Journal of Applied Input-Output Analysis, Vol. 10, 2004

Capturing the Economic Impact of a Public Institution: the Rovira i Virgili
University1

By
Maria Llop*

Abstract
This paper deals with some of the effects associated with a public institution in the terri
tory. Specifically, I use the input-output method to estimate the economic impact of theRovira i Virgili University (URV) in the region of Tarragona. First, I construct an inputoutput table for the province of Tarragona in 1999 using a non-survey method: the RAS

technique. Then I calculate the amount of expenditure generated by the presence of the
University, including investment by the URV, students consumption and expenditure of thestaff. I use the input-output demand model with this information to evaluate income creation and employment effects of the University activity in the territory. This empirical study
shows that Rovira i Virgili University plays an important role within its area of influence.

1. Introduction
Public institutions such as universities are a significant source of employment and income in a local economy. Regional economic analysis often tends to underplay the
economic impact of public institutions. The main interest usually lies in determining

the effects of industry and production, because these can be calculated easily.
The main functions of universities are research and teaching. In practice, however,a university develops a very large and complex set of activities. Universities today have
many employees, make a significant consumption of goods and services, and transfer
technology to other economic agents. Universities are therefore highly integrated within
the economic structure of their regions.

This paper analyses, at the empirical level, the economic benefits to the provinceof Tarragona accrued by the presence of the Rovira i Virgili University (URV). The
Received October 2003, final version received October 2004.

1

This study has been supported by the Rovira i Virgili University, the Ministerio de Education y Cultura (grant SEC2003-06630 and SEJ2004-07477), and the Generalitat de Catalunya (grant XT2004-0095). I am also grateful for the support of the CentrA (Fundacion Centro de Estudios Andaluces).
Useful comments and suggestions by two anonymous referees have substantially improved an earlier
version.

* Departament d'Economia, Universitat Rovira i Virgili. Avda. Universitat n°l, 43204 Reus (Spain).
Telephone: (34) 977759851. E-mail: maria.llop@urv.net.

66

Journal of Applied Input-Output Analysis, Vol. 10, 2004

economic impact of this institution is defined in terms of its input and output links
with the economy in the province. In this study I construct an input-ouput table for
Tarragona in 1999 and use it to calculate the income generated by the URV and the ef
fects of the University on employment.

The Rovira i Virgili University was founded just ten years ago as a public institu
tion. The area of influence is the province of Tarragona (in the southwest of Catalonia),
comprising 6.253 Km2 and 588.499 habitants in 1999 (9.5% of Catalonia). In 1999, theUniversity employed 998 full-time and 391 part-time persons and had 11.735 students.
Today, the URV offers over 30 different degrees in ten faculties, which are located in
the cities of Tarragona and Reus.

Similar studies have evaluated the effects from the income and employment of
universities and other non-profit institutions. For example, Moore and Sufrin (1974)
studied the economic benefits of Syracuse University through a model of macroeconomic multipliers. Also, Bleaney et alia (1992) discussed the effects of Universityof Nottingham by the estimation of the local multiplier effects and the calculation of
output and income impacts. Armstrong (1993) studied the local income and the em
ployment impact of Lancaster University, using keynesian multipliers.
Generally, a complete economic analysis of the impact of a regional university

should incorporate both measurements of the flow of annual economic activity attribut

able to the existence of the institution (short-term effects) and long-term effects (Becket alia, 1995). Long-term effects are measured in terms of the institution's contribution

to the stock of human capital and technology. However, evaluating such long-term ef

fects requires many data and these are usually very difficult to obtain. In this paper,
therefore, I shall only evaluate the short-term effects of the University's activity.
The paper is organised as follows. In the next section, I present the theoretical ap

proach used in the analysis. Section 3 describes the construction of the database for theempirical application, and section 4 illustrates the main results. At the end of the paper
are some concluding remarks.

