IDEAS home Printed from https://ideas.repec.org/p/jet/dpaper/dpaper601.html

Forecasting inbound tourists in Cambodia

Author

Listed:
  • Tanaka, Kiyoyasu

Abstract

Forecasting tourism demand is crucial for management decisions in the tourism sector. Estimating a vector autoregressive (VAR) model for monthly visitor arrivals disaggregated by three entry points in Cambodia for the years 2006–2015, I forecast the number of arrivals for years 2016 and 2017. The results show that the VAR model fits well with the data on visitor arrivals for each entry point. Ex post forecasting shows that the forecasts closely match the observed data for visitor arrivals, thereby supporting the forecasting accuracy of the VAR model. Visitor arrivals to Siem Reap and Phnom Penh airports are forecast to increase steadily in future periods, with varying fluctuations across months and origin countries of foreign tourists.

Suggested Citation

  • Tanaka, Kiyoyasu, 2016. "Forecasting inbound tourists in Cambodia," IDE Discussion Papers 601, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    • Handle: RePEc:jet:dpaper:dpaper601
    as

    Download full text from publisher

    File URL: https://ir.ide.go.jp/record/37585/files/IDP000601_001.pdf
    File Function: First version, 2016
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guido Candela & Paolo Figini, 2012. "The Economics of Tourism Destinations," Springer Texts in Business and Economics, Springer, edition 127, number 978-3-642-20874-4, December.
    2. Álvaro Matias & Peter Nijkamp & Manuela Sarmento (ed.), 2009. "Advances in Tourism Economics," Springer Books, Springer, number 978-3-7908-2124-6, March.
    3. Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844.
    4. Carlos Santos & Gualter Couto & Pedro Miguel Pimentel, 2009. "Forecasting Hotel Overnights in the Autonomous Region of the Azores," Springer Books, in: Álvaro Matias & Peter Nijkamp & Manuela Sarmento (ed.), Advances in Tourism Economics, chapter 0, pages 175-186, Springer.
    Full references (including those not matched with items on IDEAS)

    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. Massimiliano Castellani & Pierpaolo Pattitoni & Laura Vici, 2015. "Pricing Visitor Preferences for Temporary Art Exhibitions," Tourism Economics, , vol. 21(1), pages 83-103, February.
    2. Ashrafi Tannaz Alizadeh & Myrland Øystein, 2017. "Determinants of trip duration for international tourists in Norway; a parametric survival analysis," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 8(1), pages 75-86, May.
    3. Rainer Andergassen & Guido Candela & Paolo Figini, 2017. "The management of tourism destinations," Tourism Economics, , vol. 23(1), pages 49-65, February.
    4. Rostami-Tabar, Bahman & Ali, Mohammad M. & Hong, Tao & Hyndman, Rob J. & Porter, Michael D. & Syntetos, Aris, 2022. "Forecasting for social good," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1245-1257.
    5. Vuong, Van-Dai & Nguyen, Luong-Ha & Goulet, James-A., 2025. "Coupling LSTM neural networks and state-space models through analytically tractable inference," International Journal of Forecasting, Elsevier, vol. 41(1), pages 128-140.
    6. Salvatore Bimonte & Antonella D’Agostino, 2021. "Tourism development and residents’ well-being: Comparing two seaside destinations in Italy," Tourism Economics, , vol. 27(7), pages 1508-1525, November.
    7. Pilar Campoy-Muñoz & M. Alejandro Cardenete & M. Carmen Delgado, 2017. "Assessing the economic impact of a cultural heritage site using social accounting matrices," Tourism Economics, , vol. 23(4), pages 874-881, June.
    8. Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
    9. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    10. Fotios Petropoulos & Evangelos Spiliotis, 2021. "The Wisdom of the Data: Getting the Most Out of Univariate Time Series Forecasting," Forecasting, MDPI, vol. 3(3), pages 1-20, June.
    11. László Könnyid & Zsuzsanna Váradi & Zsombor Nagy & Noémi Ilyés & Orsolya H. Horváth, 2022. "The Changes in the Demographic Characteristics and Spatial Structure of Tourism Demand in the West Balaton Region’s Spa Cities," Sustainability, MDPI, vol. 14(17), pages 1-14, August.
    12. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    13. Akın, Melda, 2015. "A novel approach to model selection in tourism demand modeling," Tourism Management, Elsevier, vol. 48(C), pages 64-72.
    14. Hyndman, Rob J., 2020. "A brief history of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
    15. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    16. Cellini, Roberto & Cuccia, Tiziana, 2014. "The Tourism Industry in Italy during the Great Recession (2008-12): What Data Show and Suggest," MPRA Paper 60999, University Library of Munich, Germany.
    17. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    18. Agnieszka Wartecka-Wazynska, 2021. "Silver Tourism Economy in Rural Areas in Poland: A Fad or a Permanent Element?," European Research Studies Journal, European Research Studies Journal, vol. 0(3 - Part ), pages 729-748.
    19. Eduardo Amaral Haddad & Alexandre Alves Porsse & Wilson Rabahy, 2013. "Domestic Tourism and Regional Inequality in Brazil," Tourism Economics, , vol. 19(1), pages 173-186, February.
    20. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:jet:dpaper:dpaper601. 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: Michitaka Imamitsu (email available below). General contact details of provider: https://edirc.repec.org/data/idegvjp.html .

    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.