Page 1 of 81

Setting tuition fees in English HEIs:

A framework of principles for guiding policy in “modern universities”, with particular reference

to Staffordshire University

Professor Geoff Pugh and Dr Ian Jackson, Staffordshire University Business School ∗

Final Report The new fees market is about to kick off, but is your university match fit? asks Mike Goldstein … Surely policymakers (and those vice-chancellors egging them on) did not anticipate the impending confusion in the sector. Institutions have been left holding the baby, making massively important strategic decisions on fee levels, bursaries, scholarships and service enhancements to a time-scale that allows only rudimentary market research.

Mike Goldstein (recently retired vice-chancellor of Coventry University and chairman of the education marketing company Heist), The Times Higher, 11 February 2005.

Acknowledgement This report was commissioned by Staffordshire University’s Recruitment Management Team (RMT). The authors are grateful for support and many helpful suggestions from RMT members as well as for permission and encouragement to share and debate the findings of this report more widely.

∗ Corresponding author: Prof. Geoff Pugh, Staffordshire University Business School, Leek Road, Stoke-on-Trent, ST4 2DF. Office: 01782-294092; g.t.pugh@staffs.ac.uk Home: 01924-384452; geoff@plainfigures.com Mobile: 0791 437 7545

Page 2 of 81

Table of Contents OUTLINE OF THE REPORT...........................................................................................................................3 COMMONLY USED ABBREVIATIONS........................................................................................................3 PART 1: SETTING TUITION FEES IN HE: LITERATURE REVIEW AND PRINCIPLES FOR GUIDING POLICY ..........................................................................................................................................4 EXECUTIVE SUMMARY: PRINCIPLES FOR PRICE SETTING ...............................................................5 SETTING TUITION FEES IN HE: LITERATURE REVIEW AND PRINCIPLES FOR GUIDING POLICY..........................................................................................................................................................13 1 INTRODUCTION.................................................................................................................................13 2 METHODOLOGY................................................................................................................................15 3 HIGHER EDUCATION AS AN ECONOMIC ACTIVITY: SOME DEFINING FEATURES ..........16

3.1 HEIS AS NOT-FOR-PROFIT ENTERPRISES ........................................................................... 16 3.2 PEER EFFECTS IN HE ....................................................................................................... 17 3.3 THE HIERARCHY OF HEIS ................................................................................................ 20

4 OPTIMAL FEES AND PRICE ELASTICITY OF DEMAND.............................................................29 4.1 AWARD WITH MARKET POWER......................................................................................... 29 4.2 AWARD WITH NO MARKET POWER ................................................................................... 30 4.3 AWARD WITH LIMITED MARKET POWER (I): MONOPOLISTIC COMPETITION ......................... 31 4.4 AWARD WITH LIMITED MARKET POWER (II): OLIGOPOLY .................................................. 35

5 OPTIMAL FEES AND THRESHOLD EFFECTS ..............................................................................39 5.1 ASSUMPTIONS................................................................................................................. 39 5.2 THE “STUDY THRESHOLD”............................................................................................... 40 5.3 SOME PRINCIPLES............................................................................................................ 41

6 FEE SUBSIDIES: IMPACT ON ENTRY RATES AND IMPACT ON COMPLETION RATES .......42 6.1 STUDENT ENROLMENT (I.E., PARTICIPATION) IN HE .......................................................... 42 6.2 STUDENT COMPLETION (RETENTION) ............................................................................... 46 6.3 STUDENT CHOICE OF HEI................................................................................................. 48

7 DO STUDENTS MAKE RATIONAL CHOICES? ..............................................................................49 PART 2: APPLICATIONS .............................................................................................................................53 1. POSTGRADUATE AWARDS..............................................................................................................54

TAUGHT AWARDS ......................................................................................................................... 54 RESEARCH AWARDS...................................................................................................................... 55

2. A NOTE ON EXTERNAL SPONSORS ...............................................................................................56 3. HND AND FOUNDATION...................................................................................................................57

HND............................................................................................................................................ 57 FOUNDATION................................................................................................................................ 58

4. PLACEMENTS: ANOTHER “HOLE IN THE FENCE”? ..................................................................59 5. PART-TIME .........................................................................................................................................60 6. A NOTE ON PRICE ELASTICITY .....................................................................................................61 7. INTERNATIONAL FEES ....................................................................................................................63 8. EU FEES AND BURSARIES................................................................................................................64 9. SETTING FEES AT AWARD LEVEL ................................................................................................65

COMPROMISE BETWEEN UNIFORMITY AND FRAGMENTATION .......................................................... 65 KNOW YOUR COSTS! ..................................................................................................................... 65

PART 3: AN APPROACH TO SETTING FEES AT THE AWARD LEVEL ..............................................67 A FEE-SETTING QUESTIONNAIRE: GUIDANCE TOOL FOR AWARD TUTORS...............................74

Page 3 of 81

Outline of the Report

This Report aims to inform fee setting at Staffordshire University by deriving principles from recent research literature and by developing a theoretically informed and practical approach to fee setting at the award level. Part 1 surveys the literature and set outs principles for price setting and recruitment strategy in Higher Education. The Executive Summary sets out principles with a minimum of supporting argument. The following Literature Review sets out the theory, evidence and supporting references in detail. Part 2 provides Applications, which are informed both by the research literature and by interviews with Faculty Recruitment Managers in autumn 2006. These applications mainly highlight issues that are particular to different types of award (postgraduate, HND, Foundation) modes of delivery (part-time, distance) and/or market (local, international). In addition, we discuss issues related to external sponsorship and placements. Part 3 sets out an Approach to setting award-specific fees. This approach informs a Questionnaire that enables an award-specific fee to be set by making award-specific adjustments to a standard fee. For readers requiring results and applications rather than detailed supporting argument, we recommend moving directly from the Executive Summary to the Questionnaire in Part 3.

Commonly used abbreviations

GPA: Grade Point Average HE: Higher Education HEI: Higher Education Institution SAT: Scholastic Aptitude Test (USA)

Page 4 of 81

Part 1: Setting tuition fees in HE: literature review and principles for guiding policy

Page 5 of 81

Executive Summary: principles for price setting The recent introduction of a new fee structure together with the likely removal of the £3,000 ceiling requires clarity on pricing for our whole product portfolio. This Report derives a framework of principles for pricing policy from the latest theoretical and empirical research. In this Summary, we set out these principles and their implications for Staffordshire University’s pricing policy under the following headings:

1. Unique features of HE as a business; 2. Peer effects; 3. Hierarchy in English HE and modes of competition; 4. Implications of removing the fee cap (I): competitive tendencies for low-status

HEIs; 5. Implications of removing the fee cap (II): non-price opportunities for low-

status HEIs; 6. Market power, pricing policy and non-price competition; 7. The student’s participation decision and pricing policy; 8. Pricing policy in HE: empirical evidence; and 9. Do students make rational choices? Some implications for HEIs.

In each case, there are cross-references to the full Report, which presents each argument in detail. Throughout this Summary, the main findings and policy implications are italicised. 1. Unique features of HE as a business Considered as a business, higher education (HE) has a unique relationship with its customers that make pricing policy unusually complex. This relationship arises from a combination of features, each one of which makes HE unusual (Section 3). First, higher education institutions (HEIs) have multiple stakeholders and aims. This can help us to understand why, in contrast to normal business firms, HEIs typically subsidise their customers. The not-for-profit status of most HEIs means that profits are not distributed to owners; it does not mean that HEIs are exempt from the efficiency criterion of profit maximisation. Nonetheless, because in HE there are multiple stakeholders, pricing policies are not dictated solely by profit maximisation but are also influenced by a variety of competing aims, including academic excellence and, in particular, equity considerations such as widening participation or community development. Accordingly, in HE we should not expect to understand – or to be able to implement – pricing policy from the single perspective of profit maximisation. Secondly, HE recognises that students educate themselves and each other. Accordingly, HE uses its customers as inputs into production. Because HE uses a “customer-input technology”, student peer group effects have an all pervading importance in the economics of HE. In particular, peer effects have subtle yet important implications for both pricing policy and recruitment strategy generally.

Page 6 of 81

2. Peer effects The quality of the education any student gets depends in good measure on the quality of that student’s peers (Section 3.2). This is consistent with two common practices in HE:

1. granting scholarships to the more able students which, in effect, is a payment to the student for the value of their input; and

2. the use of average entry requirements as a factor in compiling league tables of HEIs.

Accordingly, the efficiency criterion for fee-setting suggests that subsidy (e.g., bursaries) should depend on ability: i.e., the higher (lower) the student’s ability, the higher (lower) the subsidy. Of course, equity criteria - such as participation – may suggest the opposite. The influence of peer effects on students’ application decisions is also consistent with the perception that entry requirements signal the “quality” of an award: research findings refer to the “draw of the most selective college in a student’s choice set” and the “repulsion of the least selective”. It is also consistent with local evidence that schools advise applicants to make their first choice the HEI with the higher “points” requirement. Empirical evidence on peer effects overwhelmingly suggests that they are real and significant. Moreover, there is evidence that potential applicants are sensitive to differences in the perceived quality of the peer group. This may be of particular relevance for HEIs with a particular mission for participation. The evidence suggests that the exam performance of middle-ranking students is improved by good peers and worsened by bottom-ranking peers. This, together with sociological evidence on the HE choices of working class and minority students (Section 4.3.2), suggests a possible tension between the peer effects of meeting widening participation priorities and recruitment of higher aptitude working class and minority students. It is possible that increased recruitment through widening participation may be offset as other applicants are deterred by perceived effects on the quality of the peer group. If so, then widening participation may have direct benefits for recruitment but also indirect costs for recruitment elsewhere. This is an example of the potential trade offs between profit maximising and equity involved in decision making in HE. 3. Hierarchy in English HE and modes of competition HEIs’ reputation and peer effects interact in a process of cumulative causation, whereby high reputation HEIs enjoy a “virtuous circle” of rising reputation and student quality, while low reputation HEIs may find it difficult to avoid a downward spiral of low demand, lack of selectivity, lower quality of the student intake, perceived peer effects, and further reduced demand (Section 3.3). For low-reputation HEIs unable to counteract this tendency, the consequence is likely to be incipient excess supply. The hierarchy of HEIs reinforced by this polarisation tendency has important implications for how HEIs compete: from a strategy at the top of maintaining excess demand to control the quality of the student intake; to near market clearing in the middle where quantity and quality trade off; to strategies dominated by the need to

Page 7 of 81

avoid excess supply at the bottom. The implication is that competition among HEIs appears to be limited to overlapping “bands” or segments:

• at the top, competition in the input market for scarce student quality that will improve HEIs’ educational quality and position;

• at the bottom, competition in the product market for customers who will buy the output.

At the bottom of the status hierarchy, feasible pricing strategy will tend towards a “low entry requirement, low fee” combination. However, potential countervailing tendencies may be created by appropriate non-price strategy. 4. Implications of removing the fee cap (I):

competitive tendencies for low-status HEIs Once fees are uncapped, the polarisation tendencies within English HE suggests that market forces will cause fees to be set at market rates reflecting relative reputation, a process which is already underway in the UK postgraduate market (Section 3.3.2). Accordingly, once fees are uncapped, low-status HEIs can anticipate the following consequences. Three combinations of entry conditions and fees are unlikely:

1. “high entry requirements” with “high fees” - because both will tend to depress demand for places still further below supply;

2. “high entry requirements” with “low fees” - because of inability to recruit students who meet high entry requirements; and

3. “low entry requirements” with “high fees” - because in a situation of actual or incipient excess supply market forces dictate relatively lower prices.

Consequently, the operation of market forces will push low-status HEIs towards a combination of “low entry requirement” and “low fees”, which will tend to bring demand more closely into equilibrium with supply. Otherwise, low-status universities require alternative, non-price strategies. 5. Implications of removing the fee cap (II):

non-price opportunities for low-status HEIs High- and low-status HEIs tend to adopt different educational technologies (i.e., educational production processes) (Section 3.3.2). For example, HEIs whose high-status depends on high-quality peer effects will tend to favour small classes, so that students interact, and students of compatible “college age” whose interaction can best create peer effects. Conversely, HEIs that have less of the student quality input shift to technologies that depend less on intensive student interaction, hence with larger classes, wider age and cultural disparities among students, and distance learning with little or no student interaction and little contribution from one student’s qualities to another student’s education. This differentiation of educational technology means that low-status HEIs have opportunities to differentiate themselves in areas of little or no interest to high-status HEIs. For example, by innovatory vocational adaptations of academic curricula and combinations of traditional and distance learning, it may be possible to move some way towards the “high fee, high entry requirement” combination of high-status universities. Alternatively, it may be more feasible to move towards the “low fee, high

Page 8 of 81

entry requirement” combination likely to be vacated by high-status HEIs, which would yield reputational benefits from the peer effects of a higher quality intake and correspondingly enhanced ability to recruit higher quality faculty. A further implication of polarisation and hierarchy within English HE is that the clarity of the signal provided by a degree will diminish, while the importance of the signal provided by the institution attended will increase. Hence, we have an additional reason why the differentiation of English HEIs by status implies a differentiation of tuition fees. The strategic implication may be that, where possible, low-status HEIs will need to find ways to signal quality for particular awards that are independent of the general reputation of the institution. Depending on the award, relevant signals might be found in the employability of graduates, entry of at least some graduates into high-status jobs, recognition of the award by professional bodies, external “kite marks” (such as those sought by MBA courses), and so forth. 6. Market power, pricing policy and non-price competition Both evidence and theory suggest that a consequence of the polarisation of English higher education is variable market power – higher for high-status and lower for low-status HEIs. Accordingly, the polar cases of awards with and without market power provide benchmarks to guide thinking about setting fees for actual awards (Section 4). For HEIs setting fees for awards with market power, some implications for pricing policy are as follows: the fewer the substitutes for the award, the lower the price elasticity of demand; hence, the greater the market power to set fees above (marginal) costs and earn profit (Section 4.1). However, taking into account peer group and corresponding reputation effects considerably complicates pricing policy. For, in this case, profit maximising tuition fees are set higher for the less able or less motivated and lower for the more able or more motivated, which is consistent with the practice of HEIs awarding scholarships to the most able students. Even more complexity is introduced when HEIs optimise fees not only with respect to profit but, in addition, with respect to equity. Moreover, policy makers will need to bear in mind the principle that HEIs’ ability to conduct income-related pricing – i.e., discriminating in favour of students from low-income families – depends on market power and the corresponding ability to earn profit to redistribute through means-related bursaries etc. Awards with no distinctive characteristics – i.e., awards that are interchangeable with those of competitors – have no market power and thus cannot generate profit. For awards with no market power, the implications for ability- and income-related tuition discounts are as follows (Section 4.2). Peer group and reputation effects have similar implications as in the “market power” case. High ability students can be offered lower fees, because they lower the cost of achieving a given standard of education. However, this will not be a source of competitive advantage, because homogeneous awards will all offer the same discount. Price discrimination by income is more problematic under conditions of “no market power”. No market power implies that HEIs are not in a position to forego revenue. Any loss of revenue means that total costs are not covered, which means that long-run viability is sacrificed. The condition for offering means-related bursaries appears to be some degree of market power, hence non-infinite price elasticity and ability to earn profit. In sum, under conditions

Page 9 of 81

of “no market power”, ability related discounts are potentially cost saving, thus consistent with profit maximising, whereas income related discounts are revenue detracting and thus inconsistent with profit maximising. Many awards will have some unique or at least unusual features, hence some degree of differentiation and corresponding competitive strength, but are nonetheless vulnerable to similar awards being developed by other HEIs. Typically, successful awards are flattered by imitation and thus end up competing with similar awards. This is the typical situation of awards with some or limited market power. In this case, application of the theory of monopolistic competition yields insights into the modes of competition in the English HE market (Section 4.3), and may be particularly appropriate for thinking about the typical market situation of awards offered by lower-status HEIs.

1. For distinctive awards, the profit potential differs between the short run and the long run (short run is defined as the period during which competitors are unable to provide close substitutes; the long run obtains when so many close substitutes are available that the original award is no longer distinctive).

a. In the short term, a distinctive award can earn profit. The more an award signals distinctive features valued by potential students, the greater its potential market power, the higher its fee can be set and the greater its profitability.

b. In the long term competitors are likely to supply substitutes that erode profits until all suppliers are just covering costs. In addition, the corollary of easy market entry and corresponding supply increases is that awards in low-status HEIs tend to operate with excess capacity. The long-run position of awards thus tends towards zero profit and “empty seats”.

2. The theory suggests the need for continuous effort to prolong short-run profitability. The theory also suggests some broad principles for how this may be accomplished. In particular, awards with distinctive characteristics – i.e., a differentiated product – have potential for non-price competition.

a. Product differentiation and corresponding potential for non-price competition suggest that competition with similar institutions does not have to proceed wholly or even mainly on the basis of lower price.

b. To the extent that awards can be relatively easily imitated – they cannot be patented or trademarked – barriers to entry have to be defended by continuous innovation to maintain distinctiveness.

c. Successful non-price strategies to maintain the distinctiveness of an award may perpetuate short-term market power and profitability.

d. Because award reputations are substantially determined by institutional reputations, feasible product differentiation is likely to occur within, rather than between, “bands”; although a truly outstanding award might prove to be an exception.

e. Differentiation is only sustainable if it is not easily imitated. The corollary is that “Gimmicks” a source of one-off temporary advantage only.

The theory of oligopoly also suggests principles for the pricing of awards with limited market power (Section 4.4).

Page 10 of 81

1. For HEIs formal collusion provides the most favourable outcomes. However, for HEIs as for all other forms of commercial enterprise, collusion is illegal.

2. Given that collusion is illegal, tacit collusion may allow informal communication between firms. However, tacit collusion is unstable, likely to give way to price wars ending in a low-fee, low-profit equilibrium. This suggests that even if university decision makers choose not to start a price war, they should be prepared to respond if one does break out. Conversely, to the extent that an HEI already occupies a low-fee, low profit equilibrium, then price variation is precluded as a competitive strategy.

3. If price competition is precluded, then decision makers need to concentrate on non-price competition as the main way of competing against rival institutions, focussing on innovation and corporate branding.

