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Forthcoming in Studies in Higher Education
The economic impact of higher education institutions in Ireland: evidence
from disaggregated input output tables
Qiantao Zhanga,*, Charles Larkina,b & Brian M. Luceya,c
a School of Business, Trinity College Dublin, Dublin 2, Ireland
b Cardiff School of Management, Cardiff Metropolitan University, Llandaff Campus,
Western Avenue, Cardiff, CF5 2YB, United Kingdom
c Faculty of Economics, University of Ljubljana, Kardeljeva ploščad 17, 1000 Ljubljana,
Slovenia
* Corresponding author.
E-mail addresses: qizhang@tcd.ie (Q. Zhang), larkinch@tcd.ie (C. Larkin), blucey@tcd.ie
(B.M. Lucey)
Forthcoming in Studies in Higher Education
The economic impact of higher education institutions in Ireland: evidence
from disaggregated input output tables
Abstract
While there has been a long history of modelling the economic impact of higher education
institutions, little research has been undertaken in the context of Ireland. This paper provides,
for the first time, a disaggregated input output table for Ireland’s higher education sector. The
picture painted overall is a higher education sector that adds considerable gross value to the
national economy, whether via state or other income. In 2010-11, the gross income of Irish
higher education institutions, as a total of €2.6 billion, generated gross output nationwide of
€10.6 billion. This study also contributes to the major challenges facing the sector in a post-
Bailout environment.
Keywords
Input output analysis; economic impact; Ireland; universities; institutes of technology
Introduction
In the last decades, numerous studies have examined the economic impact of such diverse
actions such as sports events (Badde and Dye 1990; Crompton 1995; Oxford Economics
2012), large scale cultural projects (Saayman and Saayman 2006; Travers 2006), and
industrial sectors (Hall, Hodges, and Haydu 2006; OECD 2004). Generally, an economic
impact analysis is useful when there is public concern about the impacts of those actions. In
the context of the fiscal crisis since 2008, there has been mounting pressure on recipients of
exchequer funding to ensure value for money, as many nations have been faced with a
tightened government budget constraint. Deriving a large proportion of income from
government bodies, higher education institutions (HEIs) are not immune to these challenges.
Nevertheless, the modern history of modelling the impact of HEIs goes back to as early as the
1970s. In the United States (U.S.), Caffrey and Issacs (1971) outlined a template which has
been followed by much of the work examining the regional impact of American universities
and colleges, often in the context of budgetary negotiations. Outside the U.S. the largest
extant set of studies is on the United Kingdom (UK), where the foundational work is that of
Brownrigg (1973) on the University of Stirling, followed by Bleaney et al. (1992) on the
University of Nottingham. In the UK and Europe, similar studies have also been conducted
on many other universities such as the University of Portsmouth (Harris 1997), the
University of Aberdeen (Battu, Finch, and Newlands 1998), and Izmir University of
Economics (Sen 2011).
The evaluation of the economic impact of HEIs has mainly been undertaken in two
methodological strands. While most early studies used a Keynesian multiplier approach,
more recent work has tended to concentrate on input output modelling. Developed by
Leontief in the late 1930s, the input output framework aims to analyse the interdependence of
industries in an economy at many geographic levels – local, regional, national, and
international. The seminar paper is Leontief (1936) and a discussion of the importance of the
approach is given in Baumol (2000). When constructing the Leontief input output model, one
is concerned with the flows of products from each industrial sector, considered as a producer,
to each of the sectors, itself and others, considered as consumers. Dependent on specific
sector classifications, the number of industries considered in practice may vary significantly.
Nevertheless, input output analysis has become one of the most widely applied methods in
economics and been recognised as a useful tool to understand the impact of individual
industries in the whole economy.
Forthcoming in Studies in Higher Education
In the UK, we have seen a number of analyses of HEIs via the input output model over the
last 15 years (Kelly and McNicoll 1997; Universities UK 2014). The model has further been
extended to construct an HEI-disaggregated input output table, with each HEI being
considered as a separate sector (Hermannsson et al. 2010a, 2010b, 2010c). To our knowledge,
little research of this kind has been undertaken in the context of Irish higher education sector.
In this paper, we provide an economic impact analysis of the majority of the Irish higher
education sector, representing one of the first public attempts to analyse the higher education
space in Ireland. Indeed, while there has been a lot of talk about the financial sustainability of
higher education and the search for new funding models in universities and other HEIs in
Ireland, little empirical evidence exists to guide policy-making. Our analysis has potential to
inform the major challenges facing the sector in a post-Bailout environment.
For an institution, sector or industry, its overall impacts are most likely to be multifaceted
and greater than what an economic impact analysis could measure. It has been widely
recognised that universities generate a wide range of benefits with impacts on the economy,
society, and their nation’s cultural life (Felsenstein 1996; Glasson 2003; Goddard and
Vallance 2013; Huggins and Johsnton 2009). Our analysis does not incorporate the human
capital, research and development (R&D), and entrepreneurial economic returns generated by
the sector, neither does it looks at the non-economic returns of education. We are conscious
that a narrow economic focus on the ‘impact’ of higher education is partial and incomplete.
The social, personal and cultural benefits both economic and other of a thriving and effective
higher education system are not amenable to easy metrification and are not captured here. To
this effect, the study, with the economic focus, attempts to answer a direct question: Does the
economy receive more than one euro’s worth of economic activity for every euro it spends on
higher education in Ireland?
The paper starts from recognition that the economic impact of Irish HEIs has hitherto not
been examined in any detail. It has five further sections. The next section gives an overview
of the historical development of the higher education sector in Ireland and highlights the
recent policy context in which the sector is operated. The third section briefly introduces the
previous research on measuring the economic impact of HEIs before outlining the
methodology. Section four describes the data we use and how they are collected. The fifth
section presents the main findings, including the output multipliers, balanced-budget
multipliers, and employment multipliers, which are also compared to those of UK universities.
