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An empirical investigation of tourism-led growth hypothesis in the european countries: evidence from augmented mean group estimator.

Xia, W., Doğan, B., Shahzad, U., Adedoyin, F. F., Popoola, A. and Bashir, M.A., 2021. An empirical investigation of tourism-led growth hypothesis in the european countries: evidence from augmented mean group estimator. Portuguese Economic Journal. (In Press)

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DOI: 10.1007/s10258-021-00193-9

Abstract

Due to urbanization and the need for people to go from one country to another either for commercial purpose or tourism, it is therefore important to determine the extent to which tourism contributes to growth. This article aims to investigate the tourism-led growth hypothesis in a sample of 34 European countries utilizing the yearly data from 1995 to 2015. The research work makes use of 8 tourism indicators, which cover different dimensions of tourism sector development such as foreign visitors' spending, and international tourist arrival. For empirical analysis, the study accounts key determinants of growth such as capital, labor and energy (renewable and non-renewable) consumption. The results from common correlated effects (CCE) augmented mean group (AMG) and groped-mean estimators confirms that there is a positive relationship between tourism, labour, capital and GDP insinuating the presence of tourism-led growth hypothesis in the European countries. Also, findings from the FMOLS show that changes in the variables leads to a proportional change in GDP. Specifically, the evidence shows that the tourism indicators play an indispensable role in promoting economic development, along with energy consumption, capital, and labor. Sustainable Combating environmental issues associated with foreign arrivals, renewable energy consumption should be encouraged to reduce environmental externalities to ensure sustainable environments for businesses and tourists’ arrivals.

Item Type:Article
ISSN:1617-982X
Uncontrolled Keywords:Tourism; growth; European countries; energy consumption; AMG estimator
Group:Bournemouth University Business School
ID Code:35233
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:01 Mar 2021 14:30
Last Modified:10 Mar 2021 08:49

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