Managing Value-at-Risk in Daily Tourist Tax Revenues for the Maldives
International tourism is the principal economic activity for Small Island Tourism Economies (SITEs). There is a strongly predictable component of international tourism, specifically the government revenue received from taxes on international tourists, but it is difficult to predict the number of international tourist arrivals, which determines the magnitude of tax revenue receipts. A framework is presented for risk management of daily tourist tax revenues for the Maldives, which is a unique SITE because it relies almost entirely on tourism for its economic and social development. As international tourism receipts are significant financial assets to the economies of SITEs, the timevarying volatility of international tourist arrivals and their growth rate is analogous to the volatility (or dynamic risk) in financial returns. The volatility in the levels and growth rates of daily international tourist arrivals are investigated in the paper. This paper provides a template for the future analysis of earnings from international tourism, particularly tourism taxes for SITEs, discusses the direct and indirect monetary benefits from international tourism, highlights tourism taxes in the Maldives as a development financing phenomenon, and provides a framework for discussing the design and implementation of tourism taxes. Furthermore, it is demonstrated that the analysis developed in this paper can be used by the Maldivian Government in determining monetary and fiscal policy, by creditors to evaluate the risks associated with providing financial support to the Maldives, and by resort operators to decide whether to expand or contract their operations.
|Date of creation:||Nov 2005|
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- McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993.
"On the relation between the expected value and the volatility of the nominal excess return on stocks,"
157, Federal Reserve Bank of Minneapolis.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- 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.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-69, July.
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