The paper concludes with a discussion of the potential contributions our study could make to
the current policy debates in Ireland.
Overview of the Irish higher education sector
Over the last few centuries, the higher education sector in Ireland has experienced
considerable expansion, with the pace of change accelerating dramatically since the 1970s. In
the early 20th century, as Coolahan (1981) notes, only 3,200 students were enrolled at five
universities in Ireland, while the latest data shows that over 208,000 students enrolled at
seven universities, 14 institutes of technology (IoTs) and six colleges in 2013-14 (HEA 2015).
The oldest university in Ireland is the University of Dublin, Trinity College, founded in 1592,
with two national institutes of higher education, which were formed in the 1970s, becoming
Dublin City University and the University of Limerick during the courses of the 1980s
(White 2001). The Dublin Institute of Technology (DIT), the oldest and largest of the IoTs,
dates back to 1887, with the majority of the IoTs dating from the mid-1960s onwards (Barry
1985; Daly 1981). During most of this time, the IoTs were largely engaged in further
education and apprenticeship activities with some of the larger institutes gradually taking on
an active role in higher education delivery. At present a number of the IoTs are aiming to
transit to the new status of technological university, pursuant to the Technological
Forthcoming in Studies in Higher Education
Universities Bill current being drafted by the Government (DES 2014). In addition, the six
colleges are those institutions with specialised course delivery in the areas such as education
and medicine.
Following the expansion of Irish secondary education in the mid-1960s, which is a result
of the introduction of free secondary education in 1969, the massification of higher education
began (Hyland 2014; O’Connor 2014). The increase in student numbers was to continue from
the early 1970s to the present day with at present 51 per cent of school leavers into
university-style higher education (OECD 2014a). The national target, as stated in the
National Plan for Equity of Access to Higher Education released in 2008, was 72 per cent of
school leavers by 2020 (HEA 2008). A key feature of the massification of higher education in
Ireland has been the establishment of the binary system which consists of universities and
IoTs. Initially known as Regional Technical Colleges, the IoTs were created as part of a
vocational education sector “for trade and industry over a broad spectrum of occupations
ranging from craft to professional level, notably in engineering and science, but also in
commercial, linguistic and other specialties” (Government of Ireland 1967, p. 11). A binary
system is the most common model for the organisation of higher education in many countries,
while in countries such as the UK there is a unified but hierarchical system (Kyvik 2004;
Mahony 1993; Meek 1991; Taylor 2003). In the context of Ireland, although there have seen
collaborations and alliances within and across the binary divide, as stated in the National
Strategy for Higher Education to 2030, there are still clear differences between universities
and IoTs in terms of research intensity and mission statements (DES 2011).
Until the 1960s, the Irish economy was largely based on agriculture and the country was
among the nations with the lowest rate of research expenditure in Europe (Boylan et al. 2011;
OECD 1966). In 1963, the percentage ratio of Irish research and development (R&D)
expenditure to Gross National Product (GNP) was 0.58, much lower than the figures in the
U.S. (1.56), the Netherlands (1.7) and the UK (2.5). Since then, in particular from the 1990s,
significant progress has been made in Ireland in this area, as the Irish Government has shown
commitment to supporting R&D in its plan to build a knowledge-based economy (Forfás
2004). In 2012, the gross expenditure on research and development (GERD) in Ireland was
nearly €3.5 billion in current prices, accounting for 2.11 per cent of GNP, at the same level as
the EU-15 and much higher than the UK (1.72) (OECD 2014b). Receiving a significant
influx of government investment for R&D, higher education benefited with the HERD in
Ireland increasing from €204 million (1998) to €898 million (2012) (Forfás 2009; OECD
2014b). Between 2000 and 2010, Ireland’s HERD intensity – the relative performance of the
HERD to the GNP – increased significantly from 0.26 per cent to 0.56 per cent, although the
increase after the 2008 financial crisis was mainly due to the reduction in GNP (Forfás 2013).
A further comparison between Ireland R&D levels – GERD, BERD and HERD – with those
of the OECD averages suggests that Ireland’s HERD intensity has always shown better
relative performance than its GERD and BERD, implying that the higher education sector in
Ireland is where its relative R&D strength lies (OECD 2014 b).
Though universities and institutes of technology have been considered to be an important
part of the national manpower and economic strategies, they only began to be considered as
part of a national innovation, research and development industrial policy towards the late
1990s (OECD 1987). This was following the milestone event of introducing free higher
education in 1996 by Minister for Education Niamh Bhreathach, TD. The period between
1996 and the present has been one of great activity in terms of national policy, with the
passage of the Universities Act 1997 and the Institutes of Technology Act 2006, the
establishment of Science Foundation Ireland in the Industrial Development Act 2003 and the
creation in 2001 of the Irish Research Councils for Humanities and Social Sciences and
Science, Engineering and Technology (now merged into the Irish Research Council). In 2006
Forthcoming in Studies in Higher Education
the Department of Enterprise, Trade and Employment published the Strategy for Science
Technology and Innovation aimed at placing research and higher education at the core of the
Irish economic policy (DJEI 2006). This was followed up by the Innovation Task Force,
which reported in 2010, again placing the universities and their role in R&D at the core of the
Irish industrial policy. Despite all this and a multitude of official and other reports on the
finances and structures of the sector, little in the way of formal economic impact analysis has
been undertaken.
