 Selection of Dependent Variables

As stated previously, this thesis tests the two main hypotheses that the demand for higher education in Canada during the period from 1976 to 1995 is responsive to labour market movements and to wage differences between university graduates and high

school graduates At the same time, the thesis also tests the hypothesis that in Canada in

the same period the demand for higher education is responsive to current family/personal income and to university tuition fees

Which data will indicate demand for higher education? Campbell and Siegel (1967) note that university enrollment data provide the most obvious source of information on demand for higher education: the higher the demand for higher education,

the more people will be enrolled in universities In their study, they use aggregate demand

enrollment data to analyze the demand for higher education in the United States from

1919 — 1964, According to their point of view that university enrollment is an ideal indicator for demand for higher education

For this study, there are two candidates for the dependent variables One is the

growth rate of university enrollment and the other is the percentage of youth aged 19 to

18

24 years® enrolled in universities Campbell and Siegel also note that it is customary to express enrollment as a ratio of some relevant population group in order to measure the intensity of demand for higher education within the relevant group For the purpose of

their study, they pick up the “eligible college age population’” The focus of this study is

on youth and it is a fact that the general age range for youth to study in universities is

between 19 to 24 years At the same time, the only available data of enrollment as a ratio

of population group in Canada are for youth aged 19 to 24 Considering all the above factors and following Campbell and Siegel, the percentage of 19 to 24 years old enrolled

in universities full-time will be used as the dependent variable of this study

The students enrolled in universities can be divided into two groups according to

the hours they attend school: full-time students and part-time students Generally speaking, the majority of full-time students do not participate in the labour force during their academic terms although they may have summer employment As for part-time university students, many of them may still be in the labour force while enrolled in universities Some of them are employed full-time, some employed part-time, and some may be unemployed In order to avoid the double calculation of those both enrolled in universities and unemployed in the labour force, only full-time students enrolled in

high education of any sort Neither is it possible for people who are institutionalized, immobilized for

reasons of health, or who are member of the armed forces to go college, even they possess high school diplomas.

3.2 Selection of Independent Variables

The selection of independent variables is also pivotal to the study There are many factors that affect the demand for higher education in Canada measured by the percentage

of youth aged 19 — 24 years old enrolled in universities This section explains the reasons for the selection of these independent variables, in relation to the key hypotheses of the study

3.2.1 Unemployment rate

One of the two main goals of this study is to test the responsiveness of university

enroliment to labour market conditions The unemployment rate is conventionally used as

a proxy for labour market conditions

'© Equals full-time equivalent aged 19-24 divided by Canada’s population aged 19-24 Original source:

Special tabulation based on the University Students Information System from the Center for Education Statistics.

As illustrated previously, human capital theory suggests that more education

generates more lifetime income (the expected return from educations) That is one of the

main motivations for individuals to continue to pursue education in universities Human

capital theory views education as a productive input, whose marginal contribution can be roughly measured by wage differentials between more and less educated people The individual will maximize net wealth by equating the marginal cost of schooling to the

marginal returns It is generally agreed that the expected return fromm education increases

with the years of schooling, although at a diminishing rate Thus, the expected return is the focus of human capital theory

Some factors will affect the expected returns" One of the most important factors

is the expected stream of future earnings The expected stream of fumture earnings can be subdivided into (a) expectations about the probability of enmployment and (b)

expectations about the level of earnings when employed In labousr surplus situations,

with little wage flexibility, the most important element in influencing the expected rate of return may turn out to be the expected probability of employment [Handa and Slolnik, 1972] Therefore, expected income becomes a function of the probability of unemployment Thus unemployment is also a key to expected income Hence, in order to

test the hypothesis that university enrollment is responsive to labourr market conditions,

!! The expected return is affected by the following principal factors: (1) the expected probability of

completing higher education; (2) the expected duration of working life, taking account of death and

withdrawal from the labour force; (3) the expected costs of acquiring the educations; and (4) the expected

stream of future earnings, which involves expectations about the future demand for, and supply of, the skill

in question.

