Centro de Estudos da União Europeia (CEUNEUROP) Faculdade de Economia da Universidade de Coimbra

Av. Dias da Silva, 165-3004-512 COIMBRA – PORTUGAL e-mail: ceuneurop@fe.uc.pt website: www4.fe.uc.pt/ceue

Sara Proença and Elias Soukiazis

Tourism as an Alternative Source of Regional Growth in Portugal.

DOCUMENTO DE TRABALHO/DISCUSSION PAPER (SEPTEMBER) Nº 34

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1

Tourism as an Alternative Source of Regional Growth in Portugal1.

Sara Proença* and Elias Soukiazis** Abstract The role of tourism gains fundamental importance especially for small countries with

privilege geographical location and favourable weather conditions. This paper examines

the importance of tourism as a conditioning factor for higher regional growth in

Portugal by employing a convergence approach of the Barro and Sala-i-Martin type.

The panel data estimation approach gives evidence of the positive impact of tourism

(through the accommodation capacity) on the growth of per capita income among the

Portuguese regions, speeding the convergence rate. On the other hand, substantial

economies to scale are detected in the tourism sector by testing the Verdoorn Law at a

regional level. Both results suggest that tourism can be considered as an alternative

solution for enhancing higher regional growth in Portugal if the supply characteristics of

this sector are improved.

Key words: tourism, conditional convergence, economies to scale, Verdoorn´s Law, panel regressions. JEL Codes: C23, D12, L83. Author for correspondence: Elias Soukiazis, Faculdade de Economia, Universidade de Coimbra, Av. Dias da Silva, 165, 3004-512 Coimbra, Portugal, Tel. + 351 239 790 534, Fax + 351 239 40 35 11, e-mail: elias@fe.uc.pt. (*) Agrarian School, Polytechnic of Coimbra, Portugal (sproenca@esac.pt) (**) Faculty of Economics, University of Coimbra, Portugal (elias@fe.uc.pt)

1 This study is a part of the MA dissertation elaborated by Sara Proença under the supervision of Elias Soukiazis.

2

1. Introduction

The tourism activity in Portugal is responsible for about 8% of the national product and

employs 10% of the total labour force. On the other hand, the receipts from tourism

contribute substantially in financing the current account deficit in this country. Almost

60% of the current account deficit is financed by receipts generated from the tourism

activity. At a regional level tourism solves the problem of unemployment and replaces

activities that lost competitive advantages (specially in the agricultural sector). In some

of the regions (Algarve in the South and islands of Madeira and Azores), tourism is the

main tradable sector employing a substantial number of labour force. All these are

convincing arguments to justify an empirical analysis that measures the impact of

tourism on economic growth, especially at a regional level.

The aim of this paper is twofold. In first place we test the importance of tourism

as a conditioning factor in improving the standards of living of the populations in the

Portuguese regions. In doing so, the well known conditional convergence approach of

the Barro and Sala-i-Martin type is used to test for convergence in per capita income

among the 30 NUTs III Portuguese regions. In second place we test Verdoorn´s Law

which relates productivity growth to the growth of output to detect economies of scale

characteristics. The presence of significant economies to scales in the tourism sector

will suggest that this sector can constitute an alternative source of economic growth

improving the standards of living of the Portuguese regions. The empirical analysis uses

the panel estimation techniques combining time-series and cross-sectional data referred

to the Portuguese regions at the NUTs II and III levels. To our knowledge, at least for

Portugal, there are no studies2 that tested the impact of tourism on regional growth or

searched for the presence of economies to scale in this sector.

The remainder of the paper has the following structure: Section 2 analyses the

disparities of per capita income among the Portuguese regions over time and gives some

information on the accommodation capacity of the tourism sector at a regional level.

The convergence hypothesis in per capita income is tested in Section 3, using tourism

(accommodation capacity) as the conditioning supply factor for higher growth and the

results are discussed. Section 4 gives evidence of the presence of economies to scale in

the tourism sector, through the estimation of the Verdoorn´s Law. The last section

concludes, summarizing the main findings. 2 Ledesma-Rodríguez, F. et al. (2001) provide a study for Brazil.

3

2. Per capita income disparities among the Portuguese Regions

Per capita income differences are significant across regions in Portugal. Table 1

describes the evolution of per capita income of the Portuguese regions at NUTs II (7

regions) and NUTs III (30 regions) desegregation levels, over a short period of 9 years,

from 1993 to 2001 where reliable data is available3. A relative position between the 30

NUTs III regions in the beginning and the end of the period, as well as, in relation to the

richest region (Grande Lisboa) are reported to detect any catching-up tendencies.

At a first instance, Table 1 reveals that the richest regions (Grande Lisboa,

Grande Porto, Algarve, Alentejo Litoral, Pinhal Litoral, Baixo Mondego, and lately

Madeira) belong to the coastal area (or near the sea regions), which are attractive places

from the point of view of tourism demand, while the poorest regions (Tâmega, Serra da

Estrela, Pinhal Interior Norte, Pinhal Interior Sul, Minho-Lima, Alto Trás-os-Montes)

are part of the in-land area, less attractive destination places for tourists4.

From 1993 to 2001, nine regions preserved their relative position, ten regions

improved and eleven deteriorated their relative position. It is important to note that the

most remarkable improvement (from the 16th position in 1993 to the 2nd position in

2001) happened with the islands of Madeira5, where tourism activity is predominant.

Another region with substantial change in its relative position is “Lezíria do Tejo”

which moved from the 14th position in 1993 to the 6th position in 2001, a non costal but

near the sea (and near the Lisbon) region.

The relative position of each region with respect to benchmark (Grande Lisboa)

doesn’t show any substantial improvement. Only seven regions increased their relative

position catching up the richest region, four stayed at the same level and all the others

(18 regions) diverged in relation to the benchmark. Therefore, there is no clear evidence

of a substantial catching-up process between the Portuguese regions during this period.

Madeira is again the region with the higher approximation to the richest region. In 1993,

Madeira’s per capita income was only 46% of Lisbon’s but after nine years jumped to

65% in 2001, being the second region with the highest per capita income in Portugal.

Madeira also reveals the highest average growth rate (13.2%) in per capita income over

the whole period, followed by “Lezíria do Tejo” growing at 10.4% on average. 3 Regional GDP is in current values since there are no regional consumer price indices to deflate GDP. 4 For a better orientation of the location of the Portuguese regions see the Map in the Appendix I illustrating the regional division of Portugal at NUTs II and NUTs III levels. 5 Madeira and also the islands of Azores benefit from an autonomous political system (having their own parliament and president) but receive a substantial financial support from the central government.

