ANALYSIS OF THE RELATIONSHIP BETWEEN THE VARIABLES IN JAPANESE TOURISTS DEMAND USING VECM AND COINTEGRATION. THE CASE OF THAILAND
Abstract
The study of this article had done to Japanese tourists which were one of the majority international tourist arrivals to Thailand and used quarterly data since 1985 to 2012. The purpose was to study the relationship between 4 factors including number of Japanese arrivals to Thailand, GDP per capita of Japanese tourists, the own price and the cross price. It was multivariate analysis which investigated dependence and interaction among a set of variables in multi-values process. The tool use was VECM and Cointegration.We could conclude the relationship in the short run of various variables in Japanese tourists demand model. It produced relationship called the income elasticity of demand and the own price elasticity of demand which was equal to 3.281 and -0.505, respectively.In addition, percentage change of GDP per capita of Japanese tourists had a negative relationship with percentage change of the own price. Finally, percentage change of the cross price had a positive relationship with percentage change of the own price.
In the long run, the number of Japanese tourist arrivals had a positive relationship with the GDP per capita of Japanese tourists and the own price also had a positive relationship with the cross price.
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[9] Chan, F. Lim, C. and McAleer, M. (2005). Modeling Multivariate International Tourism Demand and Volatility. Journal of Tourism Management, 26: 301-479.
[10] Chu, F.L .(1998). Forecasting Tourist Arrivals. Journal of Travel Research, 36: 79-84.
[11] Chu, F.L. (2008). A fractional integrated autoregressive moving average approach to forecasting tourism demand. Journal of Tourism Management, 29: 79-88.
[12] Crouch G.I. (1994).The Study of International Tourism Demand: a Survey of Practice. Journal of Travel Research, 32 (4): 41-55.
[13] Domroes, M. (1985). Tourism Resources and Their Development in Maldives Islands. GeoJournal, 10: 119-126.
[14] Enders, W. (2004). Applied Econometric Time Series. John Wiley & Son.
[15] Frances, P.H. (1998). Time Series Models for Business and Economics Forecasting. Cambridge University Press.
[16] Gray, H.P. (1966). The demand for international travel by the United State and Canada.International Economic Review, 13, 83-92.
[17] Jeffrey, P. and Xie,Y. (1995). The UK market for Tourism in China. Annals of Tourism Research, 22: 857-876.
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[21] Mirsha, P. Himanshu, B. and Mohapatra, S. (2011). The Causality between Tourism and Economic Growth: Empirical Evidence from India. European Journal of Social Sciences, 18(4): 518-527.
[22] Ouerfelli, C. (2008). Co-integration analysis of quarterly European tourism demand in Tunisia. Journal of Tourism Management, 29: 127-137.
[23] Song, H. and Witt, S.F. (2003). Tourism forecasting: the general-to-specific approach. Journal of Travel Research, 42: 65-74.
[24] Zortuk, M. (2009). Economic impact of tourism on Turkey’s economy: evidence from co-integration tests. International Research Journal of Finance and Economics, 25: 231-239.
Published
2016-11-15
How to Cite
BUNNAG, Tanattrin.
ANALYSIS OF THE RELATIONSHIP BETWEEN THE VARIABLES IN JAPANESE TOURISTS DEMAND USING VECM AND COINTEGRATION. THE CASE OF THAILAND.
Journal of Environmental Management and Tourism, [S.l.], v. 5, n. 2, p. 114-126, nov. 2016.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/402>. Date accessed: 23 dec. 2024.
Section
Journal of Environmental Management and Tourism
Keywords
tourism; VECM; Cointegration; income elasticity of demand; own price elasticity of demand
Copyright© 2024 The Author(s). Published by ASERS Publishing 2024. This is an open access article distributed under the terms of CC-BY 4.0 license.