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Anatolia: An International Journal of Tourism and Hospitality Research
Volume 17, Number 2, pp. xx-xx. 2006
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Contribution of Tourism to Economic Growth:
A Panel Data Approach
UMMUHAN GÖKOVALI
Mugla University
Faculty of Economics and Administrative Sciences
Department of Economics
48170 Kötekli, Mugla
Turkey
E-mail: [email protected]
OZAN BAHAR
Mugla University
Faculty of Economics and Administrative Sciences
Department of Economics
48170 Kötekli, Mugla
Turkey
E-mail: [email protected]
ABSTRACT
Tourism is one of the fastest growing sectors of the world economy. Tourism development may promote
economic growth both directly and indirectly, first by stimulating the growth of other sectors and second by
increasing domestic incomes and effective demand. The commonly accepted argument on the contribution
of tourism in economic growth needs to be verified empirically as well. This paper empirically investigates
whether the tourism led-growth hypothesis holds for the Mediterranean countries for the period of 19872002. A panel data approach is utilized and coefficient estimates are obtained by using fixed effect and
random effect models. As a result, the hypothesis that tourism is conducive to economic growth is verified
based on the regression results. On the whole, the empirical findings reveal that traditional factors (capital
and labor) as well as a tourism related factor contribute to economic growth for the Mediterranean countries under focus.
Key words: Economic growth, Panel data approach, Mediterranean countries.
Ummuhan Gökovalı is a faculty member in the Faculty of Business Administration and Economics, Mugla University, Turkey. She obtained her undergraduate degree in Economics from Ankara University, Turkey (1992). She
holds a Masters degree in Economics from Oklohoma State University, USA (1996) and a PhD degree from METU,
Turkey (2003). She is specialised on IPRs, economics of innovation, and economic growth/development.
Ozan Bahar is a faculty member in the Faculty of Business Administration and Economics, Mugla University, Turkey. He obtained his undergraduate degree from the Military Academy (1992). He holds both Masters (2000) and
PhD (2005) degrees in Economics from Mugla University. His area of interest includes international economics,
regional development, tourism economics, and competitiveness.
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Contribution of Tourism to Economic Growth: A Panel Data Approach
INTRODUCTION
Contemporary growth of tourism is the gradual consequence of the increase
of wealth in societies and the greater availability of goods and services that
were once considered to be the luxury. Tourism activities that used to be limited to those who are rich and have plenty of spare time, now have become a
way of life, and a consumption habit for many people in both the developed
and the developing world. Tourism is regarded as a leading sector for the 21st
century (Giles and Perry 1998) due to its significant share in the world economy. Moreover, according to the World Tourism Organization (WTO), the
tourism sector is the largest sector in the world in terms of income generation
and employment creation (Lundberg, Stavenga and Krishnamoorthy 1995).
In 2006, tourism sector is expected to contribute 10.3% to GDP and to generate
11.8% of total exports (The World Travel and Tourism Council- WTTC 2006).
Tourism sector employment is estimated at 234,305,000 jobs in 2006 accounting 8.7% of total employment (WTTC 2006).
The continuous growth of international tourism, declined between 2002
and 2003 by 1.7% to 691 million people and 523 billion dollar in 2003. Kester
(2004) puts forth three reasons for this decline. These are, the Iraq war that
took place in 2003; the SARS illness that appeared in Asia; and overall degeneration in the world economies experienced in the recent years. Nevertheless,
the growth of the tourism sector in the last few decades is beyond doubt, considering that the number of tourists over the world was 25.3 million in 1950,
and has increased 2631% in 53 years (approximately 27 times). Economically,
such massive growth is a major objective for both developed and developing
countries. Most importantly, tourism sector contributes to national income,
increases employment, ensures more egalitarian income distribution (Marcouiller, Kim and Deller 2004), has a positive effect on balance of payments,
improves technology and knowledge transfers, encourages foreign investment, acts as a catalyst for economic development, and contributes to peace
through cultural interaction (Han and Fang 1997; Göymen 2000).
Table 1 presents tourism receipts, the number of tourist arrivals and the rate
of economic growth for the Mediterranean countries as well as the percentage
share with respect to world tourism activities. The Mediterranean area serves
34.3% of world tourists and obtains 32.4% of current world tourism receipts.
