IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v44y2017i7p1211-1224.html
   My bibliography  Save this article

Comparison of bootstrap estimation intervals to forecast arithmetic mean and median air passenger demand

Author

Listed:
  • Rafael Bernardo Carmona-Benítez
  • María Rosa Nieto

Abstract

The aim of this paper is to compare passenger (pax) demand between airports based on the arithmetic mean (MPD) and the median pax demand (MePD). A three phases approach is applied. First phase, we use bootstrap procedures to estimate the distribution of the arithmetic MPD and the MePD for each block of routes distance; second phase, we use percentile, standard, bias corrected, and bias corrected accelerated methods to calculate bootstrap confidence bands for the MPD and the MePD; and third phase, we implement Monte Carlo (MC) experiments to analyse the finite sample performance of the applied bootstrap. Our results conclude that it is more meaningful to use the estimation of MePD rather than the estimation of MPD in the air transport industry. By carrying out MC experiments, we demonstrate that the bootstrap methods produce coverages close to the nominal for the MPD and the MePD.

Suggested Citation

  • Rafael Bernardo Carmona-Benítez & María Rosa Nieto, 2017. "Comparison of bootstrap estimation intervals to forecast arithmetic mean and median air passenger demand," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(7), pages 1211-1224, May.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:7:p:1211-1224
    DOI: 10.1080/02664763.2016.1201794
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2016.1201794
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2016.1201794?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hsu, Chaug-Ing & Wen, Yuh-Horng, 2000. "Application of Grey theory and multiobjective programming towards airline network design," European Journal of Operational Research, Elsevier, vol. 127(1), pages 44-68, November.
    2. Hsu, Chaug-Ing & Wen, Yuh-Horng, 2003. "Determining flight frequencies on an airline network with demand-supply interactions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(6), pages 417-441, November.
    3. Fildes, Robert & Wei, Yingqi & Ismail, Suzilah, 2011. "Evaluating the forecasting performance of econometric models of air passenger traffic flows using multiple error measures," International Journal of Forecasting, Elsevier, vol. 27(3), pages 902-922, July.
    4. Coldren, Gregory M. & Koppelman, Frank S. & Kasturirangan, Krishnan & Mukherjee, Amit, 2003. "Modeling aggregate air-travel itinerary shares: logit model development at a major US airline," Journal of Air Transport Management, Elsevier, vol. 9(6), pages 361-369.
    5. Carson, Richard T. & Cenesizoglu, Tolga & Parker, Roger, 2011. "Forecasting (aggregate) demand for US commercial air travel," International Journal of Forecasting, Elsevier, vol. 27(3), pages 923-941, July.
    6. Igor Fedotenkov, 2013. "A bootstrap method to test for the existence of finite moments," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 315-322, June.
    7. Jason Abrevaya & Jian Huang, 2005. "On the Bootstrap of the Maximum Score Estimator," Econometrica, Econometric Society, vol. 73(4), pages 1175-1204, July.
    8. Hsu, Chaug-Ing & Wen, Yuh-Horng, 2002. "Reliability evaluation for airline network design in response to fluctuation in passenger demand," Omega, Elsevier, vol. 30(3), pages 197-213, June.
    9. Gerard Jong & Andrew Daly & Marits Pieters & Stephen Miller & Ronald Plasmeijer & Frank Hofman, 2007. "Uncertainty in traffic forecasts: literature review and new results for The Netherlands," Transportation, Springer, vol. 34(4), pages 375-395, July.
    10. Grosche, Tobias & Rothlauf, Franz & Heinzl, Armin, 2007. "Gravity models for airline passenger volume estimation," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 175-183.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Mohammadian, Iman & Abareshi, Ahmad & Abbasi, Babak & Goh, Mark, 2019. "Airline capacity decisions under supply-demand equilibrium of Australia’s domestic aviation market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 108-121.
    3. Birolini, Sebastian & Jacquillat, Alexandre & Cattaneo, Mattia & Antunes, António Pais, 2021. "Airline Network Planning: Mixed-integer non-convex optimization with demand–supply interactions," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 100-124.
    4. 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.
    5. Wang, Sen & Gao, Yi, 2021. "A literature review and citation analyses of air travel demand studies published between 2010 and 2020," Journal of Air Transport Management, Elsevier, vol. 97(C).
    6. Tirtha, Sudipta Dey & Bhowmik, Tanmoy & Eluru, Naveen, 2023. "Understanding the factors affecting airport level demand (arrivals and departures) using a novel modeling approach," Journal of Air Transport Management, Elsevier, vol. 106(C).
    7. Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
    8. Tao Li, 2017. "A Demand Estimator Based on a Nested Logit Model," Transportation Science, INFORMS, vol. 51(3), pages 918-930, August.
    9. Abdelghany, Ahmed & Guzhva, Vitaly S., 2022. "Exploratory analysis of air travel demand stimulation in first-time served markets," Journal of Air Transport Management, Elsevier, vol. 98(C).
    10. Sibdari, Soheil & Mohammadian, Iman & Pyke, David F., 2018. "On the impact of jet fuel cost on airlines’ capacity choice: Evidence from the U.S. domestic markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 1-17.
    11. Chen, Jieh-Haur & Wei, Hsi-Hsien & Chen, Chih-Lin & Wei, Hsin-Yi & Chen, Yi-Ping & Ye, Zhongnan, 2020. "A practical approach to determining critical macroeconomic factors in air-traffic volume based on K-means clustering and decision-tree classification," Journal of Air Transport Management, Elsevier, vol. 82(C).
    12. Boonekamp, Thijs & Zuidberg, Joost & Burghouwt, Guillaume, 2018. "Determinants of air travel demand: The role of low-cost carriers, ethnic links and aviation-dependent employment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 112(C), pages 18-28.
    13. 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).
    14. Gizem Kaya & Umut Aydın & Burç Ülengin, 2023. "A Comparison of Forecasting Performance of PPML and OLS estimators: The Gravity Model in the Air Cargo Market," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(39), pages 112-128, December.
    15. Wen, Yuh-Horng & Hsu, Chaug-Ing, 2006. "Interactive multiobjective programming in airline network design for international airline code-share alliance," European Journal of Operational Research, Elsevier, vol. 174(1), pages 404-426, October.
    16. Hu, Yi & Xiao, Jin & Deng, Ying & Xiao, Yi & Wang, Shouyang, 2015. "Domestic air passenger traffic and economic growth in China: Evidence from heterogeneous panel models," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 95-100.
    17. 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.
    18. Frédéric Dobruszkes & Christian Vandermotten, 2022. "Do scale and the type of markets matter? Revisiting the determinants of passenger air services worldwide," ULB Institutional Repository 2013/336304, ULB -- Universite Libre de Bruxelles.
    19. Birolini, Sebastian & Cattaneo, Mattia & Malighetti, Paolo & Morlotti, Chiara, 2020. "Integrated origin-based demand modeling for air transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    20. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:44:y:2017:i:7:p:1211-1224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.