The Effect of the Introduction and Subsequent Changes to HECS on Higher Education Applications

Higher Education Division
Department of Employment, Education, Training and Youth Affairs

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In 1996 the Government announced a number of changes to the HECS arrangements. These included a lowering of the income threshold beyond which HECS would be payable, an increase in the contribution under HECS and the introduction of a differential contribution according to discipline studied based on the cost of delivery of the education and the earning potential of graduates.

This paper addresses the issue of whether these changes affected the demand or interest in undertaking higher education studies. The framework developed draws on human capital theory which views education as an investment where expenditures of time and funds are undertaken in the prospect of reaping future vocational benefits. Various factors such as HECS which affect the cost or return from undertaking education may influence the level of interest in undertaking higher education.

The analysis investigated the changes in the number of higher education applications lodged through the State Admission Centres over the past decade. It was found that the recent changes to the HECS arrangements did not appear to affect the level of interest in undertaking higher education among school leavers but there may have been an effect on other mature age applicants. This conclusion is tentative, however, as there may have been a shift in the method of application of mature age applicants away from the State Admission Centres and directly to institutions which could not be addressed in this analysis. Data was acquired directly from higher education institutions to investigate the impact the introduction of differential HECS may have had on the choices of disciplines of applicants. It was found that while discipline choice varied considerably there was no relationship between those variations and the HECS Band within which the discipline was placed.

The author of this paper was Les Andrews with helpful comments provided by
Dr Tom Karmel.

Liz Tchacos
Higher Education Coordination Branch
Higher Education Group
Department of Education, Science and Training
Location Code: 121
GPO Box 9880
CANBERRA ACT 2601

Potential students choose to undertake post-compulsory education and training by selecting the best personal alternative out of the available set of educational possibilities, employment and other options, taking into account the cost and time constraints they may face. Since this choice involves comparing the benefits and costs among the various alternatives, the decisions will be influenced by the expectations and views of the individuals, their families and peers.

The approach taken in this paper employs a framework developed from human capital theory. Education is viewed in part as an investment in human capital whereby expenditures of money and time are made to acquire education or training which provides future vocational benefits including increased income. The profitability or rate of return on that investment is a measure of the expected future benefits generated by that education or training compared to the cost of acquiring that education. It is assumed, that as with any investment, the greater the expected rate of return the more willing individuals will be to invest in, or in this case undertake, education or training.

The likely factors affecting the profitability of higher education and therefore the level of demand for higher education are addressed in this paper. One of these factors is the introduction of the Higher Education Contribution Scheme (HECS) in 1989 and the recent changes to those arrangements which have changed the level of costs and the benefits from participating in higher education. This paper attempts to ascertain whether these changes have influenced individuals’ decisions to undertake higher education studies and the types of disciplines they wish to study.

The first section of this paper presents a description of the benefits accruing to holders of higher education qualifications. These benefits relate to the labour market advantages enjoyed by graduates. Non-financial benefits such as the acquisition of knowledge on matters of interest to the individual and the development of creative or analytical abilities are acknowledged but not considered in this paper.

The second section provides an overview of changes in enrolments over the last decade and describes the policy developments associated with the introduction of HECS.

The third section analyses the factors, including HECS, which may affect the demand for higher education. In 1997, 60 per cent of the 225,000 applicants to undergraduate courses in higher education institutions came directly from their final year of school or within one year of completing Year 12. The remainder consisted of mature age students who may have undertaken other studies in the vocational education and training sector or already possess a higher education qualification and are returning to undertake another degree course. Others may have left school and have been working and have decided to undertake studies at a higher education institution. The two groups have been analysed separately as the factors impinging on their decisions to apply to undertake higher education studies may differ.

The recent changes to HECS include the introduction of a differential contribution based on the cost of the discipline and the expected income of graduates according to their discipline. The effects of the introduction of differential HECS on students’ choice of disciplines are investigated in the fourth section. The analysis is summarised and concluded in the final section.

Higher education provides a considerable array of benefits to individuals. In addition to the direct benefits of the acquisition of knowledge, the monetary benefits of continuing education past the post-compulsory years are substantial. Higher education graduates have a large and persistent labour market advantage over people with post-compulsory vocational education and training and particularly those with no post-compulsory education.