Feasible pricing is determined by the outcome of non-price strategy. For example, higher fees are favoured by a differentiated product and by a strong peer group. Conversely, lower fees are associated with “commodity” products, low barriers to entry and awards that are easily imitated. In addition (Section 4.3.3), where an award is dependent on an external sponsor, the corollary of “buyer power” is likely to limit fees and potential profitability. 7. The student’s participation decision and pricing policy The contrast between awards with and without market power highlights an apparent anomaly. We may assume that local markets are relatively insulted from competition, while the global market for international students is fiercely competitive. Yet, if so, why are part-time fees generally lower than international fees? The answer arises from considering the student’s participation decision as an investment decision (Section 5). For potential students to choose to study, the HEI has to assist them over the study threshold at which the benefits of investing in HE outweigh the costs. For high-ability students, there is no problem. Even with high fees and low quality of education, high ability students can expect a positive return on their investment. In contrast, low-ability students are likely to be marginal with respect to this study threshold. To the extent that lower student ability means lower anticipated returns, hence lower benefits from HE, HEIs can do more to ensure that for low-ability students the benefits of investing in HE exceed the costs either by reducing tuition (lowering the costs) and/or by raising the quality of education (increasing the benefits). This is consistent with current proposals for HND students; namely, in relation to students on degree programmes, to combine lower fees with more tuition. This may be an economically rational strategy if this policy mix is consistent with covering costs. Of course, even if costs are not fully covered, there may be overriding educational/social priorities for enabling potential HND students to exceed the “study threshold”. However, this implies cross-subsidy from other activities. This concept of the study threshold also helps to explain why part-time fees are generally lower than international fees. The student’s own assessment of the influence of her or his own ability on returns to higher education is not observable but highly subjective. In Stoke-on-Trent, relative to elsewhere in the UK or the pool of existing international students, low self-esteem and correspondingly low aspirations

Page 11 of 81

among secondary students limits both achievement and staying on rates. Accordingly, a particular problem for Staffordshire University is that many potential part-time students greatly under-estimate their potential returns from education. In addition, the cumulative impact of low staying-on rates and low participation in higher education is lack of the cultural capital needed for informed choices. This increases the uncertainty surrounding returns to investment in higher education and thus raises the “study threshold” of Staffordshire University’s potential part-time students. Until reforms in local schooling make a difference, Staffordshire University has no alternative but to respond with lower tuition fees; subject, of course, to covering costs or some overriding reason for staying in the part-time market. Of course, HEIs must know their own award-specific costs to determine the extent to which they can offer discounted fees and/or additional tuition to low-ability and “non-traditional” students. The study threshold concept suggests that student demand for higher education is positively related to ability. On this criterion alone, tuition fees can be positively related to ability. However, this principle may, to a greater or lesser extent, be either offset by peer effects and/or reinforced by equity criteria. 8. Pricing policy in HE: empirical evidence The available empirical suggests that the benefits of subsidy include

1. increased recruitment, 2. enhanced retention (if the subsidy is appropriately designed), and 3. reduces the influence of socio-economic status on the choice of HEI

(Section 6). Recent empirical studies suggest that if tuition subsidy is to affect participation then it has to be substantial in relation to the total cost of HE. The apparently large elasticity measure (1.5) of one major study refers to the percentage change in enrolment in response to a percentage change in the total cost of attending (i.e., not only the cost of tuition): i.e.,

5.1college attending ofcost in the change Percentage

college attending students ofnumber in the change Percentage−=

In other words, a 10 percent reduction in total costs - other factors remaining unchanged - would increase participation among relatively low income students by 15 percent. However, this quantitative result should not be regarded as reliable beyond its context. All researchers in this field emphasise that it is perilous to generalise on the basis of the experience of a single institution or study; in particular, within the population of low-income students, program effects may vary with race and ethnicity. This possibility should be taken into account in the design and analysis of such programs. Moreover, this possibility also confirms that we should look to recent empirical studies for insights rather than transferable effect sizes. Empirical studies also suggest that tuition subsidies increase college entry substantially more than they increase degree completion.

Page 12 of 81

In the context of differential fees in English HE - assuming that fees rise substantially in high status HEIs but remain at much the same level elsewhere - one consequence might be that students from low-income families are no longer able to make choices between HEIs like students of higher socio-economic status. In this case, we may anticipate displacement of infra-marginal students from higher status and more expensive to lower status and cheaper HEIs, especially where the latter have awards that can signal desirable features. However, if differential fees were to be accompanied by better funded scholarships then the potential displacement - and, hence, cross-price effects - of differential fees would be vitiated. 9. Do students make rational choices? Some implications for HEIs Recent research from the USA reveals that how financial policies are explained and presented to students does matter (Section 7). High aptitude students both face a complex system of financial supports for their college education and are those most likely to obey the model of the rational human capital investor. Overall, such students are found to act as rational investors in HE: they are sensitive to tuition, room, and board in the expected direction (lower is better); and they are attracted by grants, loans, and work-study commitments. Yet the choice behaviour of these high-aptitude students was not uniformly rational. Students responded similarly to every additional $1,000 of financial support, regardless of whether it was a grant or a loan. Moreover, two additional findings also suggest departures from fully rational decision making. First, for a grant of a given amount of subsidy, calling it a scholarship increases the probability of matriculation (enrolment) by 86 percent of the prior probability, which is a great effect for an essentially hollow feature of a grant that any college could replicate at no cost. Secondly, front-loading also engenders a strong, positive matriculation response. For a grant of a given annual amount, its being front-loaded raises the probability of matriculation by 48 percent of the prior probability. This is a substantial effect for a feature that costs an HEI little for students who very likely to stay enrolled for four years. Of course, front-loading goes in the opposite direction to a policy of staging grants to encourage completion. As yet, we have no complete explanation for these deviations from the expected behaviour of rational investors in human capital. However, the overwhelming impression is that a lack of sophistication is the problem. Parents complain that they are baffled by the aid process. They argue that HEIs do not explain their offers well. Words like “bewildering” and “confusing” are the modal words in their comments. Finally, of particular importance to HEIs committed to widening participation is evidence that the incidence of irrational student choices is inversely related to the socio-economic status of their families and, in particular, to parental experience with college choice.

Page 13 of 81

Setting tuition fees in HE: literature review and principles for guiding policy

1 Introduction The recent introduction of a new fee structure together with the likely removal of the current £3,000 ceiling requires clarity on pricing for our whole product portfolio. The project aims are 1. to derive a framework of principles for pricing policy from the latest theoretical

and empirical research, and 2. to understand the implications of these principles for Staffordshire University’s

pricing policy. Accordingly, the practical contribution of pricing principles derived from economic analysis will be two-fold:

1. to inform operational guidelines; and 2. to provide benchmarks for evaluating

a. the risks entailed in competing options, and b. the consequences of departing from narrowly optimising criteria in the

interests of overriding non-economic criteria. The framework of pricing principles will guide policy making rather than offer precise quantitative recommendations. On the one hand, general quantitative recommendations are unlikely to be appropriate for a wide range of awards in varied and changing markets. On the other, although the economics of higher education (FE) has made considerable theoretical advances in recent years, there is insufficient empirical evidence – e.g., reliable elasticity measures – to support specific quantitative proposals. Most empirical magnitudes derive from studies of the long US experience with variable fees, and researchers are at best tentative in generalising their results even to the wider American context. In the UK, fees are too recent and insufficiently variable to have supported a reliable empirical literature. Accordingly, the framework will consist of qualitative principles that are derived from theory that is consistent with empirical evidence. These principles will supplement rather than replace the information set currently used by policy makers (current and recent fees, award costs, knowledge of the award and its competitive situation, knowledge over time of the students on the award, and so forth). The intention is that these principles will guide rather than pre-empt decision making about tuition fees. The scope of the project is as follows. Strictly, full-time undergraduate fees and incentives are excluded. The main focus is on

1. part-time fees, 2. international fees, and 3. postgraduate and PhD fees;

but will also take account of, 4. HND and Foundation degrees, 5. placement fees, and 6. EU fees and bursaries

Page 14 of 81

However, the relevant theory is developed at a level of abstraction that typically does not differentiate between different awards and modes of study. Moreover, the empirical studies focus on tuition fees for full-time undergraduate students, because this is both the major concern for university policy makers and where most data is to be found. Consequently, many of the principles derived from recent theoretical and empirical studies will apply broadly to university fee setting. Subject to this caveat, the framework will be focussed as specifically as possible on the six listed priorities. Section 2 provides a brief note on methodology. The following sections (3 -7) survey the theory most relevant to the “Project Objectives” 1 and 2 as set out in the Project Specification:

1. the development of pricing principles to guide future decisions on how to price our product range; and

2. developing logical pricing between modes, levels and means of study. These sections also contribute to understanding “Project Risks”:

1. the Student Support System; 2. Market Pricing - courses charged according to market/customer propensity to

pay; and 3. the third category of risk; namely, “Competitor Pricing” - course charging set

by positioning them against competitors. We analyse at some length the implications of interaction between competing HEIs – both arms length and strategic.

The final section draws together and discusses pricing principles that may be derived from recent research in the economics of higher education.

Page 15 of 81

2 Methodology The project will comprise literature review together with interpretation for application by Staffordshire University. The literature reviewed will be mainly from recent research in the economics of higher education. However, it will also be necessary to consult research from broader educational and policy literature (for an example, see Section 2.3 below). Although tuition fees are increasingly on agendas both nationally and internationally (Jacobs and van der Ploeg, 2005), there is little economic analysis of fees from the perspective of HEIs’ pricing policies. There are certainly no “off the peg” solutions or guides. Gary-Bobo and Trannoy (2005, pp.2 and 4) sum up the current state of knowledge as follows.

Yet, it seems that the formal economic theory of university pricing …has not been studied with enough precision … and in particular, the various forms of price and non-price competition among universities are still very much unexplored.

Currently, the research is not only dispersed, much of it still in working papers rather than published in referred journals, but also highly technical. Theoretical work proceeds in the form of mathematical models. A comprehensive, more user-friendly treatment is not yet in sight. Accordingly, a major task of this project will be to:

1. set out the assumptions of relevant models; 2. provide an intuitive - rather than mathematical - account of

a. how conclusions are derived from assumptions, and b. how different assumptions are reflected in different conclusions; and

3. translate these conclusions into operational principles.

Page 16 of 81

3 Higher Education as an economic activity: some defining features

From an economic perspective, higher education is a business. Yet HE is a business with several special features, each of which presents particular challenges to policy making in higher education. In this section, we review these special features and their particular implications for pricing policy. HE is a business is many respects similar to “normal” businesses undertaking commercial activities. Winston (1999, p.13) observes:

(HE) produces and sells educational services to customers for a price and it buys inputs with which to make that product. Production is subject to technological constraints. Costs and revenues discipline decisions and determine the long-run viability of a college or university.

And yet, many will protest that HE is not - or, at least, should not be - “just” a business. This can be meant to imply that HE is ‘nobler than business’ (Winston, 1999, p.13), because humanistic, non-commercial priorities are central to the mission of HE. However, even in narrow economic terms, HE is, ‘in important ways, simply different from a business’. Winston (1999, pp.13f) codifies these economic differences as follows:

1. higher education institutions (HEIs) are generally not-for-profit enterprises; indeed, students - “customers” - are generally subsidised;

2. peer effects (HE uses a “customer-input technology”); and 3. there is a hierarchy of HEIs.

We discuss each of these in turn, although student subsidies are discussed in conjunction with peer effects and the hierarchy of HEIs.

3.1 HEIs as not-for-profit enterprises Winston (1999, p.15) clarifies the nature of HEIs as not-for-profit enterprises in terms of the “non-distribution constraint”.

Nonprofit firms are allowed to make profits and usually do; the term “nonprofit” does not mean that revenues never exceed expenditures. Instead, it means that there is no outsider to whom the enterprise can legally distribute those profits as the normal firm distributes profits to its owners … Of course, the behaviour of a nonprofit firm must respect the fact that its total costs cannot long exceed its total revenues, so that the firm may appear to be profit-motivated in its attempts to raise revenue, when in fact it is only recognising the reality that it is budget-constrained.

From this perspective, there is no inconsistency between HE as not-for-profit and “profit maximising” by HEIs. However, in HE, relative to normal businesses, there are two reasons why incentives to profit maximise may be weaker:

Page 17 of 81

1. there is no equivalent of the stock exchange as a “market for corporate control” and, hence, no corresponding threat of take-over;

2. multiple stakeholders - including students, employers, and government - together with the lack of any equivalent in HE to the principle - enshrined in both US and UK company law - that managers’ sole responsibility is to shareholders, means that the purpose of profit maximising is unclear.

Correspondingly, to the extent that the profit maximising imperative is weaker than in business, so other motivations may come to the fore (such as academic excellence and, in particular, equity considerations such as widening participation). Hence, managerial motivation and policy making in HEIs are more complex that in the purely commercial sector: whereas commercial incentives focus managerial attention onto efficiency (hence, cost minimisation and profit maximisation), in HE motivation typically values efficiency, academic excellence and equity. This more complex motivation may help to explain why ‘in sharp contrast to the business firm’ (Winston, 1999, p.17), HEIs ‘can and do subsidise their customers’. Typically, HEIs in the US (using private endowments) and in England (using HEFCE capitation) sell their product ‘at a price that is below the costs of its production’.

3.2 Peer effects in HE Peer effects define the use in HE of a “customer input technology” (Winston, 1999, p.17):

The technology of producing much of what is sold in higher education is unusual in that colleges can buy important inputs to their production only from the customers who buy their products; that is, higher education uses a customer-input technology … to a significant degree, students educate both themselves and each other, and the quality of the education any student gets from college depends in good measure on the quality of that student’s peers. Inputs of faculty and facilities matter, too, of course, but the quality of both individual students and of the student body as a group counts for a great deal in the quality of educational services that the institution delivers.

This is consistent with the common practice of granting scholarships to the more able students (in effect, a payment to the student for the value of their input) as well as with the use of average entry requirements as a factor in compiling league tables of HEIs. Peer effects have become central in more recent theoretical contributions. One reason, among several, why higher education differs from commercial markets is that ‘students are inputs into the production process of their own human capital’ (Gary-Bobo and Trannoy, 2004, p.8). In other words, education is a “customer input technology”, ‘where students are both consumers of education and co-producers of education’ (Jacobs and van der Ploeg, 2005, p.22). This suggests that peer-group effects may be important in higher education (Pugh et al., 2005, pp.30-31), in the sense that the average ability of enrolled students increases the quality of education for a given expenditure or, equivalently, decreases total cost for a give quality (Gary-Bobo and Trannoy, 2004, p.4).

Page 18 of 81

According to Jacobs and van der Ploeg (2005, p.23):

There is some quasi-experimental evidence that good students improve and bottom-ranking students worsen the exam performance of middle-ranking students (Winston and Zimmerman, 2003).

From this, they draw the following implication for HEIs:

With peer effects, universities want to reward students for their contribution to the educational process by giving them a discount on their tuition (Rothschild and White, 1995).

A similar conclusion is arrived at by Epple et al. (2003, p.15) who model college behaviour on the assumption of quality maximisation subject to a profit constraint and in the presence of peer effects, the corollary of which is that ‘tuition (i.e., fees) will decline with ability’. Accordingly, the efficiency criterion for fee-setting suggests that subsidy (e.g., through bursaries) should depend on ability: i.e., the higher (lower) the student’s ability, the higher (lower) the subsidy. Of course, equity criteria - such as participation – may suggest precisely the opposite. Epple et al. (2003, p.21) also provide evidence that this efficiency criterion for fee setting exists in reality. They use US student- and university-level data from 1995-96 to investigate ‘whether students with higher ability levels pay lower tuitions in equilibrium because of the positive externality they have on other students through the peer group effect’. If they do, it is not because institutions with higher ability students charge lower fees; indeed, Epple et al. (2003, p.27) find strong evidence of hierarchy across the more than 1,200 HEIs in the sample, such that ‘mean SAT scores (measuring peer effects) are strongly correlated with tuition, endowment, expenditures and salaries’. However, econometric analysis of the individual student data revealed that the lowest-ranked private schools give an estimated ‘$11.49 increase in financial aid for each unit increase in SAT’, because ‘peer ability is valued, implying that higher-ability students have more attractive alternatives’; while ‘top-ranked schools give negligible discounts to more able students’, because ‘the top schools face no competition “from above”’ (Epple et al., 2003, pp.40-41).1 This evidence on peer effects is suggestive rather than definitive (Epple et al., 2003, pp.46-47).

The evidence on pricing by ability is supportive of positive peer effects in educational achievement from high ability at the college level … The evidence does not, however, establish the presence of peer effects. Similar pricing would be predicted in a model where households obtain utility from having their students at schools with a more able peer group even if that more able peer group does not convey any increase in educational benefits. Nonetheless … had there not been evidence of pricing by ability, support for the hypothesis that peers convey educational benefits would have been considerably weakened.

1 Similarly, for a large sample of high aptitude students, Avery and Hoxby (2004, pp.280-81) report: ‘the correlation between the grant amount that a student receives from a college and the college’s median SAT score is -0.32.

Page 19 of 81

According to Hoxby’s (2004, p.11) editorial introduction to a particularly important recent collection of papers on the economics of college choice, ‘peers are a theme of almost sublime importance in the economics of college education’; for example:

They help explain why students upgrade (i.e., to higher-status HEIs) when given tax credits, why states create merit scholarships to encourage students to stay in-state, why high-aptitude students receive the array of aid they do, and why public universities enrol non-resident students.

This judgement reiterates the findings of Winston and Zimmerman (2004, p.395) although, so far, this judgement rests on ‘only a small, if growing, empirical base’, such that theoretical claims continue to outstrip empirical evidence. Accordingly, Winston and Zimmerman (2004) examine the methodological difficulties of analysing peer effects, survey the existing literature, and set out new evidence of their own. Winston and Zimmerman (2004, p.402) distinguish between the existence of peer effects, which are relatively well supported by the empirical literature and which help to explain industry structure in higher education; and the form of peer effects, which are not so well understood but which may be critical for justification or critique ‘on efficiency grounds’ of that structure. For example (Winston and Zimmerman (2004, p.400):

Resorting students creates winners and losers to the same extent under strictly symmetric peer effects. But if those peer effects are asymmetric so that students at different levels of behaviour or characteristics are influenced differently by their interaction with others, then peer effects introduce an issue of economic efficiency, too. How students are grouped will affect the total amount of learning produced in given participants from given resources. If weak students gain more from proximity to strong peers than the strong students lose from that association, overall learning would be increased by reducing stratification … a point … suggesting random assignment of students to colleges. But if asymmetries in peer effects run the other way so that strong students interacting with other strong students are also more sensitive to peer influence – gaining more in learning than would weak students in those circumstances – then stratification and segmentation could increase, not decrease, aggregate learning. In the extreme, stratification would be supported on grounds of efficiency if strong students were sensitive to peer quality at all levels while weak students were unaffected by peers at any level.

