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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.

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  • 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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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(3), pages 722-729, June.
    3. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    4. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    5. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    7. Suhejla Hoti & Michael McAleer & Riaz Shareef, 2005. "Modelling Country Risk and Uncertainty in Small Island Tourism Economies," Tourism Economics, , vol. 11(2), pages 159-183, June.
    8. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    9. Shareef, Riaz & Hoti, Suhejla, 2005. "Small island tourism economies and country risk ratings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 553-566.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    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. 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.
    6. Mitra, Subrata Kumar & Chattopadhyay, Manojit & Jana, R.K., 2019. "Spillover analysis of tourist movements within Europe," Annals of Tourism Research, Elsevier, vol. 79(C).
    7. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Econometric Institute Research Papers 18-031/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Zhou, Bo & Zhang, Ying & Zhou, Peng, 2021. "Multilateral political effects on outbound tourism," Annals of Tourism Research, Elsevier, vol. 88(C).
    9. Divino, Jose Angelo & McAleer, Michael, 2010. "Modelling and forecasting daily international mass tourism to Peru," Tourism Management, Elsevier, vol. 31(6), pages 846-854.
    10. Michael McAleer, 2015. "The Fundamental Equation in Tourism Finance," JRFM, MDPI, vol. 8(4), pages 1-6, December.
    11. 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.
    12. 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.
    13. Jorge V Pérez-Rodríguez & Juan M Hernández & Julián Andrada-Félix, 2024. "Modelling prices and volatilities in the sharing economy," Tourism Economics, , vol. 30(5), pages 1189-1215, August.
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    15. 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.

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