IDEAS home Printed from https://ideas.repec.org/a/sae/toueco/v29y2023i8p2032-2056.html
   My bibliography  Save this article

Does the combination of models with different explanatory variables improve tourism demand forecasting performance?

Author

Listed:
  • Xi Wu
  • Adam Blake

Abstract

The aim of this study is to assess whether combining econometric models with different explanatory variables can contribute to better tourism demand forecasts. Inbound tourism demand to the UK from seven leading markets is forecast, respectively, based on quarterly data using both individual and combination models. Causal econometric models that serve as constituents in combination take two specifications which are different in identified influencing factors. The empirical results show that generally including different explanatory variables in combination can produce better predictions according to both predictive accuracy measures and statistical tests. It suggests that the combination forecasting approach is superior to the individual one, and diversified information embedded in different explanatory variables should be integrated to improve tourism demand forecasting performance.

Suggested Citation

  • Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
    • Handle: RePEc:sae:toueco:v:29:y:2023:i:8:p:2032-2056
    DOI: 10.1177/13548166221132645
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/13548166221132645
    Download Restriction: no
    File URL: https://libkey.io/10.1177/13548166221132645?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. Gunter, Ulrich & Önder, Irem, 2015. "Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data," Tourism Management, Elsevier, vol. 46(C), pages 123-135.
    2. Holmen, Jay S., 1987. "A note on the value of combining short-term earnings forecasts : A test of Granger and Ramanathan," International Journal of Forecasting, Elsevier, vol. 3(2), pages 239-243.
    3. Song, Haiyan & Gartner, William C. & Tasci, Asli D.A., 2012. "Visa restrictions and their adverse economic and marketing implications – Evidence from China," Tourism Management, Elsevier, vol. 33(2), pages 397-412.
    4. Christiane Baumeister & Lutz Kilian, 2015. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 338-351, July.
    5. Zhang, Xinyu & Yu, Jihai, 2018. "Spatial weights matrix selection and model averaging for spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 203(1), pages 1-18.
    6. Hyndman, Rob J. & Koehler, Anne B. & Snyder, Ralph D. & Grose, Simone, 2002. "A state space framework for automatic forecasting using exponential smoothing methods," International Journal of Forecasting, Elsevier, vol. 18(3), pages 439-454.
    7. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
    8. Qiu, Richard T.R. & Wu, Doris Chenguang & Dropsy, Vincent & Petit, Sylvain & Pratt, Stephen & Ohe, Yasuo, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Asia and Pacific team," Annals of Tourism Research, Elsevier, vol. 88(C).
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. 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.
    11. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886.
    12. 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, July.
    13. Lobo, Gerald J., 1991. "Alternative methods of combining security analysts' and statistical forecasts of annual corporate earnings," International Journal of Forecasting, Elsevier, vol. 7(1), pages 57-63, May.
    14. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    15. Kourentzes, Nikolaos & Saayman, Andrea & Jean-Pierre, Philippe & Provenzano, Davide & Sahli, Mondher & Seetaram, Neelu & Volo, Serena, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team," Annals of Tourism Research, Elsevier, vol. 88(C).
    16. Francis X. Diebold & Peter Pauly, 1987. "Structural change and the combination of forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 21-40.
    17. James H. Stock & Mark W. Watson, 2003. "How did leading indicator forecasts perform during the 2001 recession?," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 89(Sum), pages 71-90.
    18. LeSage, James P & Magura, Michael, 1992. "A Mixture-Model Approach to Combining Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 445-452, October.
    19. Scott, Daniel & Hall, C. Michael & Gössling, Stefan, 2019. "Global tourism vulnerability to climate change," Annals of Tourism Research, Elsevier, vol. 77(C), pages 49-61.
    20. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Combination forecasts of tourism demand with machine learning models," Applied Economics Letters, Taylor & Francis Journals, vol. 23(6), pages 428-431, April.
    21. Gang Xie & Xin Li & Yatong Qian & Shouyang Wang, 2021. "Forecasting tourism demand with KPCA-based web search indexes," Tourism Economics, , vol. 27(4), pages 721-743, June.
    22. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
    23. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 39-46, January.
    24. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    25. Liu, Anyu & Vici, Laura & Ramos, Vicente & Giannoni, Sauveur & Blake, Adam, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team," Annals of Tourism Research, Elsevier, vol. 88(C).
    26. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    27. Luis A. Gil-Alana, 2010. "International Arrivals in the Canary Islands: Persistence, Long Memory, Seasonality and other Implicit Dynamics," Tourism Economics, , vol. 16(2), pages 287-302, June.
    28. Chan, Chi Kin & Witt, Stephen F. & Lee, Y.C.E. & Song, H., 2010. "Tourism forecast combination using the CUSUM technique," Tourism Management, Elsevier, vol. 31(6), pages 891-897.
    29. Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
    30. Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
    31. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886, July.
    32. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    33. Holt, Charles C., 2004. "Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'," International Journal of Forecasting, Elsevier, vol. 20(1), pages 11-13.
    34. Spyros Makridakis & Robert L. Winkler, 1983. "Averages of Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 29(9), pages 987-996, September.
    35. Hassani, Hossein & Silva, Emmanuel Sirimal & Antonakakis, Nikolaos & Filis, George & Gupta, Rangan, 2017. "Forecasting accuracy evaluation of tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 112-127.
    36. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2018. "The M4 Competition: Results, findings, conclusion and way forward," International Journal of Forecasting, Elsevier, vol. 34(4), pages 802-808.
    37. Shuang Cang, 2011. "A Non-Linear Tourism Demand Forecast Combination Model," Tourism Economics, , vol. 17(1), pages 5-20, February.
    38. Li, Gang & Wu, Doris Chenguang & Zhou, Menglin & Liu, Anyu, 2019. "The combination of interval forecasts in tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 363-378.
    39. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    40. Diebold, Francis X. & Pauly, Peter, 1990. "The use of prior information in forecast combination," International Journal of Forecasting, Elsevier, vol. 6(4), pages 503-508, December.
    41. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    42. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
    2. 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.
    3. 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.
    4. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    5. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    6. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    7. 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.
    8. Shaolong Suna & Dan Bi & Ju-e Guo & Shouyang Wang, 2020. "Seasonal and Trend Forecasting of Tourist Arrivals: An Adaptive Multiscale Ensemble Learning Approach," Papers 2002.08021, arXiv.org, revised Mar 2020.
    9. Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
    10. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    11. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    12. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    13. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    14. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    15. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    16. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    17. Xie, Gang & Qian, Yatong & Wang, Shouyang, 2020. "A decomposition-ensemble approach for tourism forecasting," Annals of Tourism Research, Elsevier, vol. 81(C).
    18. Bacci, Livio Agnew & Mello, Luiz Gustavo & Incerti, Taynara & Paulo de Paiva, Anderson & Balestrassi, Pedro Paulo, 2019. "Optimization of combined time series methods to forecast the demand for coffee in Brazil: A new approach using Normal Boundary Intersection coupled with mixture designs of experiments and rotated fact," International Journal of Production Economics, Elsevier, vol. 212(C), pages 186-211.
    19. 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.
    20. Jing Zeng, 2015. "Combining Country-Specific Forecasts when Forecasting Euro Area Macroeconomic Aggregates," Working Paper Series of the Department of Economics, University of Konstanz 2015-11, Department of Economics, University of Konstanz.

    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:29:y:2023:i:8:p:2032-2056. 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.