Measuring the value of externalities from highereducation

Bruce Chapman • Kiatanantha Lounkaew

Published online: 17 February 2015� Springer Science+Business Media Dordrecht 2015

Abstract This paper takes an innovative approach. We have used the idea of converting

international evidence of the size of higher education externalities as a proportion of GDP

into Australian-specific dollar equivalents and added these estimates to estimates of life-

time fiscal returns to graduates. This allows us to estimate the expected spillovers over a

graduate’s lifetime, an opportunity that has so far not been taken elsewhere. We conclude

that an additional year of higher education in an Australian context, valued at the time of a

student’s enrolment, lies between $10,635 and $15,952 in 2014 terms. We also ac-

knowledge that it is difficult and inappropriate to apply estimates of average externalities to

issues related to public sector pricing. However, having some idea of the boundaries of the

potential sizes of higher education spillovers is a valuable and interesting exercise.

Keywords Higher education financing � Higher education externalities � Highereducation policy � Higher education subsidies � Fiscal externalities

Introduction and context

The analysis following examines the value of ‘‘externalities’’, or ‘‘social spillovers’’, from

higher education, using Australian data as a case study. The basic question addressed is:

what is the economic value to society which flows from undergraduate university

B. Chapman � K. Lounkaew (&)Crawford School of Public Policy, The Australian National University, J.G. Crawford Building,Lennox Crossing, Canberra, ACT 0200, Australiae-mail: K.LOUNKAEW@ANU.EDU.AU

B. Chapmane-mail: bruce.chapman@anu.edu.au

K. LounkaewFaculty of Economics and Institute for Social and Economic Studies, Dhurakij Pundit University, 110/1-4 Prachachuen Road, Laksi, Bangkok 10210, Thailand

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High Educ (2015) 70:767–785DOI 10.1007/s10734-015-9866-x

graduates, above and beyond the private benefits accruing to the graduates themselves?1

The meanings of the term ‘‘externalities’’, and illustrative examples from the output of

higher education services, are provided in ‘‘The concept of externalities’’ Section.

Attempts to measure the value of externalities in all areas of economic activity are

extremely complex, almost always controversial, and cannot be undertaken without the

imposition of simplifying assumptions. As a result, credible estimates involve boundaries,

but even with the use of empirical ranges, the conclusions reached can be contentious and

debatable. These intricacies, and what they imply for the adoption of an acceptable

methodological approach, are an integral part of the exercise and are clarified in ‘‘Mea-

suring the true role of education’’ and ‘‘Understanding the estimation strategy’’ Sections.

An understanding of the theoretical and methodological bases of the issue leads to the

description and explanation of the estimation strategy of ‘‘Understanding the estimation

strategy’’ Section. A major, we believe unique, contribution of our exercise is to embed the

analysis into an approach using estimates of graduate lifetime earnings and to use this

method to derive approximations of the value of externalities as a proportion of discounted

lifetime earnings streams. To our knowledge, this method has not been used before.

There are three significant advantages with this strategy: one, in terms of method, it

allows us to derive dollar values of externalities which are easy to understand; two, it

incorporates techniques capable of estimating both pecuniary (for example, additional tax

revenue from graduates) and non-pecuniary (for example, health improvement) exter-

nalities; and three, the data required to make it operational are readily available for most

countries, obviously including Australia. The approach can easily be replicated

internationally.

‘‘The data and results’’ section describes the data used in the econometric aspects of the

research and reports the results. ‘‘Caveats, problems and policy issues’’ section provides

qualifications to the use of the findings, emphasising several critical conceptual and

measurement issues. This section also addresses the question of whether or not, and the

circumstances in which, our results are able to be used to inform policy makers in de-

termining the ‘‘right’’ level of public sector subsidies and/or the tuition prices which should

be set for students.

The concept of externalities

Introduction

It is obviously important to be very clear about the meaning of the term ‘‘externalities’’.

The concept is now explained in broad terms, and examples are offered that are of par-

ticular significance to higher education. An important point related to the complexity of the

nature of higher education externalities is that the process is considered to contribute to

research and development (R & D), innovation and technical change, which in turn are the

major factors contributing to productivity increase and thus to the society’s economic well-

being.

This section also explores issues related to the measurement of the determinants of

productivity (and thus per capita GDP), some part of which is conditioned by societal

investments in higher education. Significantly, there is no doubt that the nature of the

1 These typically take the form of expected higher lifetime incomes for graduates relative to those of non-graduates. See Borland (2002); Daly and Lewis (2010).

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causal relationships inherent in this line of enquiry is a contested area of empirical eco-

nomics research. This is examined in what follows. In addition to the difficulties associated

with both the conceptual bases and the measurement of technical change, there is also a

critical time dimension in this area which is considered further in ‘‘Caveats, problems and

policy issues’’ section.