Winston and Zimmerman (2004, p.404) conclude from their literature review that ‘peer effects exist in higher education’; however, ‘the evidence is not clear on the nature of any nonlinearities or interactions based on gender’. In their own investigation, Winston and Zimmerman’s (2004, p.396) ‘use individual student’s grades, Scholastic Aptitude Test (SAT) scores, and the SAT scores of their room-mates to estimate the effect of roommates’ academic characteristics on an individual’s grades’. This enables a ‘quasi-experimental empirical strategy’ as: ‘The schools selected for the analysis were chosen because their housing assignment protocols appear (near) random for first-year students’. Winston and Zimmerman (2004, p.418; emphasis added) summarise their findings as follows.

Page 20 of 81

It seems clear that peer effects exist – students’ characteristics and behaviour do, indeed, influence other students’ behaviour with conventionally measured academic characteristics (like SAT) influencing conventionally measured academic performance (like GPA) … the signs of those effects are in the direction that would motivate institutional selectivity – strong students tend to increase peers’ academic performance, and weak students tend to reduce it … But beyond that key question, the facts become less clear, and the agenda for investigation of peer effects becomes larger. So there are often different results by gender … On nonlinearities – whether peer influences operate equally and symmetrically across characteristics and behaviours – the evidence is puzzling, with strong or weak homogeneous groupings sometimes performing significantly better than those with peers of different abilities. Students of middling ability are usually more susceptible to peer influence than those at either end of the ability distribution …

Winston and Zimmerman (2004, p.417) conclude by pointing out the limitations of their findings, notably that their and previous results mostly ‘pertain to highly selective institutions’. In contrast to the evidence on pricing by student quality, ‘tuition does not vary significantly with income at the lowest ranked schools’; while, the more highly ranked schools, display ‘substantial variation of price with income’ (Epple et al., 2003, pp.43 and 46). Together, the evidence on pricing by ability and pricing by income suggest that ‘the more highly ranked schools exercise some degree of market power’, while ‘lower ranked schools exhibit behaviour that is closer to the predictions of the competitive model’. Lower ranked institutions lack market power and so must compete for high-ability students with discounts, while being unable to price discriminate against students from higher-income families. Conversely, high ranking institutions possess sufficient market power to do the opposite.

3.3 The hierarchy of HEIs Winston (1999, pp.18-21) documents the US hierarchy of HEIs, which corresponds to their endowment wealth. Accordingly (p.18; emphasis added):

The “market” for higher education is very different from commercial markets. Competitive forces will play out, but they will do so on a strikingly uneven playing field.

Endowment wealth is used to subsidise students. Because of the importance of peer effects, the greater a university’s wealth the greater its use of subsidies to select high-ability students who contribute the greatest “customer input” into the education of both themselves and of their fellow students.2 In turn, selectivity and a higher quality peer group increases demand for admission: ‘…selectivity, as measured by the ratio of 2 In the highest decile of US HEIs ranked by subsidy in 1995, the average subsidy was $22,800 a year to support a $28,500 education; in the lowest decile, the corresponding subsidy was $1,800 for a $7,900 education (Winston, 1999, p.20). In turn, these subsidies are directly related to ability (Winston, 1999, p.22): ‘Strong students pay a lower net tuition than weak ones because they contribute more on the margin to the educational activities of the university and hence get more financial aid.’

Page 21 of 81

applicants to admissions, average test scores, and high school grades is one of the most significant and sought after descriptors of a college’s educational quality’ (Winston, 1999, pp.23 and 24; for recent empirical evidence, see Avery and Hoxby, 2004, pp.262 and 272).3, 4 As demand rises, so the restricted supply of places ensures substantial excess demand - i.e., substantial unsatisfied demand at the price set for tuition - for places, which enables greater selectivity leading to higher demand … and so on, in a virtuous circle. Accordingly, the typical situation for a wealthier university is one of exacting selection criteria and excess demand. This virtuous circle for wealthy universities is mirrored by a vicious circle for poor universities: lower subsidy; lower ability students; lower demand; less selectivity; lower demand … and so on. Accordingly, the typical situation for a poorer university is tending towards open access and excess supply. In the UK, endowment does not play such a prominent role in sorting HEIs into a hierarchy. However, there is evidence that historically determined reputational advantages are prior to and, indeed, the precondition of purely financial advantages. Unlike the commercial sector where rankings change relatively rapidly (there are few companies listed in both the 1950 and 2000 FTSE 100), among HEIs relatively stable rankings are conditioned by ‘significant first-mover advantages’ (Winston, 1999, p.28). In the UK, even in the absence of fee differentials for EU students, universities are able to leverage historically determined reputational advantages into higher fees income from international students: according to McMeeking (2004, p.18), analysis of the financial statements of UK universities suggests that the Russell Group universities have been able to earn ‘a strong positive return on their investment in brand name reputations’. In the next two sections, we apply some of these theoretical insights into peer effects and hierarchy to the English HE markets and discuss implications for pricing policy in individual HEIs.

3.3.1 Polarisation and some implications in English HE Starting from historically determined reputational advantages / disadvantages, Figure 1 sets out a simple model of polarisation in English higher education. Downward arrows link the four central boxes into a causal chain: reputational advantage (disadvantage) causes high (low) demand for places at the HEI, which determines the degree of selectivity and the quality of the student intake. The primary feedback mechanism is depicted by the arrow from the “Student quality” box to the “Reputation” box and operates via peer effects: namely, the higher (lower) the quality 3 Avery and Hoxby (2004, pp.263 and 268) find that students ‘aim for greater certainty at a college with moderately high selectivity on their list, not for certainty at the least selective college’. They also report some variations in this with respect to socio-economic background: ‘… the draw of the most selective college in a student’s choice set rises from a 43 percent increase in the probability of matriculation for the low-income families to a 90 percent increase in increase in the probability for the high-income families. The repulsion of the least selective college in the choice set goes from a 1 percent decrease in the probability of matriculation for low-income families to a 33 percent decrease in the probability of matriculation for high-income families’ (emphasis added). 4 The influence of peer effects on students’ application decisions is also consistent with local experience in Stoke, where there is evidence that schools advise applicants to make their first choice the HEI with the higher “points” requirement.

Page 22 of 81

of the intake, the more positive (negative) feedback there is on reputation. These causal links together with the feedback effects introduced by peer effects are sufficient to create a process of cumulative causation, whereby high reputation HEIs enjoy a virtuous circle of rising reputation and student quality while low reputation universities mirror this with a vicious circle. A secondary feedback mechanism takes effect through the quality of academic staff (Winston, 1999, p.24):

A related feedback appears to amplify differences in faculty quality, too; good students appeal to good faculty and good faculty appeal to each other.

In turn, higher (lower) quality faculty amplify HEIs’ polarisation towards higher and lower reputations. To the extent that these processes actually operate in reality, and are not offset by countervailing influences, the tendency over time will be towards an increasingly polarised system of higher education. This tendency towards polarisation is endogenous and applies to any higher education system. However, in England this tendency is being reinforced by the Government/HEFCE policy of concentrating research funding. Greater (lesser) research funding contributes to an HEI’s reputation not only directly (depicted by the arrow linking “Concentration of research funding to “Reputation of HEI) but also indirectly, via “Faculty quality/reputation” (because not only good students but also research and a lively intellectual environment appeal to good faculty). Although the policy of concentrating research funding is exogenous to the model, the effects of the policy are endogenously determined. This is depicted by the broken arrow from “Faculty quality / reputation” to “Concentration of research funding”. Within the model, high (low) quality faculty are attracted to high (low) reputation HEIs; hence, assuming that faculty quality is at least partly defined by their ability in research, the flow of research funding tends to follow and thus reinforce the endogenously determined reputational differences. In the long run, as English universities seek to emulate the US endowment levels, we can anticipate a further endogenous reinforcing of the tendency towards polarisation (Winston, 1999, p.28).

The feedback cycle is only compounded by the fact that higher student quality implies higher postgraduate incomes, which induce more generous alumni giving …

High (low) reputation HEIs will tend to teach high (low) ability students, thus acquire relatively more (less) wealthy alumni who will be a source of high (low) levels of donations. In turn, as endowment differentials grow in both relative and absolute terms, high (low) reputations HEIs will be able to fund increasingly different levels of tuition subsidies, thereby further reinforcing differences in selectivity and student quality. This third potential feedback loop is more potential than actual in the UK context and is thus not depicted in Figure 1. Nevertheless, it is consistent with the evidence from US universities of strong and significant correlations between mean SAT scores (a proxy for average student ability, hence a measure of peer effects) tuition fees, and endowments (Epple et al., 2003; see Section 2.2, above). To the extent that UK universities succeed in their current intentions to boost their

Page 23 of 81

endowment income, and to the extent that their success mirrors their existing reputations, polarisation in UK HE will be further reinforced. Figure 1: A model of polarisation in English higher education

Source: own model developed from ideas in Winston (1999) The current situation in UK HE is more complex than the simple model of polarisation suggests. Broadly, there are three groups of universities: “Old” universities, defined by a pre-1992 Charter; the “Russell Group”, a self-selection of 19 of the oldest, most prestigious – and, consistent with our model – most research intensive universities; and the “New” or “Modern” universities with a post-1992 Charter. The hierarchy is described by Chevalier and Conlon (2003, p.4).

Currently, Old universities account for almost half of the undergraduate students in the country, almost evenly split between Russell Group and other old universities … This hierarchy of institutions is used as a comprehensive measure of quality. The three types of university differ by the degree subjects

Primary Feedback loop: via peer effects

Demand for places

Selectivity

Student quality

Secondary feedback loop: via Faculty quality / reputation

Reputation of HEI

Concentration of research funding

Page 24 of 81

offered and the emphasis placed on research and as a result the sources and amount of public funding available. Current mean statistics on A-level scores of intake students, pupil-staff ratio, research assessment and destination of graduates are statically different for the three types of institutions … For each measure, Russell Group dominates Old universities and Modern universities always have the lowest mean quality.

McMeeking (2004, pp.21 and 28) finds a similar hierarchy in his analysis of the group-specific drivers of the financial position of UK universities.

The financial results of the Russell Group of universities are statistically better than those outside the group … Russell Group institutions earn positive returns on their brand name reputation. The financial performance of the (other) pre-1992 universities is significantly associated with student-staff-ratios and the Research Assessment Exercise results … academics that can teach large numbers of students and produce international quality research will significantly improve the financial results of their university. The financial performance of the post-1992 universities is negatively related with computer and library expenditure. This expense impairs financial performance in the short term but is presumably incurred for long-term gain or due to externalities.

Nonetheless, within this three-group hierarchy, we can discern the polarisation process suggested by our model. Chevalier and Conlon (2003, p.13) find that, with the expansion of higher education, the Russell Group have ‘poached the best students out of Modern universities’, while ‘growth in the Modern university sector was made possible by attracting students of predominantly lower ability’. Moreover (Chevalier and Conlon, 2003, p.19), as measured by different cohorts’ earnings:

Returns to quality have increased … as the number of students expanded. This is consistent with the increased sorting of students … As predicted by theoretical models and experienced in the US … the increased competition for students has led to an increased heterogeneity between institutions and thus higher return to quality.

Chevalier and Conlon (2003, p.15) admit that weaknesses in their data mean that it is not possible to separate fully the effects on returns of increased institutional heterogeneity from the effects of ‘increased heterogeneity of students between institution types’. However, the authors appear not to control for peer effects, which according to our model and the underlying literature may render this distinction moot. Nonetheless, they proceed to ‘estimate the tuition fee that a representative individual entering a Russell Group university would be willing to pay over and above those charged at a Modern university in order to capture the quality premium’ (Chevalier and Conlon, 2003, pp.19-20):

… we calculate the difference in the net present value of the lifetime earnings between graduates from Modern and Russell Group universities … the annual fee differential … should range from £2,950 to £7,100. How credible are these estimates? In the US, the market for higher education is competitive and it is usually acknowledged that the fee differential matches the quality differential

Page 25 of 81

…the inter-quartile ranges in 2002 (in pounds) were £1,000 in the public sector and £5,000 for private institutions … UK evidence can also be used … universities are free to set their fees for the competitive market of non-European Union undergraduates. For this market, the mean fee differential between Russell Group and Modern universities ranges from £1,400 to £2,900 depending on faculty. So our estimates are globally in line with available evidence on fee differentials.

This potential differentiation of UK tuition fees once the current £3,000 ceiling is removed, together with the actual differentiation in the US where market forces are subject to no such constraint, are consistent with the prediction derived from our theoretical model (see Figure 2). Moreover, it is arguable that differential fees, reflecting differential earnings premiums, will induce more equity by reversing the current situation (Chevalier and Conlon, 2003, p.22): ‘By implementing a unique price in higher education (the current practice), the government subsidises graduates attending more prestigious institutions more generously than others.’

3.3.2 Implications of hierarchy for how HEIs compete The hierarchy of HEIs created and reproduced by this polarisation process has important implications for how HEIs compete in the HE market (Winston, 1999, p.27).

Movement down the hierarchy () mean less of excess demand until schools encounter increasing problems of selling the product at all - from an excess demand at the top that controls quality, to near market clearing in the middle where quantity and quality trade off, to excess supply and empty classroom seats … at the bottom.

The implication is that competition among HEIs ‘appears to be limited to overlapping “bands” or segments’ (Winston, 1999, pp.29-30):

At the bottom, it’s competition in the product market for customers who will buy the output; at the top, it’s competition in the input market for scarce students (and faculty) quality that will improve a school’s educational quality and position.

Figure 2 sets out the implications of the polarisation tendencies depicted in Figure 1 for how HEIs of differing status compete. In this 2-by-2 matrix, each cell sets out the strategic implications of HEIs’ positions in the hierarchy for their competitive combinations of price and entry requirement. High-reputation HEIs reap the benefits of their virtuous circle through excess demand, which enables selectivity. At present in England, because tuition fees are capped for EU students, high status HEIs are located in the cell that combines “High” entry requirements with “Low” tuition fees. However, this combination enables continuous reproduction of reputational advantages, thereby reinforcing selectivity and increasing excess demand (i.e., at the prevailing fee level, demand for places exceeds supply). However, once fees are uncapped, we can anticipate that market forces will cause movement (depicted by the left-hand upward arrow) towards a combination of “High” entry requirements

Page 26 of 81

(maintaining selectivity) and “High” fees, which will tend to bring demand more closely into equilibrium with supply in the high-status segment of the HE market. This is consistent both with US developments analysed by Epple et al. (2003) (reported in Section 2.2, above) and with developments in the UK market in postgraduate fees, in which there is evidence that the charging of similar fees to home students is giving way to fees set to reflect reputation.5 Conversely, the consequence of the vicious circle imposed on low-reputation HEIs is incipient excess supply. Accordingly, once fees are uncapped, for Low-status HEIs we can anticipate the following:

1. the cell combining “High entry requirements” with “High fees” does not represent a feasible option, because both will tend to depress demand for places still further below supply;

2. the cell combining “High entry requirements” with “Low fees”, although increasingly vacated by high-status HEIs, does not represent a feasible option because of inability to recruit students who meet high entry requirements; and

3. the cell combining “Low entry requirements” with “High fees” is not feasible, because in a situation of actual or incipient excess supply market forces dictate relatively lower prices.

Consequently, the operation of market forces will push low-status HEIs towards a combination of “Low entry requirement” and “Low fees”, which will tend to bring demand more closely into equilibrium with supply in the low-status segment of the HE market. 5 See “Masters market hots up” (The Times Higher, September 1 2006). ‘A market in postgraduate fees for British students is emerging, with some universities charging thousands of pounds more than others … While institutions have charged different fees for overseas students and for specialist courses such as business studies in the past, home students have usually been charged similar fees for one-year postgraduate courses. But a Times Higher survey of the 20 universities with the highest number of masters courses suggests increasing differences in fees across the sector … A Warwick spokesperson said the fees were a “straightforward reflection of the university’s’ reputation – the price reflects the fact that we are a strong institute” … But Simon Felton, general secretary of the National Postgraduate Committee, said: We accept … the right of institutions to set fees according to the cost of providing the course, but we object to universities increasing the fees based on reputation alone … it is difficult to do a cost-benefit analysis and work out whether the doors it opens are worth the extra fees.” Wes Streeting, vice-president of the National Union of Students, said: “We are greatly concerned by the increasing variation. There is a risk that it could lead to students choosing courses based on cost rather than on suitability”.’ The final comment suggests that higher postgraduate fees at high reputation HEIs may cause substitution towards lower-cost postgraduate awards at low status HEIs, especially where the latter can signal desirable features.

Page 27 of 81

Figure 2: Strategic implications of polarisation in English HE for price / entry requirement combinations

Key • Tendencies induced by market forces: • Movement introduced by successful differentiation: Source: own figure developed from ideas in Winston (1999) The model outlined in Figure 1 gives insight into polarisation within English HE, while Figure 2 helps to reveal the corresponding implications for HEI strategy as English HE comes to resemble the highly segmented HE market in the US (Clotfelter, 1999). Of course, models are simplified schematic presentations designed to highlight essential features of the HE system by suppressing complexity. One implication that emerges is that high-status universities’ strategy is centred on maintaining excess demand; conversely, low-status universities require other strategies to increase student demand. In turn, this influences high- and low-status HEIs to adopt different educational technologies (Winston, 1999, pp.25-26).

Those schools that command most of the student quality input tend to choose an educational production technology that amplifies the effects that those high quality students have on each other … residential colleges whose living arrangements facilitate student interaction … small classes so that students interact … a non-vocational “impractical” curriculum … students of

STATUS and ENTRY

REQUIREMENTS TUITION FEES

High

Low

High Demand = Supply Demand > Supply

Low Demand < Supply Demand = Supply

Page 28 of 81

compatible “college age” whose interaction can best create peer effects … Schools that have less of the student quality input shift to technologies with less of student interaction … commuter populations, larger classes, wider age and cultural disparities among students, more vocational curriculum … distance learning with little or no student interaction and little contribution from one student’s qualities to another student’s education.

