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Modelling sustainable international tourism demand to the Brazilian Amazon

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Author Info
Divino, J. A.
McAleer, M.J. (Erasmus Econometric Institute)

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Abstract

The Amazon rainforest is one of the world’s greatest natural wonders and holds great importance and significance for the world’s environmental balance. Around 60% of the Amazon rainforest is located in the Brazilian territory. The two biggest states of the Amazon region are Amazonas (the upper Amazon) and Pará (the lower Amazon), which together account for around 73% of the Brazilian Legal Amazon, and are the only states that are serviced by international airports in Brazil’s North region. The purpose of this paper is to model and forecast sustainable international tourism demand for the states of Amazonas, Pará, and the aggregate of the two states. Economic progress of the region has been achieved at a cost of destroying large areas of the Amazon rain forest. In this scenario, the tourism industry would seem to have the potential to contribute to sustainable economic development in the North region of Brazil. The paper presents unit root tests for monthly and annual data, estimates alternative time series models and conditional volatility models of the shocks to international tourist arrivals, and provides forecasts for 2006 and 2007.

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Publisher Info
Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2008-22 Revision_Date: 2009-11-26.

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Date of creation: 10 Nov 2008
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Handle: RePEc:dgr:eureir:1765013773

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Related research
Keywords: Brazilian Amazon; international tourism demand; time series modelling; conditional volatility models; forecasting;

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  2. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August. [Downloadable!] (restricted)
  3. 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(03), pages 722-729, June. [Downloadable!]
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  4. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University. [Downloadable!]
  5. Bonham, Carl & Gangnes, Byron & Zhou, Ting, 2009. "Modeling tourism: A fully identified VECM approach," International Journal of Forecasting, Elsevier, vol. 25(3), pages 531-549, July. [Downloadable!] (restricted)
  6. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(02), pages 280-310, April. [Downloadable!]
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  7. Perron, Pierre & Ng, Serena, 1996. "Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties," Review of Economic Studies, Blackwell Publishing, vol. 63(3), pages 435-63, July. [Downloadable!] (restricted)
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  8. Luis A. Gil-Alana & Juncal Cunado & Fernando Perez de Gracia, 2008. "Tourism in the Canary Islands: forecasting using several seasonal time series models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 621-636. [Downloadable!]
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  9. Pagan, Adrian, 1986. "Two Stage and Related Estimators and Their Applications," Review of Economic Studies, Blackwell Publishing, vol. 53(4), pages 517-38, August. [Downloadable!] (restricted)
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  10. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July. [Downloadable!] (restricted)
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  11. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November. [Downloadable!] (restricted)
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  12. George Athanasopoulos & Roman A. Ahmed & Rob J. Hyndman, 2007. "Hierarchical forecasts for Australian domestic tourism," Monash Econometrics and Business Statistics Working Papers 12/07, Monash University, Department of Econometrics and Business Statistics, revised Nov 2007. [Downloadable!]
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  13. Oxley, Les & McAleer, Michael, 1993. " Econometric Issues in Macroeconomic Models with Generated Regressors," Journal of Economic Surveys, Blackwell Publishing, vol. 7(1), pages 1-40.
  14. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February. [Downloadable!] (restricted)
  15. 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. [Downloadable!] (restricted)
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  16. McKensie, C.R. & McAleer, M., 1990. "On Efficient Estimation and Correct Inference in Models with Generated Regressions: A General Approach," Papers 211, Australian National University - Department of Economics.
  17. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Blackwell Publishing, vol. 16(3), pages 245-69, July. [Downloadable!] (restricted)
  18. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February. [Downloadable!]
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