Externalities defined

Externalities occur when one party’s action imposes costs or benefits on another party and

the effect is not transmitted through usual market mechanisms. Externalities are of many

different types and varieties. Externalities can have desirable or undesirable impacts, and

some have both. If these effects are beneficial to society, they are known as positive

externalities, and if they are detrimental, they are known as negative externalities. Table 1

provides general examples of positive and negative externalities.

As alluded to in the Introduction, a basic tenet of economic theory is that if no policy

action is taken by governments in the presence of externalities, consumption or production

decisions made by individuals or firms cannot be best for the society as a whole. This so-

called sub-optimality arises from the fact that the decisions taken by private citizens and

businesses with respect to the benefits and costs from consumption or production will not

take into account the value of the externalities.

It follows that the existence of positive externalities will lead markets to produce a

smaller quantity of the goods and services than is socially desirable, while negative ex-

ternalities will lead markets to produce a larger quantity of the goods and services than is

socially desirable. This is part of what is known as ‘‘market failure’’ and implies a le-

gitimate ground for government intervention (Friedman 1955)2, such that the form and

extent of a resulting subsidy or tax results in resource reallocation.3 The extent to which the

methods we employ, and the restrictiveness of the assumptions imposed on our data, render

our approach and results valuable in a policy sense is an issue examined fairly compre-

hensively after the presentation of the results.

Table 1 Types of externalitiesExternalities Example

Positive (assumed) Immunisation of viral diseases

Restoration of historic buildings

Research and development related tonew technologies

Negative (assumed) Exhaust from automobiles

Noise from airplanes

Loud music in apartment buildings

Pollution

2 This conclusion follows only if the consequences of public sector involvement improve the situation froma societal perspective. It is possible that there is also ‘‘government failure’’, which could mean that mis-guided or poorly designed policy attempts to reduce the negative impact of market failure make the societyworse off.3 Meaning, in our context, that a tuition price change for university services will be associated with a non-zero price elasticity of demand.

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Higher education externalities as fiscal externalities

In order to proceed, we need to provide a justification for the use of fiscal externalities in

our exercise. A standard textbook definition proposed by Rosen and Gayer (2009) states

that externality arises when the activity of one party affects the welfare of another in a way

that is outside the market. Another textbook definition offered by Stiglitz (2000) describes

an externality as a situation under which an ‘‘individual or firm undertakes an action that

has an effect on another individual or firm for which the latter does not pay or is not paid’’.

Based on these definitions, there are two key characteristics to qualify an activity as an

externality:

1. one party’s action imposes costs or benefits on another party; and

2. the effect is not transmitted through usual market mechanisms.

In the public finance literature, a fiscal externality exists when the behaviour of people

influences the cost of a subsidy or changes the level of tax revenue (Buchanan 1966;

Browning 1999; Wilson 1999). For example Becker et al. (1994) and Gravelle and Zim-

merman (1994) argue similarly that smoking entails negative fiscal externalities to the

society because a publicly provided medical insurance system is subsidised by tax payers’

money. In the present context, Singer (1976) argues that education enhances productivity;

hence, it increases taxes paid by graduates due to their higher incomes. These additional

taxes represent external benefits to the rest of the society because they can reduce the tax

burdens of others. Comparing Singer’s argument against the two key characteristics of

externalities described above, it can be seen that:

1. investment in education does benefit others due to potential reduction of tax liabilities;

and

2. the effect of the reduction is not conveyed through market mechanisms. If education

investment in general produces fiscal externalities, then it must also be true for

investment in higher education.

There are very many possible externalities associated with higher education invest-

ments, and these take significantly different forms. A fairly comprehensive list of what is

known as non-pecuniary externalities is provided by McMahon (Table 4 in Appendix 1),

which also provides rough orders of magnitude derived from the literature with respect to

the present values of these externalities. These data turn out to be extremely important to

the empirical methods we employ and report in ‘‘The data and results’’ section.

Different classification systems can be used to help understand the nature of higher

education externalities. One is to define externalities according to whether or not they are

‘‘pecuniary’’ or ‘‘non-pecuniary’’, where the terms suggest the capacity of the externality to

deliver financial resources directly to the government. The most obvious form is additional

taxation revenue resulting from the higher productivity of graduates, meaning higher

earnings and thus more tax receipts. A related externality takes the form of the additional

productivity of non-graduates as a result of workplace interactions with graduates.

The so-called non-pecuniary externalities usually associated with additional levels of

higher education that receive the most attention are the societal benefits from the expan-

sions of higher education, including reduced crime, improved health, more informed po-

litical debate and the higher likelihood of strengthening ‘‘civil society’’. While these

factors and others will likely have benefits that do not have a measurable social spillover,

the McMahon (2006) method allows some dollar estimates to be made of their value (as

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explained and used in ‘‘Understanding the estimation strategy’’ and ‘‘The data and results’’

Sections).

There are two additional and extremely important aspects of higher education spil-

lovers, related to technical change and the timing of the delivery of externalities. These are

taken up in detail in ‘‘Caveats, problems and policy issues’’ Section. as significant cau-

tionary qualifications to the use of our results for policy purposes.

