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Martins, L. F., Gan, Y. & Ferreira-Lopes, A. (2017). An empirical analysis of the influence of macroeconomic determinants on World tourism demand. Tourism Management. 61, 248-260
L. F. Martins et al., "An empirical analysis of the influence of macroeconomic determinants on World tourism demand", in Tourism Management, vol. 61, pp. 248-260, 2017
@article{martins2017_1734959259940, author = "Martins, L. F. and Gan, Y. and Ferreira-Lopes, A.", title = "An empirical analysis of the influence of macroeconomic determinants on World tourism demand", journal = "Tourism Management", year = "2017", volume = "61", number = "", doi = "10.1016/j.tourman.2017.01.008", pages = "248-260", url = "http://www.sciencedirect.com/science/article/pii/S0261517717300110" }
TY - JOUR TI - An empirical analysis of the influence of macroeconomic determinants on World tourism demand T2 - Tourism Management VL - 61 AU - Martins, L. F. AU - Gan, Y. AU - Ferreira-Lopes, A. PY - 2017 SP - 248-260 SN - 0261-5177 DO - 10.1016/j.tourman.2017.01.008 UR - http://www.sciencedirect.com/science/article/pii/S0261517717300110 AB - This paper considers three econometric models to determine the relationship between macroeconomic variables and tourism demand. Tourism demand is measured by the inbound visitor's population and also by on-the-ground expenditures. Macroeconomic determinants include the exchange rate, the relative domestic prices, and the World GDP per capita. The database is an unbalanced panel of 218 countries over the period 1995-2012. There is evidence that an increase in the World's GDP per capita, a depreciation of the national currency, and a decline of relative domestic prices do help boosting the number of arrivals and the correspondent expenditure level. The World's GDP per capita is more relevant when explaining arrivals, but relative prices become more important when we use expenditures as the proxy for tourism demand. In particular, we cannot reject the hypothesis of a relative prices unitary elasticity of expenditures. Additionally, we have also partitioned our data by income level and by continent. Results are robust in the first partition, but less robust in the second, although the main conclusions still hold. ER -