4

Table 1. Per capita income of the NUTs II and III Portuguese regions, 1993-2001. Years

1993 1994 1995 1996 1997 1998 1999 2000 2001 01/93

Regions (NUTS II and III)

Ran

king

%* 1 000 Euros %* Ran

king

Average change

%

Portugal 42.5 45.8 52.4 55.7 60.1 65.0 69.5 75.3 79.9 8.2

Norte 5.9 6.5 6.8 7.3 7.6 8.2 8.7 9.1 9.6 6.2

Minho-Lima 26th 38 4.2 4.8 5.2 5.6 5.9 6.3 6.7 7.1 7.5 36 25th 7.5

Cavado 17th 45 5.0 5.7 6.2 6.7 7.0 7.5 8.0 8.5 9.0 44 18th 7.6

Ave 9th 52 5.8 6.3 6.8 7.1 7.5 8.0 8.6 8.9 9.2 45 17th 6.0

Grande Porto 2nd 74 8.2 8.8 9.3 9.8 10.4 11.0 11.7 12.0 12.4 60 3rd 5.3

Tâmega 30th 30 3.4 3.8 3.8 4.0 4.4 4.7 5.1 5.5 5.9 29 30th 7.3

Entre Douro e Vouga 8th 53 5.9 6.6 6.8 7.4 7.9 8.7 9.4 9.6 10.3 50 12th 7.3

Douro 20th 44 4.9 5.4 5.3 5.9 5.8 6.0 6.6 6.9 7.8 38 23rd 6.2

Alto Trás-os-Montes 25th 39 4.3 4.8 5.1 5.4 5.5 6.0 6.3 6.7 7.1 35 27th 6.6

Centro 5.5 6.1 6.5 6.9 7.3 7.9 8.4 9.1 9.7 7.4

Baixo Vouga 5th 61 6.8 7.4 7.6 8.0 8.5 9.1 9.7 10.4 10.9 53 9th 6.1

Baixo Mondego 7th 54 6.1 6.9 8.0 8.2 8.7 9.2 9.7 10.4 11.0 54 8th 7.8

Pinhal Litoral 6th 57 6.4 7.2 7.7 8.3 8.9 9.4 10.3 10.9 11.8 58 5th 8.0

Pinhal Interior Norte 28th 35 3.9 4.4 4.3 4.7 4.9 5.5 5.8 6.4 6.9 34 28th 7.7

Dão-Lafões 24th 39 4.3 4.6 4.5 5.0 5.3 5.8 6.3 7.0 7.6 37 24th 7.4

Pinhal Interior Sul 27th 36 4.0 5.4 5.3 5.9 6.0 6.5 6.4 7.0 7.3 35 26th 8.1

Serra da Estrela 29th 34 3.8 4.2 4.1 4.4 4.8 5.2 5.6 6.2 6.6 32 29th 7.2

Beira Interior Norte 22nd 42 4.7 5.1 5.3 5.7 6.0 6.4 6.9 7.5 8.0 39 22nd 6.8

Beira Interior Sul 11th 49 5.4 6.1 7.5 7.7 8.1 8.6 9.2 10.0 10.6 52 11th 8.9

Cova da Beira 21st 42 4.7 5.2 5.8 6.4 6.5 6.9 7.4 8.0 8.6 42 20th 7.9

Lisboa e Vale do Tejo 8.6 9.2 10.5 11.1 12.2 13.3 14.1 15.0 15.8 8.0

Oeste 10th 49 5.5 5.9 6.2 6.8 7.2 7.9 8.5 8.9 9.7 47 14th 7.4

Grande Lisboa 1st 100 11.2 11.9 13.4 14.2 15.5 17.0 18.2 19.6 20.6 100 1st 7.9

Península de Setúbal 12th 48 5.4 5.8 6.9 7.3 8.1 8.9 9.1 9.2 9.7 47 15th 7.8

Médio Tejo 13th 47 5.3 5.8 7.1 7.8 8.4 9.1 9.8 10.3 10.9 53 10th 9.5

Lezíria do Tejo 14th 47 5.3 5.9 7.0 7.8 8.9 9.5 9.9 10.5 11.5 56 6th 10.4

Alentejo 5.5 5.9 6.8 7.3 7.8 8.1 8.5 9.0 9.6 7.4

Alentejo Litoral 3rd 73 8.2 8.4 9.1 10.1 11.0 11.1 11.3 10.9 11.3 55 7th 4.2

Alto Alentejo 19th 44 4.9 5.3 6.0 6.5 6.8 7.3 7.7 8.3 9.0 44 19th 7.8

Alentejo Central 15th 47 5.2 5.6 6.4 7.0 7.6 8.0 8.4 9.5 10.3 50 13th 8.9

Baixo Alentejo 23rd 39 4.4 5.1 6.3 6.2 6.6 6.7 7.1 7.5 8.1 39 21st 8.3

Algarve 4th 63 7.0 7.2 8.0 8.4 8.9 9.5 10.2 11.1 12.4 60 4th 7.5

R. A. Açores 18th 44 4.9 5.3 6.0 6.5 6.8 7.3 8.1 8.8 9.4 46 16th 8.4

R. A. Madeira 16th 46 5.2 5.6 7.8 8.4 9.5 10.7 11.5 13.2 13.4 65 2nd 13.2

Data source: INE, National Institute of Statistics, Regional Accounts, various issues. Notes: Per capita income is regional GDP per habitant at current prices. NUTs II (7 regions), NUTs III (30 regions). * Per capita income of each region relative to the richest region (Grande Lisboa), in percentage.

5

Figure 1, on the other hand, illustrates the evolution of regional disparities in Portugal

over the period 1993-2001, by using the coefficient of variation that measures the

dispersion of per capita income over time and allows to detect moments of convergence

or divergence6. A declining value indicates a reduction in regional disparities, an

increasing value reveals the widening of regional disparities in terms of per capita

income. As Figure 1 shows, regional disparities declined slightly at the beginning of the

period (1993-1996) but the disparities returned to the initial levels afterwards, both at

NUTs II level (7 regions) and NUTs III level (30 regions). Therefore, there is no solid

evidence that a dynamic process of convergence in per capita income took place among

the Portuguese regions over the period considered (almost a decade).

Figure 1. Dispersion of per capita income among the NUTs II and NUTs III Portuguese regions, over the period 1993-2001

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

1993 1994 1995 1996 1997 1998 1999 2000 2001

Years

Coe

ffic

ient

of V

aria

tion

Nuts II Nuts III

Data source: INE, National Institute of Statistics, Regional Accounts, various issues.