One area of apparent agreement concerning the measurement of pecuniary externalities

concerns the additional tax receipts resulting from the higher productivity of graduates

(and incorporating these calculations into private rate of return calculations provide what

are usually known as conventional social rates of return). But we now explain that, even in

this apparently less contentious area of the economics of education, there are major con-

ceptual issues that have to be addressed.

Measuring the true role of education

Introduction

There is a fundamental debate in education economics that is critical to the estimation of

the value higher education externalities. In essence this comes down to the relative roles

played in the labour market by two competing hypotheses: human capital theory and

screening (or signalling). Some form of resolution between them lies at the heart of the

interpretation of one of the main empirical issues of our work, the role of higher education

in the generation of pecuniary (fiscal) externalities. These opposing views, and their

relevance to the empirical methodology adopted in ‘‘Understanding the estimation strat-

egy’’ Section, are now explained.

Human capital theory, screening and the value of education

A pure human capital approach in labour economics stresses that education increases

productivity and that this higher productivity leads to higher wages and thus to fiscal

externalities generated from tax revenue. Of course, such a calculation needs also to taken

into account a negative fiscal externality, which is tax revenue foregone during the in-

vestment part of the process since at this time individuals enroled full-time in higher

education will not be receiving high earnings and will thus not be contributing much to tax

revenues. But taken in its simplest form, the human capital perspective implies that all of

the net tax benefits associated with private higher education investment should be treated

as pecuniary externalities.

However, the story does not end there because of the competing perspective, known as

the screening hypothesis. In its simplest form, screening theory suggests that instead of

increasing productivity, education acts as a signalling device and works as follows.4 More

highly educated people have shown the ability (and motivation) to be successful at

education, and this identifies them to prospective employees as having greater capacities

than the less educated. There are different aspects to screening, but arguably they share the

common ground of education as a positional good, an issue now addressed.

In his work social limits to growth, Hirsch (1976) defines positional goods as those for

which their value is determined by how they rank in comparison with the attainments of

4 See Spence (1973); Blaug (1976).

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other people. The essence of the argument relies on two key ideas: a characteristic of pure

positional goods is that the total level of welfare to be derived from such goods in a market

is fixed, and the value that these goods can provide to an individual diminishes as more

people have them. In an extreme version, it follows that an increase in the benefits derived

from positional goods for one individual is entirely at the expense of others.

For this aspect of screening in the context of education and labour market outcomes, the

value of education depends on the amount and quality of education attained by an indi-

vidual relative to attainments by others. This stands in contradistinction to human capital

theory in which it is the absolute rather than the relative amount of education that matters

in the determination of the private returns to educational investments. Because of the

presumed relationship between productivity and tax revenue, it must follow that the po-

sition taken on this issue is fundamental to the value accorded to fiscal externalities.

Incorporating human capital and screening aspects of educational investment

It is sensible, and justified by the literature, to consider that the higher earnings of uni-

versity graduates consist of returns to both pure human capital and screening. Several

empirical studies have consistently confirmed this notion.5 Consequentially, the value of

fiscal externalities will be less than would be considered to be the case in a pure human

capital framework. But how much less is a critical empirical aspect of this controversy and

has to be considered to be fundamental to the methods adopted and reported below.

Measurement in this area is extremely complicated, with Barr putting this point well: ‘‘The

validity of the [screening] hypothesis is an empirical issue which is undecided and likely to

remain so…’’6..Similarly, the ‘‘The ‘tax dividend’ point gives an efficiency case for some

subsidy [to higher education], but it is not possible to show how much.’’7 Nevertheless, for

public policy purposes in the current exercise, a decision has to be made.

Incorporating screening effects into our empirical exercise requires justification and

explanation. Since it should be noted that while empirical studies consistently confirm the

existence of screening in determining graduates’ incomes, the size of these effects varies

with data and method employed. Jaeger and Page (1996), using the US current population

survey data, have estimated the effect to be around 20–30 %. These magnitudes are

consistent with a subsequent study by Park (1999), but these two studies are not without

important limitations, now explained.

First, Jaeger and Page (1996) assumes that screening effects are independent of race.

But a later study by Averett and Dalessandro (2001) extends the Jaeger and Page (1996)

analysis to include race variables, finding the effect of race to be statistically significant.

This compromises the former paper’s estimates materially. With their improved estimation

approach, they conclude that a more accurate figure of the value of pure skill acquisition as

an explanation of the graduate earnings advantage is of the order of 60 %.

Second, Park (1999) assumes linearity in the effect of years of schooling. But subse-

quent work by Chevalier et al. (2004), using British’s Labour Force Survey data, shows

that the screening effect is nonlinear in years of schooling. They estimate the screening

effect to be around 53–58 % for a degree holder, implying pure human capital effects

(PHC) to be around 42–47 %.

5 See Hungerford and Solon (1987), Brown and Sessions (1999) and Chevalier et al. (2004).6 Barr (1993, page 719).7 Barr (1993, page 720).

