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Total tourist arrival forecast: aggregation vs. disaggregation

  • WAN, Shui-Ki

    (Hong Kong Baptist University)

  • WANG, Shin-Huei

    (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium; CEREFIM, FUNDP, Belgium)

  • WOO, Chi-Keung

    (Houston Baptist University, Texas, USA)

Total tourist arrivals are the sum of disaggregate subcomponent arrivals by country of origin. We use seven time-series models to assess whether the aggregate approach that directly forecasts the total tourist arrivals outperforms the disaggregate approach that produces the total arrival forecast as an unweighted sum of its subcomponent forecasts. Based on Hong Kong's monthly tourist arrival data, we find (a) the seasonal autoregressive integrated moving average model outperforms the other non-seasonal and seasonal models under the aggregate approach, and (b) forecast performance can be improved by the disaggregate approach.

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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2012039.

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Date of creation: 11 Oct 2012
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Handle: RePEc:cor:louvco:2012039
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  1. Bruneau, C. & De Bandt, O. & Flageollet, A. & Michaux, E., 2003. "Forecasting Inflation using Economic Indicators: the Case of France," Working papers 101, Banque de France.
  2. Granger, C. W. J., 1987. "Implications of Aggregation with Common Factors," Econometric Theory, Cambridge University Press, vol. 3(02), pages 208-222, April.
  3. Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
  4. 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.
  5. Pesaran, M Hashem & Pierse, Richard G & Kumar, Mohan S, 1989. "Econometric Analysis of Aggregation in the Context of Linear Prediction Models," Econometrica, Econometric Society, vol. 57(4), pages 861-88, July.
  6. Tobias, Justin & Zellner, Arnold, 2000. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12024, Iowa State University, Department of Economics.
  7. A. Espasa & E. Senra & R. Albacete, 2002. "Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 402-421.
  8. Lutkepohl, Helmut, 1984. "Forecasting Contemporaneously Aggregated Vector ARMA Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 201-14, July.
  9. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
  10. Cheng Hsiao & Yan Shen & Hiroshi Fujiki, 2002. "Aggregate vs Disaggregate Data Analysis - A Paradox in the Estimation of Money Demand Function of Japan Under the Low Interest Rate Policy," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A4-1, International Conferences on Panel Data.
  11. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  12. Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 0247, European Central Bank.
  13. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
  14. Van Garderen, K. J. & Lee, K. & Pesaran M., 1998. "Cross-sectional Aggregation of Non-linear Models," Cambridge Working Papers in Economics 9803, Faculty of Economics, University of Cambridge.
  15. Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
  16. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
  17. Michael P. Clements & David F. Hendry, 2002. "Modelling methodology and forecast failure," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 319-344, 06.
  18. Kohn, Robert, 1982. "When is an aggregate of a time series efficiently forecast by its past?," Journal of Econometrics, Elsevier, vol. 18(3), pages 337-349, April.
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