2. Capturing the Economic Impact of the University
The theoretical approach is based on the input-output framework. I have used thismethod to quantify the degree of URV integration in the productive system of theeconomy in the province. With this, I can also evaluate the income creation and em
ployment effects generated by the University expenditure.

The demand version of the input-output model, in matrix notation, is defined asfollows2:
AX+D=X,(1)

where A is a matrix of technical input-output coefficients, X is a vector that contains
the final output in every sector, and D is a vector of final demand. The sectorial output
is then equal to:See, for example, Miller and Blair (1985) for an exposition of the input-output analysis.

Capturing the Economic Impact of a Public Institution: the Rovira i Virgili University

X =(/ -A)[D =MD,

67

(2)

where / is the identity matrix, and M = (I - A)~l is the Leontief inverse matrix. Ex
pression (2) can be transformed in terms of variations, as follows:
AX = (I - A)1 AD = MAD,(3)

assuming that (I - A)~[ exists and assuming that A remains constant. Expression (3)determines the changes in the output values when there is a change in the final demandof an activity or a change in the final demand of all the activities simultaneously.
The model described in (3) captures the entire sequence activated in the production sphere caused by a modification in the final demand. In this sense, an increase in
the demand of one sector will generate an increase in its production to cover the new
demand and, at the same time, this sector will buy more inputs to the other sectors,
and so on. Consequently, the final effect in the sectorial production is the result of theinterdependence relationships in the productive sphere.
The model described in (3) assumes that all the final demand items are exoge
nous. The assumption that consumption demand is exogenous, however, is contrary to
the basic economic theory. Consumers earn income in payments for their endowmentsof labour supply and capital and, in the role of consumers, spend income in final
goods and services. To take into account the channel from the income increase to theincrease in the final consumption, we can extend the model by moving the householdfrom the final demand to the input-output matrix, that is, make the consumption endo
genous. This extension leads to the following expression:

A~X = (I - ~A)~l AD = MAD".

(4)

In expression (4), X is the vector of final output and has n+1 elements (n pro

duction activities and 1 household sector). Similarly, D is the vector of final demand
for the n+1 elements (n remaining final_demand for sectors and 1 final demand for the
output of households). Finally, matrix A has the following structure:

A =

A

u

v

0

where u is a column vector of sectorial consumption coefficients, calculated by divid
ing the sectorial consumption by the total value added of the economy, and v is a row

vector of value added coefficients, calculated by dividing the sectorial value added by
the sectorial output.

In this study, I define economic impact as the difference between the economic
activity in the region given the presence of the University, and the level of economic

activity there would be if the University institution did not exist. This impact can bemeasured by taking into account the amount of expenditure that is directly associatedwith the presence of the URV. This method, therefore, is in line with the accepted theory and practice in regional economic studies, which consider higher-education institu
tions as regional enterprises (Beck et alia, 1995).
To empirically implement the model I need to reflect the amount of URV expen

diture. Specifically, I have considered investment by the University, consumption by the68

Journal of Applied Input-Output Analysis, Vol. 10, 2004

University staff and consumption by the students. All these categories of expendituredefine one vector (Ae) that contains all the demand for the productive activities due tothe presence of the University:

Ae = Ai + Aw + As.

(5)

In expression (5), A/ is a vector that contains the sectorial destination of the Uni
versity's investment; Aw is a vector that reflects the sectorial destination of the con

sumption of the University's employees; and As is a vector that contains the sectorial
destination of students' consumption.

Let M* denote the elements of matrix M = (/ - A)"' for the n production activi
ties. If we combine the total expenditure defined in expression (5) with expression (3),the input-output model quantifies the sectorial production due to the presence of the
University as follows:

AX = ~M*Ae.

(6)

I can write expression (6) in the following way:

AX = /Ae + [M - /] Ae + [Af - M] Ae.

(7)

Therefore, total impact in the sectorial production (AX) is divided into three dif

ferent effects:
1.