This differentiation of educational technology - i.e., of the educational production process - means that low-status HEIs have opportunities to differentiate themselves in areas of little or no interest to high-status HEIs. For example, by innovatory vocational adaptations of academic curricula and combinations of traditional and distance learning, it may be possible to move some way towards the “High fee” - “High entry requirement” combination of high-status universities. Alternatively, it may be more feasible to move towards the “Low fee” - “High entry requirement” combination likely to be vacated by high-status HEIs, which would yield reputational benefits from the peer effects of a higher quality intake and correspondingly enhanced ability to recruit higher quality faculty. In Figure 2, these possibilities are depicted by broken arrows. A further implication of polarisation is suggested by the “signalling” theory of higher education. In brief, there are two competing theories of returns to education (see, for example, Berndt, 1991, pp.152-58 for a review of the theories and the associated problem of distinguishing between them observationally). The first is human capital theory, according to which returns to education reflect the productivity enhancing effects of education. The second is screening theory, according to which employers value educational qualifications only because they reveal otherwise unobservable ability and, hence, productivity. Conversely, for workers, the more and better the qualifications they acquire in a given time the higher the potential productivity they can signal to employers. To the extent that screening theory captures a real aspect of firms’ recruitment processes, an implication of the polarisation of English HE is that the clarity of the signal provided by a degree as such will diminish (Chevalier and Conlon, 2003, p.23) while the importance of the signal provided by the institution attended will correspondingly increase. Hence, we have an additional reason why the differentiation of English HEIs by status implies a differentiation of tuition fees. The strategic implication may be that, where possible, low-status HEIs will need to find ways to signal quality for particular awards that are independent of the general reputation of the institution. Depending on the award, relevant signals might be found in the employability of graduates, entry of at least some graduates into high-status jobs, recognition of the award by professional bodies, external “kite marks” (such as those sought by MBA courses), and so forth. For low-status universities, such signals will help to offset the effect on tuition fees of adverse reputational effects.

Page 29 of 81

4 Optimal fees and price elasticity of demand Both evidence and theory suggest that a consequence of the polarisation of English higher education is variable market power – higher for high-status and lower for low-status HEIs. In this section, we explore the consequences of this for the price elasticity of demand for the awards of different types of HEI.6 We assume that HEIs are profit maximisers. As we have seen, this is consistent with not-for-profit or “charitable status”, because profit is not distributed to shareholders, but is invested in widening participation, reputation, salaries, etc; and, in any case, revenue must at least cover costs. We consider the two extreme cases of awards supplied, respectively, by institutions with and without market power. These are not necessarily realistic. Rather, these two cases serve as benchmarks. We then consider the intermediate case of awards with limited market power. Discussion of this more realistic intermediate case is developed by way of insights from the theories first of monopolistic competition and then of oligopoly.

4.1 Award with market power In this case, the award must have some unique feature(s) for which potential students are willing to pay, and for which there are no close substitutes. This means that the award is

1. not readily available elsewhere, and 2. not easily replicable.

In this case, Jacobs and van der Ploeg (2005) demonstrate the following outcomes.

1. Optimal tuition fees are set as a mark-up over marginal cost; hence, total revenue exceeds total costs, which means that a profit is made.

2. The size of the mark-up depends on price elasticity of demand; there is an inverse relationship, such that awards with low price elasticity command a high mark-up, while awards with high price elasticity command a low mark-up.

For HEIs setting fees for awards with market power, some implications for pricing policy are as follows: the fewer the substitutes for the award, the lower the price elasticity of demand; hence, the greater the market power to set fees above (marginal) costs and earn profit. However, taking into account peer group and corresponding reputation effects – for reasons we analyse above – considerably complicates pricing policy. For, in this case, profit maximising tuition fees are set higher for the less able or less motivated and lower for the more able or more motivated, which is consistent with the practice of HEIs awarding scholarships to the most able students. Even more complexity is introduced when HEIs optimise fees not only with respect to profit but, in addition, with respect to equity. Moreover, policy makers will need to bear in mind a principle suggested by our discussion in Section 2.2 (above); namely, that HEIs’ ability to conduct income-related pricing – i.e., discriminating in favour of students 6 In the context of this paper, price elasticity of demand measures the sensitivity of student demand to fee levels; i.e., the percentage change in enrolment caused – other factors held constant – by percentage variations in tuition fees.

Page 30 of 81

from low-income families – depends on market power and the corresponding ability to earn profit to redistribute through means-related bursaries etc. A corollary of this principle is that HEIs supplying awards with low market power are likely to be the most financially constrained, hence are the most likely be caught in a trade-off between the logic of profit maximisation, which suggests ability-related tuition subsidy, and that of equity, which suggests means-related subsidy. This trade-off is likely to be particularly painful, because of the positive correlation between income and (measured) ability (for evidence from the US, see Epple et al., 2003, p.35).

4.2 Award with no market power This case is much simpler to analyse. Jacobs and van der Ploeg (2005) demonstrate that in the case of awards with no market power, optimal tuition fees are set to equal marginal cost. Hence, total revenue equals total costs, which means that the award is viable but makes no profit for other purposes. The reason for this outcome is that no market power means that there are plenty of substitutes: i.e., there are • many equivalent awards; and • no significant barriers to entry, which means that successful innovations can easily

be replicated by competitors. In this case, if we assume that all HEIs have the same costs, then for homogenous awards a single fee must emerge. Awards charging less than costs are not viable in the long run; while those charging more will experience a complete collapse in demand. Some implications of zero market power for pricing policy are as follows. 1) Price elasticity not relevant; technically: price elasticity with respect to fees is

infinite (i.e., even a small rise triggers a collapse in demand, while a small increase triggers potentially unlimited increase in demand).

2) For each award, HEIs must: a) cover costs, but no more; and b) keep costs as low as possible.

3) Cost reductions are a source of temporary profit only, because innovations leading to reduced costs can be replicated elsewhere.

4) Peer group and reputation effects have similar implications as in the “market power” case. High ability students can be offered lower fees, because they lower the cost of achieving a given standard of education. However, this will not be a source of competitive advantage, because homogeneous awards will all offer the same discount.

5) Price discrimination by income is more problematic under conditions of “no market power”. No market power implies that HEIs are not in a position to forego revenue. Any loss of revenue means that total costs are not covered, which means that long-run viability is sacrificed. The condition for offering means-related bursaries appears to be some degree of market power, hence non-infinite price elasticity and ability to earn profit. In sum, under conditions of “no market power”, ability related discounts are potentially cost saving, thus consistent with profit maximising, whereas income related discounts are revenue detracting and thus inconsistent with profit maximising.

Page 31 of 81

4.3 Award with limited market power (I): monopolistic competition

More realistic than either of the two extremes – market power and no market power – may be the intermediate case of some or limited market power. This is the case corresponding to the model of monopolistic competition, which De Fraja (2004, p.29) suggests may be appropriate for thinking about the market situation of lower status universities. As a market form, monopolistic competition has the following characteristics (see Mankiw, 1997, pp.363-370 for a textbook overview; and Archibald, 1987, pp.531-535): 1) many firms competing for the same group of customers; 2) product differentiation, so that with a product that is at least slightly different from

those of its competitors a firm has some market power (i.e., demand is not infinitely elastic); and

3) there is free entry (i.e., there is nothing to stop other firms from supplying much the same product).

The outcomes for firms in this type of market differ between the short run and the long run. The short run is defined as the period in which firms can maintain market power against competitors by producing a significantly differentiated product. This means that in the short run, the outcomes are similar to those of the “market power” model, in which the ability to generate revenue in excess of costs varies inversely with price elasticity of demand. However, in the long run even low margins of revenue over costs stimulate new entrants to supply perfect or very close substitutes. As this supply increases, so profits are competed away. The eventual - long run – outcomes are similar to those of the “no market power” model, albeit with possible “excess capacity” (Archibald, 1991, p.533). To make profit in this kind of market, enterprises have continuously to innovate either to introduce new products to benefit from short-run market power and/or to maintain the distinctiveness of existing programmes to prevent profits being competed away by suppliers of close substitutes. Hence, in this type of market, the full panoply of methods of non-price competition is devoted to product differentiation. In the case of the HE market, features of awards that are valued and regarded as distinctive by prospective students both increase demand and make demand less price elastic and are thus sources of profit. In the remainder of this section, we link these well-known principles from the theory of monopolistic competition with specific features of the HE market: first with polarisation and hierarchy; and, second, with peer effects. As we have seen, both of these are highlighted by recent research in the economics of HE markets.

4.3.1 Monopolistic competition and polarisation in HE The tendency towards polarisation among HEIs (see Section 4, above) suggests a corresponding tendency towards homogenisation between and within HEIs at opposite poles. HEIs subject to similar processes of cumulative causation – the virtuous or vicious circles of reputation, selectivity, peer effects, research funding and staff quality and endowment income outlined in Section 4 – are likely to acquire structurally similar features, thereby creating a tendency towards homogenisation between HEIs within each “band” or “segment” of the HE market. Moreover, awards are stamped with the status of the institutions at which they are provided, hence

Page 32 of 81

creating a tendency towards homogenisation of the competitive position of awards within HEIs located at similar levels of the HE market. This analysis may be qualified in two ways to bring us closer to the actual process of competition in the English HE market. 1. Polarisation has not yet resulted in a fully realised bi-polar end state but, rather, is

a tendency that interacts with other influences to shape an emergent hierarchy in which competition among HEIs is likely to be limited (as suggested in Section 4, above) to overlapping “bands” of HEIs or “market segments”.

2. Although the general reputation of HEIs constrains the ability to differentiate awards by reputation, this possibility is not altogether eliminated.

The first qualification suggests that while it will be increasingly difficult for awards based in low-status HEIs to compete with similar awards based in higher status HEIs, there should be scope to compete to be the “best in the class”. Most HEIs have particular areas of excellence, which may reflect either strategic recruitment and investment policies and/or random outcomes of initiatives “from below”. Whatever their origin, such areas of excellence provide both

1. potentially countervailing influences to polarisation, which suggest overlapping bands rather than a simple bipolar HE market, and

2. a basis for continuously differentiating awards from those of competitors within the same band, so that market power is maintained and profits continue to be earned.

Accordingly, the theory of monopolistic competition yields insights into the modes of competition in the English HE market.

1. Awards with no distinctive characteristics – i.e., awards that are interchangeable with those of competitors – cannot generate profit.

2. For distinctive awards, the profit potential differs between the short run and the long run (short run is defined as the period during which competitors are unable to provide close substitutes; the long run pertains when so many close substitutes are available that the original award is no longer distinctive).

a. In the short term, a distinctive award can earn profit. The more an award signals distinctive features valued by potential students, the greater its potential market power, the higher its fee can be set and the greater its profitability.

b. In the long term competitors are likely to supply substitutes that erode profits until all suppliers are just covering costs. In addition, the corollary of easy market entry and corresponding supply increases is that awards in low-status HEIs tend to operate with excess capacity. The long-run position of awards thus tends towards zero profit and “empty seats”.

3. The theory suggests the need for continuous effort to prolong short-run profitability. The theory also suggests some broad principles for how this may be accomplished. In particular, awards with distinctive characteristics – i.e., a differentiated product – have potential for non-price competition.

a. Product differentiation and corresponding potential for non-price competition suggest that competition with similar institutions does not have to proceed wholly or even mainly on the basis of lower price.

Page 33 of 81

b. To the extent that awards can be relatively easily imitated – they cannot be patented or trademarked – barriers to entry have to be defended by continuous innovation to maintain distinctiveness.

c. Successful non-price strategies to maintain the distinctiveness of an award may perpetuate short-term market power and profitability.

d. Because award reputations are substantially determined by institutional reputations, feasible product differentiation is likely to occur within rather than between bands; although a truly outstanding award might prove to be an exception.

e. Differentiation is only sustainable if it is not easily imitated. The corollary is that “Gimmicks” a source of one-off temporary advantage only.

In the next Section, we discuss how peer effects may be interpreted as a means of non-price competition within the HE market and, in particular, how policies influencing peer effects may also affect the relative position of low-status HEIs within their own segment.

4.3.2 Monopolistic competition and peer effects in HE Among the implications of monopolistic completion in the HE market identified above is that the more an award signals distinctive features valued by potential students the higher its fee can be set and the greater its profitability. In Section 3.2, we established that a desirable peer group is prominent among the distinctive features valued by potential students. While most empirical studies in the economics literature have focussed on peer effects in high status US HEIs, recent sociological research suggests that peer effects may have important implications for the competitive position of low-status HEIs in the UK. According to Pugh et al. (2005):

Currently, the age participation rate for young people from the highest socio-economic group is nearly six times that for the lowest, a ratio that has hardly changed as overall participation rates more than doubled over the last decade … This difference in participation by social class has been sustained over a time period where historical differences by gender and race have been reduced and even reversed.

Moreover, Reay et al. (2001, p.858) demonstrate that this persistent inequality by social class intersects with hierarchical tendencies in English HE. They argue that attention also needs to be given to the distribution of entries, which displays a divide ‘between the old and the new sectors of higher education’.

In contemporary Britain, with the transition from elite to majority system, higher education is going through a process of increased stratification … There is a political rhetoric of widening access … Yet … while more working class and minority students are entering university, for the most part they are entering different universities to their middle-class counterparts.

Of particular interest, from the perspective of market strategy for new (modern) universities is the focus of Reay et al. (2001) on non-traditional – i.e., working class and/or minority - students, ‘who as recently as ten years ago would have been very

Page 34 of 81

unlikely to be applying to university’, and who are precisely the type of students most likely to be recruited by new (modern) universities.7 Reay et al. (2001) conclude from survey and qualitative evidence that students and their parents, especially those of traditional students, want to benefit from the traditional student peer group at ‘old’ universities and thus tend to avoid ‘new’ universities associated with widening participation of non-traditional students.8 They illustrate this point with a quote from “Simon”, a white, middle-class university applicant:

I wouldn’t like to be spending … I don’t think I would actually get on with people if they got very bad grades and then got into a bad university, due to the simple class of persons there … bottom of the intellect and who deserved to be there academically. I like more intelligent conversation.

However, perhaps more revealing is the importance attached to peer group by “aspiring” working class potential applicants for HE (Reay et al., 2001, p.865). The following quotations are presented by the authors as illustrative. “Candice”, a black, working class student (Reay et al., 2001, p.866):

Because you want to go to a good university … I’ve sort of avoided all the universities with lots of black students because they’re all the universities which aren’t seen as so good. If you’re black and not very middle class and want to do well then you end up choosing places where people like you don’t go …

For “Julia” and “Lesley” , ‘both white and working class … the good university is conflated with places where there are “few people like me” … they have avoided universities with students like themselves’(Reay et al., 2001, p.867). Julia insists that

the kind of place that would have accepted me for a degree isn’t the kind of place that I would have wanted to go to … I didn’t want to go somewhere that would accept me as I was, because I’d had GCSEs and two failed attempts at A levels.

While ‘Lesley ironically sums up the problematic for students like herself’:

I would rather not do a degree than do my degree at the University of North London … It’s a bit like, you know, that Groucho remark, I don’t want to be a member of any club that will have me.

7 By “middle class”, Reay et al. (2001, p.860) refer to ‘students from families in groups I and II of the Registrar General’s social class groupings’; “working class refers to students from families in groups III Manual, IV and V’. 8 ‘Traditional students’ come from a family background having previous experiences of higher education and high participation rates, while ‘non-traditional’ students come from groups with low participation rates (Pugh et al., 2005, p.29).

Page 35 of 81

This evidence suggests that not only traditional, middle-class applicants are potentially deterred by perceptions of peer effects at new universities, but that a similarly adverse effect may be prevalent among aspiring non-traditional working class and minority applicants. In particular, it is ironic that such adverse perceptions seem to apply with particular force to universities with a reputation for widening participation (such as North London). If so, this needs to be taken into account by decision makers in modern universities. Following the US example by using ability-based scholarships to improve peer group quality is consistent with the criterion of efficiency (or profit maximisation), although not necessarily with the criterion of equity. Conversely, if needs-based scholarships lower peer quality then any deterrent effect on the recruitment of aspiring working class and minority students may entail a trade-off between equity and efficiency. The sociological evidence for the possibility of such a negative response is consistent with US evidence suggesting that low-ability peers exert negative effects on the performance of mid-ability student (Winston and Zimmerman, 2004, p.417), in which case such a response could be a rational reaction on the part of the more motivated and able working class and minority students.

4.3.3 A note on monopsony in HE markets Monopsony is the mirror image of monopolistic competition. It refers to the market structure in which a single buyer confronts many potential suppliers. The theory of monopsony suggests that powerful buyers do not allow their suppliers to charge them more than just enough to cover costs. A typical example would be a supermarket chain in relation to contracted manufacturers. In HE, a sponsor able to grant significant numbers of scholarships is likely to be in an analogous position in relation to suppliers of suitable awards. (The NHS “benchmark pricing” approach to training provision – whereby it sets both the number of students and the fee per student - may be an example of this; although a tender and award system would have a similar outcome.) The main reason is that the sponsor reduces an award to a state of financial dependence such that withdrawal of funding would threaten the viability of the award. This entails a high level of risk and renders awards with limited market power unable to set fees at a profitable level (i.e., the sponsor will set a level of support sufficient to enable the award to cover its costs but no more). Of course, there are aspects of monopsony in the relation of HEFCE with English HEIs generally. This implies a general lack of profit for HEIs insofar as they are dependent on HEFCE funding.