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In addition, Canadian studies by Ferrer and Riddell (2001), using Census data and

Riddell (2008), using the Canadian International Adult Literacy and Skills Survey, have

estimated the contribution of screening to be in the order of 27–39 %. In the Australian

context, there are two recent estimates. The first is Barrett (2012), which uses the Adult

Literacy and Life Skills Survey 2006 data and finds that 37 % of the mean return to an

additional year of schooling can be accounted for by cognitive skills acquired through

schooling (that is, the PHC).

The second Australian study considered is that of Herault and Zakirova (2011), which

uses the Longitudinal Surveys of Australian Youth to estimate the effect. It finds that

Bachelor degree completion premiums are about 8 % in the first year after completing a

degree, which they take to be a measure of the value of screening. But the earnings

advantage increases to 12–13 % in the third year, which is assumed by the authors to

reflect skills, since graduates have then been observed properly in terms of labour market

activities. It can, therefore, be inferred that the screening effect accounts for around 67 %

(0.67–8/12); the remaining 33 % is attributed to a PHC.

In aggregate, and based on these findings, we are inclined to propose the boundary of

the PHC to be in the order of 40–60 %. This is an important assumption for our exercise

because it defines the extent to which we are able to attribute fiscal externalities to graduate

average earnings advantages.

Understanding the estimation strategy

Introduction

To put a value on Australian higher education externalities, we have adopted two strate-

gies. The first involves a calculation of the fiscal externalities taking into account the

relative weights that need to be accorded to both human capital and screening contributions

to graduate relative earnings. Second, to these calculations, we need to add estimates of

non-pecuniary externalities, and for these we have relied heavily on both the conceptual

approach and empirical estimates described and analysed in McMahon (2006).8 We em-

ploy age-earnings profiles as a tool for estimating both fiscal and non-pecuniary exter-

nalities, and we explain how the data presented in Table 4 in Appendix 1 can be used in the

application.

The use of age-earnings profiles as the basic tool of the analysis

Economists commonly use human capital theory to estimate so-called social rates of return

to education, and this involves comparisons of the average lifetime earnings of graduates

and of non-graduates. Hypothetical cases can be constructed to calculate the investment

returns to the process, and there are many examples in the Australian context.9 With the

use of various methodological innovations explained below, the tool can also be used to

help determine the size of externalities, both fiscal and non-pecuniary. The externalities

can then be converted into dollar estimates (which need to be considered in a dynamic

context through a conventional discounting process).

8 These should be considered the most thorough empirical treatment of non-pecuniary education exter-nalities in the international research arena.9 See Daly and Lewis (2010).

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To illustrate what we are doing, Appendix 2 shows the sorts of comparisons in con-

ceptual terms between the lifetime earnings of graduates and of non-graduates that can be

used for our exercise. In this illustration, it is assumed that the fiscal externalities from

higher education are the point of interest and that 100 % of the additional tax revenues are

the result of the additional productivity associated with higher education only. Obviously,

from ‘‘Measuring the true role of education’’ Section, this is not an assumption that should

be used in the actual empirical implementation of our strategy and is adopted initially only

to make the method clear.

The data available from McMahon and shown in Table 4 in Appendix 1 are a critical

aspect of the exercise explained below. This is because they include empirical estimates

drawn from a large number of international sources concerning the role of many different

types of non-pecuniary externalities from higher education. It is important to understand

that these have been presented by McMahon (2006) in a way that allows us to convert them

into proportions of conventional rates of return, a point clarified in ‘‘The data and results’’

Section.

From Table 4 in Appendix 1, it should be clear that all these externalities are extremely

difficult to measure in monetary terms. For example, a conversion of a 1 % increase in a

human rights index (item 4) into a dollar figure requires knowledge of the independent

empirical relationship between a human rights index and the country-specific growth of

GDP. Similarly, the education externalities from public health are very hard to identify

since they require standardization of a measure of the health status of a country’s

population. To take this latter example further, a one-unit cost of such a health index must

then be constructed in order to convert the effect into monetary values. Yet the approach,

in combination with the age-earning profiles, still provides international approximations

that are of use in an estimation of broadly based calculations of non-pecuniary externalities

for Australia.

The method for deriving aggregated higher education externality results

The first part of our method involves calculating the direct fiscal externalities from higher

education, and this is fairly straightforward. From econometric estimation illustrated in

‘‘The data and results’’ Section, we are able to determine the additional tax paid by

graduates over their lifetimes compared to that of non-graduates, and this will allow

estimation of the extra tax receipts (the ‘‘fiscal dividend’’) from graduates. These annual

figures need then to be adjusted for the proportion of the additional earnings assumed to be

the result of the increased productivity as a result of higher education (remembering from

Table 2 Higher education externalities of OECD countries (% per annum)

Social rates ofreturn

Returns to additional non-marketexternalities

Total social rates of return to highereducationa

8.5 2.5 11.00

Source Adapted from Table 6.5 in McMahon (2006)a Non-market private returns have been omitted

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‘‘Human capital theory, screening and the value of education’’ Section that this is assumed

to be between 40 and 60 %).