Direct effect (IAe), which contains the initial increase in demand in each sector asa result of the University activity. This effect quantifies the amount of sectorial demand in investment and consumption made by the University, its employees and its
students.

2. Indirect effect ([M - /] Ae). The sector that receives the final URV demand willneed to increase the production and will also increase the input demand to the oth
ers sectors, and so on. The indirect effect is therefore caused by the interdepend
ence relationships in the productive system.

3. Induced effect ([M*- M] Ae). This effect shows the additional impact on the pro
duction of the endogeneization of consumption. Specifically, the increase in production will lead to an increase in value added, which will rise the private income andprivate consumption; as a result, production increases again, and so on.

Finally, the input-output model also shows the effects on employment in the Tarra
gona region due to the University's activity. These employment effects are calculated asfollows:

AO = O~M*Ae.

(8)

In expression (8), O is a diagonal matrix of the employment coefficients, calcu

lated as the number of workers divided by the output in each sector. If the presence of

the University helps to generate production, the activities will need new workers to sat
isfy this production. This effect is quantified in (8).

Capturing the Economic Impact of a Public Institution: the Rovira i Virgili University69

3. Database
The model described in the previous section evaluates the economic impact of theRovira i Virgili University in the productive system of the Tarragona region. However,to empirically implement this model, the activity of the URV has to be reflected in the

input-output table as a differentiated sector. I have obtained the necessary information
directly from the budget and the public accounts of the University, and for several variables I have applied some indirect calculus. The reference year is 1999, the same pe
riod for which I calculate the input-output table for the province of Tarragona.
To reflect the URV activity in the input-output table, I needed to know the amountof outlays related to the University, and the components of these variables. Summing
down the column in the input-output table, the outlays of sector j (Xj) are calculated
as:ij+Wj + M,

(9)In expression (9), the amount of outlays are equal to the intermediate inputs ( 2j<
Xij J , the value added (Wj) and the imports (Mi). The value added is defined as:
Wj = L} + Nj9

where L, includes the payments for labour services and Nj includes the profits of sectorj-Following expression (9), the intermediate inputs contain the purchases of raw

materials and other intermediate services and products. This information was obtained

directly from the URV's budget in 1999. Wages and salaries are also reflected in thisbudget. Profits include the income property obtained with the activity. The value forthe profit variable of the URV was also obtained from the University's budget. The
value of imports completes the University's outlays. For this, we have to consider thatthe output supplied by the URV is a final public service, which implies that there areno trade operations of equivalent products with foreign markets. Consequently, thevalue assigned to University imports in table 1 is zero.

To integrate URV activity into the input-output table, I also needed to compute theoutput of the University. Summing across the row in the input-output table, the amount
Table 1. Outlays of the URV, 1999.
(Thousand Euros)Intermediate Inputs

13685.05

Wages and Salaries

28746.40

Profits
Final Production
Imports

Total Outlays URV

213.1542644.60
042644.60

70

Journal of Applied Input-Output Analysis, Vol. 10, 2004

of output of a sector j (Xj) is equal to:

The element 2j, Xy is the intermediate output and contains the sales of raw materi
als and services, which are used in the production processes of the other activities. The

University, as a higher-education institution, offers final services to the rest of theeconomy, which implies that the intermediate outputs are zero. However, there is an activity involving the transfer of knowledge and technology, which I consider as an intermediate output. The value of intermediate outputs is therefore equivalent to the budget
value of the transfer services sold to firms and other institutions.

Also in expression (10), £>, is the final demand of the University. The input-output
table defines the final demand of sector j as:

Dj = Cj + Ij + Gj + Ej.

