SARIMA models forecast of passengers on domestic and international flights in Colombia.
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Abstract
The Colombian aviation sector is positioned as the country with the third largest increase in operations at air terminals in Latin America. Sustainable expansion of this sector demands planning methodology based on estimates of forecast passengers’ flows. In this context in operational planning, this paper presents several long-term predictive forecasting models based on domestic and international flight traffic operations reported by Aerocivil since 2005. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was conducted. A sequential methodology was performed to select five models from 256 estimated. The (0,1,0)×(0,1,0)12 model showed the best fit in terms of RMSEA 3.1%. The models demonstrate high performance in estimation despite the effects of COVID-19.
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