Our analysis is confined to a single base year – 2010-11 – at which time the sector was
only in the beginning of a process of downsizing staff and re-evaluating budgetary positions
as a result of an Employment Control Framework to reduce both headcount and staff costs
and in the wider context of fiscal austerity imposed by the IMF-ECB-EU Bailout of
December 2010. This challenging external macroeconomic environment must be
acknowledged while evaluating the results of this study. The choice of exercising the analysis
for a single year was mainly due to data limitations, as in Ireland there were not time-series of
input-output tables. For the academic year 2010-11, the sector had a total of 185,342 students
enrolled and employed 21,811 staff (HEA 2013). The overall expenditure of the institutional
side of the sector, not including the expenditure of staff and students, was €2.61 billion of
which €1.45 billion was provided by government sources directly (HEA 2014). From a policy
perspective, as Irish HEIs form an important part of the economy infrastructure and generate
substantial economic activity, a detailed analysis of the sector’s economic impact is needed.
Measuring the economic impact of higher education institutions
In the context of evaluation of the economic impact of HEIs, a comprehensive review of
some of the methodological and interpretational challenges can be found in Siegfried,
Sanderson, and McHenry (2007). More recent discussions include McHenry, Sanderson, and
Siegfried (2012), Garrido-Yserte and Gallo-Rivera (2009), Pastor, Pérez, and Fernández de
Guevara (2013), which papers all in effect urge caution over grandiose claims for impact.
Particularly, universities have significant downstream effects on society and on the economy
from skill enhancement, which are both conceptually and empirically difficult to measure.
Private and public benefits are clearly identified from attainment of higher education – see
Kelly, O’Connell, and Smyth (2011), Long (2010), and Oppedisano (2014) as examples of
studies that focus on different aspects of this measurement issue. In this paper we, as already
mentioned, concentrate on a high-level macroeconomic impact. Nonetheless, that we cannot
easily capture all impacts is not to say that we should avoid capturing some impacts. This
paper thus begins that process.
The methodology employed in this paper for the construction of the input output table
follows the normal approaches that have been clearly defined in previous studies. In general,
input output modelling assumes two types of spending – exogenous and endogenous.
Exogenous spending is assumed to be independent of the sectors being modelled, while
endogenous spending is determined within and reacts to shocks to the sectors. Government
spending, exports and investment are typically taken as exogenous. Household spending can
be treated as either exogenous or endogenous. If endogenous, the system is said to be ‘closed’
to the household sector and a system that is so closed yields Type II multipliers. A key
assumption underlying input output modelling is that the system is demand not supply
determined, thus the supply side is passive, fixed. We can justify this either by suggesting we
are in a situation of excess capacity and negative output gap (as was certainly the case in
Ireland in 2008-13), or if we concern ourselves with long-run scenarios where such
limitations are non-binding, that the system can draw in more than sufficient labour and
capital to eliminate capacity constraints.
Forthcoming in Studies in Higher Education
There are a variety of multiplier effects one could derive from the input output analysis,
including output, income, employment or gross domestic product (GDP). The output
multiplier for each sector refers to ‘the change in total output for the economy as a whole
resulting from a unit change in the final demand for that sector’ (Hermannsson et al. 2014).
The Type I output multiplier for a particular industry is defined to be ‘the total of all outputs
from each domestic industry required in order to produce one additional unit of output’
(Scottish Government 2011), while the Type II output multiplier incorporates ‘not only the
increase in demand for intermediate inputs but also induced household consumption effects’
(Hermannsson et al. 2014). In other words, the Type I multiplier can be defined as direct and
indirect effects, and the Type II multiplier can be defined as direct, indirect and induced
effects. As this paper is concerned with high level economic impact of Irish HEIs, it is mainly
the Type II output multipliers that are presented.
Constructing Type I and Type II output multipliers
In the standard input output model endogenous final output is determined by exogenous final
demands via the Leontief inverse. Let:
(1)
(2)
where X is an nxn matrix of intermediate sector to sector transactions with xij being the
individual element of transactions from sector i to j, q the nx1 vector of output and the 1xn
vector of value adding inputs. If we replace xij with , where
(3)
then we can express the system as
(4)
where is an nxn matrix of the technical coefficients. Subtractingfrom both sides we get
(5)
If we then multiply both sides by the inverse of the matrix yields
(6)
where is the Leontief inverse matrix, q is the endogenous vector of final outputs,
and f the endogenous vector of final demands. The Leontief inverse shows the induced effects
of any change in exogenous demand. Indirect effects arise from an increased demand for
intermediate goods and, with Type II multipliers, induced effects arise via the impact of
increased household income being directed to increased consumption demand.
The output multiplier for each sector i, , is derived from the above. It is the change in
total economic output from a unit change in final demand for that sector and is estimated as
the sum of the entries in the relevant column of the Leontief inverse. This gives gross output
attributable to the final demands for the output of sector i as
Forthcoming in Studies in Higher Education
(7)
A further exposition of input output modelling is provided by many authors; see Miller
and Blair (2009) for a pedagogical demonstration.
Constructing balanced Type II output multipliers
As mentioned earlier, a large proportion of HEI income is derived from state sources.
Government budgets are limited, thus a euro spent on higher education is, at the limit, a euro
that cannot be spent on other public sector activities. In 2013, an investigation of the financial
health of the Irish higher education sector was undertaken by an international accounting firm
Grant Thornton (2013). They noted the financial strains the system is under, and believed that
this sector had reached ‘an inflection point’, highlighting the continual decline of state
support since 2008. There is however considerable variation in the degree of state support
across institutions, with IoTs much more dependent on income from state sources than
universities (HEA 2014). Therefore it is useful to consider disaggregation of these multipliers
to reflect this. Doing so allows us then to construct ‘balanced’ multipliers. Consider the
following as being the impact for an HEI i, where G and O stand for the share of total funding
from government and other sources respectively and m is the multiplier.
(8)
This is intuitive – the impact comes from both forms of expenditure. If we subtract the
impact that comes from the government funding, , where is the multiplier for
general government we can see the ‘balanced’ impact as
(9)
Dividing this through by total spend, , we get a ‘balanced multiplier’ of
(10)
where is the government share in total final demand of the institution.
