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International Tourism Forecasts: Time-Series Analysis of World and Regional Data

Author

Listed:
  • Andreas Papatheodorou

    (School of Management, University of Surrey, Guildford, Surrey GU2 7XH, UK)

  • Haiyan Song

    (School of Hotel and Tourism Management, Hong Kong Polytechnic University, Hong Kong, Kowloon, Hong Kong SAR, PR China)

Abstract

Forecasting is an essential analytical tool in tourism policy and planning. This paper focuses on international tourism arrivals and receipts at nominal, real and per capita levels. It uses modern time-series techniques based on the period 1960–2000 to produce forecasts for 2001–2010 in the six major World Tourism Organization regions and the world. The initial diagrammatic analysis of existing data suggests that, despite conventional wisdom, evolution in the mass tourism era has not been rosy. Performance differs dramatically among the regions, fluctuations are sharp and negative tourism growth is not unusual in real and per capita terms. Similarly, the subsequent forecasts occasionally have negative signs. Policy makers should, therefore, take action to increase revenue generation but not at the expense of sustainable tourism development.

Suggested Citation

  • Andreas Papatheodorou & Haiyan Song, 2005. "International Tourism Forecasts: Time-Series Analysis of World and Regional Data," Tourism Economics, , vol. 11(1), pages 11-23, March.
    • Handle: RePEc:sae:toueco:v:11:y:2005:i:1:p:11-23
    DOI: 10.5367/0000000053297167
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    Cited by:

    1. O'Connell, Philip J. & Russell, Helen & FitzGerald, John, 2006. "Human Resources," Book Chapters, in: Morgenroth, Edgar (ed.),Ex-Ante Evaluation of the Investment Priorities for the National Development Plan 2007-2013, Economic and Social Research Institute (ESRI).
    2. Anappattath Muhammed Salim & Thomas Shiby M., 2023. "Demand for Kerala’s International Tourism by the Top Three Source Markets: A Comparative Analysis," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 11(1), pages 208-226, October.
    3. Coshall, John T. & Charlesworth, Richard, 2011. "A management orientated approach to combination forecasting of tourism demand," Tourism Management, Elsevier, vol. 32(4), pages 759-769.
    4. Morgenroth, Edgar & FitzGerald, John & FitzGerald, John, 2006. "Summary and Conclusions," Book Chapters, in: Morgenroth, Edgar (ed.),Ex-Ante Evaluation of the Investment Priorities for the National Development Plan 2007-2013, chapter 24, pages 317-333, Economic and Social Research Institute (ESRI).
      • Baker, Terence J. & FitzGerald, John & Honohan, Patrick & FitzGerald, John & Honohan, Patrick, 1996. "Summary and Conclusions," Book Chapters, in: Baker, Terence J. (ed.),Economic Implications for Ireland of EMU, chapter 12, pages 339-352, Economic and Social Research Institute (ESRI).
    5. Liang Zhu & Christine Lim & Wenjun Xie & Yuan Wu, 2017. "Analysis of tourism demand serial dependence structure for forecasting," Tourism Economics, , vol. 23(7), pages 1419-1436, November.
    6. Yang, Yang & Zhang, Honglei, 2019. "Spatial-temporal forecasting of tourism demand," Annals of Tourism Research, Elsevier, vol. 75(C), pages 106-119.
    7. Jaume Garau Taberner & Carles Manera, 2006. "The Recent Evolution and Impact of Tourism in the Mediterranean: The Case of Island Regions, 1990-2002," Working Papers 2006.108, Fondazione Eni Enrico Mattei.
    8. Carles Manera & Elisabeth Valle, 2018. "Tourist Intensity in the World, 1995–2015: Two Measurement Proposals," Sustainability, MDPI, vol. 10(12), pages 1-20, December.
    9. Anastasiou, Dimitris & Drakos, Konstantinos & Kapopoulos, Panayotis, 2022. "Predicting international tourist arrivals in Greece with a novel sector-specific business leading indicator," MPRA Paper 113860, University Library of Munich, Germany.
    10. Joaquín Alegre & Llorenç Pou, 2006. "An Analysis of the Microeconomic Determinants of Travel Frequency," DEA Working Papers 18, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    11. Leon, Costas & Eeckels, Bruno, 2009. "A Dynamic Correlation Approach of the Swiss Tourism Income," MPRA Paper 15215, University Library of Munich, Germany.

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