The number of tourists visiting the area was 237.1 million in 2003. This is an
increase of 81% compared to that in 1987. Tourism receipts reached 169.9 billion dollars with a significant increase of 224% since 1987. In 2003, the Mediterranean area was second in a�racting tourists a�er Europe, which received
57.7% of tourist movements (WTO 2004; 2005). Similarly, the Mediterranean
area holds the biggest bed capacity in the world a�er Europe and the USA,
with a share of 25% (Ekin Yazım Grubu 2003) . Although, there is no general
trend in growth rates, the growth rate of 9 countries out of 15 declined in the
year of 2003 compared to that of 1987. While the growth rate of 5 countries
increased for the same period.
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Table 1. Tourism receipts and tourist arrivals for mediterranean countries
Countries
Tourism Receipts (Billion $)
Tourist Arrivals (Billion)
1987
1990
1995
2000
2003
Albania
-
0,070
0,070
0,389
Algeria
0,100
0,064
0,032
0,096
Croatia
1,668
2,774
1,511
Cyprus
0,666
1,258
1,586
1,994
Egypt
France
Gibraltar
11,870 20,185
1987
1990
1995
2000
2003 1987 2003
0,522
-
0,030
0,040
0,032
0,041
-8
6
0,161
0,778
1,137
0,520
0,866
1,166
-1
7
2,758
6,376
8,907
7,880
1,485
5,831
7,409
-
-
2,020
2,134
2,243
0,949
1,561
2,100
2,686
2,303
7
4
2,950
4,657
4,704
1,671
2,411
2,871
5,116
5,746
3
3
31,300 30,981 37,038 36,974 52,497 60,033 77,190 75,048
3
0
-
-
-
Greece
2,268
2,587
Israel
1,342
1,382
Italy
12,174 20,016
GDP Growth
(annual %)
-
-
0,123
0,132
-
-
-
4,180
9,262 10,842
7,564
8,873 10,130 13,096 13,969
-2
4
3,490
4,571
1,379
1,063
1,063
7
1
30,400 27,493 31,222 25,749 26,679 31,052 41,181 39,604
3
0
2,379
2,215
2,417
Libya
0,003
0,006
0,004
0,097
0,079
0,097
0,096
0,056
0,174
0,142
-
-
Malta
0,327
0,495
0,818
0,754
0,856
0,746
0,872
1,116
1,216
1,127
4
-2
Monaco
-
-
-
-
-
0,214
0,245
0,233
0,300
0,235
-
-
Morocco
0,936
1,259
1,470
2,284
3,369
2,248
4,024
2,602
4,240
4,552
-3
5
2,145
3,555
5,650
6,027
7,886
6,102
8,020
9,511 12,097 11,707
6
-1
27,500 33,833 45,967 32,900 37,441 34,920 47,898 51,830
6
2
Portugal
Spain
14,760 18,593
Syrian
0,204
0,300
1,338
1,082
1,147
0,493
0,562
0,815
1,416
2,788
2
3
Tunisia
0,672
0,953
1,840
1,977
1,935
1,875
3,204
4,120
5,058
5,114
7
6
Turkey
1,721
3,308
4,957
7,636 13,203
2,468
4,799
7,083
9,586 13,341
9
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Mediterranean 52,4
78,7
119,5
136,0
169,9
131,2
161,5
170,9
230,4
237,1
-
World
172
269
401
475
523
360
451
564
686
691
-
Share (%)
30.4
29.2
29.8
28.6
32.4
36.4
35.8
30.3
33.5
34.3
-
Source: WTO and WDI (various issues)
Despite the fact that the tourism industry plays a crucial role in the world
economy, applied economists have given li�le a�ention to the empirical investigation of tourism’s contribution to economic growth. This study focuses
on the Mediterranean countries and investigates whether tourism has any
effect on economic growth in these countries. In this regard, the major contribution of this paper is to utilize a panel data approach to investigate whether
tourism contributes to economic growth for the Mediterranean countries. For
this purpose, this study has established a role for tourism alongside traditional factors such as capital and labor. The second section provides a brief
literature review on the relation between tourism and economic growth. The
model and the data with the estimation techniques and estimation results are
discussed in the third section. The fourth section is reserved for a number of
concluding remarks.