The second part of the process is more complicated. To help to simplify our under-

standing of the exercise using the McMahon (2006) approach, Table 2 provides very

broadly based aggregations of non-pecuniary higher education externalities levels for

OECD countries. There are two components of this aggregation. The first is the conven-

tional social rate of return for higher education, which captures private monetary benefits

plus benefits to GDP, including with the use of assumptions concerning technological

progress and spillovers, since these affect labour productivity and thus will be reflected in

earnings. McMahon estimates this value to be approximately 8.5 % points of the private

rate of return per year.

The other component consists of estimating values of all the non-pecuniary externalities

considered in Table 4 in Appendix 1 and expressed also as a percentage of the private rate

of return. Examples are better public health, lower deforestation, greater political stability

and improvements in human rights. It has been estimated that, out of the 11.0 % total

social rate of return to higher education reported in Table 2, the size of non-pecuniary

externalities is in the order of 2.5 % points per year.10 To perform the calculations, it is

assumed that Australian higher education externalities as a proportion of fiscal externalities

are equivalent to the OECD’s average as shown in Table 2. While this is certainly a strong

and not necessarily obvious assumption, it is also critical because it offers a new (and only)

way to calculate the total contribution from non-market externalities in terms of Australian

age-earning profiles. The latter are readily available, and our contemporary estimates are

reported in ‘‘The data and results’’ Section.

A simple example helps show how this second part is achieved. From Table 2, the

social rate of return to higher education in the OECD is approximately 8.5 % per year, and

this can be converted into an expected additional stream of total earnings per year for

graduates relative to non-graduates. This means that the value of the non-pecuniary ex-

ternality assumed to add 2.5 % per year to the social rate of return will be about 30 %

above graduate social rates of return (that is, 2.5/8.5 = 0.294), and this can be converted

into a dollar figure for Australian higher education. This then constitutes an estimation of

the value of the non-pecuniary externalities from higher education.

The data and results

Introduction

What now follows is a description of the data used in the implementation of the conceptual

and empirical methods explained above. Two numbers are of interest with respect to higher

education: the size of the direct fiscal returns to government from additional productivity

and the value of non-pecuniary externalities associated with higher education expressed as

a percentage of graduate lifetime earnings. From the explanation above of the methods to

be used, the critical data issues and results depend on estimations of the age-earnings

profiles.

10 An average estimate derived from McMahon’s consideration of a large number of studies.

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The data and age-earnings profiles

The standard approach employed in labour economics consistent with the construction of

an earnings function is an econometric equation that uses earnings of graduates as the

dependent variable and labour market experiences as independent variables.11 Because we

are interested in the additional externalities associated with higher education compared to

completing high school only, we also need to estimate the same function for high school

completers only.

We use high school completion and university graduate earnings data from the

household income and labour dynamics of Australia (HILDA) survey for 2008, with

earnings data adjusted by aggregate wage inflation 2008–2014 to derive 2014 values. The

data set includes both males and females for all dimensions of labour market status (full-

time work, part-time work, unemployed and not-in-the-labour-force). By incorporating sex

and labour market status into the earnings functions, the estimated age-earnings profiles

should be interpreted as the expected average lifetime earnings for males and females in

total. We note that (as is usual) we exclude self-employed graduates, since it is difficult to

determine precisely what their true earnings are (as distinct from an imputed capital

return). To take into account economy-wide productivity growth over time, we also impose

a 1.5 % growth per year in real earnings.

Figure 1 presents the results of the econometrics in age-earnings space. In all statistical

senses, the profiles are very familiar and we are comfortable with the notion that they

represent an accurate depiction of Australian contemporary age-earnings relationships

differentiated by education.

Using the age-earnings profile results to calculate the value of externalities

Given estimates of the average lifetime earnings differences between graduates and non-

graduates, we are now in a position to estimate the value of both the direct fiscal and non-

pecuniary externalities associated with higher education. As anticipated above, there are

several steps involved in the calculation.

One, the process begins with estimations of the total present value of lifetime tax

collectible from high school and university graduates.12 The difference between the life-

time taxes of these two groups is thus assumed to be the value of the fiscal externalities of

higher education. This estimate of the value of direct fiscal externalities is adjusted by the

value of the direct human capital (that is wealth-creating) contribution. As discussed in

‘‘Measuring the true role of education’’ Section, we have chosen 40-60 % as boundaries

to represent the extent to which higher education contributes directly to additional levels of

productivity.

11 Econometric specification of this earning function takes the following form:

lnIi ¼ b0 þ b1experiencei þ b2experience2i þ ui; ð1Þ

where Ii is the annual earnings of individual i, and experiencei is the potential length of time a graduate hasbeen employed12 We use a real discount rate of 5 per cent per annum to derive their respective present values.