Our main purpose in this study is to test the impact that tourism activity has on regional

growth and how tourism affects the convergence process in Portugal at a regional level.

The only available data7 we have at the NUTs III level (30 regions) is on a supply

indicator which measures the accommodation capacity expressed by the number of beds

available to host tourists. We have two reasons to believe that accommodation capacity

6 The coefficient of variation, given by the ratio of the standard deviation to the sample mean, is also known as σ-convergence in the growth literature. 7 Receipts from tourism would be the desirable data to consider which affect directly regional per capita incomes, but these data are only available at a national level.

6

is a reasonable proxy for measuring the impact of tourism on regional growth. In a

previous study on tourism demand in Portugal (Sara Proença and Elias Soukiazis, 2005)

the accommodation capacity variable was found to be the most significant variable

explaining tourism flows in this country. The second reason is that accommodation

capacity is a strictly exogenous supply variable, avoiding, therefore, endogeneity bias

problems that may arise in the estimation process of the convergence equation.

Table 2 presents the available data on number of beds showing the

accommodation capacity of each region over the period 1993-2001. Ranking the regions

according to the higher accommodation capacity (higher number of beds) we observe

that the first positions correspond to Algarve, Grande Lisboa, Madeira and Grande

Porto which are sea-side regions, very attractive to tourists. These regions preserve their

relative position during the whole period. The last positions with lower absolute

accommodation capacity belong mostly to the in-land area of Portugal (Cova da Beira,

Pinhal Interior Norte, Serra da Estrela and Pinhal Interior Sul). From the same ranking it

can be seen that some regions like, Península de Setúbal, Alentejo Litoral and Azores

(islands) improved their accommodation capacity significantly by the end of the period.

From 1993 to 2001, twelve regions improved their relative position, five preserved their

position and the rest (13) deteriorated their relative position. During the whole period

the total accommodation capacity increased 16%, corresponding to an annual average

growth rate of 1.8%.

The coefficient of correlation between the average change of per capita income

and average change of accommodation capacity is 0.38, revealing a considerable

positive association between the two variables during the period 1993-2001. This means

that per capita income and accommodation capacity have been moved to the same

direction in the sample of the 30 NUTs Portuguese regions. Comparing the

accommodation capacity with the evolution of per capita income one can observe that

healthier regions are regions with higher response to accommodate tourist flows (higher

supply capacity), such as Grande Lisboa, Algarve, Madeira and Grande Porto.

7

Table 2. Accommodation capacity (number of beds) in the NUTs II and III Portuguese regions, 1993-2001.

Years

1993 1994 1995 1996 1997 1998 1999 2000 2001 01/93

Regions (NUTs II and III) R

anki

ng

Unities Ran

king

Avg. change

%

Portugal 198836 202442 204051 208205 211315 215572 216828 222958 228665 1.8Norte 27294 26838 25762 26489 27184 27706 28485 28827 29523 1.0Minho-Lima 13th 3145 2864 2923 3059 3248 2800 2679 2706 2596 17th -2.2Cavado 9th 4065 4109 3892 3931 4178 3962 3997 3769 3881 11th -0.5Ave 20th 1469 1426 1520 1582 1588 1687 1709 1822 2814 16th 9.6Grande Porto 4th 12038 12316 11247 11577 11252 11988 12660 12891 12628 4th 0.7Tâmega 18th 1608 1308 1150 1264 1413 1464 1252 1243 1201 21st -3.0Entre Douro e Vouga 26th 530 537 696 694 693 651 716 596 626 27th 2.8Douro 19th 1514 1497 1445 1387 1797 1921 2157 2341 2276 18th 5.7Alto Trás-os-Montes 15th 2925 2781 2889 2995 3015 3233 3315 3459 3501 12th 2.3Centro 19544 20333 19272 20512 20942 21053 19681 20161 20099 0.4Baixo Vouga 8th 4734 4633 4024 4571 4731 4488 4032 4180 4148 10th -1.3Baixo Mondego 6th 5073 5577 5236 5391 5421 5426 5333 5299 5080 7th 0.1Pinhal Litoral 16th 2896 3068 2985 2906 2995 3051 3081 2898 2981 15th 0.4Pinhal Interior Norte 28th 359 411 432 422 494 472 462 450 448 29th 3.1Dão-Lafões 11th 3446 3563 2770 3483 3699 3844 3014 3445 3470 13th 1.3Pinhal Interior Sul 30th 126 124 117 122 119 95 93 103 166 30th 5.5Serra da Estrela 29th 275 270 336 269 299 438 435 463 475 28th 8.6Beira Interior Norte 21st 1107 1049 1165 1207 1063 997 1052 1093 1072 24th -0.2Beira Interior Sul 23rd 878 949 1272 1241 1230 1257 1182 1187 1183 22nd 4.4Cova da Beira 25th 650 689 935 900 891 985 997 1043 1076 23rd 7.1Lisboa e Vale do Tejo 45276 47341 49407 48545 48497 51028 51956 53405 53628 2.2Oeste 5th 5391 5185 5053 4793 4419 5064 5041 5181 5123 6th -0.4Grande Lisboa 2nd 31227 32341 33541 33229 33210 35476 35988 37026 37080 2nd 2.2Península de Setúbal 14th 3122 4120 4767 4446 4531 4186 4590 4758 4559 9th 5.5Médio Tejo 7th 5064 5302 5581 5691 5672 5669 5664 5746 6096 5th 2.4Lezíria do Tejo 27th 472 393 465 386 665 633 673 694 770 26th 9.1Alentejo 6631 6552 6760 7011 7660 7573 7513 7439 7318 1.3Alentejo Litoral 10th 3455 3176 3166 3156 3264 3466 3205 2935 3008 14th -1.6Alto Alentejo 22nd 961 981 1148 1286 1470 1402 1431 1490 1454 20th 5.6Alentejo Central 17th 1558 1761 1607 1683 2005 1924 2005 2158 2059 19th 3.9Baixo Alentejo 24th 657 634 839 886 921 781 872 856 797 25th 3.3Algarve 1st 80368 81153 82475 84139 84581 85096 85098 85738 86751 1st 1.0R. A. Açores 12th 3219 3290 3383 3630 3573 3592 3939 4012 4814 8th 5.3

R. A. Madeira 3rd 16504 16935 16992 17879 18878 19524 20156 23376 26532 3rd 6.2Data Source: INE, National Institute of Statistics, Tourism Statistics, various issues