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Contribution of Tourism to Economic Growth: A Panel Data Approach
LITERATURE REVIEW
Export-led growth studies will be informative for the assessment of the effects of tourism on economic growth. Export-oriented growth implies that an
expansion in the volume of export increases the foreign currency inflow, thus
generating an increase in the national income. In other words, real GNP increases as a result of increasing external demand for domestic goods and services depending on the amount of increase in exports. An expansion in exports
has positive effect on the economy through various channels, among which
are: gains from scale economies and positive externalities; lessening of foreign
exchange constraint thus facilitating imports of intermediary goods; enhancement of the competitiveness of domestic firms; stimulation of research and
development and of investment in new technologies (McKinnon 1964; Balassa
1978; Krueger, Larry and Monson 1981; Thirlwall 2000). Within this framework, numerous studies in the literature examine the causal relationship between exports and economic growth (e.g., Feder 1983; Ram 1985; Ram 1987;
Ukpolo 1994; Ghatak, Milner and Utkulu 1995; Eusufzai 1998; Shan and Sun
1998; Al-Yousif 1999; Bernard and Jensen 1999). Though the findings of these
studies vary, by and large, they demonstrated that exports have a positive
impact on economic growth, that is an improvement or expansion in exports
leads to a proportional increase in economic growth.
According to this line of thinking, if we see tourism development as an integral part of overall economic development, the relationship between tourism
exports and economic growth will be an indicator of the positive effect of tourism on economic growth (Vanegas and Croes 2003; Croes 2006). As it stands,
exports provide an external monetary resource for the economy of a country,
therefore, the revenue obtained from foreign tourists can be perceived as an
export of countries (Lundberg, Stavenga and Krishnamoorthy 1995). Consequently, countries with rich natural, historical, and cultural a�ractions would
use the tourism industry to acquire foreign currency, which in turn provides
significant support for industrialization of the country. Therefore, it is considered that tourism will contribute positively to economic growth, in line
with the hypothesis of export-oriented economic growth (Lee and Kwon 1995;
Sinclair 1998; Lim and McAleer 2000; Sharpley 2002; Mansfeld and Winckler
2004). Furthermore, besides the direct income effect, tourism sector generates
multiplier effects and contributes to the development of other sectors in the
country, such as construction, transportation, textiles, agriculture, and fishery
(Crompton, Lee and Shuster 2001; Tyrrell and Jonhston 2001).
Despite the rising importance of the tourism sector all over the world,
tourism development in relation to economic growth has not been investigated much in the literature. A few existing studies on the issue of tourism’s
contribution to economic growth provide contradictory findings. Copeland
(1991) argues that the tourism sector is one of the most important sources of
economic growth and development for many countries. In his general equilibrium international trade model, the increase in the number of foreign visitors can enhance the welfare of the country, if the price of non-tradable goods
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and services increases in an economy without taxes, foreign ownership, and
distortions (Copeland 1991). Hazari and Sgro (1995) investigate the relationship between growth and tourism, capital accumulation, consumption per
capita, and terms of trade. Their findings reveal that tourism contributes to
the long-term growth rate, especially for small countries. While many theories emphasize the importance of tourism for economic growth, there are also
contrary arguments. Hazari and Ng (1993) suggest that tourism can decrease
economic welfare and have a negative effect on economic growth under monopolistic circumstances. Nowak et al. (2004) argue that under certain conditions a ‘tourist boom’ can lead to a decrease in welfare and manufacturing
output and thereby ‘immiserize’ the residents of a country.
Although there is contradictory theoretical evidence about the positive impact of tourism on economic development and growth, this is not the case for
the empirical evidence. Most of the empirical studies found out that tourism
affects economic growth positively (see Table 2). The hypothesis that tourism
improves economic growth is verified for four Caribbean countries (Modeste
1995) and Mauritius (Durbarry 2004). Additional empirical evidence comes
from Spain. Empirical investigation confirms that there is a long-term relationship between tourism receipts and economic growth, and tourism affects
economic growth positively in Spain (Balaguer and Jorda 2002). Furthermore,
similar findings are observed for Turkey; Yıldırım and Öcal (2004) provide
evidence that in the long-term, tourism promotes economic growth in Turkey, but this relationship does not exist in the short term. Empirical findings
of Brau et al. (2003) also support the positive association hypothesis. For a
sample of 14 countries it is found that for developing countries the relation
holds to a significant extent. In a panel se�ing for Latin American countries,
the hypothesis is confirmed for low- and middle-income countries (Martin
et al., 2004). The economic effects of tourism were calculated for Fiji and the
results reveal that a 10% increase in the expenditure of tourists will lead to a
0.5% increase in GDP, 0.72% increase in real consumption, and 0.67% increase
in real national welfare (Narayan 2004).
