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Modelling international tourism demand and uncertainty in Maldives and Seychelles: A portfolio approach

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  • Shareef, Riaz
  • McAleer, Michael

Abstract

Maldives and Seychelles in the Indian Ocean are small island tourism economies (SITEs), both of which have relatively small populations, territorial sizes, land area and narrow productive bases. The two SITEs are surrounded by vast ocean and have an overwhelming reliance on international tourism for economic development. Variations in international tourist arrivals to these two SITEs have been affected by unanticipated oil shocks, natural disasters, crime and global terrorism, among others. An accurate assessment of the variations in international tourist arrivals, particularly the conditional volatility, is essential for policy and marketing purposes. The conditional mean and conditional variance of the weekly international tourist arrivals to Maldives and Seychelles from 1 January 1994 to 31 December 2003 for the five main tourist source countries are modelled. Multivariate models of uncertainty are estimated and tested. An assessment and interpretation of the estimates are made for policy makers and tour operators to reach optimal decisions on the basis of a portfolio approach to international tourism demand. The paper assesses four sets of country spillover effects between Maldives and Seychelles, namely (i) the own country effects for Maldives and Seychelles; (ii) the country spillover effects from the remaining four countries within each of Maldives and Seychelles; (iii) the own country spillover effects between Maldives and Seychelles; and (iv) the cross-country spillover effects between Maldives and Seychelles. The empirical results for both Maldives and Seychelles are discussed in terms of each of these components.

Suggested Citation

  • Shareef, Riaz & McAleer, Michael, 2008. "Modelling international tourism demand and uncertainty in Maldives and Seychelles: A portfolio approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 459-468.
    • Handle: RePEc:eee:matcom:v:78:y:2008:i:2:p:459-468
    DOI: 10.1016/j.matcom.2008.01.025
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    References listed on IDEAS

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    Cited by:

    1. Chia-Lin Chang & Michael McAleer & Christine Lim, 2010. "Modelling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan," Working Papers in Economics 10/40, University of Canterbury, Department of Economics and Finance.
    2. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    3. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Tinbergen Institute Discussion Papers 18-031/III, Tinbergen Institute.
    4. Chia-Lin Chang & Michael Mcaleer, 2009. "Daily Tourist Arrivals, Exchange Rates and Voatility for Korea and Taiwan," Korean Economic Review, Korean Economic Association, vol. 25, pages 241-267.
    5. Divino, Jose Angelo & McAleer, Michael, 2010. "Modelling and forecasting daily international mass tourism to Peru," Tourism Management, Elsevier, vol. 31(6), pages 846-854.
    6. Michael McAleer, 2015. "The Fundamental Equation in Tourism Finance," JRFM, MDPI, vol. 8(4), pages 1-6, December.
    7. Rochelle Steven & J Guy Castley & Ralf Buckley, 2013. "Tourism Revenue as a Conservation Tool for Threatened Birds in Protected Areas," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-8, May.
    8. Chia-Lin Chang & Michael McAleer & Dan Slottje, 2009. "Modelling International Tourist Arrivals and Volatility: An Application to Taiwan," Documentos de Trabajo del ICAE 2009-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. 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.
    10. Mitra, Subrata Kumar & Chattopadhyay, Manojit & Jana, R.K., 2019. "Spillover analysis of tourist movements within Europe," Annals of Tourism Research, Elsevier, vol. 79(C).
    11. Apostolos Ampountolas, 2021. "Modeling and Forecasting Daily Hotel Demand: A Comparison Based on SARIMAX, Neural Networks, and GARCH Models," Forecasting, MDPI, vol. 3(3), pages 1-16, August.
    12. Jorge V Pérez-Rodríguez & María Santana-Gallego, 2020. "Modelling tourism receipts and associated risks, using long-range dependence models," Tourism Economics, , vol. 26(1), pages 70-96, February.
    13. Zhou, Bo & Zhang, Ying & Zhou, Peng, 2021. "Multilateral political effects on outbound tourism," Annals of Tourism Research, Elsevier, vol. 88(C).
    14. Bo Zhou & Zhihong Wen & Ian Sutherland & Seul Ki Lee, 2022. "The spatial heterogeneity and dynamics of tourism-flow spillover effect: The role of high-speed train in China," Tourism Economics, , vol. 28(2), pages 300-324, March.

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