Air traffic forecast in post-liberalization context: a Dynamic Linear Models approach
Abstract
The process of air transport liberalization in Colombia began in 1991. Liberalization entailed the entry of private capital into the airport sector which subsequently led, in several temporary phases, to the privatization of the country’s main airports. Simultaneously, new air operators entered the market. This new market situation, supported by the complete deregulation of airfares, generated a dynamic and sustained growth of air transport in Colombia for two decades. Within the context of post-liberalization, this article presents a forecast (medium-term – 5 years period) of air traffic in the country’s main airport using DLMs (Dynamic Linear Models). It has the following advantages vs. the usual forecast calculation methodologies: it detects stochastic tendencies that are hidden in the time series. It also detects structural changes that allow estimating the variable effect of exogenous shocks over time without increasing the number of parameters. From the results obtained, it should be noted that the application of DLMs presents MAPE (Mean Absolute Percentage Error) values below 1%, which guarantees predictions of higher accuracy and thus introduces a new alternative model to develop reliable forecasts in air transport, at least in the medium-term.
Keyword : air traffic forecast, liberalization, Dynamic Linear Models, airport, air transport, Colombia
How to Cite
Rodriguez, Y., Pineda, W., & Diaz Olariaga, O. (2020). Air traffic forecast in post-liberalization context: a Dynamic Linear Models approach. Aviation, 24(1), 10-19. https://doi.org/10.3846/aviation.2020.12273
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Díaz Olariaga, O., & Carvajal, A. F. (2016). Efectos de la liberalización en la geografía del transporte aéreo en Colombia. Cuadernos Geográficos, 55(2), 344–364.
Díaz Olariaga, O., & Ávila, J. (2015). Evolution of the airport and air transport industry in Colombia and its impact on the economy. Journal of Airline and Airport Management, 5(1), 39–66. https://doi.org/10.3926/jairm.43
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