In 1996, as Table 1 shows, the unemployment rate among Bachelor degree holders was 5.2 per cent compared to 10 per cent for those who completed high school and 11.3 per cent for those who had not completed secondary school. Moreover, degree holders if unemployed had been unemployed for an average of 37.5 weeks compared with 42 weeks for those who completed high school and 59.6 weeks for those persons who did not complete secondary school.

Source: ABS, ‘Transition from Education to Work’, Cat. No. 6227.0, May 1996

Figure 1 indicates the number of people applying to undertake a higher education course. From 1985 to 1997, the number of total applicants for higher education undergraduate courses in Australia increased from 138,397 to around 222,300, an increase of 61 per cent. Over the same period, the number of ‘Year 12 applicants’ (that is, school leavers who completed their final year of secondary education in the two years prior their application), had a faster growth rate (74 per cent) than the number of ‘mature age applicants’ (59 per cent).

All of this growth occurred between 1985 and 1993. The number of Year 12 applicants has generally fallen since then while the number of mature age applicants reached a plateau until this year when it also declined. However, it is noteworthy that the number of applicants in 1997 is estimated to be close to the level of 1992 which remains a historically high level. That is, the fall in the number of applicants does not represent a substantial unwinding of the large increase in the number of applicants that occurred during the latter half of the 1980s. This provides evidence that long term changes have occurred in attitudes towards higher education participation.

It was recognised back in 1987 in Higher Education: A Policy Discussion Paper (Dawkins 1987) that this rapid growth in the level of participation would be unable to be solely funded by the Commonwealth Government given constraints on public expenditure. It was also noted that the (then) current system was not equitable in that the direct beneficiaries of higher education, that is graduates, contributed very little directly to the costs of its provision. The funding system consisted of a Higher Education Administration Charge (HEAC) of $250 per student per year as a contribution towards the institutions’ administrative costs. The Australian taxpayers most of whom have never participated in higher education carried the burden of financing the system.

Sources:	Australian Vice-Chancellors’ Committee 1987–1990, Unmet Undergraduate Student Demand in Universities and Colleges of Advanced Education, Canberra.
	Australian Vice-Chancellors’ Committee 1991, Unmet Undergraduate Student Demand in Higher Education Institutions, Canberra.
	Australian Vice-Chancellors’ Committee 1992–1996, Survey of Applicants for Undergraduate Higher Education Courses, Canberra.

The data for 1997 is based on information obtained directly from University Admission Centres and spliced with earlier data.

Key:	A—Introduction of the Higher Education Administration Charge
	B—Introduction of the Higher Education Contribution Scheme (HECS)
	C—Introduction of higher repayment rates for HECS
	D—Expanded seven step repayment schedule
	E—Introduction of differential HECS and lowering of income threshold

The Committee on Higher Education Funding (Wran Committee 1988) was subsequently formed to further develop the options for additional funds. This included consideration of a number of options including voucher schemes, tuition fees and loans schemes. The Committee recommended the introduction of a higher education contribution charge which largely had the elements of the current Higher Education Contribution Scheme (HECS). That is, the Committee proposed a deferrable contribution to be recouped through the taxation system with the amount of the contribution based upon the broad cost of the discipline undertaken (there were to be three cost categories).

In the 1989 Budget HECS was introduced along the lines recommended by the Wran Committee but without a differential cost structure based on discipline. Over the subsequent five years there were relatively minor changes made to HECS such as lowering of income thresholds and changes to the repayment rates. In 1996 the Government argued that the appropriate balance between public and private contributions to the cost of higher education was difficult to precisely establish but the private benefits were clearly greater than that implied by the HECS contribution which represented about 23 per cent of the average course cost. Given HECS was a flat amount and the cost associated with disciplines varied considerably, then HECS represented a widely varying proportion of course costs. This ranged widely from 36 per cent for an arts course to 13 per cent for medicine.

