Measuring Impacts of International Tourism Development on Economic Development: The Case of ASEAN Countries
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Measuring Impacts of International Tourism Development
on Economic Development: The Case of ASEAN Countries
HUỲNH TRƯỜNG HUY*, NGUYỄN PHÚ SON**, NGÔ MỸ TRÂN* &VÕ HỒNG PHƯỢNG*
ABSTRACT
The relationship between tourism development and economic development has been long determined
and measured. This paper primarily aims to measure this relationship in ASEAN countries in the 2001-
2009 period. The result indicates that tourism development has a positive effect on economic
development, specifically increasing per capita income. Countries with high urbanization levels show
even stronger impacts of tourism on per capita income. The structural changes in ASEAN economies to
industry and services has not only helped attain high economic growth, but also contributed to
improving personal income.
Keywords: international tourism development, economy, per capita income
1. INTRODUCTION
Economic benefits are usually considered as one of the main motivations for governments of
ASEAN countries (both developed and developing) to build development strategies for international
tourism over the past decades. The importance of international tourism development to economic
development was determined long ago (Ivanov & Webster, 2007; Lee & Chang, 2008; Sequeira &
Maçãs, 2008). In fact, receipts from this sector not only contribute greatly to the GDP of a country, but
also help improve the lives and income of local residents who are engaged in tourism activities and
products (Brau et al., 2007).
Although the world economy was greatly affected by recent economic crises which led to
unemployment, decreased income, and increased prices, statistics of international tourism showed an
upward trend. According to the UNWTO, international tourist arrivals were 935 million in 2010, up
6.7% from 2009 and yielded receipts of US$ 920 billion, up 7.5%. More details on the development
trend of international tourism are provided in Table 1.
* Master of Economics, Cần Thơ University
** Doctor of Philosophy, Cần Thơ University
12 | Huỳnh Trường Huy
Measuring Impacts of International Tourism Development
Table 1: Facts of World Tourism in 2000-2010
Indicator
Tourist arrival
Receipt
Unit
Million
2000
682
2005
810
2006
856
2007
914
2008
930
2009
894
2010
935
US$ billion
560
829
899
1,038
1,144
1,029
1,070
Growth rate
- Tourist
%
%
%
-
-
-
5.0
7.1
3.6
5.3
7.8
4.0
6.4
1.7
9.3
1.5
-4.0
6.7
3.8
4.2
- Receipt
13.4
3.9
-12.1
-1.9
- World economy
Source: UNWTO and WB
The world tourism regained recovery from the economic crises of 2008 and 2009, and attained such a
high growth rate as that of the world economy. The high tourism growth in 2010 can be attributed to
global events such as World Cup 2010 held in South Africa and Winter Olympics in Canada. As the
UNWTO predicted, the global tourism would maintain a growth rate of at 4-5% in 2011 with the Asia-
Pacific and the Middle East at 7-9% and 7-10% respectively.
The Asia-Pacific is regarded as one of the most visited region (second only to Europe) during the
past two decades. The UNWTO statistics show that the region was leading the world in international
tourist arrivals, with a growth of 13% in 2010. As can be seen from Figure 1, international tourist
arrivals in developing countries were rising while an opposite trend was found in Europe and America.
50,4
21,8
16,1
6,4
5,2
2010
2000
1990
Europe
Asia- Pacific
America
57,3
16,2
18,8
3,6
4,1
A
fr
ic
a
Middle East
60,3
12,8
21,2
2,2
3,5
0%
20%
40%
60%
80%
100%
Figure 1: International Tourists to Developing Countries
Source: UNWTO, 2010 (http://www.worldbank.org/data)
Economic and international tourism development in Asian developing countries has attracted the
attention of economic researchers. The noticeable case of ASEAN countries has provided much
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important evidence of the contribution of international tourism to economic development as an
important sector of the economy (Chon, 2000; Hitchcock & King, 1993).
Hence, this paper focuses on providing estimated evidence of the impacts of international tourism on
economic development of ASEAN countries as well as presenting the current state of Vietnam.
The rest of the paper is presented in the following order: theory summaries and estimated evidence of
the connection between the tourism industry and economic development (Section 2); data sources,
estimated variables and estimation model for impacts of tourism on economic development (Section 3);
analysis and hypothesis tests of the estimation model (Section 4); and conclusions (Section 5).
2. INTERNATIONAL TOURISM DEVELOPMENT AND ECONOMIC DEVELOPMENT
a. Figures:
Attaining economic development by changing the economic structure was mentioned in classical
economic theory in the middle of the 20th century and was applied by developing countries several
decades ago. Specifically, it was the switch from traditional agricultural production to industrial
production and gradually to the modernization of and focus on development of services.