(11)

Expression (11) reflects all the possible final destinations of the sectorial output:
private consumption (C,), investment (/>), public consumption (G,) and exports (£,). I
have obtained the private consumption in goods offered by the University directly fromthe budget, which incorporates the fees and public prices collected. The investment demand is zero, because there is no decision of this kind in the productive sphere materi

alised in goods supplied by the University. Public consumption is the amount of public

services produced by the University. This value is not reflected directly in its budget. I
have therefore obtained public consumption by indirect calculation, comprising the out

lays of URV minus the private consumption and intermediate outputs, because theother components in the final demand variable (exports and investment) are zero. Fi
nally, the value of exports to the foreign markets is zero, because the services producedby the URV are not traded abroad.

From the criteria described above, the final output of the University in 1999 isshown in table 2.

From the outlays and the output of the URV we can identify the University as aseparate sector from the other activities in the input-output table. However, to computethe economic impact I needed more information. This information concerns the amountof expenditure generated by the presence of the URV (vector Ae in the previous sec
tion and all the components involved).

The expenditure vector is calculated as follows. The amount of investment and its
sectorial destination (vector A/) is obtained directly from the URV budget.
Table 2. Output of the URV, 1999.
(Thousand Euros)Intermediate Outputs

1972.00

Private Consumption

9736.40Investment

Public Consumption
Exports

Total Output URV

030936.20
042644.60

Capturing the Economic Impact of a Public Institution: the Rovira i Virgili University

71

Table 3. Total Expenditure of the URV, 1999. (Thousand Euros)
SectorURV

Investment(A/)

Employees'

Student's

(Aw)

(As)

Consumption Consumption

Total

mand

De-

(Ae)

1.

Agriculture

0763.29709.191472.48

2.

Energy01027.7301027.73

0

24.04

3.

Metals

0

24.04

4.

Minerals

0

54.09

0

54.09

5.

Chemistry

0721.210721.21

6.

Machinery3269.51805.3604074.86

7.

Automobiles

0775.310775.31

8.

Food

0

3449.813768.35

7218.16

9.

Textile01027.732824.763852.49

10.

Paper

1171.97498.843533.95

5204.76

11.

Other industry

895.51564.9501460.46

12.

Construction

13005.90

336.57013342.47

13.

Commerce

06611.132355.978961.1014.

Transportation

0871.472590.363461.83

15.

Finance0492.830492.83

16.

Private services

04110.92

7771.0911882.01

17.

Public services

4838.15510.8605349.01

18.

Rovira i Virgili University

0.00

6.01

9712.369718.37

23181.04

22652.15

33266.03

79099.22

Total

To obtain the value of employees' consumption (Aw), I apply an indirect calculation. Wages and salaries is a variable in the URV budget3 but, for an accurate evalu
ation, we have to bear in mind that our context for analysis is the province of Tarra
gona. For this reason, I have reduced wages and salaries in the proportion that corre

sponds to employees who live outside this area4. The justification for this is that theconsumption of these employees has practically no impact on the local economy. Also,part of the wages and salaries is not materialised in consumption, but in savings.
Therefore, to the salaries of the workers who live in the Tarragona area I apply the pro

portion of income that is effectively transformed into consumption5. The value resulting
from this then has to be assigned to each activity. The sectorial destination of con

sumption has been obtained from the Institute Nacional de Estadistica (1995)6.
In 1999 the URV had 11.735 students, 66.5% of whom lived close to the facul
ties7. For these students, I calculated expenditure related to registration fees, academic
3 The calculation of the consumption of URV employees does not reflect the investment demand fromhouse purchases. This item is also due to the presence of the University, but no information is avail
able for it. The effects on the construction sector will therefore be undervalued.
4

In 1999, 9.7% of the employees lived outside the province of Tarragona.

5

The value is 0.8723, which indicates that the consumption is 87.23% of personal income (Fundacion
BBVA, 2000).

6 The last available information is for 1990, and concerns all whole of the Catalan economy.

72

Journal of Applied Input-Output Analysis, Vol. 10, 2004

Table 4. Employment and Final Production. Tarragona, 1999.
(Number of jobs and thousand Euros)
Sector1.

