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Comparing forecasts for tourism dynamics in Medellín, Colombia

Author

Listed:
  • Marisol Valencia Cárdenas

    (Institución Universitaria Tecnológico de Antioquia)

  • Juan Gabriel Vanegas López

    (Fundación Universitaria Autónoma de las Américas)

  • Juan Carlos Correa Morales

    (Universidad Nacional de Colombia)

  • Jorge Aníbal Restrepo Morales

    (Institución Universitaria Tecnológico de Antioquia)

Abstract

Tourism is a topic of interest to many economies around the world, but it has received limited attention in Colombia. Knowing the periods of larger tourist inflows is important for predicting coverage in services for tourists. In this paper, we compare the estimation between classical and Bayesian regression in order to choose the best alternative to predict the number of tourist arrivals to Medellin. We also identify the most significant variables affecting the influx of tourists and the models providing better fit to the associated dynamics. According to our results, the Bayesian approach shows better estimates than the classic one. In addition, the variable month is significant to explain the demands for both Colombians and foreigners. The periods with the highest incidence of visits to the city are December-January and June-July, a pattern that repeats itself every year, which is crucial for planning hotel resources

Suggested Citation

  • Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017. "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J.
    • Handle: RePEc:lde:journl:y:2017:i:86:p:199-230
    DOI: 10.17533/udea.le.n86a08
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    More about this item

    Keywords

    tourism demand; model evaluation and selection; forecasting and prediction methods; Bayesian statistics; Medellín;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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