International tourism is considered as an important factor in development of services in particular
and economic development in general in most countries (Brau et al., 2007; Hampton, 1998; Kaplan &
Çelik, 2008; Lee & Chang, 2008). Table 1 indicates that there were 935 million international tourist
arrivals in 2010 which yielded over US$ 1,000 billion for visited countries. Receipts from international
tourists accounted for 6.42% of the aggregate export value and 1.75% of the world’s total GDP
(UNWTO, 2010).
In ASEAN countries, tourism figures are very impressive. International tourist arrivals in this region
rose from 36.9 million in 2000 to 65 million in 2009, making up 32.7% of Asia-Pacific’s total arrivals
and 6.7% of the world’s total arrivals (UNWTO, 2010). Typical examples of this include Thailand,
Singapore and Indonesia where tourism industries flourish and play an important part in economic
development. In terms of contribution to economic development, tourism ranks the first place in
Thailand’s economy, second place in the Philippines’ and third place in Singapore’s. Some other
countries with budding tourism like Cambodia, Vietnam and Laos have also achieved impressive
achievements in attracting international tourists. Specifically, Vietnam’s inbound tourist arrivals rose
from 187,000 in 1990 to 3.7 million in 2009 while this figure for Laos also increased from 173,000 to
1.2 million in 2009 (UNWTO, 2010).
Concerning Vietnam, its tourism development is reflected by the following indicators. First, FDI in
the tourism industry between 1988 and 2010 was worth US$19.7 billion, accounting for 9.3% of the
country’s total FDI (GSO, 2010). More than 400 investment projects in tourism were mainly involved
in hotels and restaurants, resorts, golf courses, amusement parks, and tourism services (Vietnamnews,
2010). Second, tourism receipts leapt from US$ 1.1 billion in 2001 to US$3.6 billion in 2009 with non-
public tourism businesses and FDI respectively making up 53.7% and 31.7% of the total receipts.
According the GSO (2010), tourists came to Vietnam for travel and sightseeing (59.8%) and for
business (19.8%). Third, tourism made a positive contribution to economic development with 16.6% of
14 | Huỳnh Trường Huy
Measuring Impacts of International Tourism Development
the GDP in 2009. Moreover, it also created 450,000 direct jobs and about one million indirect jobs
(GSO, 2010).
ASEAN’s tourism development is attributed to the following factors. First, the cultural differences
and tourism products (e.g. ecotourism) are the main attractions to international tourists. Second,
cooperation in and promotion of tourism development between ASEAN members contribute to each
country’s tourism development. Third, the emergence of several economies such as Vietnam and
Cambodia has attracted global investment. Finally, cultural and socioeconomic summits held in the
region, e.g. APEC and ASEM, are also an effective way of promoting ASEAN’s image to international
friends.
It is obvious that international tourism has brought development opportunities to the world economy
in general and ASEAN economies in particular. In a microeconomic view, tourism has helped improve
the balance of payments and attract FDI to the economy. It also plays a positive role in stimulating
development of other industries like air and road transport, construction, and traditional trades (tourism
products). In a macroeconomic view, tourism creates employment and income for local residents.
b. Estimation Method:
The importance of tourism toward economic development has been long confirmed and has drawn
the attention of economists. Therefore, methods for estimating the relationship between the two factors
are diverse, depending on available data. In general, research data for this subject are usually in form of
a time series of independently observed identities (country, region, province, etc.) and are called panel
data. Usually, the method for relationship estimation is presented as a econometric model which allows
estimated coefficients to change according to observed identities over time (Cameron, 2005):
Y it it Xit u
it , i = 1,...,N and t = 1,…,T (1)
it
where Yit is a dependent variable,
Xit is a vector composed of explanatory factors,
uit is the composite error,
i is an index of independently observed identities (country, province, company, etc.)
t is an index of time series
Based on the general econometric model presented in equation (1), the impacts of tourism on
economic development are often estimated in various contexts. For instance, Kaplan & Çelik (2008),
Durbarry (2004) saw the GDP factor in form of logarithm as a dependent variable in their estimation
models. Meanwhile, in another research on the rapid development of countries with emerging tourism,
Brau et al. (2007) measured the effects of tourism on the growth rate of per capita income as a
dependent variable. More recently, Sequeira & Maçãs (2008) and Martin et al. (2004) used per capita
income (in logarithm) to measure changes of tourism-related factors like receipt share in the GDP and
international tourist share in the total population.