4.4 Award with limited market power (II): oligopoly The Higher Education Funding Council for England (HEFCE) tacitly assumes that English HEIs are not all competing for students against the 100 or so others in the English HE system.9 Instead, an HEI like Staffordshire competes mainly with a few 9 This assumption is consistent with conclusions reached by The National Committee of Inquiry into Higher Education (1997), which as well as recommending the introduction of performance indicators also suggested that a means should be found of allowing different institutions to be compared. Its suggested method, of dividing institutions into ‘families’ containing those with similar characteristics and aspirations, was rejected by the Performance Indicators Steering Group, as it was felt that a fixed division of institutions into groups would not be helpful. However, the group accepted the principle

Page 36 of 81

other post-1992 universities in the same region. To the extent that these HEIs are aware of one another and strategically interact, then this type of competition can be analysed by the theory of the market structure known as oligopoly. In this case, Staffordshire University does not compete in a monopolistically competitive national market, where there are many university providers, but on a regional basis with a few self-selecting universities such as MMU, UCE, LJM, Wolverhampton and Derby. Hence, an oligopoly is defined as a market where there are relatively few firms in direct competition (Gravelle and Rees, 2004: 400). Also, firms in oligopoly tend to offer differentiated goods and services as do universities. In addition, two important characteristics separate oligopoly from monopolistic competition. Firstly, there are barriers to entry (and exit) with an oligopoly similar to a monopoly in this respect but unlike monopolistic competition. At the firm-level this feature tends to occur because there are few new entrants in the short-run; although, at the product-level, universities can provide new awards relatively straightforwardly. Secondly and most importantly, firms in an oligopoly recognise there is strategic interdependence, because there are only a few firms operating in the market or regional market (Sloman, 2006: 182). Therefore, a firm is affected by the decisions of its rivals in the same way as the firm will affect the rival by its own decisions. As a consequence of strategic interdependence, a firm operating under oligopoly is pulled in two opposite directions. One is to compete (non-collusive oligopoly) and the other to collude (collusive oligopoly). The former will allow joint profit-maximising between firms, but is illegal under UK and EU company law; whereas the latter is legal but tends to result in fierce and costly wars conducted by price and advertising amongst other means (Krugman and Wells, 2006: 367). Since neither extreme outcome is desirable (that is, acting profitably but illegally or acting less than profitably but legally), there tends to be tacit collusion between firms in an oligopoly where one firm will take the lead on price-setting. There are two types of tacit collusion on price.

1. dominant firm price leadership, where a firm with a greater market share will set price and the other firms follow; and

2. barometer firm price leadership, where a firm with the greatest reputation will set the price and the other firms follow.

Over recent years the economics literature on oligopoly has been dominated by the Game Theoretic approach to analysing strategic interdependence, which provides a cogent analysis of strategic interdependence for a few firms where there is scope for price-setting by individual firms. The type of game typically used to model business interactions is the prisoners’ dilemma. Figure 3 applies the principles of the prisoners’ dilemma to analyse the strategic interdependence of two universities and the outcome of their fee-setting decisions. University 1 may be thought of as Staffordshire, while University 2 denotes a composite of all relevant rivals (as noted above). This game models the kind of situation in which a university and its competitors are in a market where 1. there is interdependence, such that the outcome of (say) pricing decisions depends

on the reactions of competitors, 2. they cannot formally collude (non-cooperation), and that indicators needed to be viewed in the context of the institution’s circumstances, and only compared with others in similar circumstances. Therefore it introduced the concept of an ‘adjusted sector average’, or benchmark, for comparison. (Text paraphrased from HEFCE, 2006, p.11.)

Page 37 of 81

3. whose objectives differ (conflict). Figure 3: The Prisoners’ Dilemma applied to fee setting in higher education

University Two

High fee

Low fee

High fee

2: 2

Both universities make high profit)

-1: 3

University 1’s profit collapses; University 2’s makes very high

profit

University One

Low fee

3: -1

University 2’s profit collapses; University 1’s makes very high

profit

0: 0

Price war (resulting in both

universities making zero profit; i.e., break-even or just covering

costs) *

* The Nash Equilibrium or dominant strategy Source: own example derived from established principles. The numbers in each cell denote profit levels. For example, in Cell 1 (top left-hand) both universities set high fees and make a high profit of two. There can be no formal collusion between institutions to bring about this high fee, high profit outcome, since this is illegal. However, through one or other form of price leadership, tacit collusion is a possibility. Yet this model demonstrates that such tacit collusion is unstable in the sense that both universities have an incentive to compete rather than to collude. Moving clockwise from Cell 1, Cell 2 depicts the consequences of University 1 choosing to set high fees while University 2 sets low fees. Assuming all other factors constant, University 1 loses market share to University 2, with the result that University 1 makes a loss (-1) and University 2 makes a very high profit (3). Conversely, moving counter-clockwise from Cell 1, Cell 3 depicts the consequences of University 1 choosing to set low fees while University 2 continues to set high fees. Here it is University 1 that gains market share and profit at the expense of University 2. Cells 2 and 3 also depict unstable situations, for once one university sets low fees the other has an overwhelming incentive to follow. Cell 4, finally, depicts the outcome of both universities setting low fees; namely, they both make zero profit (i.e., they both break even in the sense of covering all costs, which include such investment as is necessary for sustainability). This, finally, is the uniquely stable situation called the

Page 38 of 81

Nash Equilibrium. Cell 4 is such an equilibrium, because market-based incentives drive both universities to move from Cell 1 towards Cell 4, and it is only in Cell 4 that there is no incentive for either university to change its pricing policy. Only in the situation depicted in Cell 4 (low fees - zero profit) is each player doing as well as possible given the actions of the other players. In any other situation, the model predicts a price war, the outcome of which will be the situation depicted in Cell 4.

4.4.1 Principles arising from oligopoly theory The economic literature on oligopolies suggests three main principles. For HEIs formal collusion provides the most favourable outcomes. However, for HEIs as for all other forms of commercial enterprise, collusion is illegal. Indeed, University policy makers might do well to follow the details and outcome of the Office of Fair Trading inquiry into allegations of a fee-fixing cartel among leading independent schools in breach of the Competition Act. In March 2006, the Office of Fair Trading provisionally found Fifty of England's top independent schools to be in breach of the Competition Act 1998, which came into force in 2000, by sharing information about fees. In a provisional finding, it said this meant parents were charged higher fees than they otherwise would have been (See BBC News, 09/11/2005: http://news.bbc.co.uk/1/hi/education/4420822.stm).10 Given that collusion is illegal, tacit collusion may allow informal communication between firms. However, game theory suggests that tacit collusion is unstable, likely to give way to price wars ending in a low-fee, low-profit equilibrium. This suggests that even if university decision makers choose not to start a price war, they should be prepared to respond if one does break out. Conversely, to the extent that an HEI already occupies a low-fee, low profit equilibrium, then price variation is precluded as a competitive strategy. In principle, price competition includes such incentives as bursaries, which are a discount on the university fee. If price competition is precluded, then decision makers need to concentrate on non-price competition as the main way of competing against rival institutions, focussing on innovation and corporate branding.

10 At the onset of the investigation, the Daily Telegraph (16/09/2003) commented as follows: ‘This much seems to emerge without doubt from the emails that circulated between the bursars of many of our most famous schools and have now become public. These conscientious men appear to have gone about their work of comparing the proposed fee increases at their schools in a rather innocent way, with little understanding that what they were doing might be in breach of competition law. It is true that, when Bill Organ, the bursar of Winchester, sent his governors a note giving the fee increases at 20 leading schools and suggesting, in the light of this information, that Winchester should raise its fees by nine per cent, he did include the words: "Confidential, please, so we aren't accused of being in a cartel." But the bursars believed, I am sure, that they were fulfilling their duty to their schools to maximise income while minimising the risk that parents might go elsewhere.’

Page 39 of 81

5 Optimal fees and threshold effects 11 Market power and no market power - cases 1 and 2 in the previous section - are extremes. They are benchmarks to guide thinking about setting fees for actual awards that, in practice may have some rather than much or zero market power. However, these benchmark principles may be directly applicable to awards that serve particular types of student; namely, local part-time and international. 1. The discussion of awards with market power (Case 1) is directly relevant to

decision making about part-time fees, particularly to the extent that local markets are relatively insulated from competition. This is consistent with evidence of ‘some degree of price discrimination against nearby residents’ uncovered by Epple et al. (2003, p.42).

2. The award with no market power (Case 2) is more relevant to setting fees for international students, who potentially choose between a wide range of awards offered by universities across the English-speaking world (and beyond, given the global trend towards English language awards).

In this case, why are part-time fees generally lower than international fees? To clarify this apparent anomaly, we consider the problem of optimal fees from the perspective of the potential student. In principle, a student’s decision regarding higher education has the same structure as any investment decision: if the net present value of the investment is positive, then there is a case for the investment. This condition is satisfied if the present value of the lifetime benefits of higher education (i.e., all future benefits discounted to give a single “present value”) exceeds the total costs of acquiring higher education. To this may be added an important qualification that is of particular importance for universities engaged in widening participation. In general, the greater the uncertainty of future returns, the greater the margin over costs that is required before undertaking any investment (Dixit and Pindyck, 1994). In the case of potential students, this applies with particular force to “non-traditional” entrants, whose lack of “cultural capital” typically reduces their access to the information required for an informed choice (Pugh et al., 2005, pp.31-33). The implication is that “non-traditional” entrants require a higher rate of return than “traditional” entrants. Of course, better information may help to close the gap.

5.1 Assumptions We assume that a student’s lifetime return from higher education is positively influenced by: 1. the student’s own ability; 2. the skill premium (i.e., the additional earnings arising from higher education),

which depends on a. the ratio of skilled to unskilled workers in the economy (the higher the

ratio, the lower the return) and b. the quality of education provided by the university (the higher the quality,

the higher the return). 11 Much of this section is derived from Gary-Bobo and Trannoy (2004).

Page 40 of 81

Conversely, lifetime return is negatively influenced by: 1. the opportunity costs of foregone earnings while studying; 2. living costs; and 3. tuition fees. As in any investment decision, current costs are weighted more highly than future returns, because future sums of money are less valuable than present sums; and the more so, the greater the degree of uncertainly about the future sums.

5.2 The “study threshold” The student’s lifetime returns will be positive if and only if the positive contribution of “own ability” exceeds the combined influence of the other factors. This condition is set out in Figure 4. Figure 4: Student’s return on investment in higher education

+++

>

education ofQuality - feesTuition

costs Living earnings Foregone

economy in unskilled:skilled Ratio of Influence

ability sstudent' of Influence

ifonly and if positive HE Return to

The higher the right-hand side, the higher the student’s

study (i.e., participation) threshold. The “study threshold” is the point where the two sides of this equation are equal. This is the point at which the potential student is indifferent between participating and not participating in HE. For potential students to choose to study, the HEI has to assist them over this threshold. To do this, the HEI can influence only (or, at least, mainly)

1. tuition fees (a negative influence on student demand) and 2. the quality of education (a positive influence on student demand).

Reducing tuition fees and/or increasing the quality of the education both reduce the right-hand side of the equation, thereby lowering the study threshold and encouraging participation in HE among marginal individuals for whom it would previously not have been worthwhile.

Page 41 of 81

The participation decisions of high-ability students will be unaffected by fee and quality changes. For high-ability students, positive returns from their investment in HE are not in question. Even with high fees and low quality of education, high ability students can expect a positive return on their investment. In contrast, low-ability students are likely to be marginal with respect to this “study threshold”. To the extent that the influence of students’ own ability on returns is lower (on the left-hand side of the equation), HEIs can help to ensure that low-ability students exceed the “study threshold” by either reducing tuition and/or raising the quality of education (on the right-hand side). This is consistent with current proposals for HND students; namely, in relation to students on degree programmes, to combine lower fees with more tuition. This may be an economically rational strategy if this policy mix is consistent with covering costs. Of course, even if costs are not fully covered, there may be overriding educational/social priorities for enabling potential HND students to exceed the “study threshold”. However, this does imply cross-subsidy from other activities. This concept of the “study threshold” also helps to explain why part-time fees are generally lower than international fees. The student’s own assessment of the influence of her or his own ability on returns to higher education is not observable but highly subjective. In Stoke-on-Trent in particular, low self-esteem and correspondingly low aspirations among secondary students limits both achievement and staying on rates. This is acknowledged, for example, by the Local Education Authority, which has recently invested substantial sums in school-level programmes designed to build self-esteem and aspirations. Accordingly, in terms of our equation, a particular problem for Staffordshire University is that many of our potential part-time students greatly under-estimate their potential returns from education. In addition, the cumulative impact of low staying-on rates and low participation in higher education is lack of the cultural capital needed for informed choices. This increases the uncertainty surrounding returns to investment in higher education and thus raises the “study threshold” of Staffordshire University’s potential part-time students (in effect, by adding the influence of uncertainty to the left-hand side of the equation).12 Accordingly, until reforms in local schooling make a difference, Staffordshire University may have no alternative but to respond to these characteristics of its local market with lower tuition fees; subject, of course, to covering costs or some overriding reason for staying in the part-time market. Alternatively, influencing local perceptions of the quality of education and, correspondingly, the expected returns would have the same effect.

5.3 Some principles Some implications of the “study threshold” and underlying theory of investment in human capital are as follows.

12 The greater the uncertainty surrounding the returns to HE, the greater the risk for applicants and the greater the return required to compensate their risk. Hence, the more uncertain are potential applicants about their own abilities and corresponding future returns to HE, the higher the study threshold.

Page 42 of 81

1. A student’s demand for higher education is positively related to ability. Hence, tuition fees can be positively related to ability. However, this principle may, to a greater or lesser extent, be by either offset by peer and reputation effects and/or reinforced by equity criteria.

2. The University must know its own award-specific costs to determine the extent to which it can

a. offer low-ability students discounted fees and/or additional tuition, and b. offer “non-traditional” students discounted fees and/or additional

tuition. 3. To be fully useful as a guide to policy making, economic analysis must be

informed by the wider knowledge base of research into higher education; in particular, into the determinants of student demand and widening participation.

4. In many markets, adjustment towards market price takes place very slowly (the labour and housing markets in the UK are two major examples). Accordingly, as the example of HND policy illustrates, a process of ad hoc (trial and error) annual adjustment may - but need not - yield a good approximation to optimal outcomes.

6 Fee subsidies: impact on entry rates and impact on completion rates

In this section, we survey recent empirical evidence on the impact of financial support on

1. student enrolment (i.e., participation) in higher education, 2. student completion (hence, retention), and - to a more limited extent - 3. student choice of HEI.

This empirical literature has a particular focus on students from low-income families Avery and Hoxby, 2004, p.241). All the studies currently published are from the US, and all focus on full-time students who are US citizens (even when data on other types of students is available; see, for example, Linsenmeier et al., 2001, p.7-8). However, this recent empirical literature does yield insights and underpinning evidence for more widely applicable principles. In brief, the evidence discussed in this section suggests that the benefits of subsidy include

4. increased recruitment, 5. enhanced retention (if scheme appropriately designed), and 6. reduces the influence of socio-economic status on the choice of HEI.

However, the evidence also suggest that to be effective subsidies need to be large in relation to the total costs of studying (not just in relation to fees).

6.1 Student enrolment (i.e., participation) in HE In theory, subsidising students should have the effect of increasing participation in higher education:

Page 43 of 81

Our standard model of human capital predicts that such cost subsidies will raise the optimal level of schooling (Dynarski, 2002, p.279).

This assumption informs the argument in the previous section (see Figure 4). However, corresponding empirical evidence in sparse and generating it remains a challenge:

Despite the dollars devoted to aid programmes … there is little evidence that these subsidies serve their goal of increasing college attendance … Determining whether aid expands access to college is an empirical challenge (Dynarski, 2003, p.279).

In attempting to anticipate the implications of removing the £3,000 cap on tuition fees, US studies provide the most useful source of evidence on the effects of variable fees on attendance rates, completion rates and choice of HEI. This evidence is surveyed by Dynarski (2002), who notes (p.1) that, in the US:

… the direct cost of schooling (i.e., of higher education) is quite heterogeneous. First, tuition prices vary widely across schools. During the 2000-2001 academic year, college tuitions varied from zero at some community colleges to over $27,000 at Ivy League institutions. Second, institutions heavily discount these “sticker” prices for many students, using detailed information on family finances and academic merit to engage in finely-tuned price discrimination.

Dynarski (2002, p.1) warns that most empirical studies on the effects of tuition costs are flawed, because the response of schooling to price is poorly identified.

That is, variation in schooling prices that identifies its effect on schooling is not exogenous to unobserved determinants of schooling.

For example, if unobserved ability influences both participation and financial aid, then it becomes very difficult to identify the independent effect of financial aid on participation.13 Dynarski’s (2002) alternative to studies suffering from this methodological flaw is to examine

13 Linsenmeier et al. (2001, p.2) make a similar point concerning the methodological shortcomings of previous studies on the impact of tuition fees on enrolment decisions, the effects of different types of financial aid on student enrolment, and the effects of college costs on enrolment at a particular institution: ‘A potential problem with many of these papers is that the data lack a source of variation in college costs of financial aid composition that is exogenous to student characteristics. College financial aid offers often depend on the characteristics of the student; students who are considered more desirable by the college administration may receive more generous offers. Hence, college costs and financial aid packages are likely to be correlated with student characteristics. As a result, in a regression of the attendance decision on net college cost, it is difficult to identify the independent effect of college cost. In particular, the coefficient on college cost may partially reflect the impact of unobserved characteristics of the student’ (emphasis added).

Page 44 of 81

work that has used quasi-experimental methodology to isolate exogenous sources of variation in schooling costs in order to determine their effect on schooling decisions.

Dynarski (2002, p.3) applies her preferred “quasi” or “natural experiment” approach to evaluate the effects of the Georgia Hope Scholarship programme on college attendance.

In 1993, Georgia introduced the Georgia Hope Scholarship … which allows free attendance at Georgia’s public colleges for state residents with at least a B average in high school. Those attending private colleges are eligible for an annual grant … $3,000 by 1996.

She uses Current Population Survey data from each year 1989-97 to identify the effect of the Hope Scholarship through ‘relative changes (i.e., changes from before to after introduction) between Georgia and the rest of the southeastern United States in college attendance rates. Dynarski’s (2002, p.4) econometric estimates of these relative changes ‘suggest that for each $1,000 of subsidy, the college attendance rate rises by four to six percentage points’. However, ‘this effect is almost fully concentrated among white and upper-income youth’, because,

1. poorer scholarship recipients had other sources of funding reduced, and 2. a lower proportion of low-income, black youth meeting the academic

requirement of the scholarship. Linsenmeier et al. (2001) use a similar approach to evaluate the impact of enhanced financial support for low-income students - around $4,000 per year from 1998-99 - at a major selective university in the northeastern US (NEU).14 The study focuses on US citizens and measures the change in the probability of acceptance of the offer of admission to NEU caused by the policy change. The main findings advanced by Linsenmeier et al. (2001, pp.22-23) are that the policy change increased the likelihood of enrolment by low-income students by about three percentage points, ‘although the effect is not statistically significant’. In contrast: ‘The effect among low-income minority students was about twice that size and statistically significant at the 10 percent level.’ Linsenmeier et al. (2001) discuss the corresponding questions arising from these results. First: ‘Why didn’t NEU’s change from loans to grants have a statistically discernable impact on the overall yield rate among low-income applicants?’ The authors suggest two explanations.