Agriculture

2.

Energy3.

Metals4.

Minerals5.

Chemistry

6.

Machinery

Automobiles

7.

Employment

Final Production

(a)

(b)

(a) / (b)23507

1244359

0.01892901

2823905

0.0010703

50360

0.01404154

3313720.01255648

7370370.007710420

8420250.0124

1447

43373

0.0334

8.

Food

6921

10935430.0063

9.

Textile2969

3515130.0084

10.

Paper

3585

2545010.0141

11.

Other industry

5335

3061850.017412.

Construction

34858

1930275

0.0181

13.

Commerce

55520

38546850.014414.

Transportation

10712

7215140.014815.

Finance

4587

38363130.0012

16.

Private services

30096

2010406

0.015017.

Public services

36913

10787070.0342

18.

Rovira i Virgili University

1327

42644

0.0311material, public transportation and leisure services8. For the remaining 33.5% of stu

dents, I added living expenditure9. Finally, I applied a common criterion based on the
demand of students that would be generated if the University did not exist and they

had had to study at other universities (Lewis, 1988). Specifically, I used the informa
tion related to the higher-education students from the province of Tarragona to otheruniversities before the foundation of the Rovira i Virgili University. The sectorial desti
nation of the amount of students' consumption has been obtained from the Instituto

Nacional de Consumo (1998)10. In this way I obtained the vector As1.
Table 3 shows the expenditure related to the presence of the University in 1999.
By sectors, construction receives the most overall demand (16.9%), followed by private
services (15%) and the Rovira i Virgili University (12.3%). By components, students'
expenditure is the largest value, whereas the values for employees' consumption and7 I include in this area the administrative division of Alt Camp, Baix Camp, Tarragones and Baix
Penedes.

8 To make an accurate estimation of students' consumption, I did not take into account the living ex
penditure of the students that lived near the faculties, because this expenditure cannot be directly attributed to the URV presence.

9 In order to capture the attraction of new students coming far away from Tarragona, this category includes all the students coming from other areas of Spain.

10 According to the sectorial proportions in this source, in some cases the sectorial values of students'
consumption is zero.