8

3. The importance of tourism on regional growth and convergence

The well known conditional convergence equation in per capita income (Barro and

Sala-i-Martin, 1991; 1995) is used to test the impact of tourism on regional growth at

the NUTs III level. The convergence equation relates the growth of per capita

income, , to the initial level of per capita income, (the neoclassical

assumption of absolute convergence, Solow, 1956) and the accommodation capacity in

the tourism sector, , as the conditioning factor (the assumption of conditional

convergence), given by:

tiy ,ln∆ 1,ln −tiy

tiTUR ,

tititiiti uTURyby ,,1,, lnlnln +++=∆ − γα (1)

In the convergence equation (1) regions are supposed to converge at distinct “steady

sates” (given by different intercepts αi), the convergence coefficient is expected to be

negative b<08 and γ≠0 for convergence to be conditional. Equation (1) is estimated by

using panel data estimation techniques9, combining 30 regions for a period of 9 years

(1993-2001), resulting in a sample of 270 observations. The estimated results are

reported in Table 3. The first part of the table presents the results of absolute

convergence (the neoclassical hypothesis) and the second part gives evidence on

conditional convergence (endogenous growth theory) testing the significance of

accommodation capacity as the conditioning factor for higher regional growth. The

usual methods of estimation are used with panel data, namely, the pooled OLS

assuming a common intercept for all regions and common slops, the Fixed Effect

method (LSDV) assuming specific individual effects captured by individual regional

dummies, the Random Effect method (GLS) assuming that regional specific effects are

random, and finally a dynamic panel data estimation approach based on the recent

developments of Arellano and Bond (2002)10.

The first part of Table 3 gives evidence of absolute convergence in per capita

income among the 30 Portuguese regions over the period 1993-2001, confirming the

idea that absolute convergence occurs among economies (regions or countries) with

similar characteristics. The convergence coefficient is negative and statistically

8 The convergence coefficient in this equation is defined as b = (1-e-βT) and the convergence rate is given by β = - ln(1-b)/T. For this explanation see Tondl (2001). 9 A comprehensive analysis of the use of panel data in estimating the convergence equation can be found in Islam (1995). 10 According to Arellano-Bond estimation technique, equation (1) is estimated in first differences and uses as instruments all the lagged variables to solve the problem of endogeneity of . 1,ln −tiy

9

significant in all methods of estimation. Considering the most efficient method of

estimation (lower standard errors) based on the dynamic panel estimation approach of

Arellano and Bond, convergence runs at a 3.65% annual rate which is rather slow.

Table 3. Convergence in per capita income among the 30 NUTs III Portuguese regions, 1993-2001

Absolute convergence: tititi uyby ,1,, lnln ++=∆ −α

Estimation Methods Constant 1,ln −tiy Convergence

Ratea β

Half Distance

Timeb 2R SEE D.F.

Arellano-Bond 0.1461 -0.0372 -0.0365 19 0.0323 0.0426 238

(GMM) (134.660)* (-84.3669)*

Pooled 0.1285 -0.0284 -0.0280 25 0.0363 0.0426 238

(OLS) (7.2588)* (-3.1621)*

Fixed Effects * -0.0937 -0.0896 8 0.1357 0.0403 209

(LSDV) (-6.2398)*

Random Effects 0.1791 -0.0417 -0.0409 17 0.0565 0.0421 238

(GLS) (8.5583)* (-3.9123)*

Hausman Test Chi-Squared (1) = 20.3659 significance level 0.00000640

Conditional convergence: tititiiti uTURyby ,,1,, lnlnln +++=∆ − γα

Estimation Methods Constant 1,ln −tiy tiTUR ,ln Convergence

Ratea β

Half Distance

Timeb 2R SEE D.F.

Arellano-Bond 0.0924 -0.0590 0.0121 -0.0573 12 0.0223 0.0429 237

(GMM) (8.4185)* (-13.9175)* (26.5801)*

Pooled 0.1111 -0.0415 0.0055 -0.0407 17 0.0531 0.0422 237

(OLS) (5.7792)* (-3.9199)* (2.2864)*

Fixed Effects # -0.1065 0.0401 -0.1012 7 0.1413 0.0402 208

(LSDV) (-6.2223)* (1.5384)

Random Effects 0.1582 -0.0599 0.0080 -0.0582 12 0.0811 0.0416 237

(GLS) (6.1887)* (-4.8038)* (2.4586)*

Hausman Test Chi-Squared (2) = 16.1748 significance level 0.0030739

Notes: (a) The annual convergence rate is given by β = - ln (1-b)/T. (b) Half of the reduction in regional asymmetries is given by e-βT = -1/2, therefore, the time to reduce half of the asymmetries is T = -ln (2)/β (see Tondl, 2001). Values in brackets are t-ratio, D.F. is Degrees of Freedom and SEE is the Standard Error Estimate. (*) Indicates that the coefficient is statistically significant at 5%. (#) Individual dummies are not statistically significant. Hausman test: tests the hypothesis (H0) Random Effects vs. (HA) Fixed Effects.

10

According to this result, it will take 19 years to reduce half of the differences existing in

per capita income between the Portuguese regions. The Hausman test, which tests the

Random Effects hypothesis versus the Fixed Effects hypothesis, gives evidence in favor

of the observable individual effects captured by the different intercepts. The individual

regional dummy variables are all statistically significant revealing that there are

different structures in the production function between the 30 Portuguese regions which

have to be taken into account. When differences in structures are controlled for, by the

individual dummy variables convergence runs at a higher rate, 8.96% per annum. In this

case it will take only 8 years to reduce half of the disparities in per capita income among

the Portuguese regions. The degree of explanation in the regression also increases

substantially when individual specific effects arte introduced into the convergence

equation. The Fixed Effects estimation method, therefore, suggests that convergence is

better performed as conditional than absolute.

Our purpose in this study is not to search for the structural factors which might

explain the growth of per capita income. Endogenous growth theory has suggested that

human capital, technology, capital accumulation, innovation, among other factors are

important conditioning elements explaining growth differentials and controlling

differences in steady states among different economies (countries or regions).

Unfortunately, data on these structural factors with increasing returns to scale properties

are not available at a regional level in Portugal. Our intention in testing conditional

convergence focuses on the importance of tourism activity as a conditioning factor for

higher regional growth. The second part of Table 3 presents the estimation results of

testing this hypothesis, by introducing into the convergence equation the

accommodation capacity variable reflecting the supply dynamism of the tourism sector.

In this context the growth of per capita income among the Portuguese regions is

explained by the convergence factor (initial level of per capita income) and additionally

by the accommodation capacity of each region to host tourists. This last variable

controls differences in the supply structure of the tourism sector along the Portuguese

regions.