However, there is also empirical evidence that contradicts the positive relationship between tourism and economic growth. The hypothesis that tourism
leads to economic development was rejected for Korea (Oh 2005). Campos
and Sequeira (2005) utilizing a panel technique found that in general there is
no significant contribution of tourism to economic growth within a sample of
509 countries.
MODEL AND DATA SET
There is an extended literature concerned with the estimation of growth models. Although there is no single growth model to utilize, most of the models
include investment shares, labor force, and human capital as explanatory variables . Labor force is one of the main determinants of growth rate of countries
producing output. Similarly, capital formation is another major force behind
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Study
Data Set
Dependent
Variable
Technique
Independent
Variables
Martin, Morales
and Scarpa
(2004)
Time series
1985-98 for 21
Latin American
countries
GDP per capita
Panel data
Oh (2005)
Time series
1975-2001 for
Korean
Real GDP
ADF tests for
cointegration,
F-test for
Granger
causality in
VAR model
Real aggregate
tourism receipts
Rejection of the
hypothesis
Durbarry
(2004)
Time series
1970-1999 for
Mauritius
Real GDP
OLS
Physical capital,
human capital,
real tourism
receipts per
tourist and real
export
Support for the
hypothesis
Balaguer and
Jorda
Time series
1975-97 for
Spain
Real gross
domestic
product
ADF tests for
cointegration,
F-test for
Granger
causality in
VAR model
International
tourism earnings
and real effective
exchange
Support for the
hypothesis
Campos and
Sequeira
(2005)
Time series
1980-99 for
509
observations
Growth rate of
per capita GDP
Panel data
Tourist arrivals,
tourism returns
(%) and tourism
returns (USD)
Rejection of the
hypothesis
Modeste
(1995)
Time series
and crosssection 198192 and 197592, 4
Caribbean
countries
Growth in per
capita GDP
OLS with
dummy
variables
(LSDV)
Growth in tourism
output per head
Support for the
hypothesis
Brau, Lanza
and Pigliaru
(2003)
Time series
1980-1995 for
14 small
countries within
a sample of
143 countries
Average annual
real per capita
GDP growth
OLS crosscountry
Per capita GDP
1980, share of
trade in GDP
1980-95,
standard
deviation of
growth rates
1980-95 and
average share of
tourism receipts
in GDP 1980-95
Support for the
hypothesis
Yıldırım and
Öcal (2004)
Time series
1962-2002 for
Turkey
GNP
VAR model
Real tourism
revenues, real
savings to proxy
for investment
and labor force
Support for the
hypothesis
Rate of growth of
tourists per
capita, gross
domestic
investment, public
spending on
education,
Contribution of Tourism to Economic Growth: A Panel
Data Approach
general
government
Table 2. A selection of empirical studies on the tourism-led growthconsumption
hypothesis
(2002)
Conclusion
Support for the
hypothesis
Source: Compiled from Authors
economic growth and investment towards capital formation promotes economic growth as well. Capital formation can be distinguished into two broad
categories; physical capital and human capital. In addition to investment
in physical capital, investment in human capital contributes to economic
growth. Most importantly, a well developed labor force with educational attainment and health facilities is able to produce more for a given resource base
(Lucas 1988; Romer 1990; Barro 1991, 1995; Benhabib and Spiegel 1994). Our
model includes these ‘core’ variables, as well as a proxy for a tourism-related
variable to test the hypothesis that tourism contributes to economic growth
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for Mediterranean countries. The model to be estimated includes gross fixed
capital formation as a percentage of GDP (GFCFGDP), tourism receipts as a
percentage of exports (TOUEX), and the growth of the labor force (GLF) as
explanatory variables for the growth rate of GDP (GGDP). All data comes
from the World Bank (WDI, 2005) except for the tourism receipts data, which
come from the World Tourism Organization. The data set is a panel made up
of 13 Mediterranean countries and 16 years beginning from 1987 to 2002. The
econometric model to be estimated is,
GGDP= ß0 +ß1 (GFCFGDP) + ß2 (TOUEX) + ß3 (GLF) + u
Estimation Techniques
A panel estimation technique is used when the data set combines both time
series and cross sections . The main advantage of a panel data set over a cross
section is that it permits greater flexibility in modeling differences in behavior across observation units (Greene 2000: 559-60)- in this case, countries. The
framework is,
yit= αi + β’xit+ εit
(1)
In equation (1), αi is an individual effect which is constant over time t (t
=1987,…, 2002) and specific to the cross-sectional unit i (i =1.., 13). There are
K regressors in xit, excluding the constant term, with ?it as the error term. As
it stands, equation 1 is a classical regression model. There are two basic approaches to generalize this model. These are the fixed-effect and the randomeffect approaches. In the first case, ?i is taken as a group of specific constant
terms in the regression model, while in the la�er case, ?i is treated as a group
specific disturbance.