Table 5. Input-Output Transactions Matrix. Tarragona, 1999. (Thousand Euros)
3

2

1

4

5

7

6

8

9

10

11

12

13

14

15

16

17

URV

Total

1

362221

0

0

212

6994

0

0

652779

10338

11112

28809

1100

229200

0

0

945

14262

0

1317972259455

235741

10637

93656

178761

73568

3144

26628

29200

32904

27462

67714

406091100175120153116945

82971

4835

2670040

3

585

141

8273

812

1437

82022

2048

252

21

534

2538

30132

0

173

0

0

0

0

128968

4

112

198

179

20038

3663

10054

217

2603

49

417

472

234451

2351

29

0

1327

65

0

276225

5

38861

9347

663

10998

156982

26212

972

6550

21470

15537

42658

13242

43674

808

575

24225

23039

366

436180

6

12170

5309

349

3701

7363

75311

2976

2810

1318

1888

3665

138324

93206

2980

2762

9449

13628

275

377485

7

174

0

0

0

0

34

2422

0

0

0

0

0

9290

325

0

60

140

0

12444

8

172145

0

0

0

4466

0

0

25316

7624

221

0

0

184177

152

0

2996

8228

0

405324

9

3111

85

28

1120

3000

4294

397

634

102860

1204

7391

869

3469

375

0

1809

2194

41

132881

10

0

226

16

1183

4835

733

50

2865

724

38732

1568

1795

17192

1840

16228

31302

4474

606

124368

11

4281

452

54

1710

5108

23543

2039

4768

1705

2331

28141

30576

35926

4697

230

2895

4184

349

152988

12

1145

3247

217

1929

1157

1516

87

394

246

66

407

0

61444

7251

59885

131541

13402

2396

28632913101291

32898

11513

17569

44429

115997

10372

38274

20205

24582

17293

284426

210080

34719

61074

54723

54715

953

1135116

14

17334

6636

696

8496

9324

13809

935

7567

2745

2929

3637

59105

77788

34524

67826

32790

13025

832

359999

15

1506

3756

86

1498

3656

5254

427

1564

1381

1278

1987

43007

49224

5484 2783245

10273

1968

41

2915634

16

2028

12002

259

4825

13635

13523

2148

5326

2278

3571

3766

64819

13491413572

208235133491

92791

2992

714174

17

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

URV

12

424

24

86

177

370

22

33

4

8

12

58

77

43

77

362

183

0

1972

776430 1310461

32995

16783344498644623928256

778362202169137316169807207147 3320290

55513332927013685

11448098

Total

969616 1558102

74

Journal of Applied Input-Output Analysis, Vol. 10, 2004

investment are similar.

To calculate the occupation effects (see expression (8) of the model), we need toknow the relationship between employment and final production in each activity. This
information is given in table 4. The values for employment are from the Instituto Na
tional de Estadistica (1999), and the final production is the one used to calculate theinput-output table for Tarragona in 1999, which I shall explain below.

The input-output table is constructed on the basis of a non-survey method: the
RAS technique (Bacharach, 1970). This technique allows us to project an input-output

coefficient matrix to a future period by using a reference coefficient matrix. The tableof origin is the input-output table for Catalonia in 1987 (Cambra Oficial de Comerg,
lndustria i Navegacio de Barcelona and Departament de Comerg, Consum i Turisme,

1992). So, in this exercise I calculate a spatial projection of the input-output coefficientmatrix (from Catalonia to Tarragona) and a temporal projection (from 1987 to 1999).
To apply the RAS method I also need to know the sectorial value added for the
Tarragona area, the intermediate inputs (the sum of columns in the unknown matrix ofintermediate transactions) and the intermediate outputs (the sum of rows in the new intermediate transactions matrix).
The sectorial value added for the province of Tarragona was obtained from theFundacion BBVA (2000). I calculated the intermediate inputs by assuming that the relationship between these inputs and the value added in the original table of 1987 is reproduced in the new table. The amount for final output can then be calculated as thesum of the intermediate inputs and the value added in each activity. Finally, I haveadapted the intermediate outputs of the original input-output table to preserve the identity between the intermediate inputs and the intermediate outputs in the projected table.
Using the criteria described above, I applied the RAS method. Table 5 shows the

input-output transactions matrix for Tarragona in 1999, in which the activity of the
URV is reflected as a differentiated sector. This allows us to show the interdependencesof the University with the other sectors of production.

Finally, to calculate the consumption coefficients (the vector u in matrix A) I

need to know the sectorial values of final consumption for Tarragona in 1999. The

amount of consumption was obtained from the Fundacion BBVA (2000). The sectorial
destination of this variable was obtained by using the information of the Instituto Na
tional de Estadistica (1995).

4. Results of the Economic Impact
This section summarises two types of results reported by the model: the income creation and the employment effects of the Rovira i Virgili University.
Before showing these global effects, we can use the input-output model to analyse

the income multiplier for the University sector. This multiplier is equal to the sum of
the elements corresponding to the URV column in the Leontief inverse matrix (matrix
M). The resulting value quantifies the diffusion effect to the rest of the production

sphere when the URV receives a unitary and exogenous injection. This multiplier isequal to 1.594, which means that every unit of inflows received by the University is

Capturing the Economic Impact of a Public Institution: the Rovira i Virgili University

75

Table 6. Multipliers in Higher Education Studies.
(Huggins and Cooke (1997))
Multiplier(diffusion effect)

University

Bristol Polytechnic

1.15

Lancaster

1.15 - 1.25

Lancaster Polytechnic

1.50

Liverpool

1.45

Manchester

1.17- 1.25

South Shields

1.30

Southampton University

1.20

Stirling

1.24- 1.54

Strathclyde University

1.66-2.15

University of East Anglia

1.20

Wolverhampton Polytechnic

1.03- 1.10

Yorkshire & Humberside

1.30

Rovira i Virgili

1.59

Table 7. Production Effects of the URV, 1999. (Thousand Euros)

SectorURV

Employees'

Students'

Investment

Consumption

Consumption

Total Effect1.