Constructing Type I and Type II employment multipliers
We can also calculate employment multipliers, analogously with the gross output multipliers.
Instead of the output flows being included in the A matrix, we include job numbers, scaled by
output. As with the output multipliers we can create both Type I and Type II employment
multipliers. Due to space limitations, this section does not include detailed discussions of the
mathematical process of employment multipliers, which could be found in Scottish
Government (2011).
Data
Our analysis draws on a number of data sources, both primary and secondary. Due to data
limitations we exclude the colleges of education and the private HEIs such as Hibernia
College and Royal College of Surgeons in Ireland. The main focus of our analysis is therefore
on the seven universities and the 14 IoTs, where the bulk of public and private spending and
students are located, and the results are reported for the university sector and the IoT sector
respectively. To implement the input output analysis for each institution, the first and
foremost thing to do is to construct an HEI-disaggregated input output table, which views
Forthcoming in Studies in Higher Education
each institution as a separate sector and captures its income and expenditure under different
categories.
The HEI-disaggregated input output table was developed based on the 2010 Input-Output
Table for Ireland with an individual row and column being created for each institution. The
2010 Input-Output Table for Ireland was published by the Central Statistical Office (CSO) in
January 2014, providing a detailed picture of the transactions of goods and services by
industries and consumers in the Irish economy (CSO 2014). An essential task was to separate
out the HEIs from the ‘Education Service’ sector as a whole from the National Accounts. The
disaggregation was proceeded in two steps. Firstly, we disaggregated the ‘Education Service’
sector in the national table into a University sector, an IoT sector, and a residual education
sector. Secondly, we further disaggregated the two new sectors into each individual
institution. After that, we had an augmented input output table as the basis for our analysis.
Creating separate columns for each HEI (HEI expenditure)
In an input output table, a column reveals the total expenditure of a sector and how it is
divided between intermediate inputs, imports and value added. Table 1 below describes the
data sourced in creating a separate column for each HEI, with the level of detail
differentiating universities and IoTs, while Table 2 details the attribution of expenditures for
the individual HEIs and the two sectors. Data on the institute expenditure in 2010-11 was
sourced from the Higher Education Authority (HEA), the statutory planning and policy
development body for higher education and research in Ireland. Both the university and IoT
sectors include institutions that vary significantly in terms of size measured by expenditure
(HEA 2014). The HEA accounting data also shows the compensation of employees,
consisting of all payments in cash as well as in kind.
[Table 1 near here]
[Table 2 near here]
To estimate imports for each institution, we used data provided by the Irish Universities
Association (IUA) through an analysis of university supplier information in 2010-11. As
indicated by IUA (2014), the proportion of goods and services purchased by Irish universities
from nationally based businesses ranges from 77 per cent for University of Limerick to 97
per cent for University College Cork. While there is no comparable detailed information on
the supplier base of IoTs, we used the average ratio for the university sector as a proxy for
IoTs in the estimation of their imports. Therefore, we assume that imports to each IoT
accounted for 10 per cent of the value of total output in the year of 2010-11, although it could
be expected that many IoTs, in particular those smaller ones, would be more likely to
purchase goods and services from proximate businesses.
Operating surplus and product taxes less subsidies were determined for each university
and IoT as the same proportion of overall expenditure as in the education service sector as a
whole. These elements represent a small share of overall expenditure: 2.7 per cent for
operating surplus, and 1.3 per cent for product taxes less subsidies. Finally, the amount of
intermediate purchases from Irish industries was determined as the residual after deducting
all the above cost elements from the total expenditure. It was assumed that the university and
IoT sectors purchase from other industries in the same way shown by the education service
sector as a whole.
We could demonstrate the calculation using Trinity College Dublin as an example. In
2010-11, Trinity College Dublin spent €82.6 million on the purchase of goods and services
from external suppliers, with 18.5 per cent of that amount (€15.2 million) being imported
Forthcoming in Studies in Higher Education
from overseas businesses. Operating surplus and product taxes less subsidies, using the same
shares as in the education service sector, were €8.7 million and €4.2 million respectively.
Compensation of employees, according to the HEA data, cost Trinity College Dublin a total
of €217.5 million. Deducting all these cost elements from the total expenditure gives us total
intermediate consumption of €75.2 million.
Creating separate rows for each HEI (HEI income)
In an input output table, a row reveals the total income of a sector and how it is divided
between intermediate sales to other production sectors and sales to final demand sectors such
as households, government and exports. Table 3 below describes the data sourced in creating
a separate row for each HEI, and in Table 4 we show, in more detail, the input output rows
which reflect the particular structure of the individual HEIs and the two sectors, i.e. how
income of Irish HEIs is divided by source at the institutional level. A few notes should be
made to clearly explain the elements included in Table 4. First, under the category of ‘Irish
Government’, academic fee income refers to the amount paid by the HEA, while contribution
in respect of overheads is the amount paid by Science Foundation Ireland (SFI). Second,
under the category of ‘Exports’, academic fee income is the amount paid by international
students, industry income refers to the amount paid by international companies and is
allocated as 50 per cent of total income from industry, and other income means the amount
paid by international students and is allocated by the share of the number of international
students. Last, the category of ‘Other’ is determined as a residual item. As shown in Table 4,
it is clear that income from the Irish Government accounted for a large share of total income
for both the university and IoT sectors (HEA 2014). In comparison, universities were more
successful than IoTs in sourcing international funding, e.g. international student tuition fees,
research grants and industry funding.
[Table 3 near here]
[Table 4 near here]
Taking Letterkenny Institute of Technology as an example, each row is created as follows.
The Institute generated the total income of €30.7 million from all types of sources in 2010-11.