Source: CANSIM database The series for unemployment rate forl5-year-old and over is

D980745, the series for age 15 — 24-year-old is D980746

In Canada, unemployment incidence is unevenly distributed among different age groups More young people are unemployed than adults (Figure 3.1) As previously

noted, some studies argue that higher education reduces the probability of being unemployed, i.e., people continue to their higher education to reduce the probability of unemployment and hence to increase expected income Using the unemployment rate difference between high school graduates and university graduates, the study will check whether university enrollment increases with an increase in this unemployment rate difference

The study also includes the unemployment rate for high school graduates This unemployment rate is a signal for high school graduates If it is higher, it signals there are

no more jobs available for the high school graduates, which at the same time implies a lower opportunity cost to enter university

It is important at this stage to note that there are other channels through which the

unemployment rate may influence university enrollment Mattila (1982) argues that business cycles may strengthen the effect on labour market movements on university enrollment, but the direction of the effect is not clear He notes that there are two kinds of effects One is a “discouraged worker” effect, which increases enrollment during a recession In a recession, if youth are unable to get jobs, some of them may decide that it

is a good time to return to school The second one is an “added worker” effect, which will

also reduce enrollments during the recession The “Added worker” effect implies that when a parent is unemployed, the son or daughter may not be able to enroll in university

24

Perhaps over-all unemployment should have larger impact on university enrollment However, the “added worker effect” is not a focus of this study

In summing up, the selected variables employed in this study are (1) the

differential in unemployment rates by educational attainment and (2) the unemployment

level for high school graduates as one measure of opportunity cost

Since this study makes a comparison between university graduates and high school graduates, unemployment rates by educational attainment are the key data in this study The data are obtained from Statistics Canada’s Labour Force Annual Average

(Cat 71-220-XPB)

It is necessary to point out that there were some changes in the definition of “high

school education” From 1976 to 1983, high school education included persons who had either completed their secondary education or had at least some secondary education, but did not have any post-secondary education; the 1984 — 89 figures included persons who had 9 — 13 years education From 1990 on, the figures only include those who graduate from secondary schools The inconsistency stems from the changes in the definition content will be discussed in more detail in the next section

The unemployment rate differential between high school graduates and university graduates” is computed according to unemployment rates by educational attainment

!? Tt equals to the unemployment rate for higher school graduates minus the rate for university graduates

3.2.2 Wage differentials

Another key objective of the thesis is to test the hypothesis that the demand for higher education in Canada is affected by the wage differential between university graduates and high school graduates The wage differential between university graduates and high school graduates is important since wage differentials represent the direct pecuniary benefit of education Therefore the wage differential between the two different

education levels is a key independent variable in the study

As noted earlier, there are wage differentials between the highly educated and the less educated and wage level increases with additional years of schooling (though at a diminishing rate) In addition, it is suggested that the wage discrepancy for the less educated decreases with an increase in work experience Therefore, different age groups

have different wage differentials The wage differential between university graduates and

high school graduates for young people is a “current perspective” factor that affects youth’s decision about whether to continue to higher education, while the wage

differential between university graduates and high school graduates for adults is a “future

perspective” factor that affects youth’s decision-making Hence some young people prefer to enter university after completing high school to improve the probability of being employed and have higher earnings, while others choose to participate in the labour force

as soon as they graduate from high school in a hope of bridging the wage gap between

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themselves and those with a higher education level through accumulating more work experience

Therefore, two groups of wage differentials will be used in the study: 1) the wage

differential between university graduates and high school graduates for younger people;

and 2) the wage differential between university graduates and high school graduates for adults This sensitivity analysis will show whether the different wage differentials will have the same impact on individuals’ decision making for entering university

Since most university graduates begin to have job earnings around the age of 25,

we first consider the wage differentials between university and high school graduates for those aged between 25 and 34 The other group is the wage differentials for those aged 25

— 54

Since no published estimates of wages by education levels are available, the

wages by education levels used in this study were retrieved from the Survey of Consumer Finance microdata file The microdata were used to obtain a time series of average nominal wages for 25—34—year—olds" for the period from 1976 to 1995 The real wages

are obtained by deflating the nominal wages'* Then real wage differentials were

constructed by using the real wages earned by university graduates minus the real wages earned by high school graduates The same procedure is followed to estimate average

education premiums for the larger sample for the 25 to 54 year olds

3 «Wages” are actually annual earnings (full-time wages and salaries, and self-employment earnings) for all 25 — 34 year olds

_As well, the level of wages currently available to those with only a high school education is included to capture the “opportunity cost” of enrolling in university This

variable is also constructed using the Survey of Consumer Finance microdata

3.2.3 Disposable personal income

In demand theory, demand for goods is assumed to be determined by two

economic factors: income, and prices, given preferences.'* It is assumed that these two factors are independent, in the sense that a change in one or more of them does not cause changes in the others

Education is a product of a special kind Demand for education (or more accurately demand for higher education in this study) should thus be positively related to current family/personal income (affordability).'° With an increase in family/personal income, going to universities becomes more affordable Although personal income is not

the only financial resource to support study in universities, it is a main resource for the

majority of university students So it is reasonable that income be used as one of the explanatory variables

