IDEAS home Printed from https://ideas.repec.org/a/bla/presci/v69y1990i1p31-42.html
   My bibliography  Save this article

Forecasting Models For Tourism Demand In City Dominated And Coastal Areas

Author

Listed:
  • Ann Clewer
  • Alan Pack
  • M. Thea Sinclair

Abstract

ABSTRACT The paper uses Structural time series models to forecast the demand for tourism by nationality in coastal and city‐dominated Spanish provinces. Intervention variables arc introduced lo take account of sudden shocks to tourism demand, such as the bombing of Libya and football's World Cup, The model demonstrates the considerable differences in demand by nationality, and in seasonably, which can occur at the sub‐national level. The Structural model generally provided more accurate forecasts than Box‐Jenkins models. The results indicate that, ceteris paribus, the tourism demand growth rates in the Spanish provinces considered are unlikely to revert to their previous high levels.

Suggested Citation

  • Ann Clewer & Alan Pack & M. Thea Sinclair, 1990. "Forecasting Models For Tourism Demand In City Dominated And Coastal Areas," Papers in Regional Science, Wiley Blackwell, vol. 69(1), pages 31-42, January.
  • Handle: RePEc:bla:presci:v:69:y:1990:i:1:p:31-42
    DOI: 10.1111/j.1435-5597.1990.tb01201.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1435-5597.1990.tb01201.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1435-5597.1990.tb01201.x?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
    ---><---

    Citations

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


    Cited by:

    1. Juan L. Eugenio-Martin, 2016. "Estimating the Tourism Demand Impact of Public Infrastructure Investment: The Case of Malaga Airport Expansion," Tourism Economics, , vol. 22(2), pages 254-268, April.
    2. Juan Luis Eugenio-Martín & Noelia Martín Morales & Riccardo Scarpa, 2004. "Tourism and Economic Growth in Latin American Countries: A Panel Data Approach," Working Papers 2004.26, Fondazione Eni Enrico Mattei.
    3. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    4. Montserrat Hernández-López, 2004. "Future Tourists' Characteristics and Decisions: The Use of Genetic Algorithms as a Forecasting Method," Tourism Economics, , vol. 10(3), pages 245-262, September.

    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:bla:presci:v:69:y:1990:i:1:p:31-42. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1056-8190 .

    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.