In 1996 HECS was increased, the income threshold which would attract repayments was lowered and a differential HECS contribution introduced. Disciplines were placed into three HECS bands based upon the cost of delivering the course and on the average earning potential of graduates from those disciplines. Disciplines such as law, medicine and veterinary science which are high earning and/or high cost have been placed in HECS Band 3 with a HECS contribution of $5,500. HECS Band 2 disciplines which attract a $4,700 HECS contribution include science, engineering, agriculture, architecture and business/economics. Disciplines such as arts, education and nursing are in HECS Band 1 with a $3,300 contribution. Disciplines such as nursing are high cost but have been placed in Band 1 because of their relatively low earning potential. Other characteristics of the HECS arrangements were retained. That is, HECS is deferrable and payable through the taxation system—no qualified student would be prevented from entering higher education because of an inability to pay at the time of enrolment. The timing of the major changes to HECS since its introduction are indicated in Figure 1.

Many previous attempts, Lewis and Vella (1985) and Chapman (1997), to analyse the demand for higher education have used student enrolments or commencements in higher education as the measures of demand or interest for higher education. The Higher Education Council (of the National Board of Employment, Education and Training reported on the operation of the HECS including its effects on the access to higher education (Higher Education Council 1989–1996). These approaches address the issue of access to higher education but do not take into account the supply constrained nature of higher education (that is, not every person who wishes to enrol in higher education is able to attend because of a shortfall in available places).

During the mid-1980s to mid-1990s the number of applicants who did not receive an offer of a place ranged from 40 to 90,000 (Australian Vice-Chancellors’ Committee 1987–1990; 1991; 1992–1996). These estimates are likely to be an upwardly biased estimate of the real level of unsatisfied demand as they are not adjusted for those students who have unduly restrictive course preferences, those who may reject an offer or those who may have applied in two or more states and are, therefore, subject to double counting. Nonetheless, they do indicate that the level of unsatisfied demand should not be ignored—the number of applicants who do not receive an offer has ranged from 23 to 40 per cent of all applicants over the last decade. Even with the various adjustments to this raw figure noted above, it would remain at non-trivial levels subject to wide variation from year to year. Changes in the level of unsatisfied demand can result from variations in the level of publicly funded places in institutions and the admission policies of institutions as well as changes in the number of applications for higher education.

The level of applications has been chosen as a measure of demand or interest for higher education for this paper although it should be noted that estimates of applications are also subject to some measurement error. The estimates of applications used in this paper are derived from data of applications made through the various State Tertiary Admission Centres. This data can be affected by changes in university admission system procedures and in particular changes in the proportion of applications that are made directly to institutions, which are not included in the Admission Centres’ data bases. Mature age students may be increasingly applying directly to universities which will have the effect of depressing the measured number of applications. Nonetheless, given the large and varying number of applicants that are unable to enrol in higher education institutions, there is added information to be gained from modelling demand in terms of applications and not commencements or enrolments.

Many factors impinge upon an individual’s decision to continue their studies past the compulsory years of schooling to complete Year 12 and to apply to enter higher education. These will include the range of other education and training options available to them, the possibility of employment and the level of wages associated with employment and the costs involved in undertaking further education and training. The approach taken in this analysis is to examine the influences on each of the decision points affecting the final decision to apply to enter a higher education course.

The number of Year 12 applicants to higher education is dependent upon a several factors. First, there is the size of the student population in Year 12 from which applicants are drawn. The Year 12 student population is determined by the population of 16 and 17 year olds, and the Year 12 apparent retention rate. Changes in the size of the population aged 16 to 17 years over the past decade have been relatively small and have had only a minor effect on the potential numbers of students applying to enter higher education. The second factor, the Year 12 apparent retention rate, has had a major influence on setting the size of the feeder group to higher education and will be discussed in some detail.

As Figure 2 below shows the apparent Year 12 retention rate increased strongly over the decade to 1992 and has since fallen back. This increase in apparent retention rates was associated with large shifts in the full-time labour market activity of teenagers. This is to be expected since for teenagers there is a choice after completing compulsory schooling between continuing to Year 12 or seeking full-time work. In 1978, 41 per cent of the teenage population worked full-time whereas in 1996 some 17 per cent were employed full-time. These changes were also in part associated with an increase in the proportion of teenagers working part-time, from 10 to 29 per cent over the same period. As teenagers have increasingly stayed on at school it appears that employment is still seen as an important activity with 30 per cent of school students engaged in part-time work.