The evidence from Table 3 is encouraging showing that the supply capacity of

the tourism sector influences positively the growth of per capita income in the

Portuguese regions. The coefficient of the accommodation capacity variable is positive

and statistically significant in all methods of estimation but not in the LSDV case.

Another interesting result is that the convergence rate is higher in all methods of

11

estimation comparing to the previous case of absolute convergence (fist part of Table 3).

The Arellano-Bond dynamic panel estimation (our preferable method) suggests that

convergence in per capita income is conditional and runs at a higher rate of 5.73%

(against 3.65% in the absolute convergence case), so the time to eliminate half of the

differences in per capita income reduces from 19 to 12 years when differences in

accommodation capacity in the tourism sector are controlled for. The quantitative effect

of this variable is also considerable. Every 1% increase in accommodation capacity in

the tourism sector generates 0.01% increase in per capita income in the Portuguese

regions. In fact, tourism activity induces higher growth in per capita income and higher

convergence, conditioning the standards of living of the Portuguese regions.

4. Economies of scale in the tourism sector: Verdoorn´s Law

Keynesian growth theory (Myrdal, 1957, Kaldor, 1981, Thirlwall, 1999), endogenous

growth theory (Barro and Sala-i-Martin, 1991, 1992 and Sala-i-Martin, 1996) and more

recently the New Economic Geography (Krugman, 1991, Krugman and Venebles,

1995) all emphasize the importance of increasing returns to scale as the driving force of

regional growth. Economic activities with substantial economies to scale characteristics

will generate a cumulative process of growth which can be virtuous and sustainable.

Once a region gains competitive advantages in sectors with increasing returns to scale

properties, it will enhance higher productivity, higher growth and turn difficult to other

regions (or countries) to compete at the same activities (Kaldor, 1970). A growth

process will take place with cumulative causation tendencies and learning by doing

characteristics. The development of the cumulative growth process is based on

Verdoorn´s Law (1949) which relates the growth of productivity to the growth of output

of the respective sector.

The original version of Verdoorn´s Law considers that industry or

manufacturing are the only sectors exhibiting increasing returns to scale properties,

since they produce mainly tradable goods. This happens because increasing returns to

scale is a function of the market size, and therefore international market is the place

where economies to scale can be explored. In this context, agricultural sector exhibits

decreasing returns to scale (subject to demand and supply constraint) and services

constant returns (Kaldor, 1981). Endogenous growth theory, on the other hand, argues

12

that human capital and investment on technology and innovation, in the long run,

display increasing returns to scale characteristics, inducing higher growth. Differences

in human capital explain differences in growth rates between different economies

(countries or regions). In turn, New Economic Geography claims that increasing returns

to scale are generated in the non-agricultural sector and explain the formation of

clusters. Agricultural sector is not mobile (land is fixed) and, therefore, agricultural

activity is against the clustering. Although, focus has been given in the industrial sector

as the sector generating higher returns to scale, and where Verdoorn´s Law has mostly

been tested, it is worthwhile to search for such properties in other sectors as well,

especially in services. Nowadays, services show a growing share relatively to other

economic activities, so it is possible to detect substantial economies to scale in this

sector. Leon-Ledesma (1998) testing Verdoorn´s Law for the Spanish economy found

significant economies to scale in activities related to services. Our purpose in this

section is to test Verdoorn´s Law in the tourism sector searching for gains in

productivity in this type of activity.

Verdoorn (1949) was the first author to detect a positive significant relationship

between the growth of labour productivity and the growth of industrial output. He

argued that the causality runs from output to productivity with an elasticity of 0.45 in a

cross-section analysis, suggesting that productivity is endogenous to the growth process.

According to this result, a 10% increase in industrial output generates 4.5% increase in

labour productivity. Verdoorn´s equation takes the following form:

p = a + bq with p = q - e (2)

where p is the growth of productivity, q the growth of output, e the growth of labour, a

is autonomous productivity (not depending on the growth of output) and b>0 the

elasticity of labour productivity with respect to output reflecting economies to scale

properties11.

Kaldor (1966) reinvented Verdoorn´s Law in his attempt to explain the causes of

the slow economic growth in the U.K. He estimated Verdoorn´s Law by using a sample

of 12 OCDE countries for the period 1953-1964 confirming a strong relation between

the growth of productivity and the growth of output (with an elasticity 0.5) in the

industrial sector. To avoid a spurious relationship between productivity (p = q-e) and 11 Verdoorn´s equation can be written alternatively as: q-e=a+bq → q=a/1-b + (1/1-b)e. Therefore, the economies to scale are given by 1/1-b in a Cobb-Douglas production function with labour as the only input. If the coefficient of Verdoorn is b=0.5 then the economies to scale are 2. Constant economies to scale are obtained when b is not statistically different from zero.

13

output growth (q) when labour grows at low rates or it is stagnant, Kaldor suggested an

alternative way to test the validity of Verdoorn´s Law:

e = c + dq with c = -a and d = 1-b (3)

With this specification Kaldor assumes that labour is also endogenous in the growth

process depending on the strength of demand (output growth). According to Kaldor a

1% increase in output will generate 0.5% increase in labour productivity or 0.5%

increase in employment. Kaldor (1975) explained that the Verdoorn´s equation (2 or 3)

reflects properties of the technical progress function or learning by doing curve

capturing both static and dynamic economies to scale. The static economies to scale are

related with the volume and the scale of production obtained by higher division of

labour (higher specialisation) and the dynamic economies to scale are induced by higher

capital accumulation, technical progress and innovation. Verdoorn´s equation replicates

dynamic characteristics between the growth of productivity and the growth of output

and not static characteristics between the level of productivity and the scale of output. In

other words, the growth of output stimulates the growth of productivity thought the

realisation of static and dynamic economies to scale.

Our purpose in this section is to test the validity of Verdoorn´s Law in the

tourism sector across the NUTs II Portuguese regions during the short period

1995-2002, where data is available. The output in the tourism sector is measured by the

gross value added (VA) in the “Accommodation and Restoration” activity, the only

output measure we have related to the tourism sector at a regional level. The full data on

VA (at current and constant prices)12 and employment, as well as, the growth rates of

output, labour and productivity in the tourism sector are given in the Appendix B.

Using the available data, we plot the relationship between the growth of

productivity and the growth of output (Verdoorn´s relation) and alternatively the growth

of labour and output (Kaldor´s relation) in the tourism sector for the 7 NUTs II regions.