1. Because ‘the change in financial aid (loan replacements of approximately $4,000 per year) was fairly small relative to the average financial aid package of low-income students - $25,734, of which an average of about $20,000

14 Financial aid for low-income students consists of three components: grants, loans, and jobs (Linsenmeier et al., 2001, pp.4-6). ‘The cost of attending NEU rose from $27,729 in 1988 to $34,171 in 2000, and NEU’s financial aid packages grew along with it. (All dollar figures … are expressed in 1999 dollars …). In 1988, the standard financial aid package included $2,028 in job aid, rising slightly to $2,109 in 2000. Over the same period, the base loan amount increased from $3,731 to $4,063, and the remaining grant component increased from a median of $11,865 to $14,842 … The new policy … made NEU more attractive to low-income students by giving them grants in place of the loans … a low-income student who would have been expected to borrow $4,000 per year was instead given an additional $4,000 in grants … The total amount of financial aid was not affected, only its composition.’

Page 45 of 81

would have been in grants … It may be that this incremental change was too small to have had a detectable effect on enrolment decisions’ (Linsenmeier et al., 2001, p.20).

2. A ‘closely related possibility is that the underlying elasticity may be small, so the effect of a program of this size was not big enough to be estimated precisely given the inherent noisiness of the process’ (Linsenmeier et al., 2001, p.20).

Second (Linsenmeier et al., 2001, p.21): why did the program appear ‘to have had a larger effect on the matriculation of minority students?’. Here, the authors offer the following explanation (Linsenmeier et al., 2001, p.22):

… although we have no direct evidence, the result is consistent with differing perceptions between minorities and non-minorities about the cost of financing college through loans. Such differences may be due to greater uncertainty among minorities about the future returns to college education, and hence ability to repay loans.

From this, the authors conclude with some useful advice to researchers and policy makers in the area:

While it is perilous to generalise on the basis of the experience of a single institution, an important lesson emerges from our analysis: within the population of low-income students, program effects may vary with race and ethnicity. This possibility should be taken into account in the design and analysis of such programs.

Another “natural experiment” was provided by the 1981 decision of the US Congress to abolish the Social Security student benefit programme, ‘which at its peak provided grants totalling $3.9 billion a year … to one out of eight college students’ (Dynarski, 2003, p.279). In 1980, the average annual payment to the child of a deceased parent was $6,700, which was large compared to the then costs of tuition in both public universities and private four-year colleges (respectively, $1,900 and $7,100). This large and sharp policy change affected some students but not others. Accordingly, Dynarski (2003) uses this as a source of variation in student aid that is exogenous to unobserved student attributes that influence college attendance and, hence, suitable to isolate - and so identify - the incentive effect of aid on college attendance. In contrast to Linsenmeier et al. (2001), Dynarski (2003) evaluates the effect of large financial incentives on the participation of relatively low-income families (who, moreover, were more likely to be black). Moreover, Dynarski’s (2003) results pertain to participation in general rather than to entry into one selective university. She finds that aid eligibility increases the probability of attending college by age 23 by 24.3 percentage points, which is a statistically significant and robust result. She also finds evidence that, although not statistically significant, suggests an increase in the probability of completing at least one year of college by 16.1 percentage points. In addition, she combines these results with data on the opportunity cost of attending college to obtain an elasticity of attendance with respect to schooling costs of about 1.5: i.e.,

Page 46 of 81

5.1college attending ofcost in the change Percentage

college attending students ofnumber in the change Percentage−=

In other words, a 10 percent reduction in total costs - other factors remaining unchanged - would increase participation among these relatively low income and disproportionately black students by 15 percent. Dynarski’s (2003) finds large and statistically significant effects from large financial incentives. These contrast with the smaller and, even in the case of minorities, less statistically significant and smaller effects from smaller financial incentives. This is consistent with a suggestion from Dynarski (2003, note 29; emphasis added) concerning the possibility of heterogeneity in the response to aid:

It is plausible that the effect of aid is non-linear. For example, in the presence of liquidity constraints (i.e., obstacles to borrowing to finance higher education), a threshold amount of aid may be needed to affect behaviour, leading a large grant to have a larger per-dollar effect than a small grant. It is also plausible that the marginal effect of aid falls as aid rises. Further, a given dollar of aid may have a different effect on a student who is on the margin of entering college as compared to one who is on the margin of completing college.

If we take these remarks in conjunction with the advice of Linsenmeier et al. (2001) concerning possible variations in the effect of aid between different ethnic groups, then we may conclude that recent empirical studies yield insights rather than transferable effect sizes.

6.2 Student completion (retention) The starting point of Dynarski’s (2004) empirical investigation of state tuition policy and degree completion is the observation that:

A handful of well-identified studies has established that tuition subsidies increase college entry, but the evidence they increase college completion is weak (Dynarski, 2004, p.1).

Of the three previous studies on completion rates, one is of doubtful relevance (focussing on veterans’ educational benefits), one finds positive effects but cautions that these estimates are sensitive to specification, and Dynarski (2003) finds positive effects but the estimates lack statistical significance (see above). Dynarski (2004) investigates the effect of student aid on completion of higher education by estimating the impact of merit aid programmes, which were introduced in 12 US states during the 1990s (Dynarski, 2004, pp.2 and 5-6): these programmes ‘waive tuition and fees for students who achieve a minimum GPA in high school, typically 3.0, and maintain a minimum GPA in college, typically 2.5 to 3.0’. Accordingly, whereas traditional merit aid programs ‘subsidised only the highest-performing students’ who ‘are unlikely to alter their decisions to complete a degree based on whether they receive the subsidy’, these ‘newer merit programs are open to

Page 47 of 81

larger numbers of students who are of modest academic ability’ so that in each of the 12 programs ‘at least 30 percent of high school seniors have grades and test scores that qualify them for an award’. Typical examples of the value of merit aid are Arkansas ($2,500 for both public and private universities) and Georgia (the value of tuition/fees for public and $3,000 for private universities). Dynarski’s (2004, p.6) methodological approach is, again, that of the natural experiment:

I use a treatment-control approach, comparing educational outcomes in states that do and do not introduce merit aid programs. States that never introduced merit programs, or introduced them after the period under analysis, constitute the control group. Relative changes in educational attainment in the states that introduce merit aid identify the effect of merit aid.

The sample analysed consists of 22- to 34-year olds in the 2000 census, corresponding to the high school classes of 1984 through 1996. The census includes measures of degree completion as well as a wide variety of control variables. Dynarski (2004, pp.10 and 19) finds the following statistically significant results:

… the share of individuals who completed an AA rose by one percentage point among those born in merit states, relative to those born in the rest of the South, when a merit program was introduced …The estimate is economically significant: the baseline probability of AA receipt is 6.6 percent. The analogous estimate for completing a BA is … two to three percentage points. … the baseline probability of completing a BA (is) 21.5 percent).

In addition, Dynarski (2004) finds a positive spillover effect on the probability of completing an MA degree, even though postgraduate education is not subject to merit program subsidy. Dynarski (2004, p.18) is unable to isolate the purely financial impact of the programme on demand, because

1. ‘merit aid programmes tend to lead to a moderate increase in tuition prices, which affects those who are not eligible for the merit aid programmes’, and

2. the estimates ‘also reflect the effect of merit aid on effort in high school’. Consequently, demand elasticity cannot be isolated and ‘results should be extrapolated to other subsidy programs with caution’. However, by combining results in this study with previous college entry analysis, Dynarski (2004, p.19) is able to conclude that ‘merit programs increase college entry by about twice as much as they increase degree completion’. Bettinger (2004) investigates the causal relationship between needs-based financial aid and student retention. In particular, he focuses on the effects of the Pell Grant programme, which ‘is the largest means-tested financial assistance available to post-secondary students across the United States’, on ‘student persistence between the first and second year of college in adjacent years’ (Bettinger, 2004, pp.207 and 231). His survey of the small number of relevant previous studies suggests that Pell Grants have ‘had either no effect or a very small positive effect on enrolment’, and previous studies on financial aid more generally find a positive effect on retention (Bettinger,

Page 48 of 81

2004, pp.213 and 219). Using a unique database made accessible by privileged access to anonymous student data from Ohio’s public universities, he employs a variety of ingenious empirical strategies yielding results supporting the following conclusions (Bettinger, 2004, p.230).

The panel identification results suggest strongly that a Pell Grant reduces dropout rates. The regression-discontinuity results show similar results although they are more fragile.

Bettinger’s evidence, combined with Drnarski (2003) suggests that ‘need-based aid affected both enrolment and completion’ (Bettinger, 2004, p.231). ‘Most importantly’ (Bettinger, 2004, p.230):

… it implies that federal and state need-based policies and aid matter and that they influence the likelihood that students continue from year to year in college.

Moreover: ‘The finding that aid increases persistence may suggest that front-loading financial aid programs may improve student retention in the first years of college’ (Bettinger, 2004, p.230). However, further research ‘examining the effect of financial aid on retention over a longer stretch of time may be important’ (Bettinger, 2004, p.232).

6.3 student choice of HEI Dynarski (2003) extends her analysis by distinguishing between the substitution effects of student benefits, whereby students on the margin are influenced between non-participation and participation, and the income effect, whereby infra-marginal students (those who would participate even in the absence of benefits) alters the quality of the HEI attended (e.g., private or public, two-year or four-year colleges). Because the data is insufficient for formal estimation of this income effect on school choice, Dynarski (2003, p.20) uses results from a 1972 Social Security Administration survey of student beneficiaries to gain some insight into this issue. She concludes as follows (emphasis added):

Overall, then, those receiving Social Security student benefits made schooling choices much like those of the typical college student. This is remarkable, since the beneficiary population was disproportionately black and low-income. In 1972, 12.5 percent of college-going beneficiaries were black, as compared to 8.3 percent of all college students of the same age. More than half of college student beneficiaries had family incomes below $39,000, while only 35 percent of all families with a full-time student between the ages of 18 and 24 fell into that income range. That the college choices of this group look much like the average student suggests that Social Security student benefits influenced not only the level of education chosen but the quality of the school attended, as well. The benefits appear to have played a compensatory function, inducing them to make schooling choices like students of higher socio-economic status.

Page 49 of 81

If we apply this finding to the likely coming of differential fees in English HE, then - assuming that fees rise substantially in high status HEIs but remain at much the same level elsewhere - one consequence might be that students from low-income families are no longer able “to make schooling choices like students of higher socio-economic status”. In this case, we may anticipate displacement of infra-marginal students from higher status and more expensive to lower status and cheaper HEIs. However, if differential fees were to be accompanied by ‘better funded scholarships and a well thought out income contingent loan scheme’ then the impact on access ‘would be at worse neutral and could even have a positive impact’ (Greenaway and Haynes, 2003, p.F162). In this case, the potential displacement - and, hence, cross-price effects - of differential fees would be vitiated.

7 Do students make rational choices? Avery and Hoxby (2004) is unusual in that sophisticated econometric analysis of a large quantitative dataset on students’ college choices compiled from the authors’ own survey is complemented by qualitative insights drawn from open-ended questions included in the survey. Avery and Hoxby (2004, pp.239 and 240) investigate a large sample of high aptitude students,15 because such students both face a ‘complex system of financial supports’ for their college education and are those most ‘likely to … closely obey the model of the rational human capital investor’. The authors set themselves the task of ‘determining whether students were behaving like rational investors in their own human capital’ (Avery and Hoxby, 2004, p.280). Their answer is a ‘qualified yes’ (Avery and Hoxby, 2004, p.290).

Overall, we would describe the college choice behaviour of the high-aptitude students in our sample as sensitive to college attributes in the expected direction … they are sensitive to tuition, room, and board in the expected direction (lower is better). They are attracted by grants, loans, and work-study commitments. Although we find that students from different backgrounds do exhibit somewhat different college choice behaviour, the differences are not dramatic and much college choice behaviour is shared by the entire array of high-aptitude students (Avery and Hoxby, 2004, p.288).

Yet the choice behaviour of these high-aptitude students was not uniformly rational. One test constructed by the authors was to measure whether students’ college choices ‘responded as differently to grants, loans and subsidies as they should, given the very different degree of subsidy incorporated in these three forms of aid’ (Avery and Hoxby, 2004, p.274). They find that students ‘failed this test: they responded similarly to every additional $1,000, regardless of whether it was a grant or a loan’. Moreover, two additional findings also suggest departures from fully rational decision making. First, ‘for a grant of a given amount, calling it a scholarship increases the probability of matriculation by 86 percent of the prior probability’. Here, the authors comment: ‘This is a great effect for an essentially hollow feature of a grant that any college could replicate at no cost’ (Avery and Hoxby, 2004, p.276). Secondly: ‘Front-loading

15 These are students with very strong academic credentials. The average student in the sample was in the 90th percentile of Scholastic Aptitude Test (SAT) scores for all SAT takers (Avery and Hoxby, 2004, p.249).

Page 50 of 81

also engenders a strong, positive matriculation response. For a grant of a given annual amount, its being front-loaded raises the probability of matriculation by 48 percent of the prior probability. Again, this is a substantial effect for a feature that costs a college little for students who very likely to stay enrolled for four years … Because of discounting and inflation, front-loading does cost a college something but not much in comparison to the cost of inducing a student to attend by raising the amount of his grant’ (Avery and Hoxby, 2004, pp.276-278). Avery and Hoxby conclude (2004, p.289) as follows.

… the students in our sample exhibit some hard-to-justify responses to aid that they are offered. They are excessively attracted by loans and work study, given the value of these types of aid compared to grants. They are attracted by superficial aspects of a grant, like its being called a scholarship (with a name) and its being front-loaded … All these behaviours are deviations from the expected behaviour of a rational investor in human capital.

Finally, Avery and Hoxby (2004, pp.289-90) consider competing theoretical explanations of apparent irrationality in students’ college choice – namely, lack of sophistication and credit constraints - in the light of qualitative evidence generated by their survey.

A lack of sophistication accounts for at least some of the self-defeating responses to aid: credit constraints cannot explain why a student would be strongly attracted by a grant’s being called a scholarship (when it costs the college nothing to do it). A lack of sophistication probably also accounts for the attraction of front-loaded grants – an alternative explanation is impatience, but this seems unlikely in a population of students who so obviously do not exhibit impatience as a rule. They all have records that show that they can work hard now in return for gains in the distant future. Credit constraints are also not a good explanation for the attractiveness of front-loading, because a front-loaded grant does not reduce the credit needs of families who know that their child will be enrolled for four years … The overwhelming impression is that a lack of sophistication, and not credit constraints, is the problem. Over and over, these parents complain that they are baffled by the aid process. They argue that the colleges do not explain their offers well. They complain that other families are more “in the know” … we think it is revealing that words like “bewildering” and “confusing” are the modal words in their comments.

Finally, Avery and Hoxby (2004, p.289) advance evidence suggesting that the incidence of irrational student choices are inversely related to the socio-economic status of their families and, in particular, to parental experience with college choice.

We should note that these peculiar behaviours are generally not shared by the students whose parents have high incomes or who themselves attended very selective colleges.

Of course, it is not easy to derive principles from evidence of irrational behaviour. Even where there is evidence of irrational behaviour, policy makers should be cautious of making policies that assume irrational decision making by applicant. First,

Page 51 of 81

irrational behaviour is likely to be unpredictable. And, secondly, irrational behaviour is unlikely to be sustainable, because people learn! References Archibald, G. (1987) Monopolistic Competition, in: Eatwell, J., Milgate, M. and

Newman, P. (Eds) (1987) The New Palgrave Dictionary of Economics, Vol.3. London: The Macmillan Press.

Avery, C. and Hoxby, C. (2004) Do and Should Financial Aid Packages Affect Students’ College Choices? In: Hoxby, C. (2004), pp.239-299.

Berndt, E. (1991) The Practice of Econometrics. Reading, Mass.: Addison-Wesley. Bettinger, E. (2004) How Financial Aid Affects Persistence. In: Hoxby, C. (2004),

pp.207-233. Clotfelter, C. (1999) The Familiar but Curious Economics of Higher Education. The

Journal of Economic Perspectives, 13(1) (Winter), pp.3-12. Chevalier, A. and Conlon, G. (2003) Does it Pay to Attend a Prestigious University?.

Institute for the Study of Labor, Discussion Paper No.848 (August). Available on-line from www.iza.org

De Fraja, G. (2004) Education and Redistribution. Rivista Di Politica Economica, May-June. Version used available on-line, at http://www.rivistapoliticaeconomica.it/2004/mag-giu/DeFraja.pdf

Dixit, A. and Pyndyck, R. (1994) Investment under Uncertainty. Princeton, NJ: Princeton University press.

Dynarski, Susan (2002) The Behavioural and Distributional Implications of Aid for College. American Economic Review, 92(2), pp.279-285. Pre-publication on-line version available from Susan Dynarski’s website.

Dynarski, Susan (2003) Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion. American Economic Review, 93(1), pp.279-288. Pre-publication on-line version available from Susan Dynarski’s website.

Dynarski, Susan (2004) State Tuition Policy and Degree Completion. Harvard University, Kennedy School of Government (unpublished manuscript).

Epple, D., Romano, R. and Sieg, H. (2003). Peer Effects, Financial Aid and Selection of Students to Colleges and Universities: An Empirical Analysis. Journal of Applied Econometrics, 18, pp.501-25. Version used available on-line, in pre-publication form, at http://www.gsia.cmu.edu/afs/andrew/gsia/workproc/roster/full-time/epple/jae_brookings.pdf

Gary-Bobo, R. and Trannoy, A. (2004) Efficient Tuition Fees, Examinations, and Subsidies. CESifo Working Paper No.1189 (May 2004). On-line at:

Greenaway, D. and Haynes, M. (2003) Funding Higher Education in the UK: The Role of Fees and Loans. The Economic Journal, 113(485), pp.F150-F166.

HEFCE (2006) Review of performance indicators: Consultation to inform the review. Higher Education Funding Council for England (November 2006). Available on line (as of 13/09/2006) at: http://www.hefce.ac.uk/pubs/hefce/2006/06_34/06_34.pdf

Hoxby, C. (2004; Ed.) College Choices: The Economics of Where to Go, When to Go, and How to Pay for It. A National Bureau of Economic Research Conference Report. Chicago: University of Chicago Press.

Hoxby, C. (2004) Introduction. In: Hoxby, C. (2004), pp.1-12.

Page 52 of 81

Jacobs, B. and van der Ploeg, F. (2005) Guide to Reform of Higher Education: a

European Perspective. London: Centre for Economic Policy Research (September 2005) (forthcoming in Economic Policy). On-line at:

Linsenmeier, D., Rosen, H. and Rouse, C. (2001) Financial Aid Packages and College Enrolment Decisions: An Econometric Case Study. Princeton University Industrial Relations Section Working Paper 459.

