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Comparative analysis of government forecasts for the Lisbon Airport

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  • Samagaio, António
  • Wolters, Mark

Abstract

The study examines the official forecasts for airline passenger numbers for the Lisbon metropolitan area. Auto-regressive and exponential smoothing models are used to develop independent forecasts for passenger numbers. The forecasts show that the government forecasts are at the top end of estimates and should be considered overly optimistic.

Suggested Citation

  • Samagaio, António & Wolters, Mark, 2010. "Comparative analysis of government forecasts for the Lisbon Airport," Journal of Air Transport Management, Elsevier, vol. 16(4), pages 213-217.
    • Handle: RePEc:eee:jaitra:v:16:y:2010:i:4:p:213-217
    DOI: 10.1016/j.jairtraman.2009.09.002
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    References listed on IDEAS

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    1. Everette S. Gardner, Jr. & Ed. Mckenzie, 1985. "Forecasting Trends in Time Series," Management Science, INFORMS, vol. 31(10), pages 1237-1246, October.
    2. Nenad Njegovan, 2005. "A leading indicator approach to predicting short-term shifts in demand for business travel by air to and from the UK," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 421-432.
    3. Grubb, Howard & Mason, Alexina, 2001. "Long lead-time forecasting of UK air passengers by Holt-Winters methods with damped trend," International Journal of Forecasting, Elsevier, vol. 17(1), pages 71-82.
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    3. de Paula, R.O. & Silva, L.R. & Vilela, M.L. & Cruz, R.O.M., 2019. "Forecasting passenger movement for Brazilian airports network based on the segregation of primary and secondary demand applied to Brazilian civil aviation policies planning," Transport Policy, Elsevier, vol. 77(C), pages 23-29.
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    5. Sun, Shaolong & Lu, Hongxu & Tsui, Kwok-Leung & Wang, Shouyang, 2019. "Nonlinear vector auto-regression neural network for forecasting air passenger flow," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 54-62.
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    7. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    8. Dantas, Tiago Mendes & Cyrino Oliveira, Fernando Luiz & Varela Repolho, Hugo Miguel, 2017. "Air transportation demand forecast through Bagging Holt Winters methods," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 116-123.
    9. Jin, Feng & Li, Yongwu & Sun, Shaolong & Li, Hongtao, 2020. "Forecasting air passenger demand with a new hybrid ensemble approach," Journal of Air Transport Management, Elsevier, vol. 83(C).
    10. Nieto, María Rosa & Carmona-Benítez, Rafael Bernardo, 2018. "ARIMA + GARCH + Bootstrap forecasting method applied to the airline industry," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 1-8.
    11. Ryazanov Vlas, 2013. "Air mobility of people and airport growth potential in regions of Russia," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 22(22), pages 97-110, December.
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    14. Banerjee, Nilabhra & Morton, Alec & Akartunalı, Kerem, 2020. "Passenger demand forecasting in scheduled transportation," European Journal of Operational Research, Elsevier, vol. 286(3), pages 797-810.

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