The two alternative relationships are shown in Figure 2 and 3 respectively, where a

positive relationship is confirmed in all cases, supporting the validity of Verdoorn´s

Law. The coefficient of correlation indicates that the association between productivity

(p) and output (q) (Verdoorn´s relation) is stronger than the association between labour

(e) and output growth (q) (Kaldor´s relation).

12 When output is measured in constant prices the estimation period is shorter, 1997-2002. The reason is that the price deflator in the tourism sector which is used to deflate the data on “Accommodation and Restoration” is given only posterior to 1997.

14

Figure 2. Verdoorn´s relationship between productivity (p) and output growth (q) in the tourism sector. a) Current prices, 1995-2002 b) Constant prices, 1997-2002 (r = 0.718) (r = 0.614)

q

p

-10 -5 0 5 10 15

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

q

p

-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5

-2.5

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

Figure 3. Kaldor´s relationship between labour (e) and output growth (q) in the tourism sector. a) Current prices, 1995-2002 b) Constant prices, 1997-2002 (r = 0.393) (r=0.549)

q

e

-3 0 3 6 9 12 15 18

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

qe

-3 0 3 6 9 12 15 18

-2.5

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

To test in a more formal way the validity of Verdoorn´s Law we use a panel data

estimation approach relating productivity growth to output growth in the tourism sector.

The estimated equation has the following form:

(4) titiiti uqbap ,,, ++=

In this equation i = 1,…,7 refers to region, t = 1,…,8 to time, ai is the autonomous

productivity different for each region and b the Verdoorn´s coefficient.

Table 4 presents the results from the estimation of Verdoorn´s Law, both when

output in the tourism sector is measured at current or constant prices. It is shown that in

all cases the Verdoorn´s coefficient is positive and statistically significant in all methods

of estimation suggesting a robust relationship between the growth of labour productivity

and growth of output in the tourism sector. The elasticity of productivity with respect to

output is very similar in the three alternative methods of estimation. When output is

measured at constant prices (the more appropriate), the coefficient of Verdoorn (b=0.54)

is closer to the original value found by Verdoorn and Kaldor. This elasticity suggests

that a 1% increase in output enhances 0.54 % increase in productivity or 0.46% increase

15

in employment in the tourism sector. The same value of the Verdoorn coefficient is

associated with substantial economies to scale equivalent to 2.176. Output in the

tourism sector is doubled when labour in this sector increases by 1%. These are strong

evidence that the tourism sector in Portugal is subject to increasing returns

characteristics, therefore, tourism activity can be considered as an alternative source of

regional growth in this country.

Table 4. Estimation of Verdoorn´s Law in the tourism sector at NUTs II level. a) Current prices, 1995-2002

Estimation Method Constant b 2R Standard Error D.F.

Pooled -2.0364 0.7069 0.5055 2.9265 47

(OLS) (-2.1517)* (7.0752)*

Fixed Effects # 0.7132 0.4929 2.9636 41

(LSDV) (6.9834)*

Random Effects -2.0253 0.7056 0.4998 2.9592 47

(GLS) (-2.1571)* (6.9979)*

Hausman Test Chi-Squared (1) = 0.2523 signifince level 0.6155

Verdoorn´s Equation tititi uqp ,,, 706.0025.2 ++−=

Economies to Scale tititititi ueqebb

aq ,,,,, 401.3888.611

1 ++−=⇔−+−=

b) Constant prices, 1997-2002 Estimation Method Constant b 2R Standard Error D.F.

Pooled -2.4511 0.5420 0.3576 2.7236 33

(OLS) (-3.5970)* (4.4636)*

Fixed Effects § 0.5466 0.3309 2.7795 27

(LSDV) (4.3588)*

Random Effects -2.4445 0.5404 0.3456 2.7958 33

(GLS) (-3.7386)* (4.3538)*

Hausman Test Chi-Squared (1) = 0.0795 significance level 0.7780

Verdoorn´s Equation tititi uqp ,,, 540.0445.2 ++−=

Economies to Scale tititititi ueqebb

aq ,,,,, 176.2319.511

1 ++−=⇔−+−=

Notes: Values in brackets are t-ratio. (*) Indicates that the coefficient is statistically significant at 5%. (#) The dummy variables are not statistically significant except for Azores. (§) The dummy variables are not statistically significant except for Norte and Azores.

16

5. Conclusions

The purpose of this study was twofold: first, to test the impact of tourism on regional

growth and see how tourism affected regional convergence in Portugal. Second, to

search for the presence of economies to scale in the tourism sector implying, therefore,

that tourism activity can contribute substantially for higher regional growth in Portugal.

The first issue has been addressed by using a convergence approach in per capita

income in an attempt to explain how regional differences have been developed over

time. Through the concept of σ-convergence we have shown that there is not any

dynamic process of altering the asymmetries in per capita income between the 30 NUTs

III Portuguese regions, over the period 1993-2001. Through the concept of conditional

convergence we found evidence that the Portuguese regions converge to distinct “steady

states” and that tourism (accommodation capacity) is an important conditioning factor

improving significantly the standards of living. A 1% increase in accommodation

capacity in the tourism sector induces 0.01% increase in per capita income in the

Portuguese regions. When the accommodation capacity variable is introduced into the

convergence equation, the annual rate of convergence in per capita income increases

from 3.67% to 5.73% and the time to eliminate half of the differences in per capita

income reduces from 19 to 12 years.

The second issue has been addressed by estimating Verdoorn´s Law in order to

detect economies to scales in the tourism sector. Output in this sector is measured by the

gross value added in the “Accommodation and Restoration” activities at current and

constant prices for the sample of the NUTs II Portuguese regions. A preliminary

analysis of the relationship between the growth of labour productivity and the growth of

output suggests a significant positive association between the two variables giving

evidence in favour of Verdoorn´s Law. The panel data estimation of the Verdoorn´s

equation confirms satisfactorily the presence of significant economies to scale in the

tourism sector in all different methods of estimation. The Verdoorn´s coefficient found

implies that a 1% increase in output in the tourism sector induces 0.54% increase in

labour productivity or 0.46% increase in employment in this sector. This result enable

us to detect substantial economies to scale in the tourism sector in Portugal suggesting

that output doubles when a positive variation in labour input takes place.

From the point of view of economic policy the whole analysis shows that the

improvement of the supply characteristics of the tourism sector is a necessary condition

17

for this sector to contribute positively in regional growth, therefore, tourism is an

alternative source of growth in Portugal.

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APPENDIX A

Map of the 7 NUTs II and 30 NUTs III Portuguese regions

Source: INE, National Institute of Statistics, Regional Accounts, 1995.