The relationship between retention and the labour market was tested more rigorously using multi-variate analysis. This statistical technique allows the effects of various factors to be isolated and identified. Various specifications describing the relationship between the level of the apparent retention rate and the changes in student attitudes to remaining at school and the labour market were tested and are at Table A1 in the Appendix.

The influences of labour market conditions, as measured by the proportion of teenagers in full-time employment, show that an increase in the number of teenagers in full-time employment is associated with a fall in the apparent retention rate. It is possible to test for the direction of causation in the association between the labour market and retention by employing a Grainger Causality test (see Appendix) which determines whether changes in full-time employment precede or lag changes in the apparent retention rate. This test found that the fall in full-time employment opportunities for teenagers contributed to the rise in the number of students remaining until Year 12.

This relationship between school and full-time employment is consistent with many other studies such as Gregory and Duncan (1980) where a ‘discouraged worker effect’ was found to be operating with a deterioration in full-time employment opportunities leading young people to leave, or not enter, the labour market. While Gregory and Duncan did not examine whether such discouraged young people were remaining at school, Merrilees (1981) found that young teenagers in particular remained at school because of poor full-time employment prospects.

The proportion of teenagers in part-time employment was not found to affect significantly the Year 12 retention rate. This is consistent with Larum and Beggs (1989) who found that while full-time employment had a significant effect on school participation, part-time employment did not. They indicated that a possible explanation for this is that while the growth in part-time employment opportunities may entice some young people to leave school, for others it may act as an educational subsidy and make remaining at school more attractive (that is reduce some of the income loss from remaining at school).

Sources:	Australian Bureau of Statistics 1978–1996, The Labour Force, Cat. No. 6203.0
	Australian Bureau of Statistics 1992, 1996, Schools Australia, Cat. No. 4221.0
	Department of Employment, Education and Training 1987, Schooling in Australia: Statistical Profile No. 1.

Government income support—Secondary Allowance Scheme(SAS) and subsequently secondary AUSTUDY—also reduces the income loss from remaining at school for some students. This has not been specifically addressed in this paper because of the difficulty of developing an indicator which fully captures the effects of income support. Previous attempts at analysing the effect of income support are inconclusive. Larum and Beggs (1989) modelled income support as a product of the maximum annual grant and the proportion of school students receiving income support. They found a positive relationship between income support and post-compulsory school participation. A later and more detailed study by Chapman (1992) found that while the real value of income support and student coverage increased over the period 1980 to 1990 when retention rates were increasing, it was difficult to disentangle the effects of SAS/secondary AUSTUDY from the other changes happening at the same time. These included a major effort by the Commonwealth Government to publicise the value of remaining at school and a widening of the school curriculum to make it more attractive to students who were not continuing to higher education. Chapman showed that there was no unambiguous evidence to suggest that SAS/secondary AUSTUDY had a substantial impact on school participation over the decade to 1990.

The introduction of HECS in 1989 was analysed in this paper to ascertain whether school students who were remaining at school until Year 12 in order to undertake higher education studies were dissuaded from doing so by the introduction of HECS. The introduction of HECS was not found to have significantly affected apparent retention rates.

There was a general upward trend with apparent retention rates up to 1992 unaccounted for by labour market conditions and likely to be related to changing attitudes towards education. A lagged dependent variable was introduced to capture the effects of the gradually changing attitudes of young people towards remaining until Year 12. It is not possible to identify the main reasons for these changes in attitudes. As explained above, government policy through this period was strongly encouraging of increased school retention and there was a general increase in the minimum educational standards for entry to jobs. After 1992, however, apparent retention rates declined. This was not explained by the influence of labour market conditions or prior changes in the level of retention. A dummy variable was introduced into the equation specification at Table A1 to capture the effects of this reversal in apparent retention rates since 1992 but this does not explain the reversal. One possible explanation is that the fall in apparent retention rates has been as much apparent as real given their basis of calculation.

The apparent retention rates estimated by the Australian Bureau of Statistics (1992; 1996) is defined as the percentage of students of a cohort group who continued to Year 12 from the commencement of their secondary schooling. For example, Year 12 apparent retention rates are calculated as a the number of Year 12 students in year n as a proportion of the number of Year 7 students n-5 years before. Many factors, such as changes in the number of repeat students and the number of immigrants entering school between Years 8 and 12, will affect the apparent retention rate. The level of net immigration was tested in this paper and found to significantly affect apparent retention rates. The decline in the level of net immigration from the relatively high levels of the late 1980s could account for much of the decline in apparent retention rates.