In Canada, the expenses of higher education, such as university tuition fees and

some out-pocket-expenses, are deductible for income tax purposes, hence this study will

!4 The real wage differential is computed from the nominal wage differential by dividing the nominal wage

differential by CPI and multiplying by 100 (1986=100)

'S Preferences are difficult to measure, especially for a “special product” like education Thus preferences

are taken as given.

use personal incomes (before tax) instead of personal disposable incomes Real personal

incomes" are retrieved from CANSIM series D44953

3.2.4 Private costs of higher education

The probability of being employed and having a higher lifetime income stream are the main incentives for individuals to pursue study at university But higher education costs, such as university tuition fees and foregone earnings, restrict individuals’ demand for higher education Therefore, higher education costs are included in the regressions as

a factor that affects individuals’ decision about whether to continue studying at university

There are two kinds of costs associated with higher education: public costs and private costs The public costs are the costs borne by the economy (or the whole society) The private costs are the costs borne privately by the individual Vaillancourt (1995)

calculates that in Canada the total costs of a given amount of education is significantly higher than its private costs, owing to public subsidization Vaillancourt’s calculation

shows that the amount of private costs borne by the individual increases with the amount

of education: from $737 for college, to $1,994 — $2,064 for undergraduate studies for

different fields, and to $ 2,064 for university graduates studies [Vaillancourt, 1995, p 544,

‘6 Actually an individual’s capability also plays a role in the demand for education, especially for higher education Since personal capability is difficult to measure, this study assumes a homogenous capability of all individuals

'7 Real personal income equals nominal personal income divided by consumer price index (CANSIM series

number E305030, 1986 =100) and multiplied by 100.

Table 3] Certainly, individuals will not care about the public cost They only care about the private costs since this is the cost borne by themselves if they decide to pursue higher education Hence in this study only private cost will be taken into account

As analyzed earlier, increased years of schooling are associated with increases in lifetime income streams This is one of the main incentives for youth to continue a university education For an individual, it is assumed that the decision about going to university is very much a rational decision; that is, it is made based on a careful cost- benefit analysis Only when the present value of benefits exceeds the present value of

costs, will an individual decide to continue his/her higher education If private costs of

higher education increase, enrollment in university is expected to fall Hence, private

costs are an important variable in deciding university enrollment

Private costs can be broken into two components: tuition fees and non-fee costs Tuition fees are relatively straightforward to calculate Non-fee costs are more complicated They mainly include foregone earnings and out-of-pocket expenses Foregone earnings are the real opportunity cost of entering universities Many out-of- pocket expenses will occur no matter whether you enter university or not.'* Therefore out- of-pocket expenses can be excluded from the study

Foregone earnings are the expected incomes given the probability of being unemployed (Pinemployea) for young people aged 15 — 24, theoretically computed aS Ergegone

= Prnemployed X O + (1 — Punemptoyea) X Earnings The calculation of foregone earnings is much

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more difficult in practice It is generally argued that foregone earnings constitute a big percentage of total private costs of studying at university In Canada, the estimated

foregone earnings account for more than two thirds of the total private costs for

undergraduate degrees [Vaillancourt, 1986].'° But there are no consistent statistics on foregone earnings of studying at university According to the above equation, the study will use the unemployment rate for high school graduates” and the wage for high school graduates aged 25 — 34 as the combination of opportunity costs of continuing higher education

Therefore, both out-of-pocket cost and foregone earnings — the non-tuition-fee costs for higher education — are omitted here and only university tuition fees are used as a proxy of higher education costs The university tuition fee price series real growth rates

(%)*, is the data used here, which is from Education Quarterly Review, 1997 (Cat no 81

— 003 — XPB)

'8 The out-of-pocket expenses for university students are slightly different from the ones occurred to non- university students since the students have to expend money on textbooks and other study-related expenses '® Tn Francois Vaillancourt’s study [p 451, Table 1] conducted in 1986, he assumes that the foregone

earnings are two-thirds of the net (of income taxes) earnings of men without a university degree discounted

at 3% and summed over 3 or 4 years,

*° The ideal unemployment rate used to calculate opportunity costs is the unemployment rate for high school graduates aged 15 — 19 Since this data is not available, the study will use the unemployment rate for high school graduates as one of the components of opportunity costs of going to university

*! The tuition fee price series and its growth rate are adjusted for inflation Source: Education in Canada,

Statistics Canada, Cat no 81-229.