3. DATA AND ECONOMETRIC MODEL
a. Data and Description of Variables:
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Data used in this research are mainly collected from the UNWTO statistics including information
related to macroeconomic and tourism indicators of eight ASEAN countries (with Brunei and Myanmar
being absent due to insufficient data) in the 2001-2009 period. Hence, the data source is described as a
panel with i=8 and t=9.
Two major indicators employed to evaluate a country’s tourism are international tourist arrivals (A)
and receipts (R) from international tourists in a particular year. In general, the latter is used more often
and calculated in form of a proportion in GDP (RGDP) to show specialization level of tourism in an
economy (Eugenio-Martín et al., 2004; and Sequeira & Maçãs, 2008). An important indicator of
economic development is per capita income (pGDP) and usually selected as a dependent variable to
assess the impacts of tourism on economic development (Eugenio-Martín et al., 2004; and Sequeira &
Maçãs, 2008).
Besides tourism specialization, other macroeconomic indicators, namely economic openness and
proportion of urban residents, also contribute significantly to per capita income. Specifically, economic
openness (O) is determined by the ratio of total export value to GDP and implies free trade of a country
(O 0). If O = 0, then the economy is closed. This ratio signifies that free trade will engage foreign
investors in exploring investment opportunities and lead to travel between countries.
According to Niên giám thống kê (Statistical Yearbook) 2010, about 20% of international tourists
came to Vietnam for business. In addition, this indicator is an important part of GDP and directly affects
per capita income. Finally, the proportion of urban residents (U) is considered as an important indicator
that is in direct proportion to per capita income (Kojima, 1996).
Table 2 : Description of Variables
Standard
Indicator
Unit
Mean
Min.
Max
deviation
9,798
1.38
pGDP
RGDP
O
USD
%
5,360
2.43
306
0.64
45.5
17.5
39,950
4.95
%
154.6
48.0
106.1
25.8
438.1
100.0
U
%
Source: Calculations based on UNWTO data.
Table 2 shows that the dependent variable pGDP has a standard deviation greater than its mean
value, implying a lack of normal distribution. It is thus necessary to convert it before estimation to
produce a near-normal distribution and better results (Chatterjee & Hadi, 2006). There are usually
different conversion methods depending on the distribution shape of the variable (left or right-tilted).
Based on the H0 hypothesis on normal distribution described in Appendix A, the testing for normal
distribution of the converted dependent variable shows that it can be converted in one of the three forms:
log(pGDP), 1/ (pGDP) , and 1/(pGDP).
b. Estimation Model:
Based on equation (1) and given indicators, the estimation model for impacts of tourism on economic
development is presented below:
16 | Huỳnh Trường Huy
Measuring Impacts of International Tourism Development
pGDP it 1it RGDP 2itO 3itUit u
it (4)
it
it
it
According to the theory of the estimation model with panel data, there are two methods for
evaluating equation (4), namely fixed effects (FE) model and random effects (RE) model (Gujarati,
2004).
- In the FE model, the slope ( it ) for each country (i) is allowed to change, but is fixed in time (t).
Thus, equation (4) is re-presented as follows:
8
pGDP N RGDP O U u
it (5)
it
1
k
k
1it
it
2it it
3it it
k2
where Nk stands for dummy variables corresponding to each country (i), and uit = λt + μi is called a
time-affected error (λt) and varies among countries (μi). With the use of dummy variable, equation (5) is
called the least squares dummy variable (LSDV) model.
- In the RE model, each country is supposed to be randomly observed. Therefore, the slope of each
country (i) includes random errors:
i1 1 i
(6) where is the mean value of the slope and εi is an error.
1
Substituting equation (6) for general equation (4) results in the following RE model:
pGDP 1 1it RGDP 2itOit 3itUit uit i (7)
it
it
or
pGDP 1 1it RGDP 2itOit 3itUit wit (8)
it
it
Last, the Hausman test is employed to determine whether the FE model or RE model is more
appropriate for the estimation (Cameron, 2005) with the null hypothesis that there is no correlation
between non-observed factors and explanatory factors in the models [Cov(εi, Xit) = 0].
4. RESULTS AND DISCUSSIONS
Most of the estimation coefficients of both aforementioned models can show a statistical and
theoretical significance. Specifically, tourism development greatly contributes to economic development
of ASEAN countries and increases income of their residents. Additionally, the positive relationship
between free trade and per capita income enhancement is also identified. Like the research results by
Kojima (1996), the estimation results in this research point out that the higher the proportion of city
dwellers, the higher the income of residents of ASEAN countries.