Nonetheless, there may be other factors at work. Lamb (1996) has investigated possible reasons for the fall in retention. His report is useful in clarifying those factors that are unlikely to be major explanations for this shift in retention as well as identifying those factors that may be associated with the fall in retention. The growth in alternative vocational education and training options including improved school-industry links and integrated school/vocational education programs may be seen as producing the downturn in apparent retention rates. The evidence in support of this proposition is mixed, however.

While growth in initial vocational education courses has grown considerably, other evidence suggests that this growth has not occurred among early school leavers. Indeed, the TAFE participation rates for 16 and 17 year olds have generally been static during the 1990s. Similarly, increases in the number of apprenticeships cannot explain the overall decline in apparent retention rates. Apprenticeships grew steadily during the late 1980s when at the same time apparent retention rates also increased. The number of apprenticeships fell during the 1991 recession along with the decline in retention.

An alternative explanation is that young people have changed their views on the value of remaining at school. The strong expansion in the number of young people completing Year 12 during the 1980s may have reduced its economic value. Lamb also reported that Teese (1996) found that success at school has an influence on retention rates. That is, the decline in apparent retention rates was greater in regions and among groups where failure rates increased, suggesting that academic success at school is a strong influence on subsequent plans for education and training.

These findings support the conclusion that, while some of the increase in the apparent retention rate in the late 1980s was partly due to declining full-time employment opportunities for teenagers the major influence was a shift in attitudes towards education. Over the past half decade these attitudes appear to have in part reversed.

The second influence on the number of Year 12 applicants to higher education is the proportion of Year 12 students who decide to apply to undertake higher education studies. As Figure 3 below indicates this rate has fluctuated between 36 and 41 per cent over the period 1986 to 1997. This stability is surprising given the large variation in the apparent Year 12 retention rate over the period.

Sources:	Australian Bureau of Statistics, Schools Australia, Cat. No. 4221.0
	Australian Vice-Chancellors’ Committee 1987–1990, Unmet Undergraduate Student Demand in Universities and Colleges of Advanced Education, Canberra.
	Australian Vice-Chancellors’ Committee 1991, Unmet Undergraduate Student Demand in Higher Education Institutions, Canberra.
	Australian Vice-Chancellors’ Committee 1992–1996, Survey of Applicants for Undergraduate Higher Education Courses, Canberra.

The data for 1997 is based on information obtained directly from University Admission Centres and spliced with earlier data.

The application rate is likely to be influenced by a broad range of variables. These will include perceived changes in the costs and benefits of undertaking higher education, perceived likelihood of obtaining a place in an institution as well as alternative education and training options. The benefits of participating in higher education and obtaining a qualification have been discussed previously in this paper and will not be investigated further. The lifetime income of a person not participating in higher education can be represented by areas A and D in Figure 4 below and the additional benefits from participating in higher education can be represented by areas E and F. It is assumed that these additional lifetime benefits have not changed sufficiently over the last decade to affect potential students’ interest in undertaking a higher education course.

The costs of undertaking higher education include out-of-pocket expenses for books, additional living expenses, etc. and can be represented by area B with the opportunity cost associated with studying and not working represented by area A. That is, participation in higher education precludes obtaining income from employment, at least full-time employment. This opportunity cost is reduced for those students who receive income support through AUSTUDY, combine part-time work with education participation or obtain vacation employment. The effects of HECS can be represented in two ways—if HECS is paid up-front it is another out-of-pocket expense represented by area C but if it is deferred and repaid through the taxation system, these payments can be represented by subtracting area F from the additional benefit of higher education, areas E and F.

Other factors may influence the number of applications. The perceived likelihood of obtaining a place in a higher education institution may also affect the number of applications by discouraging some potential students when entry standards are rising. A proxy variable that can be used to capture this effect is the number of applicants who do not receive an offer as estimated each year by the Australian Vice-Chancellors’ Committee. Finally, other training options may be seen either as alternatives to higher education or as a complement to higher education courses.