19

APPENDIX B

Table 1. Gross Value Added in the “Accommodation and Restoration” sector.

a) Current prices, 1995-2002 Years

1995 1996 1997 1998 1999 2000 2001 2002

Regions (NUTs II) Millions of Euros

Norte 312 334 375 416 450 467 492 571

Centro 248 262 288 327 354 366 392 432

Lisboa e Vale do Tejo 782 819 937 1 150 1 222 1 278 1 334 1 393

Alentejo 84 88 101 116 125 130 144 156

Algarve 342 347 390 427 458 482 533 580

Continent 1 769 1 851 2 091 2 435 2 609 2 723 2 895 3 132

R. A. Açores 19 20 24 26 27 29 32 36

R. A. Madeira 147 155 187 205 220 228 256 279

Portugal 1 935 2 026 2 302 2 666 2 856 2 980 3 183 3 447

b) Constant prices (1997=100), 1997-2002

Years

1997 1998 1999 2000 2001 2002 Regions (NUTs II) Millions of Euros

Norte 3.75 4.03 4.24 4.24 4.23 4.64

Centro 2.88 3.21 3.37 3.39 3.50 3.62

Lisboa e Vale do Tejo 9.37 11.05 11.42 11.48 11.67 11.62

Alentejo 1.01 1.13 1.19 1.20 1.26 1.29

Algarve 3.90 4.09 4.26 4.37 4.49 4.53

Continent 20.91 23.50 24.47 24.68 25.16 25.69

R. A. Açores 0.24 0.26 0.26 0.26 0.28 0.30

R. A. Madeira 1.87 2.00 2.08 2.08 2.24 2.25

Portugal 23.02 25.79 26.86 27.05 27.72 28.39

Data Source: INE, National Institute of Statistics, Regional Accounts, various issues. INE, National Institute of Statistics, Consumer Price Index, December, 1997-2002.

Table 2. Total labour in the “Accommodation and Restoration” sector, 1995-2002. Years

1995 1996 1997 1998 1999 2000 2001 2002 Regions (NUTs II) Thousands

Norte 47.7 48.8 51.7 55.0 57.8 60.5 62.5 65.6

Centro 34.4 34.4 37.2 41.7 44.2 43.9 44.8 47.3

Lisboa e Vale do Tejo 73.2 76.6 78.2 85.8 87.8 87.7 91.3 92.7

Alentejo 13.4 13.5 14.6 15.6 16.1 16.6 17.2 17.5

Algarve 17.3 18.3 19.9 20.3 21.1 22.2 23.1 23.5

Continent 186.0 191.6 201.5 218.4 227.1 230.8 239.0 246.6

R. A. Açores 2.0 2.2 2.3 2.7 2.9 2.9 3.0 3.2

R. A. Madeira 7.1 7.3 7.9 8.2 8.6 8.8 9.1 9.6

Portugal 195,2 201.2 211.8 229.4 238.5 242.5 251.0 259.3

Data Source: INE, National Institute of Statistics, Regional Accounts, various issues.

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Table 3. Average annual growth rate of output, employment and productivity in the tourism sector. a) Current prices, 1995-2002

Regions (NUTs II) q % e % p %

Norte 8.63 4.55 4.08

Centro 7.93 4.55 3.38

Lisboa e Vale do Tejo 8.25 3.37 4.88

Alentejo 8.84 3.81 5.03

Algarve 7.55 4.38 3.17

Continent 8.24 4.13 4.11

R. A. Açores 9.13 6.71 2.42

R. A. Madeira 9.15 4.31 4.84

Portugal 8.50 4.53 3.97

b) Constant prices (1997=100), 1997-2002

Regions (NUTs II) q % e % P %

Norte 4.25 4.76 -0.51

Centro 4.57 4.80 -0.23

Lisboa e Vale do Tejo 4.30 3.40 0.90

Alentejo 4.84 3.62 1,22

Algarve 2.98 3.33 -0.35

Continent 4.19 3.98 0.21

R. A. Açores 4.37 6.60 -2.23

R. A. Madeira 3.66 3.90 -0.24

Portugal 4.14 4.34 -0.2

Data Source: INE, National Institute of Statistics, Regional Accounts, various issues. INE, National Institute of Statistics, Consumer Price Index, December, 1997-2002.

21

References Arellano, M., and Bond, S. (2002), Panel Data Estimation Using DPD for Ox, Oxford, Nuffield College. Barro, R., and Sala-i-Martin, X. (1991), “Convergence across States and Regions”, Brooking Papers on Economic Activity, Vol 1, pp 107-182. Barro, R., and Sala-i-Martin, X. (1992), “Convergence”, Journal of Political Economy, Vol 100, pp 223-251. Barro, R., and Sala-i-Martin, X. (1995), Economic Growth, McGraw-Hill International Editions. INE, National Institute of Statistics, Portugal, “Regional Accounts”, various issues. INE, National Institute of Statistics, Portugal, “Tourism Statistics”, various issues. INE, National Institute of Statistics, Portugal, “Consumer Price Index”, 1997-2002. Islam, N. (1995), “Growth Empirics: a Panel Data Approach”, Quarterly Journal of Economics, Vol 110, pp 1127-1170. Kaldor, N. (1966), “Causes of the slow rate of Economic Growth in the United Kingdom”, published in The Essential Kaldor edited by Targetti F. and Thirlwall A.P., (1989) Duckworth, London. Kaldor, N. (1970), “The Case for Regional Policies”, Scottish Journal of Political Economy, Vol XVII, nº 3. Kaldor, N. (1975), “Economic Growth and the Verdoorn Law - A Comment on Mr. Rowthorn´s Article”, Economic Journal, Vol 85, pp 891-896. Kaldor, N. (1981), “The Role of Increasing Returns, Technical Progress and Cumulative Causation in the Theory of International Trade and Economic Growth”, Économie Appliquée, nº 4. Krugman, P. (1991), “Increasing returns and economic geography”, Journal of Political Economy Vol 99, pp183-199. Krugman, P., and Venables, A. (1995), “Globalization and the inequality of nations”, Quarterly Journal of Economics, Vol 110, pp 617-650. Ledesma-Rodríguez, F. et al. (2001), “Panel Data and Tourism: a Case Study of Tenerife”, Tourism Economics, Vol 7, pp 75-88. Leon-Ledesma, M. (1998), “Economic Growth and Verdoorn’s Law in the Spanish Regions”, International Review of Applied Economics, Vol 14, pp 55-69.

