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Bibliographic Note
ARDELEANU, Dorian.
What are the overall factors that influence the level
of tourism development?
, Uppsala 2021. 53 pp.
Degree Project. Uppsala University
Acknowledgments
This publication has been produced during my scholarship period at Uppsala
University, which is funded by the Swedish Institute. My master’s studies
in Sweden would have been impossible without their financial support. I am
especially grateful to my subject reader, Brian Danley, for his suggestions
and guidance during the writing process. I am also thankful to my professors
for the obtained knowledge and skills during the master’s studies at Uppsala
University, as well as to all amazing people that I had the pleasure to meet
on Gotland.
List of Figures
1
The positive relationship between GDP per capita and num-
ber of tourists . . . . . . . . . . . . . . . . . . . . . . . . . .
14
2
Correlation Matrix . . . . . . . . . . . . . . . . . . . . . . .
17
3
Emissions - Tourism relationship
. . . . . . . . . . . . . . .
23
4
Number of international arrivals . . . . . . . . . . . . . . . .
25
5
Regions
. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
26
List of Tables
1
VIF
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19
2
Overall Regression Results . . . . . . . . . . . . . . . . . . .
22
3
Regression Results. Developed European & Post-Soviet and
Post-Socialist . . . . . . . . . . . . . . . . . . . . . . . . . .
28
4
Regression Results. Africa & Latin America . . . . . . . . .
31
5
Regression Results. Small & Big Countries . . . . . . . . . .
36
6
List of countries included (1) . . . . . . . . . . . . . . . . . .
45
7
List of countries included (2) . . . . . . . . . . . . . . . . . .
46
Acronyms
BLUE
Best Linear Unbiased Estimator
DEA
Data Envelopment Analysis
FMOLS
Fully Modified Ordinary Least Squares
GDP
Gross Domestic Product
MLR
Multiple Linear Regression
SME
Small and Medium Businesses
UNWTO
United Nations World Trade Organization
VIF
Variance Inflation Factor
WEF
World Economic Forum
Contents
1
Introduction
1
2
Literature Review
3
3
Theory
9
4
Methodology
12
5
Data Processing
18
5.1
Fixed Effects
. . . . . . . . . . . . . . . . . . . . . . . . . .
18
5.2
MLR Assumptions . . . . . . . . . . . . . . . . . . . . . . .
19
6
Results
21
6.1
Effects by region
. . . . . . . . . . . . . . . . . . . . . . . .
26
6.1.1
Developed European Countries
. . . . . . . . . . . .
27
6.1.2
Post-Soviet and Post-Socialist Countries . . . . . . .
29
6.1.3
African Countries . . . . . . . . . . . . . . . . . . . .
30
6.1.4
Latin American countries . . . . . . . . . . . . . . . .
32
6.1.5
Small and Big Countries . . . . . . . . . . . . . . . .
33
7
Conclusion
38
Bibliography
40
Appendix
45
1
Introduction
During the last decades, the tourism sector has been constantly evolving and
expanding. As a result, it has become an important part of the economies
of many countries, creating many jobs and contributing substantially to
the states’ gross domestic product. The significance of tourism is therefore
doubtless. Developing this industry would bring a series of positive exter-
nalities, leading to a virtuous circle, in which more visitors contribute to the
economic development of a region, and a more advanced economy is expected
to bring a higher number of tourists through different indirect channels.
Thus, it is particularly interesting to find out what is the influence of dif-
ferent macroeconomic, social, demographic, and infrastructural factors over
the level of tourism development because it can give useful insights to the
policymakers. The purpose of this paper is to analyze the effect that some
factors have over the growth of tourism. More concretely, it investigates the
impact of the economic development, of the level of emissions, economic free-
dom, education, and intentional homicides. Initially, one would expect the
economic growth to have a positive impact over tourism development since
these two factors tend to be mutually beneficial for each other. The effect
of the emissions could be ambiguous because, on one hand, higher emissions
are worsening the ecological situation which is demotivating tourists to visit
the country. On the other hand, higher emissions are strongly related to
more flights and more cars used by travellers themselves. Economic freedom
is clearly expected to influence tourism growth in a positive way because
more open economies tend to benefit more from capital and labour mobility,
and they have a more developed transport and logistic infrastructure. The
latter is also more evolved in countries with better education - this is why
more years of schooling are expected to indirectly influence tourism growth
in a positive way. Last, the number of intentional homicides is a strong
indicator of safety issues, which are extremely unattractive for the majority
of tourists.
The study is based on a panel data that includes information regarding
130 countries over a time period of 20 years, between 1995 and 2015. A
big amount of cross-sectional data is necessary in order to give universally
applicable results, whereas a long time-series helps to see the evolution of
the outcomes over time. The results are obtained using a method called
1
fixed effects estimation. This model controls for the omitted variable bias
that appears when the unobserved heterogeneity is constant over different
time periods.
In the Literature Review chapter, studies with a similar topic of investi-
gation are discussed. Particular focus is made on the research that included
the same or similar independent variables in order to see the differences and
the analogies between papers. The next chapter is dedicated to theory that
is not directly related to this paper’s study topic, but is useful in explaining
the results. It includes a discussion of the relationship between tourism and
crime levels, the effect of education on businesses, Human Capital Theory,
the effect of economic freedom over the country’s economic development,
and the effect of the 2008-09 crisis. Chapter 4 represents an overview over
the data collection methods, including the sources used and the independent
variables included. Besides that, the correlation between regressors is dis-
cussed, as well as its potential effect over the results. The following chapter
presents the statistical methods used to process the collected dataset, and
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