The relationship between these factors and the proportion of Year 12 students applying to enter a higher education can be described as:

d APP12/d HECS <= 0	d APP12/d AUSTUDY >= 0
d APP12/d TAFEPOP = ?	d APP12/d U >= 0
d APP12/d RWJ <= 0	d APP12/d UD <= 0

The decision to apply to undertake higher education studies is binary in nature (that is, an individual decides whether or not to apply). For prospective students as a group the application rate will lie between 0 and 1. Accordingly, the values of dependent variable, the application rate, can be similarly constrained by the following logistic transformation:

The influence of the labour market on the application rate was found to be complicated. A deterioration of the labour market towards the end of Year 12 when students are deciding whether to apply for higher education courses increases the application rate. A deterioration in the labour market conditions in the previous year when students are in Year 11, however, reduces the application rate. This apparently contradictory effect can be explained by the changing composition of Year 12 students in response to labour market conditions. A worsening in job opportunities in Year 11 encourages students to continue to Year 12, which is consistent with the findings of the factors affecting Year 12 apparent retention rates described above. These students, however, do not all appear to be remaining until Year 12 with the intention of continuing their studies in higher education and thus they have a negative effect on the application rate.

An interesting finding was that an increase in the number of students in Year 12 has a positive effect on the Year 12 application rate. Inclusion of this variable reduces the statistical significance of the influence of the current state of the labour market for teenagers, as measured by the level of youth unemployment, suggesting collinearity between the variables. This was confirmed by regressing the level of youth unemployment against the size of the Year 12 student population (see equation at Table A2). This suggests a cohort effect operating on the level of unemployment of young people. The supply of young people to the labour market increases particularly strongly in years with relatively large numbers of students completing Year 12 which raises the number of unemployed teenagers looking for a full-time job. This in turn appears to increase the application rate to higher education institutions.

The youth unemployment variable discussed above represents the opportunity cost of attending further education given the probability of finding employment. An increase in youth unemployment reflects a reduced likelihood of obtaining employment, thereby decreasing the opportunity cost of further study. It does not account for changes in the opportunity cost arising from changes in the level of wages if employment is found. The level of real full-time junior wages was introduced to capture this effect. Increases in the real full-time junior wage were found to depress the number of applications. This is to be expected as an increase in junior wages raises the opportunity cost of undertaking higher education studies. It should be noted, however, that the level of real junior wages has generally fallen over the last decade and has tended to raise the level of applications.

Participation in the vocational education and training sector was found to have no significant effect on interest in higher education courses. This is consistent with the sectors serving different educational needs.

The difficulty of obtaining a place, measured by the number of applicants who did not receive an offer of a place in the year previous to the application year, had a positive effect on the application rate. This appears counter-intuitive as more students appear to apply as it becomes more difficult to obtain a place. The application rate, however, is a measure of the number of students who apply to enrol within two years of finishing school. What may be happening is that students who do not receive an offer when they first apply after finishing school reapply the following year.

The level of income support provided through tertiary AUSTUDY was not incorporated into the analysis. It is difficult to identify a variable which can reasonably capture the effects of tertiary AUSTUDY. The allowance is paid at varying rates dependent upon individual income if the student is assessed as being financially independent, and family income and assets if they are financially dependent. Eligibility for the allowance, in part or in full, has varied over time as the income and assets tests and definitions of student financial independence have changed. As a consequence it is not possible to analyse the influence of tertiary AUSTUDY on student applications even though it may be expected that it is an important form of income supplementation for many students. Chapman (1992) found that as tertiary AUSTUDY became less generous from the mid-1980s, both in terms of the real value of the grant and coverage of students, it was difficult to show that it had a discernible effect on education participation rates.

Recent changes to the HECS arrangements involved reducing the income threshold, raising the amount of HECS and introducing a differential HECS. It was not possible to analyse separately the effect of these changes on the level of applications. The overall effects of the recent changes to HECS was also analysed and found to have no effect on the application rate (see Table A2). The reasons for this lack of effect may be revealed by work undertaken by Chapman and Salvage (1997). They analysed the impact of the recent changes to the HECS arrangements on the financial rates of return to school leavers undertaking higher education. They found that the changes had not greatly decreased the high rates of return and were unlikely to have reduced the financial attractiveness of undertaking higher education.