The fixed effect model assumes that differences across units can be captured
in as differences in the constant term. Let yi and Xi be the T observations for
the unit i, and let εi be an associated Tx1 vector of disturbances. Hence, the following equation is estimated for the fixed effect model;
yit= αi + β’xit+ εit
(2)
?i and ? are parameters to be estimated. On the other hand, the random effects model can be formulated as:
yit= α + β’xit+ ui + εit
(3)
In equation (3), there are K regressors in addition to the constant term. ui is
the random disturbance characterizing observation i and is constant through
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time. In random effects specification, it is assumed that individual effects are
uncorrelated with the other regressors,
E (Xu) =0.
This hypothesis is the basis for the Hausman test, which tests random versus fixed effects. The Hausman test is a test of choice between fixed and random effect models under the hypothesis of no correlation between individual
effects and the regressors. If the hypothesis is rejected, then the fixed effect
estimator is more efficient.
The fixed effects model is the appropriate specification if the focus is on a
specific set of units; whereas the random effects model is a more appropriate
specification if the focus is on n number of units that are randomly drawn
from a large population (Baltagi 1995).
Estimation Results
Table 3 shows regressions for growth rates of GDP. Since heteroscedasticity
could be an important problem across countries, the standard errors for the
coefficients are based on a heteroscedacticity-consistent covariance matrix.
The result for the pooled ordinary least squares (OLS) regression is reported
for comparison purposes with respect to fixed (FE) and random effects (RE)
models. In all three estimations, the F test confirms that coefficients are jointly
different from zero and significant. The RE model is selected by the Hausman
test over the FE model. Estimation results indicate that there are significant
first-order auto-correlations in the FE and RE models.
Since auto-correlation may be serious problem, we corrected for auto-correlation and the corrected estimation results are given in Table 4. Despite the
auto-correlation in estimations reported in Table 3, the resulting changes in
the parameter estimates and standard errors are quite modest when the autocorrelation is corrected (Table 4). The Hausman test again favors RE over FE.
Furthermore, significant growth differences were not observed across the different periods that are not accounted for by capital, labor and tourism variables. Hence, regressions that include time effects are not reported for space
considerations.
According to the estimation results in Table 4, all estimates have the expected sign, and coefficients are jointly and significantly different from zero. Since
the Hausman test indicates the selection of a random effect model, only RE
estimation results are discussed. RE estimation results indicate that proxies
for labor, capital, and tourism affect the economic growth rate positively for
the period between 1987 and 2002, for the selected Mediterranean countries.
Moreover, even though there is evidence for auto-correlation; there is not
much difference between the value of the coefficients of the results of FE and
RE. While a 1% increase in investment share of GDP increases the growth rate
by around 13%, a 1 point increase in the growth of the labor force increases
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Table 3. Estimation Results
Variables
OLS Levels
Fixed Effects
Random Effects
GFCFGDP
0.129
(0.063)**
0.21
(0.078)**
0.149
(0.066)**
GLF
0.328
(0.169)*
0.631
(0.5)
0.34
(0.2)*
TOUEX
0.066
(0.03)**
0.083
(0.062)
0.065
(0.034)*
F Tests
5.7 (3, 204)**
2.36 (15, 192)**
2.361 (15, 192)**
Hausman test
3.18
AR(1)
-2.646**
-3.792**
-3.021**
AR(2)
2.479**
1.606
2.211
Dependent variable: Growth rate of GDP.
Notes:
(1) Figures in italics under the coefficient estimates are heteroscedasticity consistent standard
errors. Figures in parenthesis are degrees of freedom. Asterisks * and ** indicate statistical
significance at the 10% and 5% levels, respectively.
(2) AR(1) and AR(2) are tests for first-order and second-order serial correlations, asymptotically
N (0,1).