Mankiw, G. (1997) Principles of Economics. London: The Dryden Press. Pugh, G., Coates, G. and Adnett, N. (2005) Performance Indicators and Widening

Participation in UK Higher Education. Higher Education Quarterly, 59(1) (January), pp.19-39.

Reay, D., Davies, J., David, M., and Ball, S. (2001) Choices of Degree or Degrees of Choice: Class, ‘Race’, and the Higher education Choice Process. Sociology, 35(4), pp.855-874.

Winston, G. (1999) Subsidies, Hierarch and Peers: The Awkward Economics of Higher Education. The Journal of Economic Perspectives, 13(1) (Winter), pp.13-36.

Winston, G. and Zimmerman, D. (2004) Peer Effects in Higher Education. In: Hoxby, C. (2004), pp.395-424.

Additional sources not cited Rolle, A (2003) Getting the Biggest Bang for the Educational Buck: An Empirical

Analysis of Public School Corporations as Budget Maximising Bureaus. In: Fowler, J. (2003; Ed.) Developments in School Finance: 2001-02. Washington: US Department of Education, Institute of Education Sciences, pp.25-53. On-line at:

Rothschild, M and White, L (1995) The Analytics of Pricing in Higher Education and other Services in which Customers are Inputs. Journal of Political Economy, 103 (June), pp.573-86.

Tobias, Justin (2003) Are returns to schooling concentrated among the most able?. A semiparametric analysis of the ability-earnings relationships. Oxford Bulletin of Economics and Statistics, 65(1), 1-29.

Page 53 of 81

Part 2: Applications

These applications are informed both by the research literature and by interviews with

Faculty Recruitment Managers in autumn 2006. The Report and the Executive

Summary explain and present principles that apply generally to HE pricing policy and

recruitment strategy. These Applications mainly highlight issues that are particular to

different types of award (postgraduate, HND, Foundation) modes of delivery (part-

time, distance) and/or market (local, international). In addition, we discuss issues

related to external sponsorship and placements.

Page 54 of 81

1. Postgraduate awards We consider taught and research awards separately.

Taught awards

Taught postgraduate awards are generally in very competitive markets. Setting fees

too high could price us out of the market. However, setting fees too low may not have

the desired effect on demand, because fees and entry requirements can act as signals

of quality. That low fees and/or entry requirements may not increase recruitment is

suggested by both recent research and some local experience.

Theory and evidence suggest that low fees and/or entry requirements may give rise to

a vicious circle of low-aptitude intake, poor peer group, adverse reputation effects,

recruitment declines, and downward pressure on fees. There is some local experience

that suggests a similar vicious circle of low fees and/or entry requirements, weak

intake, low retention, adverse reputation effects and downward pressure on fees.

Some policy implications:

1. Potential vicious circle effects can be induced by a weak intake.

2. Students, especially mid-ability, are very sensitive to peer effects (Section

3.2).

3. Both fees and entry requirements may be interpreted as signals of quality.

Hence, lower fees may not increase recruitment.

4. A source of competitive advantage for awards developed in less selective HEIs

may be delivery models – e.g., distance learning - in which the quality of the

award is less dependent on student interaction (Part 1, Section 4). This reduces

the importance of the local peer group. However, distance learning in its

various modes can be seen as second class in relation to campus education by

students, but may be attractive to external sponsors on cost grounds.∗

∗ The point about distance learning being seen as “second class” in relation to campus awards comes from discussion with one Faculty Recruitment Manager. In at least some international markets, there is anecdotal evidence that scholarships attract students onto distance learning awards, but that students would not be willing themselves to pay fees equivalent to the value of the scholarship.

Page 55 of 81

Research awards

Full-time The case for raising fees is that supervision is time-consuming and thus expensive.

The case against is that there seem to be positive externalities – or “hidden benefits” –

from a community of research students and their interaction with academic staff. For

example, Leeds Metropolitan University recently advertised 100 PhD studentships to

make: “A significant investment in our postgraduate research student community”

(Times Higher, 21/06/2006).

The policy implication is that decisions should be made on the basis of a cost-benefit

analysis. The practical difficulty lies in the long-term and intangible nature of some

benefits, which thus require consensus about their valuation as well as the appropriate

discount rate to compare the value of future benefits with current costs.

Part-time The current situation for part-time research students is one of low fees and low

numbers. However, because this category of student is currently financially irrelevant,

we can afford to experiment. The following proposal is not in the first instance

derived from evidence in the literature. Rather, it is based on the personal experience

of one of the authors, in the Business School, of supervising two part-time PhD

students. One was very senior in a major public sector body; the other was senior and

rising. Both were using the PhD as a way to leverage their careers, and both would

have been prepared to pay fees an order of magnitude greater than the current rates.

However, in terms of economic theory, the proposal is consistent with the theory of

first-degree price discrimination.

The proposal assumes high aptitude students, that projects are work related, and that

the student anticipates a high return from their MPhil/PhD. In this case, we should

charge what the market will bear subject to a minimum fee to ensure at least a

minimum acceptable level of supervision. Moreover, given small numbers, the fee

could be set by individual negotiation and the student offered a perfectly customised

service, subject to University regulations. This approach entails perfect price

discrimination and is profit maximising. It is tantamount to treating part-time research

Page 56 of 81

award as a personalised form of CPD, similar to mentoring/coaching with elements of

extended consultancy (given that the research may be job related).

2. A note on external sponsors

There are considerable advantages when students are sponsored by external bodies. If

sponsorship is merit based, this may entail higher entry qualifications. If needs based,

sponsorship may enable higher fees than students would be prepared to pay. However,

the disadvantage is that fees are likely to be limited by the market power of the

sponsor.

The sponsor is likely to be a powerful buyer in relation to many potential suppliers

(HEIs). Consequently, scholarships are unlikely to more than cover costs; hence, will

not be a source of significant profit. Moreover, there is exposure to risk of policy

change: e.g., in the case of the LSC, amendments to their core skills agenda and

corresponding changed funding priorities.

The theory of monopsony – i.e., the market structure in which a single buyer

confronts many potential suppliers – suggests that powerful buyers do not allow their

suppliers to charge them more than is just enough to cover costs. A typical example

would be a supermarket chain in relation to contracted manufacturers. In HE, a

sponsor able to grant significant numbers of scholarships is likely to be in an

analogous position in relation to suppliers of suitable awards. The NHS “benchmark

pricing” approach to training provision – whereby it sets both the number of students

and the fee per student - may be an example of this; although a tender and award

system would have a similar outcome. For the theory underlying the disadvantages,

see Part 1, Section 4.3.3.

Page 57 of 81

3. HND and Foundation

Between HND and Foundation awards, there are both similarities and differences.

Hence, we consider them in one Section but separately.

HND

The current position is one of differential fees between degree awards and HND. This

raises two issues.

The first issue is the apparent anomaly of lower fees (£2,100 compared to £3,000 for a

degree) combined with a significantly higher tuition and administration input. This

may be resolved by considering student participation decisions as investment

decisions. The problem in recruiting to HND awards is that for students the

anticipated benefits are lower, which reflects: lower aptitude; weaker peer effects; and

more uncertain outcomes (Part 1, Section 5.2). The solution is for HEIs to reduce

costs and/or increase the benefits of HE to the point where the costs of undertaking an

HND are less than the anticipated benefits. In this way, HEIs can lower the threshold

at which students perceive participation to be worthwhile. Of course, this policy is

subject to covering costs unless progression / retention considerations justify a

subsidy for HND∗ or equity considerations suggest a cross-subsidy.

The second issue is that of progression from HND onto level three of a degree award.

This gives rise to perverse incentives; namely, why should a student pay £3,000 for

L1 and L2 when there is the alternative to enrol on an HND? This is tenable in the

long run only if HND and degree can be separated. Otherwise, policy may be based

on the assumption of persistent irrational behaviour (for the pitfalls of this approach to

policy making, see Part 1, Section 7). Formerly, separation was achieved by the

requirement of a 24, then an 18 month top-up. Now, this has shrunk to bridging

requirements. This raises two questions. First, will these bridging requirements prove

sufficient to offset the attraction of cost saving? And, second, will even these bridging

requirements be competed away as HEIs try to attract applicants? Alternatively, it is

∗ HND can provide a fallback in cases of failure at Level 2 on degree awards.

Page 58 of 81

possible that the greater prestige of a degree will provide the necessary separation, as

long as this has a present value of more than £1,800. In sum, this second issue points

to a potential “hole in the fence”, in which case the present position may not be

sustainable. This suggests that the present policy needs to be monitored for

unintended consequences.

Foundation Foundation year fees are also set lower than degree fees. However, subject to costs,

here there is no problem in principle, because these are separate markets. It is not

possible to substitute from a £3,000 award.

Foundation degree (mainly part-time) fees are relatively low. This is for the same

reasons as HND. To offset relatively low anticipated benefits - e.g., for teaching

assistants and care workers – HEIs must raise benefits and/or reduce costs.

In general, the more marginal the student, the lower the costs needed to attract the

student into HE. However, an important qualification to this guideline may be the

payment of fees by employers or the availability of external sources of finance such as

means tested government support or Career Development Loans. Related issues

concern the type of employer (e.g., for-profit, public or “3rd sector”), whether or not

the training is a statutory requirement, and the scope for partnerships, discount for

scale, bundling effects etc. The implications of the various possible combinations are

as follows.

1. Low returns and the student pays implies a low fee, because this is both

economically rational - subject to covering costs - and consistent with equity.

2. High returns and either the student or the employer pays implies a higher fee,

although this is conditional on lack of close substitutes. Low fees subsidise

employers and/or students.

3. A higher fee still may be justified if the training is a statutory requirement,

although this is again conditional on lack of close substitutes.

Page 59 of 81

4. Placements: another “hole in the fence”?

We need to clarify objectives about charging for placements. Should charges be set to

cover costs or to make a profit? Conversely, there are some strong arguments urging

caution on charging for placements: the cost of collection; and the encouragement of

avoidance strategies such as students intermitting and arranging their own

“placement”. As a general principle, to the extent that there is no market power to

exploit, it will be difficult to charge students more than the service is worth to them.

Indeed, any attempt to do so may well be counter-productive via possible effects on

retention. Moreover, policies based on the assumption of irrational behaviour are

unlikely to be sustainable (Part 1, Section 7).

A possible compromise is to offer placements as a service, with a transparent link

between service and price. The price that students are willing to pay is a market test of

how much students value the service. This may vary between awards. If so, pricing

for placements may need to be flexible. In any case, do not expect placements to be a

source of profit

Page 60 of 81

5. Part-time

Should part-time (PT) fees be in line with full-time (FT) fees? In principle, the same

criteria apply as for HND and Foundation awards. The question to address is whether

it is necessary to lower the participation threshold at which the anticipated benefits of

participation exceed the costs. In part, this depends on returns for the student and who

pays, the student or the employer. If benefits for the student or the student’s sponsor

are likely to exceed costs then there is a case for fees parity. If not, if anticipated

benefits are lower than the costs, then charging the equivalent of full-time fees to part-

time students could price us out of the market.

In practice, HEIs do not know with any precision either the relevant price elasticities

or, most important, students’ study (participation) thresholds. Consequently, sudden

large increases in part-time fees incur high risks.

1. If the award is subject to very high price elasticity – i.e., student demand is

very responsive to fee changes – then a large fee increase could cause a more

than proportionate fall in demand and a consequent fall in revenue.

2. An even worse outcome would occur if potential part-time students had a

similar participation threshold and a large fee increase took them from above

the threshold (anticipated benefits exceeding costs) to below the threshold

(anticipated benefits falling short of costs). In this case, the consequence of a

large fee increase would be a complete collapse in demand.

Accordingly, to avoid these risks, there is a case for continuing with different PT and

FT fees and making incremental adjustments.

It is also necessary to consider whether or not FT and PT are separate markets. If not,

then there is substitution problem (i.e., potential full-time students can choose lower

cost part-time study for the same award). If FT and PT modes are not separate

markets, so that substitution can occur, then there is a case for fees parity. Conversely,

if FT and PT modes are separate markets then, on this criterion, different fees may not

be a problem (subject, as ever, to costs and the overriding balance of priorities).

Page 61 of 81

Setting part-time fees entails the following trade-offs. Maintaining low fees protects

participation yet, if costs are not covered, may amount to subsidising either students

or employers. Conversely, parity with full-time fees may inhibit participation but may

enable the HEI to at least cover costs (subject to the relevant elasticities and threshold

effects).

6. A note on price elasticity∗

In the context of fees, price elasticity is a measure of the percentage change response

in the numbers recruited to a percentage change in fee.

If the percentage rise in fee is greater than the percentage fall in recruitment, then fee

income rises. This effect implies unexploited market power. Conversely, if the

percentage rise in fee is less than the percentage fall in recruitment, the fee income

falls.

Implementation of the elasticity concept may be either intuitive or model based,

although the latter is very demanding on data and research time. Yet, however they

may be determined, elasticity values relate to small price changes: e.g., the impact of

price rise from £8 to £10 per credit. Elasticity measures are not reliable for very large

changes: e.g., the impact of price rise from £8 to £25 per credit. A large rise in fees

could cross a crucial study (participation) threshold thereby triggering a collapse in

demand. This principle also implies that elasticity measures are not easily transferable

between different systems, HEIs or awards with different types of students.

The policy implication is to minimise risk by making incremental changes. Avoiding

sudden large changes minimises the danger of crossing unknown student thresholds.

∗ For extended discussion of price elasticity in HE markets, see Part 1, Section 4 (in particular, 4.1 and 4.2) and Part 1, Section 6.1. For the concept of the study threshold, see Part 1, Section 5.2.

feein change Percentagetrecruitmenin change Percentage demand of elasticity feeTuition −=

Page 62 of 81

An incremental approach entails the further advantage of gathering information over

time to improve intuitive estimates of price elasticities. It should also be taken into

account that study or participation thresholds are likely to vary by type of student:

e.g., lower for an “adult returner” with less time to accrue benefits to offset the costs

of study, but higher for younger students working for professional qualifications (who

are also likely to be less credit constrained). However, in all cases, if fees are raised to

the extent that the study threshold is crossed, so that costs exceed anticipated benefits,

then demand may collapse.

Page 63 of 81

7. International fees

International student demand, like student demand generally, is influenced both by

factors not under the control of HEIs - such as competitors’ prices and the relative

cost of living – and by some that are. Some of the factors under the control of HEIs

are easily imitated and thus not a source of enduring competitive advantage: in the

case of international students, these include extending period in the UK by placements

and help with visa applications. Sustainable competitive advantage depends more on

the fundamentals of price and reputation. However, in the case of international

recruitment, institutional arrangements are also important.∗

The general reputation of HEIs is increasingly made transparent by easily accessible

league tables. However, there is scope for differentiating the particular reputation of

awards by external “kite marks”. Different institutional arrangements also affect

international recruitment: for example, recruitment through the open market, agents,

and International partners. In particular, moving from the open market to recruitment

through agents and international partners enables potential applicants to be provided

with information that increases the ability of HEIs to differentiate their awards and

fees.

A related issue is charging policy for franchise and quality assurance services.* In

principle, if charges are related only to numbers, then the home HEI bears the risk of

under-recruitment. Moreover, this approach reduces incentives of the partner to invest

in recruitment. An alternative approach is to combine a fixed charge to cover total

costs and numbers-related charge above this level. This approach both reduces risk

and increases incentives to recruit.

∗ Based on discussions with Professor Peter Reynolds, Director of the International Office. For some relevant theory, see the Part 1, Section 4.3.1.

Page 64 of 81

8. EU fees and bursaries∗

At Staffordshire University, first impressions suggest that the £3,000 fee has caused a

“dramatic” fall in recruitment of EU students. However, as yet there is a lack of hard

data (either local or systemic). First principles suggest possible explanations. EU

students may have access to lower cost substitutes. Continental HEIs typically charge

zero or nominal fees and many are providing awards with English as the language of

instruction (in particular, to compete in international postgraduate markets with US,

UK and other English speaking HEIs).

Policy responses include international partnerships for level three top-ups and dual

certification. There may also be a case for fee reductions, particularly if there were to

be a pay-off in progression to postgraduate awards. (This assumes, of course, that

price discrimination in favour of non-UK EU citizens would be legal.)

∗ This Section is based mainly on local experience and anecdotal evidence.

Page 65 of 81

9. Setting fees at award level

In this final section, we consider some general principles for setting fees at award

level. We then emphasise the need to take award costs into account.

Compromise between uniformity and fragmentation

Objectives may vary between awards; for example, HEIs may apply a different

balance of efficiency and equity criteria to full-time and part-time awards. Moreover,

even if HEIs set uniform objectives, variations on both the supply side (costs) and on

the demand side (elasticities) introduce potential heterogeneity among awards.

Common principles for fee setting applied to heterogeneous awards imply different

outcomes. At the limit, this suggests a different fee for each award, which could prove

costly in terms of managerial and administrative time. However, there are

compromises possible between extremes of uniformity and fragmentation. For

example, within faculties, related awards may be grouped into blocks for fee setting,

even if some awards might be in a category of one.∗ The faculty may be the natural

limit for such grouping, because inter-faculty variations are likely to be large relative

to intra-faculty variations, reflecting greater differences in both awards and students.

Know your costs!

The default position is that heterogeneous awards are priced “as if” they were

homogeneous, rather than setting award fees to match variations in both revenues and

costs. The demand conditions that determine award revenue cannot be determined

with precision; although experience, application of sound theoretical principles and

market research can move projections away from the purely arbitrary towards the

transparent and informed end of the spectrum. In contrast, the supply of awards is

under the control of HEIs. Hence, award costs should be known precisely. However,

in practice, HEIs do not yet have full information on costs at award level. Yet without

knowledge of what awards cost, it will be difficult to progress far from a simple

∗ This suggestion arose from discussions with Faculty Recruitment Managers.

Page 66 of 81

uniform fee towards pricing heterogeneous awards. For HEIs to know whether awards

are loss making, covering costs or profitable, projected revenue on its own cannot

inform decision making. HEIs must also know what their awards cost!

The final part of this Report presents a framework for setting award specific fees. It

proposes simple approaches to take account of both variable demand conditions

(hence revenue) and variable supply conditions (hence costs).

