Measuring the value of externalities from higher education · externalities, and if they are...
Transcript of Measuring the value of externalities from higher education · externalities, and if they are...
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: [email protected]
B. Chapmane-mail: [email protected]
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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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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