Air traffic forecast in post-liberalization context: a dynamic linear models approach

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dc.contributorhttps://orcid.org/0000-0001-7774-951X
dc.contributorhttps://orcid.org/0000-0002-4858-3677
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dc.contributorhttps://scholar.google.es/citations?user=5KmOl5oAAAAJ&hl=es
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dc.contributorhttp://scienti.colciencias.gov.co:8081/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001561684
dc.contributorhttp://scienti.colciencias.gov.co:8081/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001256491
dc.contributorhttp://scienti.colciencias.gov.co:8081/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199
dc.creatorRODRIGUEZ, Yesid.
dc.creatorPINEDA, Wilmer.
dc.creatorDIAZ OLARIAGA, Oscar.
dc.date.accessioned2020-05-28T20:01:48Z
dc.date.accessioned2022-09-28T13:47:52Z
dc.date.available2020-05-28T20:01:48Z
dc.date.available2022-09-28T13:47:52Z
dc.date.created2020-05-28T20:01:48Z
dc.date.issued2020-05-28
dc.identifierRodriguez, 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
dc.identifierhttp://hdl.handle.net/11634/23520
dc.identifierhttps://doi.org/10.3846/aviation.2020.12273
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3646563
dc.description.abstractThe 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.
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dc.rightshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.rightsAtribución-NoComercial-SinDerivadas 2.5 Colombia
dc.titleAir traffic forecast in post-liberalization context: a dynamic linear models approach
dc.typeGeneración de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos


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