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Myrdal, G. (1957), Economic Theory and Under-Developed Regions, Duckworth, London. Sala-i-Martin, X. (1996), “Regional Cohesion: Evidence and Theories of Regional Growth and Convergence”, European Economic Review, Vol 40, pp 1325-1352. Proença, S., and Soukiazis, E. (2005), “Demand for Tourism in Portugal: A Panel Data Approach”, CEUNEUROP, Discussion Paper nº 29, February (www4.fe.uc.pt/ceue). Solow, R. (1956), “A Contribution to the Theory of Economics”, The Quarterly Journal of Economics, Vol 70, pp 65-94. Thirlwall, A. P. (1999), Growth and Development, 6th Edition, Macmillan, London. Tondl, G. (2001) Convergence after Divergence? Regional Growth in Europe, Springer, Wien. Verdoorn, P. (1949) “Fattori che Regolano lo Sviluppo Della Produttivita del Lavoro”, L’Industria, Vol 1, pp 3-10. English translation by A.P. Thirlwall in L. Pasinetti (ed.), Italian Economic Papers, Vol. II, (Oxford University Press, 1993).

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List of the Discussion Papers published by CEUNEUROP

Year 2000 Alfredo Marques - Elias Soukiazis (2000). “Per capita income convergence across countries and across regions in the European Union. Some new evidence”. Discussion Paper Nº1, January. Elias Soukiazis (2000). “What have we learnt about convergence in Europe? Some theoretical and empirical considerations”. Discussion Paper Nº2, March. Elias Soukiazis (2000). “ Are living standards converging in the EU? Empirical evidence from time series analysis”. Discussion Paper Nº3, March. Elias Soukiazis (2000). “Productivity convergence in the EU. Evidence from cross-section and time-series analyses”. Discussion Paper Nº4, March. Rogério Leitão (2000). “ A jurisdicionalização da política de defesa do sector têxtil da economia portuguesa no seio da Comunidade Europeia: ambiguidades e contradições”. Discussion Paper Nº5, July. Pedro Cerqueira (2000). “ Assimetria de choques entre Portugal e a União Europeia”. Discussion Paper Nº6, December.

Year 2001 Helena Marques (2001). “A Nova Geografia Económica na Perspectiva de Krugman: Uma Aplicação às Regiões Europeias”. Discussion Paper Nº7, January. Isabel Marques (2001). “Fundamentos Teóricos da Política Industrial Europeia”. Discussion Paper Nº8, March. Sara Rute Sousa (2001). “O Alargamento da União Europeia aos Países da Europa Central e Oriental: Um Desafio para a Política Regional Comunitária”. Discussion Paper Nº9, May.

Year 2002 Elias Soukiazis e Vitor Martinho (2002). “Polarização versus Aglomeração: Fenómenos iguais, Mecanismos diferentes”. Discussion Paper Nº10, February. Alfredo Marques (2002). “Crescimento, Produtividade e Competitividade. Problemas de desempenho da economia Portuguesa” . Discussion Paper Nº 11, April. Elias Soukiazis (2002). “Some perspectives on the new enlargement and the convergence process in Europe”. Discussion Paper Nº 12, September.

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Vitor Martinho (2002). “ O Processo de Aglomeração nas Regiões Portuguesas”. Discussion Paper, Nº 13, November.

Year 2003 Elias Soukiazis (2003). “Regional convergence in Portugal”. Discussion Paper, Nº 14, May. Elias Soukiazis and Vítor Castro (2003). “The Impact of the Maastricht Criteria and the Stability Pact on Growth and Unemployment in Europe” Discussion Paper, Nº 15, July. Stuart Holland (2003a). “Financial Instruments and European Recovery – Current Realities and Implications for the New European Constitution”. Discussion Paper, Nº 16, July. Stuart Holland (2003b). “How to Decide on Europe - The Proposal for an Enabling Majority Voting Procedure in the New European Constitution”. Discussion Paper, Nº 17, July. Elias R. Silva (2003). “Análise Estrutural da Indústria Transformadora de Metais não Ferrosos Portuguesa”, Discussion Paper, Nº 18, September. Catarina Cardoso and Elias Soukiazis (2003). “What can Portugal learn from Ireland? An empirical approach searching for the sources of growth”, Discussion Paper, Nº 19, October. Luis Peres Lopes (2003). “Border Effect and Effective Transport Cost”. Discussion Paper, Nº 20, November. Alfredo Marques (2003). “A política industrial face às regras de concorrência na União Europeia: A questão da promoção de sectores específicos” Discussion Paper, Nº 21, December.

Year 2004 Pedro André Cerqueira (2004). “How Pervasive is the World Business Cycle?” Discussion Paper, Nº 22, April. Helena Marques and Hugh Metcalf (2004). “Immigration of skilled workers from the new EU members: Who stands to lose?” Discussion Paper, Nº 23, April.

Elias Soukiazis and Vítor Castro (2004). “How the Maastricht rules affected the convergence process in the European Union. A panel data analysis”. Discussion Paper, Nº 24, May.

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Elias Soukiazis and Micaela Antunes (2004). “The evolution of real disparities in Portugal among the Nuts III regions. An empirical analysis based on the convergence approach”. Discussion Paper, Nº 25, June. Catarina Cardoso and Elias Soukiazis (2004). “What can Portugal learn from Ireland and to a less extent from Greece? A comparative analysis searching for the sources of growth”. Discussion Paper, Nº 26, July. Sara Riscado (2004), “Fusões e Aquisições na perspectiva internacional: consequências económicas e implicações para as regras de concorrência”. Documento de trabalho, Nº 27, Outubro.

Year 2005 Micaela Antunes and Elias Soukiazis (2005). “Two speed regional convergence in Portugal and the importance of structural funds on growth”. Discussion Paper, Nº 28, February. Sara Proença and Elias Soukiazis (2005). “Demand for tourism in Portugal. A panel data approach”. Discussion Paper, Nº 29, February. Vitor João Pereira Martinho (2005). “Análise dos Efeitos Espaciais na Produtividade Sectorial entre as Regiões Portuguesas”. Discussion Paper, Nº 30, Abril. Tânia Constâncio(2005). “Efeitos dinâmicos de integração de Portugal na UE” Discussion Paper, Nº 31, Março. Catarina Cardoso and Elias Soukiazis (2005). “Explaining the Uneven Economic Performance of the Cohesion Countries. An Export-led Growth Approach.” Discussion Paper, Nº 32, April. Alfredo Marques e Ana Abrunhosa (2005). “Do Modelo Linear de Inovação à Abordagem Sistémica - Aspectos Teóricos e de Política Económica” Documento de trabalho, Nº 33, Junho. Sara Proença and Elias Soukiazis (2005). “Tourism as an alternative source of regional growth in Portugal”, Discussion Paper, Nº 34, September.

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