State grant income, which mainly relates to recurrent grants from the HEA, amounted to
€14.8 million, while fees arising from public funding paid directly from the HEA were €3.4
million. The institute was also able to secure research grants of €869,000 from the State and
other semi-state agencies. In total, the Irish Government contributed €19.1 million to
Letterkenny Institute of Technology in 2010-11, accounting for as high as 62.6 per cent of its
total income. Export income includes tuition fees paid by international students and
international research grants, which in combination was €944,000 for the Institute. Income
apart from exports and Irish Government funding is determined as a residual item and
distributed along the row in the input output table based on proportions of the overall
education service sector.
Results
Output multipliers
With the application of the modelling, we find IoTs with a Type I output multiplier of 1.1 and
universities with a Type I output multiplier of 1.27. These may seem low by comparison with
other sectors, for example ‘Warehousing’ at 1.7 or ‘Retail Trade’ at 1.4. The relatively small
Type I output multipliers of universities and IoTs might suggest that they tend not to source
much intermediate inputs from other industrial sectors in the country. These figures are
Forthcoming in Studies in Higher Education
however in line with comparable studies. Hermannsson et al. (2010b) suggest a Type I output
multiplier for Welsh universities of 1.33, and for Scotland and Northern Ireland they find the
same multiplier of 1.30 (Hermannsson et al. 2010a, 2010c).
Of perhaps more interest are Type II multipliers as these show the direct, indirect and
induced output effects. Figure 1 below displays conventional Type II impact estimates for
individual Irish HEIs, with the use of the HEI-disaggregated input output table. An overall
impression is that Irish HEIs, either universities or IoTs, exhibit rather high Type II
multipliers, indicating that they have a relatively strong impact on the economy via the
household expenditure. Among the 21 HEIs considered in the analysis, the lowest
conventional Type II output multiplier is 3.62, associated with Dún Laoghaire Institute of Art,
Design and Technology, while Letterkenny Institute of Technology shows the highest
multiplier of 4.25.
After determining the Type II output multipliers for the higher education sector, it is able
to report the overall economic impact of universities and IoTs in Ireland. In 2010-11, with a
gross income of €2.6 billion, the 21 institutions included in the analysis generated a gross
output nationwide of €10.6 billion. Of the €10.6 billion, €7.4 billion was contributed by the
university sector and €3.2 billion by the IoT sector. Irish HEIs thus form an important part of
the economic infrastructure, and generate substantial economic activity.
[Figure 1 near here]
There is a distinction between Dublin-based universities and those universities situated
elsewhere with regard to their Type II multipliers. In particular, the three universities in the
capital city – Dublin City University, Trinity College Dublin, and University College Dublin
– are among the top institutions for impact, with multipliers between 4.14 and 4.17. By
comparison, the other four universities are lower with the highest multiplier of the group at
3.86. However, the IoT sector does not seem to show the same geographic split, with
Letterkenny Institute of Technology, located in County Donegal which borders Northern
Ireland, having the biggest economic impact of all higher education colleges in Ireland.
In comparison to the other industrial sectors in Ireland, the individual HEI Type II
multipliers are not the highest, but all of them are above the median value of the expanded
input output table which has a total of 79 sectors. These multipliers, even at the lower end,
are high by comparison to other studies, although not perhaps abnormally so. Kelly,
McNicoll, and McLellan (2004) in a study of the impact of the University of Strathclyde
founded multipliers of between 1.2 and 1.7. Examining the impact of the University of
Portsmouth, in the 1990s, Harris (1997) estimated multipliers of 1.66. A study of Scottish
universities by Hermannsson et al. (2013) puts typical multipliers at just over 2, while
individual HEI Type II multipliers of 2 to 2.2 were estimated for Northern Irish HEIs
(Hermannsson, Lisenkova, and McGregor 2011) and of between 1.9 and 2.2 for Welsh HEIs
(Hermannsson et al. 2010b).
In comparison, a study of London HEIs by Hermannsson et al. (2014) provided typically
higher figures than those found in other UK studies, with most institutions having a multiplier
of around 3. London however is unique in that its 43 universities form the largest
concentration of higher education in Europe. Universities and colleges in London employ
about 20 per cent of the country’s total staff and win around a quarter of the national total
research funding. Thus, it is highly probable that factors such as economies of co-production
across the city are at play in the generation of these high multipliers. In the case of Ireland,
this effect seems to be more apparent in the university sector than in the IoT sector, the
reason for which needs further investigation.
Forthcoming in Studies in Higher Education
It should also be noted that, although not strictly comparable, these multipliers of Irish
HEIs are higher by a significant margin than the overall national fiscal multiplier of 0.5 as
used by the IMF and the Irish Fiscal Advisory Council (IFAC 2013) and those of the
Economic and Social Research Institute (ESRI), which range from 0.3 to 1.2 (Bergin et al.
2013). Our estimates here are closet but greater than the overall expenditure multipliers in
O’Farrell (2013), ranging from 1.06 to 1.76. One should also notice the short-run government
investment multiplier of 1.8, which is of a similar magnitude, as found by Clancy, Jacquinot,
and Lozej (2014).
It is also possible to look at the sectoral impact by examining the intra-sectoral multipliers
(recall that the overall multiplier is made up of the sum of the individual column elements of
the Leontief inverse). From Table 5 we can see that an injection of one euro into the
university/IoT sector results in an increase mainly in ‘Distribution, Transport and
Communication’ of 54c/52c, in ‘Business Services’ of 68c/63c, in ‘Other Services’ of
€1.36/€1.26 and an increase in overall economic output via increase income and concomitant
spending of €1.18.
[Table 5 near here]
Balanced output multipliers
Figure 2 shows balanced multipliers for each HEI. As can be expected, netting out the impact
of government support reduces quite significantly the impact of each HEI. The range of
impact is now also expanded from its previously highly condensed distribution. Raw
multipliers vary, but slightly, with the lowest being 85 per cent of the highest. Taking into
account government expenditure the lowest being 30 per cent of the highest.
