Reviews in TourismTourism and economic growth: A review of empirical literature☆
Introduction
The importance of tourism receipts, and the analysis of their effects, has aroused the interest of an increasing number of economists. It is considered that tourism expenditure is an alternative form of export that can contribute to improving a country's balance of payments, favour employment and generate additional tax revenues (Archer, 1995, Belisle and Hoy, 1980, Davis et al., 1988, Durbarry, 2002, Khan et al., 1990, Uysal and Gitelson, 1994, West, 1993). In short, tourism receipts can favour a country's economic growth through their positive influence on the economy as a whole by way of spillovers and other externalities (Marin, 1992).
From an empirical perspective, Lanza and Pigliaru (2000) were the first to investigate the relationship between tourism and growth, when they observed that countries that were highly specialised in tourism shared two characteristics: they were small countries and their per capita average income grew rapidly. This initial idea gave rise later on to a large number of publications aiming to verify the tourist-led growth (TLG) hypothesis – i.e. the hypothesis according to which tourism generates economic growth – from an econometric perspective. This literature analyses whether there actually is a relationship between tourism and economic growth and the causality of this relationship. Thus, from the first attempt by Balaguer and Cantavella-Jordà (2002), which tested this hypothesis for the case of the Spanish economy between 1975 and 1997, an increasing number of articles with the same objective – although for different countries, using different methodologies and obtaining different results – have been published. In this paper, we undertake a review of the main studies published to the beginning of 2013, and classify them according to their methodology using a chronological criterion, because time, in our opinion, determines the methodological advances implemented in each of them.
With this aim, the paper is divided into seven main sections which follow. Section 2 provides a historical introduction to research in this field. Section 3 classifies and analyses the works that use time series econometric techniques to corroborate the TLG hypothesis. Section 4 classifies the studies that use panel data. Section 5 analyses papers which apply cross-sectional data. The discussion of the results is presented in Section 6. Finally, the main conclusions are offered in Section 7.
Section snippets
Historical introduction to tourism-led growth hypothesis
Tourism attracted relatively little attention in the academic literature on economic development until the twenty-first century. There are, however, some early studies which have focused explicitly on tourism's economic contribution. A study by Gray (1966), for example, provided per capita income elasticities of 5.13 for US demand for tourism in the rest of the world and 6.6 for Canadian demand. Other early studies focused explicitly on tourism's economic contribution to developing countries (
Time series analysis
Despite the existence of previous studies that analysed different economic effects of tourism, publications focused on the existence of a causal relationship between tourism and economic growth are relatively recent and have increased in number since 2002, as can be observed in Table 4 of the Appendix.
The first time-series analysis study on this subject was reported by Balaguer and Cantavella-Jordà (2002), although previously Ghali (1976) estimated, by using OLS (ordinary least square), that
Panel data analysis
Together with the above-mentioned studies, which basically analysed the causal relationship between growth and tourism activities, a series of papers have been published which examine the relationship between those two variables by using panel data econometric techniques, with the advantage of providing a larger data sample. Generally, these studies, which are noted in Table 5 of the Appendix, analyse the economic elements behind the relationship between the two variables from different
Cross-sectional analysis
To eliminate the effects of the economic cycle and of possible structural changes from the estimations made previously, some economists have used cross-sectional data to analyse the relationship between growth and tourism. Nevertheless, the use of this technique is questionable. All variables are measured at the same point in time, meaning that predetermination for example, as in the Granger causality test, cannot be tested. Herzer and Vollmer (2012) summarise a number of criticisms of these
Discussion
After reviewing the main studies devoted to the analysis of the relationship between tourism and economic growth, we can synthesise some ideas that aim to explain the sense of causality of this relationship and the factors on which it depends.
Table 1, Table 2, Table 3 reflect the strengths, weaknesses, conclusions and interesting issues observed and drawn from the different sections of this article. Table 1 shows that most of the studies are based on time series and referred to a single
Conclusions
This study provides a descriptive survey of the empirical evidence analysing the relationship between tourism and economic growth. From a sample of 87 studies, 55 pointed to a univocal relationship between tourism and economic growth, 16 identified a bi-univocal relationship, 9 indicated that the connection flowed from economic growth to tourism and, finally, 4 did not identify any relationship at all between them. Nevertheless, these empirical results are very sensitive to the selection of
Acknowledgements
The authors acknowledge financial support by SEJ 132. They also acknowledge the suggestions made by two anonymous reviewers and by Stephen J Page.
María P. Pablo-Romero, Ph.D. in Economics. Her main research interests are related to economic growth and energy.
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María P. Pablo-Romero, Ph.D. in Economics. Her main research interests are related to economic growth and energy.
Jose A. Molina-Toucedo, Associate Professor. His research focuses on tourism, the fashion industry and the economy of flamenco music and dance.
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Acknowledgements: The authors are grateful for the financial support received from the project SEJ-132 of the Andalusian Regional Government.
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