Figure 5 describes the estimated number of Year 12 applicants over the past decade employing Model 1 at Table A2 in the Appendix. It illustrates that the introduction of HECS in 1989 has had a small effect on the number of Year 12 applicants—they are estimated to have fallen by 20,000 persons representing 14 per cent of applications. It is not possible to ascertain whether this represents a permanent reduction of interest in participating in higher education or a postponement of interest to later in life.

As Figure 5 shows, there appeared to have been a delayed effect associated with the introduction of HECS in 1989. While the application rate after 1990 is estimated to have decreased by approximately 6 percentage points because of the introduction of HECS—for example from 42 to 36 per cent in 1990—in 1989 the decline was estimated to be only 2 percentage points. The decline in 1989 represented about 3 per cent of those who did not apply to enrol in higher education institutions, although this would represent a slightly higher proportion of those who would be eligible to apply but choose not to apply. This percentage decline is similar to the estimates gained from a survey carried out by Robertson et al. (1990) in 1989 to investigate the effect of HECS. The survey was restricted to Victoria and Western Australia and found that 8 per cent of those Year 12 students eligible to apply but not applying gave HECS as a very important reason for not applying. An explanation for this small effect may be that students in Year 12 are largely committed to a course of action upon completing Year 12 and are reluctant to alter their plans.

A similar methodology to that used to analyse Year 12 applicants was employed to identify the influences on mature age applicants’ decisions to apply for higher education. The number of applications was expressed as a share of the 20–45 year old age group to control for demographic factors. This age group represents over 90 per cent of non-teenage higher education students. Similar variables to those described for modelling Year 12 applications were tested and are presented in Table A3 in the Appendix.

Improvements in the labour market, as measured by the relative level of employment compared to the population, have a dampening effect on applications. This is understandable as an improvement in employment opportunities effectively raises the cost of participating in higher education by increasing the opportunity cost of alternative labour market activities. There was also a slight upward trend in the application rate of mature age persons. The underlying factors affecting this trend are difficult to identify but may result from a change in attitudes towards the vocational benefits of higher education over the period, reinforced by the general realisation that industry is increasingly demanding more skilled workers. No relationship was found between participating in the vocational education and training sector and the number of mature age applicants, implying vocational education and training and higher education are supplying quite different consumers of educational services. Similarly, the level of unsatisfied demand does not appear to affect the number of applications from mature age students.

While the level of applications from this group does not appear to have been affected by the introduction of HECS in 1989, the analysis indicates that they may have been reduced due to the recent HECS changes. The number of applicants is tentatively estimated, employing Model 1 at Table A3, to have fallen by 10,000 persons or 10 per cent of mature age applicants due to the changes to HECS announced in 1997. This must be qualified in two ways. First as was noted above, the estimates of applications used in this paper are derived from data of applications made through the various State Tertiary Admissions Centres. The data is affected by changes in the share of applications that are made directly to institutions which are not included in the State Admission Centres’ data bases. Mature age students may be increasingly applying directly to institutions. This will have the effect of depressing the measured number of applications by this group. Secondly, as this is the first year following the changes to HECS in 1996, it is not possible to ascertain whether this fall in applications represents a permanent reduction in interest in participating in higher education or a deferral of interest to later years. Higher education services have the character of a service which can be postponed or delayed until conditions are more appropriate for the individual. Potential students may have decided to delay applying for courses in anticipation of further changes to the HECS arrangements in later years.

This finding is broadly supported by the Report of Ministerial Committee of Advice to Minister for Tertiary Education and Training (1997) which investigated the demand for tertiary studies in engineering and science in Victorian universities and found that HECS changes may have had an influence on the number of mature age applicants. They opined that as many mature age students combine study with part-time employment that are subjected immediately to HECS.

We now test whether the introduction of the differential HECS arrangements has influenced the level of applications by discipline. Late in 1996, universities were requested by the Department to provide information on the change in the number of applications by discipline. Some 20 institutions (out of 37 institutions) have provided information which can be used for modelling purposes.