[Figure 2 near here]
As shown in Figure 3, the balanced multipliers for Ireland (both sectors) are compared to
73 UK HEIs across England, Scotland, Wales and Northern Ireland. We note that the Irish
institutions are well distributed. Five institutions rank in the top 20 for balanced expenditure
multipliers – Dublin City University, University College Dublin, Trinity College Dublin,
University of Limerick and Letterkenny Institute of Technology. Only two rank in the lowest
quartile, namely Dublin Institute of Technology and Cork Institute of Technology. Looking at
an all-island comparison, we see the Irish HEIs performing well, with only Queen’s
University Belfast showing a balanced budget multiplier above the median.
[Figure 3 near here]
A closer examination of Figure 3 reveals how different types of institutions compare
against each other. The very largest multipliers, as Figure 3 shows, belong to specialist
institutions – London Business School (LBS), London School of Economics and Political
Science (LSE) and London School of Hygiene and Tropical Medicine (LSHTM). Amongst
comprehensive institutions the Irish HEIs, namely University College Cork, University
College Dublin and Trinity College Dublin stand out. It is noteworthy that in reality only
these three institutions, together with the University of St Andrews, can be described as fully
comprehensive universities in the top 20, by which we mean covering all aspects of higher
education inclusive of the arts and humanities, social sciences, physical and life sciences,
mathematics, medical and para-medical disciplines. This is important since the 1997
Universities Act orientates itself towards comprehensive institutions when allowing the use
of the title university. An additional matter is that the status of the HEI does matter. IoTs and
Forthcoming in Studies in Higher Education
small universities tend to have low balanced multipliers, reflecting the limited diversity of
income sources that exist for these HEIs. A greater diversity of income sources appears to
allow for a higher balanced Type II multiplier. In Figure 4 we show the average balanced
type II multiplier versus average income, across regions and types. One imagines that the
ideal relationship, from the perspective of the exchequer, is a downward slope, with a
negative relationship between spending and outcome. This we do not see. Irish universities
have on average the highest balanced multiplier this comes with the highest average income.
[Figure 4 near here]
Employment multipliers
Table 6 shows both Type I and Type II employment multipliers for each Irish HEI. One may
interpret these as being the effects of an additional one million euro on employment. On
average, the investment on the universities supports, in addition to the employment in the
sector of 13,701, an additional 1,781 persons through indirect effects and an additional
66,470 persons via induced demand. These figures are high, but are in line with the findings
of some U.S. studies (Siegfried et al. 2007). Cautions are needed in the interpretation of such
high employment multipliers. That said, it is well recognised that the high salary levels paid
to high skilled workers can result in high sectoral (and institutional) multipliers (Moretti 2010;
Moretti and Thulin 2013). Also, Type I employment multipliers compare well in magnitude
for other Irish economic sectors calculated from disaggregated input output tables. For
example, Morrissey and O’Donoghue (2013) disaggregated the 2007 input output table and
obtained information for marine industries with an employment multiplier of 2.9.
[Table 6 near here]
Discussion and conclusions
In this paper, we have explored issues surrounding the expenditure impacts of Irish HEIs on
the economy of Ireland by applying an input output analysis. Our empirical exercise
estimates the output, balanced, and employment multipliers for each of the 21 higher
education institutions in Ireland. In overall, the results suggest that Irish HEIs have
significant economic impacts on the national economy, and compare favourably with their
counterparts in the UK.
While HEIs show average Type I output multipliers, they are among the sectors with the
highest Type II output multipliers. A possible explanation for this could be that,
compensation of employees forms a larger share of expenditure of HEIs and might be, on
average, at a higher level in comparison to other industrial sectors. At the institutional level,
there seems a clear distinction between universities in Dublin and those outside in terms of
their economic impacts. More specifically, Dublin-based universities show relatively higher
multipliers than those situated elsewhere in the country, a finding which is consistent with
results from London (Hermannsson et al. 2014). Universities in London demonstrate
significantly higher multipliers than those located in other UK regions, suggesting the
existence of agglomeration effects (i.e. the size of the regional economy). Although the
Dublin effect is minor when compared to the one in London, it still indicates, in the Irish
context, that agglomeration plays a role in explaining spatial variations in university
economic impacts.
It has also been found that Irish HEIs show significantly different balanced multipliers,
which essentially net out the impact of government support. It is the universities that lead the
rankings of balanced multipliers, while IoTs and small universities tend to have low
multipliers, which might be in association with the limited diversity of their income sources.
Forthcoming in Studies in Higher Education
Irish HEIs are therefore not at the same level of resilience when now facing budget cuts from
the Irish government. Those institutions which are more heavily dependent on the
government funding will encounter more struggles than the ones with more diverse income
sources. In other words, a greater diversity of income source of comprehensive universities
probably insures them against the negative impacts the current budget environment could
otherwise have.
To a certain extent, the 2010 input output table and associated employment and household
expenditure data might reflect a society still transiting from an artificial environment, induced
by the bubble, which is particularly when examining the high employment multipliers. The
underlying assumption of input output modelling, apart from linearity of the economy, is that
the linkages are stable and change slowly. This has been the case for Ireland to a great degree,
but whether this held over the period around the boom and the bust is debatable (Keogh and
Quill 2009). It is a direction which future research could follow.
Whilst our analysis has the potential to contribute to the current policy debates about
higher education in Ireland, a number of caveats need to be stated. Firstly, although there is
considerable degree of certainty about the inputs and outputs of each individual HEI, this can
always be refined. In particular, it would be useful to obtain greater depth of information on
the expenditure on purchased goods and services for the majority of IoTs. Secondly, there
might be potential data issues, as earlier argued, in relation to the 2010 input output table.
