Analysis of the Tourism - Environment Relationship From an Econometric Perspective; Case Study: European Countries

Abstract

The upward trend of the tourism industry and its impact on the global economy is in contradiction with the degradation of the environment and the intensification of global warming. Therefore, naturally, one question arises: are tourism and environment allies or enemies? The right of mankind and the economic interest, must surpass the right of nature to survival? Statistical data reveal promising developments in the tourism sector and its contribution to the global economy. According to the report "Travel & Tourism, Economic impact 2018, World", the total contribution of Travel & Tourism industry in 2017 reached 10.4% of GDP, with a 4% estimated increase in 2018. The effect of this industry on global employment is also a positive one, providing directly over 118 million jobs (3.8% of total employment). Taking into account indirect impact as well, the travel & tourism industry provides over 313 million jobs, meaning that one in 10 jobs worldwide is supported by this industry. In a world where increasing opportunities to ensure a large number of quality jobs is more and more important, tourism is seen as a catalyst for human development. On the other hand, mankind faces an increase in the average global temperature of 1 Celsius degree compared to the pre-industrial period, specialists drawing attention that there is a real danger of worsening this situation. In this context, the present paper aims at analyzing the two-way relationship between tourism and environment, base on a panel of statistical and econometric methods. Thus, data covering the last 10 years, provided by EUROSTAT for the 28 countries of the European Union are analyzed. The set of indicators is focused on three main pillars: Tourism pillar, Environmental Pillar and Economy and digital economy background Pillar. The statistical analysis of the data set includes Descriptive statistics tools, Principal Component Analysis, non-parametric statistical tests and statistical correlation and regression.