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Two, to obtain non-pecuniary externalities, we assume they are proportional to the

direct fiscal externalities, and following McMahon (2006), we accord the proportionate

value to be 30 %. In summary, our approach reflects an assumption that the total value of

higher education externalities is the sum of direct fiscal externalities and non-pecuniary

externalities, all measured as proportions of the private rate of return to higher education.

The value of externalities from Australian higher education: results and discussion

Table 3 presents the present values of our estimates of the average externalities associated

with Australian higher education for both a 4-year degree and for each year of the degree.

There are two columns representing the assumptions that the PHC is either 40 or 60 %.

The essential result is that our best estimate of the addition of the non-pecuniary and

direct fiscal dividends to government from higher education in present values lies between

about $10,635 and $15,952 in 2014 terms for each year of an average university graduate

experience.

These estimates can be compared usefully to recent analyses of Australian data on the

same issue. Most importantly, Norton’s Graduate Winners report in 2012 provides an

examination of the financial and non-financial benefits of investment in Australian uni-

versity education. Several key findings of this work are of interest in the context of our

exercise. First, the report provides empirical evidence of the existence of financial and non-

financial externalities. Second, Norton acknowledges the importance of public benefits in

deciding university education subsidies. A supplementary exercise to examine net public

financial benefits is based on lifetime tax paid by a degree holder minus tuition subsidies

and shows that public benefits with respect to fiscal externalities differ with respect to the

discipline studied, implying that subsidies should be set to reflect the average benefits

associated with each discipline.

Fig. 1 Average Australian graduate age-earnings profiles (2014)

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Savage and Norton (2012) examine the non-financial benefits from university education

in Australia. They conducted statistical analyses investigating causal relationships between

the acquisition of a university education and such non-financial benefits as wellbeing,

volunteering, civics, social distance and relationships, social aspects of job type and private

non-financial aspects of job type. They find that a university education apparently provides

positive influences on health, life satisfaction, civic behaviour and, in general, receptivity

to people from different cultures. However, their analysis does not go beyond the testing of

the existence of the relationships and into the more complicated arena of attempting to put

a dollar value on the size of these relationships. That is the essential difference between

their analysis and the aim of this current exercise.

Caveats, problems and policy issues

Introduction

We are acutely aware of the limitations of our method, in two respects: one, we have not

been able to take sufficiently into account several significant dimensions of potential higher

education externalities and, in particular, the implications of higher education for that most

important aspect of per capita economic growth, technological progress, and two, the role

of time on the delivery of benefits. Further, the simple rule in neo-classical economics i.e.

to attain allocative efficiency in the presence of market failure, governments should sub-

sidise or tax activities to the extent of the marginal value of the externalities may not be

informed particularly accurately with the use of our estimates. All three issues are now

addressed.

The critical role and understanding of technical change

The contribution of ‘‘technical change’’ to economic growth has been the focus of eco-

nomic theory and empirical analyses for a long time. The term can mean many things and

take many forms, with some of the critical issues concerning the relationship between

technical change and higher education being as follows:

1. Technical change directly affects productivity growth, and there is a literature

emphasising the notion that higher levels of education influence this process

positively;

2. R & D is considered to be the main contributing factor to innovation, and there are

clear associations between progress in R & D and expansions of the research

conducted in higher education; and

Table 3 Present values of higher education externalities (Four-year degree) in 2014 terms

Assumed PHC 0.50 0.60

Total 4-year degree $42,539 $63,809

Per year of higher education $10,635 $15,952

Calculations assume a 10 % downward ability/motivation adjustment

778 High Educ (2015) 70:767–785

123

3. Education contributes to the implementation of new technologies and facilitates the

adjustment of the labour force to both positive forces (such as innovation) and adverse

shocks (such as unanticipated financial crises).

While there is general conceptual agreement that the processes and factors outlined

above are extremely important, a major issue in undertaking an evaluation of externalities

is that there is no agreed empirical method which allows the above forces and their

complex interactions to be measured. This point matters considerably for an interpretation

of the methods and results reported.

A consideration particular to be highlighted is that, if the focus of the work is on those

externalities for which there is an agreed methodological basis, yet this focus essentially

ignores the contribution of higher education to technical change, it must be the case that the

statistical boundaries reported understate the true (and unmeasured) value of higher

education externalities. This should be seen as an important limitation of all work in this

area.

The role of time in the delivery of externalities

It should be clear that the complexities associated with understanding and measuring the

interaction of higher education and technical change are significant. There is also a further

conceptual and measurement issue related to the timing of delivery of externalities. This is

now considered briefly.

An important question relates to how long it takes for a more highly educated individual

to help to deliver the types of externalities from higher education into valuable outcomes

for society? It obviously takes time for a new university student to become a graduate,

often as long as 5 or 6 years. Once a new graduate is in the workforce, there will be a

further period before the productivity benefits of higher education can be realised. The

processes of on-the-job training are fundamental to returns to investments in human

capital, and these are likely to have many different forms and durations.