This is not to question the validity of the data source, but to call for much more caution when
interpreting the results, especially those of employment multipliers. Thirdly, the scope of this
study is clearly defined by the method – input output analysis – which has been undertaken.
Our analysis, while enabling a discussion of the effects of increasing or decreasing exchequer
funding to HEIs in the immediate, does not provide a statement on the effects of that change
towards a wider industrial policy. It is of necessity silent on issues of return-on-investment in
education and quality in higher education, the evaluation of which is the matter for a different
study. Lastly, we have yet to include the impact of students due to data limitation. It has been
suggested by evidence from the UK that the impact of students is modest – around 1/10 of the
magnitude of balanced Type II output multipliers (Universities UK 2014). Nonetheless, this
has not been captured.
Our results could provide clear counterfactuals on the effects of the presence or absence of
an HEI on a local economy, which could be taken into account in the allocation of future
budgets for higher education in Ireland. Also, the results could be used to examine present
debates of mergers and co-location of institutions and how their income diversity will result
in desirable or undesirable policy outcomes. From a policy perspective, less developed
regions could concentrate more on developing a dense system of high-tech and innovative
firms to enhance the interactions between universities and firms, as the economic impact of
HEIs, especially the universities, is positively related to the presence of a critical mass of
agglomeration in the metropolitan area. Indeed, it has been suggested that, “while universities
can play an important role they are often supported by a dense system of institutions”
(Huggins and Johnston 2009, p. 1101). Empirical evidence about the impact that HEIs have
on local employment and how many direct and indirect jobs an HEI can support in a locality
could be derived from the analysis and taken further by the policymakers in building closer
university-business partnerships.
Ultimately, this study is the first step in forming an evidence base for policy decision. Irish
higher education institutions, as a whole, provide the public exchequer with ‘value for money’
in that they have strong gross economic outputs, generate strong net economic outputs, and
are commensurate, if not slightly superior in specific instances, with their UK counterparts.
This result, in the context of a small open economy suffering a protracted and deep recession,
Forthcoming in Studies in Higher Education
should provide the Department of Public Expenditure and the leadership of the higher
education sector in Ireland with a source of pride.
Acknowledgements
The authors acknowledge support from the Irish Research Council (RPG2013-6 (SFI/HEA
Assessing the Impact of Publicly-Funded Research, Development and Innovation), Theme 2).
We also wish to thank Ned Costello of the Irish Universities Association, Tom Boland and
Muiris O’Connor of the Higher Education Authority, Niamh Brennan of Trinity College
Dublin, Maurice Peat of University of Sydney, Michael Dowling of Dublin City University
and Stephen Kinsella of University of Limerick for valuable insight and assistance.
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Table 1. Summary of HEI columns.
Column
component
Level of detail
Data source
Universities
IoTs
Total expenditure
Individually determined
Individually determined
HEA (2014)
Imports
Individually determined
Proxied by assuming ratios
for the university sector as
whole hold for IoTs
IUA (2014)
Operating surplus
Proxied by assuming ratios
for the education service
sector as whole hold for
universities
Proxied by assuming ratios
for the education service
sector as whole hold for
IoTs
CSO (2014)
Compensation of
employees
Individually determined
Individually determined
HEA (2014)
Product taxes less
subsidises
Proxied by assuming ratios
for the education service
sector as whole hold for
universities
Proxied by assuming ratios
for the education service
sector as whole hold for
IoTs
CSO (2014)
Intermediate
expenditures
Determined as a residual
item and distributed
uniformly across all
universities in the same
pattern as the education
service sector as whole
Determined as a residual
item and distributed
uniformly across all IoTs in
the same pattern as the
education service sector as
whole
CSO (2014)
Forthcoming in Studies in Higher Education
Table 2. Attribution of expenditures for Irish HEIs, 2010-11.
HEI
% of total expenditure
Imports
Operating
surplus
Compensation
of employees
Product taxes
less subsidises
Intermediate
expenditures
Athlone Institute of Technology
9.3
2.7
67.5
1.3
19.2
Cork Institute of Technology
9.6
2.7
66.9
1.3
19.5
Dublin City University
1.6
2.7
66.9
1.3
27.5
Dublin Institute of Technology
9.5
2.7
67.1
1.3
19.4
Dún Laoghaire Institute of ADT
8.9
2.7
56.3
1.3
30.9
Dundalk Institute of Technology
9.0
2.7
67.6
1.3
19.4
Galway-Mayo Institute of Technology
9.6
2.7
71.0
1.3
15.4
Institute of Technology, Blanchardstown
9.3
2.7
69.6
1.3
17.1
Institute of Technology, Carlow
9.4
2.7
69.1
1.3
17.5
Institute of Technology, Sligo
9.0
2.7
66.6
1.3
20.4
Institute of Technology Tallaght, Dublin
9.1
2.7
66.6
1.3
20.3
Institute of Technology, Tralee
9.9
2.7
68.9
1.3
17.2
Letterkenny Institute of Technology
9.8
2.7
76.5
1.3
9.7
Limerick Institute of Technology
9.4
2.7
68.5
1.3
18.1
Maynooth University
1.2
2.7
59.5
1.3
35.3
National University of Ireland, Galway
1.6
2.7
60.8
1.3
33.6
Trinity College Dublin
4.7
2.7
67.8
1.3
23.5
University College Cork
0.7
2.7
59.1
1.3
36.2
University College Dublin
1.6
2.7
65.5
1.3
28.9
University of Limerick
6.9
2.7
53.7
1.3
35.4
Waterford Institute of Technology
9.3
2.7
70.0
1.3
16.7
Universities
2.9
2.7
62.5
1.3
30.6
IoTs
10.0
2.7
68.0
1.3
18.0
Forthcoming in Studies in Higher Education
Table 3. Summary of HEI rows.
