Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach
Cutting Edge Research Methods in Hospitality and Tourism
ISBN: 978-1-80455-064-9, eISBN: 978-1-80455-063-2
Publication date: 25 January 2023
This chapter examines the nexus between the between tourism growth and income inequality in the top 10 tourist destinations in the world by using the advanced econometric technique namely quantile-on-quantile (QnQ). This approach combines the two approaches, that is, the nonparametric estimation and quantile regression and regresses the quantile of the tourism growth onto income inequality quantiles, thus enabling the effect of the income inequality on across different conditional tourism growth distribution. It also allows to explain a comprehensive picture of the overall interdependence and nonlinear relationship between the examined variables. The result from QnQ approach shows a negative association between income inequality and tourism growth, however, the country-specific analysis shows wide variations within and across different quantiles of variables. Notably, on the one hand, a strong negative association between the variables is found in China, France, Spain, Italy, Russia and the USA implying that tourism expansion minimizes the income inequality. On the other hand, a strong positive association is noted in Germany, Turkey, Mexico and the UK, which means that growth in tourism widens the income inequality. These outcomes provide important policy direction for tourism management in the respective countries.
Raza, S.A., Shah, N., Kumar, R.R. and Alam, M.S. (2023), "Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach", Okumus, F., Rasoolimanesh, S.M. and Jahani, S. (Ed.) Cutting Edge Research Methods in Hospitality and Tourism, Emerald Publishing Limited, Bingley, pp. 71-93. https://doi.org/10.1108/978-1-80455-063-220231006
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Copyright © 2023 Syed Ali Raza, Nida Shah, Ronald Ravinesh Kumar and Md. Samsul Alam