Page 67 of 81

Part 3: An approach to setting fees at the award level

The final part of this Report introduces and sets out a questionnaire that enables an

award-specific fee to be set by making award-specific adjustments to a standard fee.

This approach is designed to secure uniformity of principles and procedure in setting

award-specific fees.

Our definition of fee is interchangeable with award price and revenue per student.∗

We begin with a broad approach to differentiating fees by award.

1) Start from a University target or “standard” fee (Sf). In principle, this is uniform

across the HEI and will be set according to the HEI’s criteria such as the

requirement to break even. It could start from the current default level of £3,000.

Whatever the initial standard fee, it will change over time. It can be benchmarked

against other HEIs, both competitors and non-competitors, and take into account

wider factors such as changes in cost of living differences (e.g., between Stoke

and elsewhere), which is suggested by evidence that students are more sensitive to

variations in total student costs than variation in tuition fees only.

2) Departures from the standard fee have to be justified with respect to agreed

principles. The standard fee is adjusted up or down as follows.

a) For full costs per student and subsidies (e.g., HEFCE capitation) deviating

from the university average. In principle, costs and subsidies are either under

the HEI’s control or known. However, we should take into account the

administrative cost of calculating costs!

b) For demand conditions, to justify, according to agreed criteria, either a

premium over the target fee or a discount from the target fee. Demand

conditions are not under the control of HEIs or precisely known. Hence, in

principle, demand driven premiums or discounts will be harder to calculate

than adjustments for costs and subsidies.

c) For “external” benefits and “external” costs, to account for the net benefits of

meeting other agendas (“spin-offs”). These are even harder to calculate than

∗ Fee ≡ price ≡ revenue per student.

Page 68 of 81

market based premiums or discounts. Because “spin-offs” are difficult to

quantify, some agreed criteria may be needed as to “what counts” in this final

round of adjustment.

Next, we outline these adjustment principles in detail.

a) Adjusting for Costs & Subsidies

First, we adjust for costs (C) per student. This means adjusting for the difference

between the aggregate cost per student to the university (UC) and the award cost per

student (AC):

(UC – AC).

In calculating both UC and AC, we take account of full costs, which include:

1) Fixed costs, which are the same for all awards - e.g., costs of corporate

management and administration; and

2) Variable costs, which differ between awards. Such award specific costs include:

staff costs (including pastoral & learning support); varying costs according to

whether the award is classroom, project or laboratory/studio based; claims on

central services; recruitment costs, which differ according to the duration of the

award; disbursement costs; and other award specific costs such as waste

management.

Second, we adjust for subsidy (S) per student. This involves calculating the difference

between aggregate university subsidy per student (US), which takes into account all

student-related revenue (excluding fees) coming into the university, and award level

subsidy per student (AS), including HEFCE capitation and widening participation

premiums. As for costs, we calculate the deviation of the latter from the former:

(US – AS).

A check on award cost and subsidy calculations would be the requirement, say for

each faculty, that total costs plus subsidies calculated at award level do not exceed

Page 69 of 81

total faculty costs plus subsidies. Of course, this constraint can be applied at any level,

up to and including the HEI itself.

b) Adjusting for demand conditions

Fee premiums (P) or discounts (D) are to be justified in terms of price elasticities

and/or related HEI objectives. In all cases, adjustments for different elasticities – a

premium where demand is insensitive to price or a discount where demand is very

sensitive to price – are subject to the overriding priorities of the HEI, whether these

are profit maximising (hence, fee maximisation) or equity promoting (prioritising,

say, widening participation).

Influences on price elasticities include the type of student, because of corresponding

variations in:

1) likely benefits from HE, i.e. returns on investment (financial, psychic; etc.), hence

different “threshold” levels (i.e., fee levels at which the costs equal the anticipated

benefits of HE);∗

2) family income, hence in ability to pay; and

3) credit constraints, i.e. in ability or willingness to borrow.

In addition, price elasticities are likely to be influenced by the source of finance; in

particular, whether the student is self or employer financed. In the case of employer

financing, price elasticities will also be influenced by the type of employer (private,

public or third sector), the size and vulnerability of training budgets, the likely

benefits to employers, and whether or not the training is a statutory requirement. In all

cases, the major influence on price elasticity of demand for an award is the

availability of substitutes, which may arise from both nearby competitors and

competitors located elsewhere if student or employers perceive distance learning to be

an acceptable substitute.

∗ For the concept of the threshold, see Part 1, Section 5.2.

Page 70 of 81

c) Adjusting for “spin-offs”

External benefits (Eb) may arise from a particular contribution to enacting the HEI’s

mission (e.g., with respect to widening participation, regeneration, or knowledge

transfer), positive reputation and peer effects, and other sources of long-term pay-off

such as staff development and retention. Conversely, unintended external costs (Ec)

may arise arise from negative peer effects. However, while such positive “spin-offs”

are hard to measure, negative ones may exist as theoretical possibilities still awaiting

a more reliable evidence base.

To adjust the standard fee level (Sf), we convert both external benefits and external

costs into per student terms: external benefits per student (AEb); and external costs

per student (AEc).

Finally, we now combine the components of our approach – setting a standard fee and

then applying adjustments – into a pricing formula. We present two versions. The first

is fully quantitative and stays close to theory. However, at this stage of experience

with award specific fees, it is too complex for practical use. Accordingly, a second

version is developed in order to meet the overriding criterion of being easily

operational.

Pricing formula (1): fully quantitative

The pricing formula set out in Equation 1 is too unwieldy and its information

requirements are too great to be operational. However, it is the starting point for

deriving a simpler, operational pricing formula.

Equation 1:

F = Sf – (UC – AC) + (US – AS) + P – D – (University AEb – Award AEb)

+ (University AEc – Award AEc)

Here, the award specific fee (F) is set to equal the standard fee plus and minus the

series of adjustments set out in Equation 1.

Page 71 of 81

• UC > AC implies a reduction from Sf, because the award is tending to reduce

average University costs.

• UC < AC implies an addition to Sf, because the Award is tending to increase

average university costs.

• US > AS implies an addition to Sf, because the Award is reducing the average

subsidy.

• US < AS implies a reduction from Sf, because the Award is increasing the

average subsidy.

• If demand conditions justify a discount (D), then P = 0

• If demand conditions justify a premium (P), then D = 0

• University AEb > Award AEb implies an addition to Sf to offset a lower than

average contribution to external benefits (i.e., the award should make a higher

than average contribution through fee income).

• University AEb < Award AEb implies a reduction from Sf, because the award

is generating an above average external contribution (i.e., this justifies a

below-average contribution to fee income)

• University AEc and Award AEc are interpreted by analogy with the external

benefits, University AEb and Award AEb.

Pricing formula (2): “quasi quantitative”

We appeal to a series of simplifying assumptions to develop an operational pricing

formula.

The first simplifying assumption recognises that the existing state of knowledge

probably does not permit precise quantitative measurement of external benefits, and

certainly not of external costs. Hence, we propose that HEIs assess qualitatively the

net external benefits of each award – or group of related awards - and translate this

assessment into a “quasi quantitative” equivalent. In each case, estimated levels of net

external benefits to the University should be justified in open debate and then

translated into one of, say, three corresponding bands of fee reduction: neutral;

significantly above average; and exceptional. Then a corresponding downward

adjustment can be made to the standard fee (Sf); for example:

Page 72 of 81

1) broadly neutral means no adjustment – it is to be expected that most awards

will be broadly neutral with respect to their net external benefits, meaning that

there contribution is more or less in line with the university average;

2) £250, for awards that contribute net external benefits significantly above the

university average; and

3) £500 for an award contributing exceptional net external benefits.

Applying this simplification transforms Equation 1 into Equation 2:

Equation 2:

F = Sf – (UC – AC) + (US – AS) + (P – D) + Net External Benefits

The second simplifying assumption is that HEIs such as Staffordshire just break even.

The more an HEI depends on HEFCE funding then the less likely it is to do better

than break even. The underlying reasoning (Part 1, Section 4.3.3) is that HEFCE is a

powerful buyer in relation to many suppliers, a position somewhat analogous to

supermarket chains and small suppliers. If HEIs were systematically making profit,

then HEFCE would lower the subsidy. The implication is set out in Equation 3:

Equation 3:

Sf = UC – US

In tendency, the standard fee (Sf) just covers the difference between University costs

per student (UC) and university subsidy per student (US). By rearranging Equation 3,

we obtain: UC = Sf + US. In other words, per student costs are just covered by the

standard fee plus per student subsidies.

Use Equation 3 to substitute for Sf in Equation 2: hence,

F = (UC – US) – (UC – AC) + (US – AS) + (P – D) + Net External Benefits

Finally, simplify the formula by cancelling terms;

F = (UC – US) – (UC – AC) + (US – AS) + (P – D) + Net External Benefits

Page 73 of 81

hence:

Equation 4:

F = (AC – AS) + (P – D) + Net External Benefits

Starting from Equation 1 with 11 terms, we have reduced this by applying plausible

assumptions to Equation 4 with five terms. Equation 4 states that if we set to zero fee

premiums (P), discounts (D) and Net External Benefits, then the award fee (F) makes

up the difference between average award costs (AC) and average award subsidies

(AS). If we set only Net External Benefits to zero, then adding a premium (P) entails a

profit per student or deducting a discount (D) entails a loss per student. Finally, Net

External Benefits allow a third influence on award specific fees.

Given that the HEI in the aggregate just covers its costs, then fee discounts must be

balanced by premium fees elsewhere. Similarly, fee reductions justified by positive

net “external” benefits also have to be balanced by fee premiums elsewhere.

The pricing formula is the bridge between research results on pricing policy in HE

and an operational tool for guiding fee setting at award level. The final part of this

Report sets out a questionnaire that translates Equation 4 into a framework for setting

award specific fees, which can be easily modified after consultation and experience.

Use of a common framework for setting fees will achieve transparency and three

consequent benefits: the framework

1. makes explicit the assumptions and principles used to set fees,

2. enables comparison between awards both within faculties and between

faculties and, if outcomes do not match expectations,

3. helps subsequent analysis and organisational learning.

In addition, the framework should help to anticipate sources of profit and loss, along

with the justification in each case.

Page 74 of 81

A fee-setting questionnaire: guidance tool for Award Tutors

The questionnaire set out below is informed by the methodology set out in the

previous section and is designed to help assess the appropriate fee for individual

awards (or “families” of awards). It provides a tool to implement a process of

adjustment to a standard fee. The adjustments take account of the supply side (costs

differences between awards), the demand side (willingness and ability to pay) and net

benefits not reflected in current revenue. At each stage of the adjustment process, all

magnitudes are indicative and will need to be recalibrated in the light of experience.

Completion requires little precise information but necessarily sacrifices precision,

relying more on informed judgement than hard data. The approach is “quasi-

quantitative” rather than fully quantitative: Moreover, Award Tutors make fractional

adjustments to a standard fee (rather than adjustments in monetary terms). This

enables the separation of the adjustment process from the setting of the standard fee.

Across all awards, adjustments at award level can be made fiscally neutral by

specifying that the average fee must equal the standard fee. This constraint may be

imposed at faculty level or at any other level deemed appropriate.

Page 75 of 81

Step 1: Calculate net cost adjustment per student a) Award Costs 1.

Faculty Student-academic staff ratio:16, 17 = ___ (Faculty ratio) University Student-academic staff ratio: = ___ (University ratio)

ratio staff -student Universityratio staff -studentFaculty

= ___

The final ratio (i.e., Faculty ratio ÷ University ratio) is: *

1. Up to and including 0.75 r Score 1 2. Over 0.75 and up to and including 1.00 r Score 2 3. Over 1.00 and up to and including 1.25 r Score 3 4. Greater than 1.25 r Score 4

* Ratio < 1 (> 1) means the faculty student-staff ratio is greater (less) than the University ratio. Hence, other things being equal, the faculty’s awards are low (high) cost with respect to staffing.

2. Do your students make use of: 1) Predominantly classrooms _______

2) Predominantly studios or laboratories with minimal equipment and/or

consumables: e.g., drama studio; cartographical laboratory _______

3) Predominantly studios or laboratories with expensive equipment and/or consumables: e.g. TV, film or recording studios; forensic science laboratory etc. _______

You have ticked:

“Score” as follows:

1) only Score 1 1) and 2) Score 1 2) only Score 2 1), 2) and 3) Score 2 1) and 3) Score 3 2) and 3) Score 3 3) only Score 4

16 In principle, the same calculation could be made for administrative, technical and “other” staff. At present, the calculations will be kept as simple as possible. 17 Each SURF student may be counted as 0.15 of a FTE, on the basis that the University receives 15% of the fees paid by SURF students. Part-time students may be accounted for according to the same principle.

Page 76 of 81

3. Disbursement per student: including residentials; books; placements; other (specify)

Total Cost

1. 5% of the course fee or less q Score 1 2. Over 5% and up to and including 15% q Score 2 3. Over 15% and up to and including 33⅓% q Score 3 4. More than 33⅓% of the course fee q Score 4

4. Other award costs per student: e.g. waste management; costs associated

with professional accreditation; other (specify)

Total Cost

1. 5% of the course fee or less q Score 1 2. Over 5% and up to and including 15% q Score 2 3. Over 15% and up to and including 33⅓% q Score 3 4. More than 33⅓% of the course fee q Score 4

Total cost adjustment score

• Score each question • Add-up question scores to find the total cost adjustment score: _________

b) Award subsidies Take account of HEFCE capitation to obtain the net cost band Assumptions and procedure: There is insufficient data on Widening Participation and other sources of subsidy at award level. Hence, only the three HEFCE bands will be taken into account: high; medium; and low. Use the table of “subsidy adjustment scores” (below). This adjusts the total cost score to take account of both different rates of HEFCE capitation and the proportion of overseas students on the award (who do not attract HEFCE subsidy). For example, an award in a high-band subject with mainly home/EU students (up to 25% overseas students) is relatively high subsidy and scores -4 to reflect a significant adjustment to the cost score. Conversely, a low-band award with more than 75% overseas students is relatively low subsidy and scores zero, so that no adjustment is made to the cost score.

Page 77 of 81

Subsidy adjustment scores Proportion of overseas students HEFC Capitation

Proportion 0 to 25%

Proportion 26 to 50%

Proportion 51 to 75%

Proportion 76 to 100%

High -4 -3 -2 -1 Medium -2 -1.5 -1 -0.5 Low -1 -0.75 -0.5 -0.25 Obtain the net cost score: *

Net cost score = Total cost adjustment score + Subsidy adjustment score * The maximum net cost score is 15.75 (i.e., a maximum cost adjustment score of 4 for each of the four cost questions and a minimum subsidy adjustment score of -0.25). The minimum net cost score is 0 (i.e., a minimum cost adjustment score of one for each of the four cost questions and a maximum subsidy adjustment score of -4). Translate the net cost score into a fee adjustment for Step 1 as follows: *

Net cost score

0-1 2-3 4-5 6-10 11-12 13-14 15-16

Corresponding fee adjustment

Discount - 2

1 Discount

- 31

Discount - 6

1 Zero

Premium

+ 61

Premium + 3

1 Premium

+ 21

* An alternative conversion scheme is offered in Appendix 1. Step 1 fee adjustment: % ________

Page 78 of 81

Step 2: Estimate fee premium or fee discount 1. Predicted Returns to Student:

q Low q High 2. Predominantly Employer Financing: q No q Yes 3. Employer ability and willingness to pay: q Low q High 4. Award satisfying legal or regulatory requirements? q No q Yes 5. Close Substitute for award elsewhere:

q Yes q No 6. Are there other sources of finance: e.g. Career Development Loans; funding agencies (e.g., the LSC); overseas governments; etc. q No q Yes Each answer scores one point.18 Each response in the left-hand column indicates a discount, whereas each response in the right-hand column indicates a premium. The range of outcomes is as follows: Left 6 5 4 3 2 1 0 Right 0 1 2 3 4 5 6

Corresponding fee adjustment

Discount:

- 21

Discount: - 3

1 Discount:

- 61

Zero Premium: + 6

1 Premium:

+ 31

Premium: + 2

1

18 This is easily amended. For example, there may be a case for up-weighting the response to Qu.5.

Page 79 of 81

Step 3: Assess net external benefits * There are four levels that take into account the net external benefits to the University of a specific award. All levels are translated into per student terms and discounted from the fee.

The external benefit is neutral: no change in the course fee q The external benefit is modest: 6

1 reduction in the course fee q

The external benefit is significant: reduction by 31 q

The external benefit is unusually substantial: reduction by 21 q

* Including widening participation effects, contributing to agendas such as community participation and regeneration, reputation and/or recruitment benefits, staff development, etc.

Step 4: Calculate Overseas Student Adjustment Adjustment for overseas students Overseas students recruited in the normal way incur relatively high recruitment and support costs: these are reflected in the “Non-Scholarship” row. Overseas students recruited through externally funded scholarship programmes incur relatively lower costs: these are reflected in the “With Scholarship” row.

Proportion of overseas students

Proportion 0 to 25%

Proportion 26 to 50%

Proportion 51 to 75%

Proportion 76 to 100%

Corresponding fee adjustment

(fraction of the total fee)

Non-Scholarship 0 6

1 31 2

1

With Scholarship 0 12

1 61 4

1

Page 80 of 81

Step 5: Calculate fee adjustment

Fee adjustment = (Step 1 + Step 2 + Step 3 + Step 4)

Fee adjustment = ± Net cost adjustment + Premium – Discount – Net external benefits + Overseas student adjustment = _______ (as a fraction) = _______ (as a proportion) * * For example, 1/6 = 0.1666 (to four significant figures). The percentage fee adjustment is the proportional adjustment multiplied by 100; hence, 0.1666 × 100 = 16.66 percent.

Step 6: Calculate award fee Fee = Standard fee ± Percentage fee adjustment = £__________ * * Can be calculated as: Fee = Standard fee × (1 + r), where r is the proportional adjustment calculated in Step 5. For example, if the standard fee is £3,000, and the fractional fee adjustment is 1/6, then: Fee = £3,000 × (1 + 0.1666) = £3,000 × (1.1666) = £3,499.80, which may be rounded to £3,500.

Page 81 of 81

Appendix 1: Alternative translation of the net cost score into a fee adjustment

Net cost score

0-1 2-4 5-7 8 9-11 12-14 15-16

Corresponding fee adjustment

Discount -1/2

Discount -1/3

Discount -1/6

Zero Premium +1/6

Premium +1/3

Premium +1/2