Agriculture5673.7110750.05

12862.90

29286.66

2.

Energy12218.82

13652.84

17415.9343287.59

3.

Metals1084.60

514.58453.282052.46

4.

Minerals

1999.96432.04508.512940.515.

Chemistry

2644.66

3447.92

3693.34

9785.92

6.

Machinery

6110.852616.95

2265.6810993.48

7.

Automobiles

686.361505.73984.503176.60

8.

Food

3929.77

8374.4410187.03

22491.24

9.

Textile1420.072816.445940.26

10176.77

10.

Paper

2181.191453.605556.549191.33

11.

Other industry

2246.071669.57

1449.035364.67

12.

Construction

14109.42

1717.772512.77

18339.95

13.

Commerce12259.39

17213.78

17090.1146563.28

14.

Transportation

2122.502779.505349.5310251.53

15.

Finance3882.884908.314209.7113000.91

16.

Private services

6266.15

9988.55

16629.37

32884.07

17.

Public services

5322.96984.62695.747003.32

18.

Rovira i Virgili University

50.83

54.38

9781.24

9886.45

84210.18

84881.08

117585.49

286676.75

Total

76

Journal of Applied Input-Output Analysis, Vol. 10, 2004

Table 8. Production Effects of the URV. Direct, Indirect and Induced Effects, 1999.
(Thousand Euros)

Sector

1.

Direct EffectAgriculture1472.48

IndirectInducedEffectEffect12128.07

15686.11

29286.66

Total Effect

2.

Energy1027.7320536.55

21723.31

43287.59

3.

Metals

24.04

1227.22801.202052.4654.09

2204.42682.002940.51

4.

Minerals5.

Chemistry

721.213702.895361.82

9785.92

6.

Machinery4074.872854.974063.64

10993.48

7.

Automobiles

775.3198.85

2302.443176.60

8.

Food7218.163220.1012052.98

22491.24

9.

Textile3852.49

1974.674349.61

10176.77

10.

Paper

5204.76

1700.282286.299191.33

11.

Other industry

1460.461298.312605.905364.672787.94

18339.95

12.

Construction

13342.47

2209.54

13.

Commerce

8967.109309.30

28286.8846563.28

14.

Transportation

3461.832481.314308.3910251.53

15.

Finance492.834816.01

7692.07

13000.91

16.

Private services

11882.01

4408.64

16593.42

32884.07

17.

Public services

5349.01

0.00

1654.317003.32

18.

Rovira i Virgili University

Total

9718.37

14.94

153.149886.45

79099.22

74186.05

133391.47

286676.75

transformed approximately into 1.6 units of income. This result is very close to thosein other similar studies. Table 6 shows a comparative exposition of multipliers inhigher education studies cited in Huggins and Cooke (1997).
Universities generally play an important role within its local economy,

which canbe quantified in terms of output and income effects. The values in table 6 suggest that
the URV multiplier is in line with other similar studies of universities' impact. From ta
ble 6, therefore, we can take our results as general enough to measure the economic

impact and income generation of the Rovira i Virgili University in the Tarragona region.

Table 7 summarises the production effect of URV activity, the total of which is286676.75 thousand euros. Investment by the University produces 29.4% of the total

effect, the employees' consumption produces 29.6% while the students generate the remaining 41%.