Row component
Level of detail
Data source
Universities
IoTs
Income from
exports
Individually determined
Individually determined
HEA (2014)
Income from Irish
Government
Individually determined
Individually determined
HEA (2014)
Income from other
final demand
categories and
intermediate
demand
Income apart from exports
and Irish Government
funding is uniformly
distributed along the row
based on proportions of
the overall education
service sector
Income apart from exports
and Irish Government
funding is uniformly
distributed along the row
based on proportions of
the overall education
service sector
CSO (2014)
Forthcoming in Studies in Higher Education
Table 4. Attribution of income sources for Irish HEIs, 2010-11.
HEI
% of total income
Irish Government
Exports
Other
State
grants
Fee
income
State
research
grants
Over-
heads
Fee
income
EU
research
grants
Industry
income
Other
income
Other
Athlone Institute of Technology
43.3
13.4
5.7
0.0
2.4
1.0
0.0
0.4
33.7
Cork Institute of Technology
44.6
12.5
11.4
0.0
2.0
2.0
0.0
0.3
27.2
Dublin City University
14.2
15.6
18.7
0.0
8.3
1.9
0.7
3.5
37.0
Dublin Institute of Technology
49.6
10.7
6.1
0.0
2.1
1.1
0.0
0.3
30.0
Dún Laoghaire Institute of ADT
38.1
15.4
3.6
0.0
2.8
0.6
0.0
0.4
39.1
Dundalk Institute of Technology
37.5
13.2
8.6
0.0
2.4
1.5
0.0
0.5
36.4
Galway-Mayo Institute of Technology
45.8
12.4
3.1
0.0
2.2
0.6
0.0
0.6
35.3
Institute of Technology, Blanchardstown
46.3
13.0
2.0
0.0
2.3
0.4
0.0
0.5
35.4
Institute of Technology, Carlow
43.2
16.0
2.8
0.0
2.9
0.5
0.0
0.4
34.2
Institute of Technology, Sligo
39.4
16.1
3.8
0.0
2.9
0.7
0.0
0.4
36.9
Institute of Technology Tallaght, Dublin
44.4
14.4
4.1
0.0
2.6
0.7
0.0
0.4
33.4
Institute of Technology, Tralee
47.0
12.0
4.3
0.0
2.1
0.8
0.0
0.4
33.4
Letterkenny Institute of Technology
48.2
11.1
2.8
0.0
2.0
0.5
0.0
0.6
34.8
Limerick Institute of Technology
43.2
11.8
5.4
0.0
2.1
1.0
0.0
0.5
36.0
Maynooth University
20.1
25.1
12.7
0.0
9.8
1.1
0.5
3.2
27.5
National University of Ireland, Galway
23.4
17.9
19.6
0.0
10.4
2.6
0.8
0.8
24.5
Trinity College Dublin
20.8
14.6
18.1
1.1
9.2
2.6
0.4
2.1
31.2
University College Cork
19.0
14.4
17.0
0.0
8.7
2.3
0.7
3.0
34.9
University College Dublin
22.9
14.0
11.3
1.3
10.4
2.5
0.4
2.1
35.0
University of Limerick
18.6
17.3
7.7
0.0
9.1
1.6
0.4
4.4
40.8
Waterford Institute of Technology
34.8
12.5
17.6
0.0
2.2
3.2
0.0
0.4
29.2
Universities
20.3
16.0
15.1
0.5
9.5
2.2
0.6
2.6
33.3
IoTs
43.9
12.7
7.1
0.0
2.3
1.3
0.0
0.4
32.3
Forthcoming in Studies in Higher Education
Table 5. Sectoral Type II impacts of universities and IoTs.
Sector
Universities
IoTs
Agriculture, Forestry and Fishing
0.026
0.026
Business Services
0.683
0.633
Construction
0.018
0.015
Distribution, Transport and Communication
0.542
0.526
Manufacturing
0.256
0.215
Other Services
1.363
1.291
Income Effect
1.188
1.180
Note: Table shows the Type II impact of universities and IoTs on each broad economic sector.
Forthcoming in Studies in Higher Education
Table 6. Employment multipliers for Irish HEIs.
HEI
Type I employment
multipliers
Type II employment
multipliers
Letterkenny Institute of Technology
1.06
8.84
Galway-Mayo Institute of Technology
1.07
8.17
Athlone Institute of Technology
1.07
8.04
Limerick Institute of Technology
1.07
7.80
Institute of Technology, Blanchardstown
1.07
7.77
Institute of Technology, Carlow
1.06
7.74
Institute of Technology, Sligo
1.07
7.70
Cork Institute of Technology
1.06
7.51
Waterford Institute of Technology
1.06
7.48
Dublin Institute of Technology
1.07
7.42
Institute of Technology, Tralee
1.06
7.30
Dundalk Institute of Technology
1.07
7.27
Trinity College Dublin
1.13
6.90
Institute of Technology Tallaght, Dublin
1.06
6.73
National University of Ireland, Galway
1.11
6.07
University College Dublin
1.16
5.82
Dún Laoghaire Institute of ADT
1.07
5.77
Dublin City University
1.13
5.65
University College Cork
1.16
5.36
University of Limerick
1.15
4.91
Maynooth University
1.09
4.45
Note: HEIs are listed in descending order for Type II employment multipliers.
Forthcoming in Studies in Higher Education
Figure 1. Raw Type II output multipliers for Irish HEIs.
Forthcoming in Studies in Higher Education
Figure 2. Raw and balanced Type II output multipliers for Irish HEIs.
Forthcoming in Studies in Higher Education
Figure 3. Balanced Type II output multipliers for Irish and UK HEIs.
Forthcoming in Studies in Higher Education
Figure 4. Relationship between balanced Type II output multipliers and income.
