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Modelling International Tourism Demand and Volatility in Small Island Tourism Economies

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Author Info

  • Riaz Shareef

    () (School of Accounting, Finance and Economics, Edith Cowan University)

  • Michael McAleer

    (School of Economics and Commerce, University of Western Australia)

Abstract

Small Island Tourism Economies (SITEs) vary in their size, land area, location, narrow resource bases, economic development, an overwhelming reliance on tourism, and a consistent inflow of foreign direct investment for economic growth. SITEs differ in their ethnic diversity, political systems, economic and environmental vulnerability, ecological fragility, and the risks facing investors. Owing to natural disasters, ethnic conflicts, crime, and the threat of global terrorism, there have been dramatic changes in the arrivals of international tourists to SITEs. These variations in international tourism demand to SITEs, particularly the conditional variance (or volatility) in international tourist arrivals, have not previously been analysed in the tourism research literature. An examination of the conditional volatility of international tourist arrivals is essential for policy analysis and marketing purposes. This paper models the conditional mean and conditional variance of the logarithm of monthly international tourist arrivals and the growth rate (or log-difference) in the monthly international tourist arrivals for six SITEs, namely Barbados, Cyprus, Dominica, Fiji, Maldives, and Seychelles. Diagnostic checks of the regularity conditions of the logarithm of monthly international tourist arrivals and their growth rates suggest that the estimated univariate models of trends and volatility are statistically adequate. Therefore, the estimated models are appropriate for purposes of public and private sector management of tourism. Acknowledgements: The authors wish to thank Felix Chan, Suhejla Hoti, Christine Lim and two anonymous referees for helpful comments and suggestions. The first author is most grateful for a UWA Research Grant, and the second author wishes to acknowledge financial support of Australian Research Council.

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Bibliographic Info

Paper provided by Edith Cowan University, School of Accounting Finance & Economics in its series Working papers with number 2005-17.

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Length: 35 pages
Date of creation: Dec 2005
Date of revision:
Handle: RePEc:ecu:wpaper:2005-17

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Web page: http://www.ecu.edu.au/schools/accounting-finance-economics
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Related research

Keywords: Island economies; small size; vulnerability; international tourism demand; arrival rate; trends; volatility; time-varying conditional variance; GARCH; GJR; asymmetry; shocks; regularity conditions;

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Citations

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Cited by:
  1. Chia-Lin Chang & Michael McAleer, 2010. "Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates," KIER Working Papers 712, Kyoto University, Institute of Economic Research.
  2. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer & Roengchai Tansuchat, 2010. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," Working Papers in Economics 10/27, University of Canterbury, Department of Economics and Finance.
  3. Jose Angelo Divino & Michael McAleer, 2009. "Modelling the Growth and Volatility in Daily International Mass Tourism to Peru," Documentos del Instituto Complutense de Análisis Económico 0915, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  4. Chia-Lin Chang & Michael McAleer & Christine Lim, 2009. "Modelling Short and Long Haul Volatility in Japanese Tourist Arrivals to New Zealand and Taiwan," CIRJE F-Series CIRJE-F-647, CIRJE, Faculty of Economics, University of Tokyo.
  5. Chia-Lin Chang & Michael McAleer & Dan Slottje, 2009. "Modelling International Tourist Arrivals and Volatility: An Application to Taiwan," Documentos del Instituto Complutense de Análisis Económico 0906, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  6. Jose Angelo Divino & Michael McAleer, 2009. "Modelling and Forecasting Daily International Mass Tourism to Peru," CIRJE F-Series CIRJE-F-651, CIRJE, Faculty of Economics, University of Tokyo.

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