IDEAS home Printed from https://ideas.repec.org/a/sae/toueco/v11y2005i4p517-537.html
   My bibliography  Save this article

Testing Alternative Dynamic Systems for Modelling Tourism Demand

Author

Listed:
  • Maria M. De Mello

    (Centro de Estudos de Economia Industrial, do Trabalho e da Empresa (CETE), Universidade do Porto, Faculdade de Economia do Porto, Rua Dr. Roberto Frias, 4200-464 Porto, Portugal)

  • Natércia Fortuna

    (Centro de Estudos Macroeconómicos e Previsão (CEMPRE), Universidade do Porto)

Abstract

This paper presents an empirical study of tourism demand dynamics and identifies areas in which the scrutiny of relationships between theoretical and empirical considerations is likely to produce new insights. A flexible general form of a Dynamic Almost Ideal Demand System (DAIDS) is derived to analyse UK tourism demand for the neighbouring destinations of Portugal, Spain and France during 1969–97. Nested within the general dynamic structure are Deaton and Muellbauer's static AIDS model itself, the partial adjustment model and the auto-regressive distributed lag model, which are tested against the general dynamic alternative. The empirical results obtained show that DAIDS is a data-coherent and theoretically consistent model, providing evidence of the robustness of this methodology for tourism demand analysis in a temporal context. Moreover, the dynamic model offers statistically strong evidence of the inadequacy of the orthodox static AIDS and other restricted models for the consistent reconciliation of data and theory within their formulations. Estimates for tourism price and expenditure elasticities are obtained, permitting a comparative analysis of the relative magnitudes and statistical relevance of the long-run and short-run sensitivity of UK tourism demand to changes in its determinants.

Suggested Citation

  • Maria M. De Mello & Natércia Fortuna, 2005. "Testing Alternative Dynamic Systems for Modelling Tourism Demand," Tourism Economics, , vol. 11(4), pages 517-537, December.
    • Handle: RePEc:sae:toueco:v:11:y:2005:i:4:p:517-537
    DOI: 10.5367/000000005775108719
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5367/000000005775108719
    Download Restriction: no
    File URL: https://libkey.io/10.5367/000000005775108719?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
    ---><---

    References listed on IDEAS

    as
    1. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
    2. Maria De Mello & Kevin Nell, 2005. "The forecasting ability of a cointegrated VAR system of the UK tourism demand for France, Spain and Portugal," Empirical Economics, Springer, vol. 30(2), pages 277-308, September.
    3. Gordon Anderson & Richard Blundell, 1983. "Testing Restrictions in a Flexible Dynamic Demand System: An Application to Consumers' Expenditure in Canada," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(3), pages 397-410.
    4. Andreas Papatheodorou, 1999. "The demand for international tourism in the Mediterranean region," Applied Economics, Taylor & Francis Journals, vol. 31(5), pages 619-630.
    5. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, October.
    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. Bonham, Carl & Gangnes, Byron & Zhou, Ting, 2009. "Modeling tourism: A fully identified VECM approach," International Journal of Forecasting, Elsevier, vol. 25(3), pages 531-549, July.
    2. 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.
    3. Jian-Wu Bi & Tian-Yu Han & Hui Li, 2022. "International tourism demand forecasting with machine learning models: The power of the number of lagged inputs," Tourism Economics, , vol. 28(3), pages 621-645, May.
    4. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
    5. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
    6. Jorge M. Andraz & Nélia M. Norte & Hugo S. Gonçalves, 2016. "Do tourism spillovers matter in regional economic analysis? An application to Portugal," Tourism Economics, , vol. 22(5), pages 939-963, October.
    7. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.
    8. İhsan Erdem Kayral & Tuğba Sarı & Nisa Şansel Tandoğan Aktepe, 2023. "Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
    9. Ogechi Adeola & Nathaniel Boso & Olaniyi Evans, 2018. "Drivers of international tourism demand in Africa," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 53(1), pages 25-36, January.
    10. Mihaela Simionescu, 2017. "The Relationship Between Tourist Arrivals And Accomodation In Romanian Regions. A Panel Data Approach," Revista de turism - studii si cercetari in turism / Journal of tourism - studies and research in tourism, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 23(23), pages 1-2, June.
    11. Saayman, Andrea & Viljoen, Armand & Saayman, Melville, 2018. "Africa’s outbound tourism: An Almost Ideal Demand System perspective," Annals of Tourism Research, Elsevier, vol. 73(C), pages 141-158.