Table 3: Estimation Results
Model
Fixed Effect
Standard error
Random Effect
Coefficient Standard error
0.216***
Coefficient
0.123***
RGDP
O
0.035
0.044
(3.54)
(4.90)
0.232*
0.503***
0.001
0.001
UEH-JED No.211 March 2012 | 17
(5.07)
0.124***
(16.21)
0.478
(1.24)
0.880
2.621
0.116
0.000
(1.90)
U
0.007
0.385
0.084***
(10.81)
2.598***
(5.47)
0.844
0.008
0.475
Constant
R2
u
ε
0.608
0.116
Prob>F. ( 2
)
0.000
***,* statistical significance level with p < 0.01 and 0.1
On the whole, all coefficients of both models are statistically significant and similar in the impacts of
improving per capita income of ASEAN residents. As mentioned earlier, it is necessary to select a more
suitable model. According to the Hausman test result, Chi2 has a value of 362.86 at the statistical
significance level of 0.000 (Prob>Chi2). This means that the H0 hypothesis is rejected, leading to the
conclusion that the FE model is more suitable.
Empirically, the explanatory factors in the model show correlation with non-observed variables and
between themselves. In other words, the RE model seldom fulfills conditions for measurement of
economic indicators (Gujarati, 2004). In this research, the cross-testing of factors indicates correlation
between explanatory factors to some extent (see Appendix B). Hence, Table 4 is to present the
coefficients of impacts of tourism on per capita income, corresponding to two indicators, namely the
proportion of urban residents and economic openness.
Table 4: Estimation Coefficients of RGDP in FE Model
Coefficient
Percentage of Urban Residents (%)
Economic Openness
20
40
60
80
100
0.329
3.24
≤1
>1
RGDP
0.061
1.61
0.251
3.61
0.130
0.78
0.037
0.74
0.126
2.69
0.172
3.64
Error
Value (p)
0.354
0.001
0.472
0.471
0.018
0.015
0.000
From the data of Table 4, countries with a percentage of urban residents ranging from between 20%
and 40% such as Laos (27.5%), Thailand (32.4%) and Vietnam (26.5%) to over 80% like Singapore
(100%) show positive effects of tourism on per capita income. As analyzed earlier, Thailand and
Singapore have long developed tourism industries while Laos and Vietnam have recently been
considered as attractive destinations for international tourists due to their new tourism forms and
political stability.
18 | Huỳnh Trường Huy
Measuring Impacts of International Tourism Development
Furthermore, trade liberalization has increased the contributions of tourism to economic development
by attracting foreign investment to services including tourism. Trade liberalization also stimulates travel
of investors and creates favorable conditions for tourism to develop along with economic development.
5. FORECASTS AND POLICY RECOMMENDATIONS
Forecasts in this research has an empirical significance to policy recommendations connected with
the relationship between enhancement of living standards and tourism development as well as economic
openness and urbanization in developing countries. For example, more tourism receipts can increase
personal income, and so can trade liberalization and urbanization because the residents can have more
access to the labor market.
The data of 2001-2009 can help predict changes in the above-mentioned indicators in the 2010-2020
period (with the mean value belonging to 2015). Here are two basic prediction methods consistent with
characteristics of these indicators:
- The forecast of per capita income (pGDP) and trade liberalization (O) can be conducted with the
following formula:
pGDP pGDP (1 r )t
s
it
i0
i
- Urbanization and proportion of international tourism receipts in GDP only vary to the maximum of
100% (Vj = [0,100], j = U, RGDP). In other words, the variation is presented as a logistic function.
Here is the formula for the forecast of these indicators:
100
Vit
1 A.e.t
Parameters A and ρ can be worked out by solving the equation with the values of U and RGDP given
in the 2001-2009 period.
The forecast results are provided in Table 5.
Table 5: Changes Between Periods of 2010-2020 and 2001-2009 (%)
Country
pGDP
11.00
14.94
14.36
7.63
RGDP
3.89
O
U
Cambodia
Indonesia
Laos
0.89
-5.22
0.54
-2.12
-5.88
1.73
0.10
3.51
2.88
2.11
3.73
1.24
1.10
0.07
0.87
1.64
-4.39
2.40
Malaysia
Philippines
Singapore
Thailand
Vietnam
3.09
8.71
-2.71
0.36
7.36
9.86
2.59
13.19
6.54
UEH-JED No.211 March 2012 | 19
The per capita income indicator is predicted to rise by over 10% on average in 2010-2020. Vietnam
is expected to attain a growth of over 13% in per capita income. Noticeably, tourism receipts are
forecast to grow faster than trade liberalization and urbanization.