It follows that estimating the value of externalities must address the time dimensions

involved. To take a current example outside of higher education, a particular level of a tax

on carbon emissions can be seen to be extremely good or extremely poor policy depending

on how long it takes for the presumed benefits to be realised. That is, putting a value on

externalities requires a large number of dynamic modelling inputs, none of which is

obvious in empirical terms.

The one way in which we have attempted to take time dimensions into consideration

empirically is through the choice of the time preference (discount) rate and the built-in

productivity growth assumption. While we believe we have adopted a plausible figure, this

too has to be the subject of further thought and examination.

Conceptual difficulties with ‘‘policy implications’’

As implied in the Introduction, the provision of estimates of the value of externalities is

potentially very important for higher education public policy, for two reasons:

1. Governments are interested in economic wellbeing, and there is no doubt that one of

the critical factors contributing to social and economic progress is education; and

2. A basic economic principle is that governments should offer incentives and impose

penalties in such a way that socially desirable activities are encouraged (through

High Educ (2015) 70:767–785 779

123

subsidies) and that socially undesirable behaviour is discouraged (through higher

levels of direct taxation).

It should be obvious that these issues potentially have fundamental implications for a

number of policy questions, such as: what is the appropriate level of government subsidies

for higher education? and what prices should be set for undergraduate tuition that max-

imise the efficiency of resource allocation to the sector? However, there are several clear

and critical aspects to the use of our results for subsidy/pricing decisions which need to be

recognised.

The first is that we have not attempted to distinguish the value of higher education

externalities by discipline studied in the way that Norton (2012) did, and in some respects,

our approach is uncomfortably aggregate in nature. It is perhaps true that some spillovers,

such as with respect to diminished crime and enhanced health, do not vary with respect to

the area of study and/or the eventual occupation of the graduate. But this cannot be the case

on average with respect to average fiscal income tax dividends simply because, for ex-

ample, medical specialists and most lawyers will earn higher lifetime incomes than most

teachers or nurses. It follows that more disaggregated analyses are an obvious next step in

the application of our methods.

Second, and more contentious in our view, is that the results reported here have been

derived from the use of average graduate incomes and thus are not directly relevant to the

derivation of a subsidy rule for the government. That this is true is not contentious unless

the externalities of the average graduate are roughly the same as they are for the ‘‘mar-

ginal’’ graduate, the last student admitted into the Australian university system. This may

very well be the case, but we have no way of knowing and finding the presumption

unconvincing. There is at least no empirical evidence for the proposition.

What the above important caveat means is that our calculation of the average dollar

value for graduates cannot be used directly as an accurate guide for a government to set

prices/subsidies for public sector universities. Instead, the value of the exercise beyond the

research innovation involved in the development of the method lies in the accounting

benefit for the budget and non-financial social aspects associated with the provision of

higher education.

Many of the methodological and policy issues remain yet to be resolved with respect to

the true value and meaning of externalities from universities. Even some the complexities

are worth describing to encourage humility and caution with the respect to the clarity of the

estimates that emerge of the value of higher education processes.

Conclusion

Our analysis has traversed a highly complicated area of economic analysis, in conceptual,

theoretical and measurement terms. Estimating the value of the externalities associated

with higher education is a difficult area in the economics of education literature, yet it is

also arguably a critical component for public policy in this area. We have devised a method

which has not been used before and which could be applied quite easily to similar cal-

culations in all countries.

We have reported the complexities with as much accuracy as we can, and we have

endeavoured to be precise with respect to the limitations of method and the necessary

restrictions of the assumptions required. It should be stressed, again, that the measurement

issues are such as to imply that the range of estimates produced should be interpreted to be

780 High Educ (2015) 70:767–785

123

lower boundaries of the true (and in reality, unmeasurable) externalities from higher

education. With this caveat, we have some confidence that the calculations offered are

consistent with the sound application of theoretical and methodological economic and

statistical principles.

One reason this job has been difficult and our conclusions open to debate is that many

aspects of this exercise have not been done in an Australian context (for example, the value

of crime reductions are taken from OECD average estimates). As well, there are many

technical and theoretical complications associated with these issues and our method.

A further complication is that there is no evidence that the value of the non-pecuniary

externalities differs in a systematic way between courses studied, disciplines and profes-

sions, and consequently like most analysis in this area, we have imposed the assumption

that the spillovers will be delivered independently of these factors. This has been ap-

proached through calculation of the externalities for the hypothetical average person en-

roling in higher education. An additional and related point is what this all means in a policy

context, and we stress that our estimates should not be used as a guide for price setting and/

or determining the extent of subsidies: this is because there is no reason to believe that

these average calculations truly reflect the situation of the marginal student. And even if

the average and marginal values are the same, it is still the case that behavioural responses

to price changes would occur in reality in response to different levels of subsidies.