At the sectorial level, commerce receives the largest impact (16%). This is fol

lowed by energy (15%), private services (11%) and agriculture (10%). These four sec
tors therefore jointly receive 52% of the overall impact. We should point out here once
more that the results of the model underestimate the real effect on construction activity

because the lack of data means that I have not taken into account purchases of resi
dence made by the URV employees.

The overall economic impact can also be divided into direct, indirect and inducedCapturing the Economic Impact of a Public Institution: the Rovira i Virgili University

77

Table 9. Employment Effects of the URV, 1999. (Number of jobs)
SectorInvestment

Employees

Students

644

1221

1460

3325

75

84

108

267

Total

1.

Agriculture

2.

Energy3.

Metals

91

43

38

172

4.

Minerals

151

33

38

222

5.

Chemistry

122

159

170

451

6.

Machinery

454

195

169

818

7.

Automobiles

138

302

197

637

8.

Food

149

319

387

856

9.

Textile

72

143

302

517

10.

Paper

185

123

470

778

11.

Other industry

235

175

152

562

12.

Construction

1531

186

273

1991

13.

Commerce

1061

1490

1479

4031

14.

Transportation

189

248

477

915

15.

Finance

28

35

30

93

16.

Private services

564

899

1496

2959

17.

Public services

1095

203

143

1440

18.

Rovira i Virgili University

10

10

1838

1858

6795

5867

9229

21890

Total

effects (table 8). The last row in this table indicates that the global impact was 3.62

times larger than the initial demand generated by the University. The decomposition of
the production effects shows that direct effect is 27.6%, indirect effect is 25.9% and in
duced effect is 46.5% of the overall impact. By activities, the indirect effects are espe

cially large in energy, agriculture and commerce because these activities are very inte
grated into the productive system. The induced effects show the largest values in com

merce, energy, private services, agriculture and food. As is logical, the endogeneizationof households causes the major impact in those activities with higher connection with
consumption demand.

Finally, table 9 shows the occupation effects generated by the presence of the Uni
versity. We can see that in 1999 the Rovira i Virgili University created 21890 jobs.
Commerce received the largest effect, with 18.4% of the overall occupation. The effectreceived by agriculture is also important. This is explained mainly by the students andemployees demand for consumption.

We should point out that the values in table 9 have to be taken very carefully. The
input-output model assumes that production technology is fixed and implies that the
proportion of workers is fixed. This hypothesis does not take into account any techno

logical changes in the productive processes or changes in the proportion of employ
ment.

78

Journal of Applied Input-Output Analysis, Vol. 10, 2004

5. Concluding Remarks
Universities today are large economic institutions that can have an important impact on
their local economy. The size of these institutions illustrates the importance of higher-

education activity in generating income and economic growth in regional economies.
In this paper I have presented a way of calculating the economic effects of a pub
lic institution of higher education. Specifically, I have used the input-output method toanalyse the economic contribution of the Rovira i Virgili University in the Tarragona

area. For the empirical application, I constructed an input-output table for the provinceof Tarragona in 1999, using the RAS technique. By incorporating the URV into the ta
ble as an individual activity, I have shown how the University affects sectorial production and job creation.

The URV has a clear economic impact on the productive system. The largest im
pact of the University's investment is on construction; consumption by URV employees

mainly benefits commerce, energy and agriculture. Finally, the biggest impact of stu
dent demand is on energy, commerce and private services. In conclusion, my study
shows that there is a real and large economic contribution produced by the University's
expenditure at the territorial level.

Finally, for several reasons, we have to take the values in this paper with the usual

caution for empirical applications. Firstly, the input-output method assumes that pro

duction technology is invariable in all activities, which implies that the adjustments inthe productive systems are rigid. Secondly, the model does not take into accountchanges in prices, so adjustments come only from changes in quantities. Finally, there
are information deficiencies that have to be taken into account. The Tarragona region is
not always covered by the official sources of information. In some cases, therefore, I

have had to apply indirect calculations for the unknown variables.

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