    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. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    2. Maria M. De Mello & Natércia Fortuna, 2005. "Testing Alternative Dynamic Systems for Modelling Tourism Demand," CEF.UP Working Papers 0501, Universidade do Porto, Faculdade de Economia do Porto.
    3. Guizzardi, Andrea & Mazzocchi, Mario, 2010. "Tourism demand for Italy and the business cycle," Tourism Management, Elsevier, vol. 31(3), pages 367-377.
    4. Price, David W. & Gislason, Conrad, 2001. "Identification of habit in Japanese food consumption," Agricultural Economics, Blackwell, vol. 24(3), pages 289-295, March.
    5. Li, Gang & Song, Haiyan & Cao, Zheng & Wu, Doris Chenguang, 2013. "How competitive is Hong Kong against its competitors? An econometric study," Tourism Management, Elsevier, vol. 36(C), pages 247-256.
    6. De Zhou & Xiaohua Yu & Thomas Herzfeld, 2015. "Dynamic food demand in urban China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(1), pages 27-44, February.
    7. Oral CAPPS, 1993. "Uses Of Supermarket Scan Data In Demand Analysis," Emerging Data Issues in Applied Food Demand Analysis; s21693capp01, S216, Food Demand and Consumption Behavior Regional Committee.
    8. Deschamps, P J, 1993. "Joint Tests for Regularity and Autocorrelation in Allocation Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(2), pages 195-211, April-Jun.
    9. Peng, Bo & Song, Haiyan & Crouch, Geoffrey I., 2014. "A meta-analysis of international tourism demand forecasting and implications for practice," Tourism Management, Elsevier, vol. 45(C), pages 181-193.
    10. T. Kesavan & Zuhair A. Hassan & Helen H. Jensen & Stanley R. Johnson, 1993. "Dynamics and Long-run Structure in U.S. Meat Demand," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 41(2), pages 139-153, July.
    11. Kyrre Rickertsen, 1998. "The demand for food and beverages in Norway," Agricultural Economics, International Association of Agricultural Economists, vol. 18(1), pages 89-100, January.
    12. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer, 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," CIRJE F-Series CIRJE-F-735, CIRJE, Faculty of Economics, University of Tokyo.
    13. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.
    14. Ramesh Durbarry, 2008. "Tourism Taxes: Implications for Tourism Demand in the UK," Review of Development Economics, Wiley Blackwell, vol. 12(1), pages 21-36, February.
    15. Marie-Louise Mangion & Ramesh Durbarry & M. Thea Sinclair, 2005. "Tourism Competitiveness: Price and Quality," Tourism Economics, , vol. 11(1), pages 45-68, March.
    16. Philippe J. Deschamps, 2003. "Time-varying intercepts and equilibrium analysis: an extension of the dynamic almost ideal demand model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 209-236.
    17. Adam G. Walke & Thomas M. Fullerton Jr., 2019. "Metropolitan Hotel Sector Forecast Accuracy in El Paso," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 179-191, June.
    18. Isabel Cortés-Jiménez & Ramesh Durbarry & Manuela Pulina, 2009. "Estimation of Outbound Italian Tourism Demand: A Monthly Dynamic EC-LAIDS Model," Tourism Economics, , vol. 15(3), pages 547-565, September.
    19. Chen, Shu-Ling & Chern, Wen S. & Lin, Yi-Ru & Liu, Kang Ernest, 2015. "Effects of food safety and health risk information on demand for food in Taiwan," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205452, Agricultural and Applied Economics Association.
    20. Marie-Louise Mangion & Chris Cooper & Isabel Cortés-Jimenez & Ramesh Durbarry, 2012. "Measuring the Effect of Subsidization on Tourism Demand and Destination Competitiveness through the AIDS Model: An Evidence-Based Approach to Tourism Policymaking," Tourism Economics, , vol. 18(6), pages 1251-1272, December.

    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:sae:toueco:v:11:y:2005:i:4:p:517-537. 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: SAGE Publications (email available below). General contact details of provider: .

    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.