With these important qualifications and complexities, we are prepared to present a very

approximate and aggregate range of the expected discounted value of the externalities

associated with an additional year of higher education in an Australian context, valued at

the time of enrolment and on average. This range, in 2014 dollars, is between $10,635 and

$15,952 (or around $42,000 to $64,000 for a 4-year degree).

Acknowledgments We are grateful to the Australian Research Council for financial support with Linkagegrant number LP 110200496. A version of this paper was originally prepared for the Higher Education BaseFunding Panel on behalf of the Australian Government Department of Education, Employment and WorkPlace Relations, and we are grateful for their permission to publish the research. We acknowledge also thevaluable input of several referees, one of whom made exceptionally productive suggestions. This paper usesunit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. TheHILDA Project was initiated and is funded by the Australian Government Department of Families, Housing,Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute ofApplied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper,however, are those of the authors and should not be attributed to any Australian Government Departments orthe Melbourne Institute. Errors, omissions and the views expressed are those of the authors only.

Appendix 1

See Table 4.

High Educ (2015) 70:767–785 781

123

Table

4Estim

ates

ofeducationexternalities

Typeofoutcomeaffected

by

education(1)

Per

centchangein

outcomeofeducation

after40Years

(2)

Basisforestimate(3)

Source(4)

1.Betterpublichealth

Positive,

butpublicversusprivatehealth

effect

unknown

Micro-regressionsonly.AID

Seduc.

potential

Grossman

andKaestner

(1997)

2.Lower

pop.growth

0%

inAfrica,;elsew

here

;fertilitybut:

health

AppiahandMcM

ahon(2002)

3.Dem

ocratization

36%

:in

dem

ocracy(i.e.freedom

house

index

up2.9

(from

3.7)to

6.6

Note:Thisinvestm

entof$13.80per

capitaraises

gross

enrolm

entrate

byabout20%

points.

Includes

2.3

%formore

volunteering.2%

ofmarket

rate

Includes

more

fin.gifts:12%

giveover

3%

oftheirincome

Volunteeringandfinancialgivingare

ateach

incomelevel

4.Human

rights

4%

:in

human

rights,onfreedom

house

index

5.Politicalstability

3.1

%:in

politicalstability,internat’

countryrisk

guide

AppiahandMcM

ahon(2002)

6.Lower

crim

erates

2%

;in

homiciderate

1.2

%:in

property

crim

eButsecondaryenrolm

entreduces

property

crim

e9%

ifincome

controlled

for.

AppiahandMcM

ahon(2002)

Plus2%

rate

ofreturn

dueto

Lessincarcerationcosts

Lochner

(1999)

7.Deforestation

0.3

%;in

annual

forest(andwildlife)

destructionrate

Alloccurfrom

combined

indirect

effectsofslower

population

growth,less

poverty,more

dem

ocracyandfaster

economic

growth.

AppiahandMcM

ahon(2002)

8.Water

pollution(ForIndia,better

data)

13%

;in

water

Pollution

McM

ahon(2002)

9.Airpollution

14%

:,growth

increasesit.

10.Poverty

reduction

18%

;in

Poverty

Pri.&

Jr.secin

villages

AppiahandMcM

ahon(2002)

11.Inequalityreduced

8%

;in

Inequality(inGIN

I)Only

ifaccess

widened

AppiahandMcM

ahon(2002)

782 High Educ (2015) 70:767–785

123

Table

4continued

Typeofoutcomeaffected

by

education(1)

Per

centchangein

outcomeofeducation

after40Years

(2)

Basisforestimate(3)

Source(4)

12.Geographic

Positiveas

HCisgained

Jr.Sec

helpsprovinces

13.Spillovers

NegativewhereHCleaves

Higher

Ed.:em

igration

14.Inform

alknowledge

dissemination

Overlaps1–13aboveunknownnet

effects

Technologiesraisenon-m

arket

productivitytoo

e.g.Moretti(2002)

15.More

schooling

20%

:in

enrolm

entrates

From

2%:in

investm

ent

McM

ahon(2002)

SourceAdaptedfrom

Table

6.5

inMcM

ahon(2006)

High Educ (2015) 70:767–785 783

123

Appendix 2

Figure 2 below illustrates several elements pertaining to the calculation of private rates of

return as well as the value of fiscal externalities. In the figure, Y represents gross earning

and T represents tax paid by each level of education.

Where:

(a) is the total opportunity cost of government in terms of foregone tax income;

(b) is the total after-tax earnings in the first 4 years upon completing Y12;

(c) is the total private costs of pursuing university study;

(d) is the total additional tax paid by a university graduate;

(e) is the total additional after-tax earnings of university graduate;

(f) is the total tax paid for 4 years after completing Y12 until retirement; and

(g) is the total after-tax earnings from 4 years after completing Y12 until retirement.

With the figure, private benefits and fiscal externalities can be calculated as follows:

1. Private benefit = (e)–(b)–(c); and

2. Fiscal externalities = (d)–(f)–(a).

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