Modeling to Forecast International Tourism Demand in Thailand
Keywords:Forecasting, Negative binomial regression, Poisson regression, Tourism demand
This study attempted to develop and certify a demand model to forecast international tourism demand in Thailand using 4 key macroeconomic variables which are foreign direct investment, exchange rate, inflation rate and openness of trade. This study examines Poisson regression and negative binomial regression. Overdispersion is encountered when fitting with the Poisson regression model. The study finds that the negative binomial regression model is the best model to develop for international tourism demand in Thailand. Exchange rate, inflation rate and openness of trade are three components in the model. The exchange rate and inflation rate have negative relationships with international tourism demand in Thailand. On the other hand, the openness of trade has a positive relationship with international tourism demand in Thailand.
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