In order to highlight the effect of differential HECS on the number of applications, the change in applications by discipline is compared to the overall change in applications of -4.4 per cent (see Table 2). For example, the number of applications in the education discipline had risen by 6 per cent relative to the change in applications overall. While it is not possible to check the accuracy of the limited detailed data, it is noteworthy that the overall change in applications obtained from all 37 universities in early 1997 (-3.4 per cent) is close to that derived from the 20 institutions that responded in detail late in 1996 (-4.4 per cent).

The placement of disciplines in the HECS Bands 2 and 3 has not apparently affected the number of applications for these disciplines. While science had experienced one of the greatest decline in applications of any discipline, engineering had a similar decline in the number of applications as that for all disciplines. Of the other HECS Band 2 disciplines, business/economics had a similar decline to that for all disciplines, while agriculture had a substantial increase in the number of applications. Moreover, placement of disciplines in the other Bands did not lead to consistent changes in the number of applications. The number of applicants in arts, placed in Band 1, fell by 7 per cent relative to overall applications, while those for law, placed in Band 3, increased by 6 per cent relative to the change overall.

(1) Based on those 20 institutions providing data.
(2) These are simple averages of institutional data.

The relationship between the HECS Band of a discipline and the change in the number of applications was tested more rigorously using multi-variate analysis.(see Table A4 in the Appendix).

It was found that while disciplines in Band 2 generally experienced a 1.5 per cent fall in applications greater than those in Band 1, this was not a statistically significant difference. Similarly, disciplines in Band 3 experienced a 6.9 per cent increase in applications compared to Band 1 but this was not a significant difference. This lack of significance arises from the great variability in the change in applications across disciplines and institutions. The model provided a very poor explanation of the changes in applications implying little evidence of any systematic pattern in the changes in applications according to the HECS Band in which the discipline was placed. This result is confirmed by The Report of Ministerial Committee of Advice to Minister for Tertiary Education and Training (1997) which similarly found no apparent relationship between changes in demand for courses in Victorian universities and the HECS Band within which they were placed. Factors other than the HECS Band of the discipline may be affecting interest in disciplines at the higher education level. For example, in the case of science there has been a long term decline in the proportion of the student population undertaking science courses at the post-compulsory secondary level.

The approach taken in this paper draws on human capital theory to produce testable propositions regarding the influences of various factors including HECS on the demand or interest to undertake higher education. That is, applications to higher education are viewed as the result of decisions that potential students make by weighing up the benefits and costs of higher education and choosing among a range of employment, education and training options. This decision can be affected by a number of factors which may influence the benefit-cost calculus. The introduction of HECS and subsequent changes to the arrangements can be expected to affect the perceived returns to undertaking higher education if potential students expect to earn in excess of the income thresholds at which HECS is payable.

The analysis in this paper addressed the issue of the extent to which this increase in the perceived cost of participating in higher education actually influenced potential students’ behaviour in applying for entry to higher education institutions. The changes to the HECS arrangements in 1996 do not appear to have significantly reduced the number of Year 12 applicants in 1997. The reason for this may lie in the small effect the HECS changes are likely to have made to the large returns to studying at the higher education level.

The number of mature age applicants may have been affected by the recent changes to HECS but it is too early to know whether this may be a permanent effect or a rescheduling of higher education plans. This conclusion is also tentative given the possibility that more mature age students may be applying directly to higher education institutions which will reduce the number of applications as measured in this paper. This will require further monitoring before definite trends can be discerned.

The introduction of a differential HECS charge based on discipline does not appear to have affected the level of applications by discipline. The level of applications by discipline varied widely between institutions unrelated to the discipline’s particular HECS Band.

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	*Higher Degree*	*Undergrad. Degree*	*Skilled Vocational*	*Basic Vocational*	*Completed High School*	*Did Not Complete High School*	*Total*
Unemployment Rate (%)	3.8	5.2	5.5	8.6	10.0	11.3	8.4
Duration of Unemployment (avg)	35.4	37.5	46.9	49.1	42.0	59.6	48.4

Discipline	Per cent Change⁽²⁾
Band 1:
Arts	-7
Education	+6
Health (excluding medicine)	+2
Band 2:
Architecture	-5
Business/Economics	-1
Science	-7
Engineering	-1
Agriculture	+13
Band 3:
Law	+6
Veterinary Science	+26
Medicine	0