Modelling sustainable international tourism demand to the Brazilian Amazon
Jose Angelo Divino and
Michael McAleer
No EI 2008-22, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute
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.
Keywords: Brazilian Amazon; conditional volatility models; forecasting; international tourism demand; time series modelling (search for similar items in EconPapers)
JEL-codes: C22 C53 Q23 (search for similar items in EconPapers)
Date: 2008-11-10
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Citations: View citations in EconPapers (9)
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https://repub.eur.nl/pub/13773/EI2008-22.pdf (application/pdf)
Related works:
Working Paper: Modelling Sustainable International Tourism Demand to the Brazilian Amazon (2009)
Working Paper: Modelling Sustainable International Tourism Demand to the Brazilian Amazon (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:13773
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