Table 4. Auto-correlation corrected estimation results
Variables
OLS Levels
Fixed Effects
Random Effects
GFCFGDP
0.124
(0.064)*
0.214
(0.079)**
0.132
(0.065)**
GLF
0.373
(0.171)**
0.735
(0.522)
0.377
(0.179)**
0.082
0.15
0.082
(0.032)**
(0.072)**
(0.033)**
6.78 (3, 191)**
2.47 (15, 179)**
2.472 (15, 179)**
TOUEX
F Tests
Hausman test
5.54
Dependent variable: Growth rate of GDP.
Notes:
Figures in italics under the coefficient estimates are heteroscedasticity consistent standard errors.
Figures in parenthesis are degrees of freedom. Asterisks * and ** indicate statistical significance at
the 10% and 5% levels, respectively.
1) In classification of Mediterranean destination some European countries are included as well
like France, Italy, Spain, Portugal and Greece. WTO (2005:96) makes the comparisons between
these two regions despite the fact that some countries are counted in both regions. So it should be
kept in mind that these two regions share some countries while making comparisons.
2) Unfortunately there is no available time series data on human capital for Mediterranean countries, hence we were not able to include human capital in our regression.
3) Countries included in the regression are Algeria, Egypt, France, Greece, Israel, Italy, Malta, Morocco, Portugal, Spain, Syria, Tunisia, and Turkey. Croatia, Cyprus, Gibraltar, Libya and Monaco are
excluded from the analysis due to unavailability of the data on some of the core variables.
4) This part is mostly borrowed from Greene (2000)
5) We have used tourism receipts as a percentage of GDP as an alternative explanatory variable.
However, the coefficient on this variable is not significant. It is only significant at 14% level. Neither the sign nor the significance level of the coefficients on other explanatory variables change
when tourism receipts as a percentage of GDP is included.
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Contribution of Tourism to Economic Growth: A Panel Data Approach
the growth rate by around 0.4 point. When the share of tourism receipts as a
percentage of exports increases by 1%, the growth rate of GDP increases by
8% . The hypothesis that tourism affects income growth is therefore accepted
for Mediterranean countries for the period considered.
CONCLUSIONS AND IMPLICATIONS
The fact that tourism is one of the rapidly growing sectors of the world economy is beyond doubt. The development of the tourism sector not only increases economic growth directly, but also stimulates the growth of other sectors
through backward and forward linkages and increases domestic incomes and
effective demand. Since the tourism sector plays a major role in economies,
it is crucial to empirically verify the positive relation hypothesis as is commonly accepted. Verification of this hypothesis leads to very important policy
consequences. Once the positive relationship is verified, governments need
to become actively involved in fostering the tourism sector. Tourism can be
especially important for developing countries where foreign exchange earnings are a constraint on import of raw and investment goods for industrialization.
Drawing on the experience of the Mediterranean countries, the empirical
investigation of tourism’s contribution to growth for the period 1987-2002 indicates that traditional factors (capital and labor) as well as tourism-related
factors are conducive to economic growth. These findings are important due
to the scarcity of scholarly research that explains economic growth in terms
of traditional and tourism-related factors for the Mediterranean countries.
More specifically, acceptance of the positive relation hypothesis and acceptance of tourism-led growth have implications for formulating tourism based
development policies. As far as long-term and sustained growth is concerned,
in addition to investment in traditional factors, investment in tourism and
well-planned tourism operations are important to maximize tourism earnings. However, tourism related policies should be carefully designed so as to
operate with an infrastructure that is conducive to the tourism sector. Policy
makers should be careful in designing policies, especially in weighing up the
share of investment between tourism and other productive sectors. A highly
promoted tourism sector can lead to ‘immiserizing growth’ since tourism is a
highly volatile sector open to exposure by external factors and shocks, leaving
a country in poor economic conditions.
This study can be extended in several directions. First, in this paper, we are
unable to include a human capital variable in our regressions due to unavailability of data. Hence, a future research agenda involves more empirical investigation when data for human capital variable is available. Also, our study
is restricted to Mediterranean countries, thus future research could focus on
other tourism-specialized countries, so that regional comparison could be
done in terms of to what extent tourism contribute to growth.
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Ummuhan Gökoval - Ozan Bahar
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Anatolia: An International Journal of Tourism and Hospitality Research
Ummuhan Gökoval - Ozan Bahar
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Submi�ed : 05 January 2006
Resubmi�ed : 06 April 2006
Resubmi�ed : 24 April 2006
Accepted : 02 May 2006
Refereed anonymously
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