The forecast results are suitable for Vietnam situation where tourism is in process of development
with more and more artistic, cultural and natural attractions being recognized in the world and
preserved. This is important for international tourists to know of and choose the country as their
destination. Hence, the promotion and popularization of tourism not only enhance its development
potentials, but also increase personal income.
5. CONCLUSION
Contributions of tourism to economic development such as employment creation and income
improvement have long been recorded in many studies. In general, this research will hopefully provide a
closer look at the role of tourism development in economic development of ASEAN countries which
have witnessed impressive economic and tourism growth in recent years. Several major points of this
research are summarized as follows:
First, panel data are pretty appropriate for estimation of the relationship between tourism
development and economic growth. Specifically, the FE model with the correlation between explanatory
factors indicates the high practicality of the estimation.
Second, countries with an average proportion of urban residents show greater effects of tourism on
personal income because most of them have agriculture-dependent economies, hence a high proportion
of rural residents. As a result, economic changes toward industry and services as in Vietnam will
definitely promote tourism’s impacts on economic development in general and increase personal income
in particular.
In conclusion, the research results are empirical evidence that offers researchers and administrators
an overview on measuring impacts of macroeconomic factors like tourism and free trade on economic
development.
Appendices
Appendix A: Conversion and Testing of Hypotheses
Conversion
(pGDP)3
Chi2
55.8
47.8
24.5
7.2
P(Chi2)
0.000
0.000
0.000
0.028
0.018
0.024
0.000
0.000
(pGDP)2
(pGDP)1/2
log(pGDP)
1/(pGDP)
1/(pGDP)1/2
1/(pGDP)2
1/(pGDP)3
8.0
7.4
23.7
34.9
20 | Huỳnh Trường Huy
Measuring Impacts of International Tourism Development
Appendix B: Cross-testing of factors
Factor
Log(pGDP)
RGDP
O
U
Log(pGDP)
1
RGDP
0.421*
0.834*
0.883*
1
O
U
0.511*
1
0.160
0.743*
1
* statistical significance level with p < 0.01.
References
Brau, R., A. Lanza, & F. Pigliaru (2007), "How Fast Are Small Tourism Countries Growing? Evidence from the
Data for 1980-2Brau, R., A. Lanza, & F. Pigliaru (2007), "How Fast Are Small Tourism Countries Growing? Evidence
from the Data for 1980-2003," Tourism Economics, 13:603-614.
Cameron, A.C. (2005), Microeconometrics: Methods and Applications, Cambridge University Press.
Chatterjee, S. & A.S. Hadi (2006), Regression Analysis by Example, vol. 607, LibreDigital.
Chon, K.S. (2000), Tourism in Southeast Asia: A New Direction, Routledge.
Durbarry, R. (2004), "Tourism and Economic Growth: The Case of Mauritius," Tourism Economics, 10:389-401.
Eugenio-Martín, J.L., N.M. Morales, & R. Scarpa (2004), "Tourism and Economic Growth in Latin American
Countries: A Panel Data Approach," Fondazione Eni Enrico Mattei Working Paper Series, NOTA DI LAVORO 26.
GSO (2010), Niên giám thống kê 2010 (Statistical Yearbook 2010), Thống kê Publisher.
Gujarati, D.N. (2004), Basic Econometrics, New York: McGraw Hill.
Hampton, M.P. (1998), "Backpacker Tourism and Economic Development," Annals of Tourism Research, 25:639-
660.
Hitchcock, M. & V.T. King (1993), Tourism in South-east Asia, Psychology Press.
Ivanov, S. & C. Webster (2007), "Measuring the Impact of Tourism on Economic Growth," Tourism Economics
13:379-388.
Kaplan, M. & T. Çelik (2008), "The Impact of Tourism on Economic Performance: The Case of Turkey," The
International Journal of Applied Economics and Finance, 2:13-18.
Kojima, R. (1996), "Introduction: Population Migration and Urbanization in Developing Countries," The
Developing Economies, 34:349-369.
Lee, C.C. & C.P. Chang (2008), "Tourism Development and Economic Growth: A Closer Look at Panels," Tourism
Management, 29:180-192.
Sequeira, T.N. & N.P. Maçãs (2008), "Does Tourism Influence Economic Growth? A Dynamic Panel Data
Approach," Applied Economics, 40:2431-2441.
UNWTO (2010), "Compendium of Tourism Statistics and Data Files," in Yearbook of Tourism Statistics, World
Tourism Organization.
Vietnamnews (2010), "Vietnam Travel with Opportunities of ASEAN Tourism Investment."
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