This paper studies the dynamics of economic growth and tourism evolution for 80 countries during the period 1995–۲۰۱۶٫ The variables representing economic and tourism growth are growth rates of per capita GDP and international tourist arrivals per inhabitant respectively. Using the concept of economic regime, the paper introduces a notion of distance between the dynamical paths of different countries. Then, a Minimal Spanning Tree and a Hierarchical Tree are constructed to detect groups of countries sharing similar performance. The two main clusters we find can be interpreted as two groups of countries with high and low performance in the tourism sector and are coherent with the business cycle. The evolution of such clusters shows three main stylized facts: certain countries move across clusters; the low performance cluster tends to span, while the high performance one tends to be (more) compact; the distance between the two groups increases in time.

Introduction

In this paper, the relationship between tourism and economic growth is explored. To this end, the study introduces an alternative non parametric methodology to the very well-known econometric tools commonly used in the empirical literature investigating tourism and economic growth. This methodology is used to study the dynamics of economic growth and tourism performance for 80 countries during the period 1995–۲۰۱۶٫ The fact that the methodology do not need to assume a particular model to study the relationship between the variables under study allows to understand the dynamic behaviour of the countries in the sample and to compare their performance. With this usage, the socalled tourism-led-growth-hypothesis (TLGH) can be seen in a different light and could call for a complete reformulation. In particular, our contribution to the TLGH literature includes the possibility of testing if different countries cold admit a similar model representing the dynamics in tourism and economic growth. In addition, this tool can be used when working with panel data to test the homogeneity of individuals in the panel. This central hypothesis of homogeneity of individuals is addressed by using clustering techniques that help to find homogeneous groups of countries with similar dynamics in tourism and economic growth. Then panel data can be correctly used for each cluster in the sample. The tourism sector is recognized to positively contribute to the economic growth process of a country through different channels, including the fact of course that it is a currency earner sector; that stimulates physical and human capital accumulation, and pushes (and uses) technology and innovation. At the same time, tourism promotes directly and indirectly other economic industries such as transportation, hospitality or retailing (see Mayer & Vogt, 2016). In particular, international tourism is a source of foreign currency that facilitates the acquisition of capital goods and technologies, which can be used in other production processes. In addition, it plays a significant role stimulating investments in new infrastructure and promoting competition, creating employment and corresponding household income. Last but not least, it must be noted that tourism is a significant sector of diffusion of technical knowledge, and potentially it can stimulate research and development.