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A new approach to modelling and forecasting monthly guest nights in hotels

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  • Brannas, Kurt
  • Hellstrom, Jorgen
  • Nordstrom, Jonas

Abstract

Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect the daily mean check-in and the daily check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables is minute.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 18 (2002)
Issue (Month): 1 ()
Pages: 19-30

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Handle: RePEc:eee:intfor:v:18:y:2002:i:1:p:19-30

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Web page: http://www.elsevier.com/locate/ijforecast

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References

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  1. Melenberg, B. & Soest, A.H.O. van, 1991. "Parametric and semi-parametric modelling of vacation expenditures," Discussion Paper 1991-44, Tilburg University, Center for Economic Research.
  2. Martin, Christine A. & Witt, Stephen F., 1989. "Forecasting tourism demand: A comparison of the accuracy of several quantitative methods," International Journal of Forecasting, Elsevier, vol. 5(1), pages 7-19.
  3. Kurt Brannas & Jorgen Hellstrom, 2001. "Generalized Integer-Valued Autoregression," Econometric Reviews, Taylor & Francis Journals, vol. 20(4), pages 425-443.
  4. Brewer, K. R. W., 1973. "Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models," Journal of Econometrics, Elsevier, vol. 1(2), pages 133-154, June.
  5. Gonzalez, Pilar & Moral, Paz, 1995. "An analysis of the international tourism demand in Spain," International Journal of Forecasting, Elsevier, vol. 11(2), pages 233-251, June.
  6. Young, Peter & Pedregal, Diego, 1997. "Comments on "An analysis of the international tourism demand in Spain" by P. Gonzalez and P. Moral," International Journal of Forecasting, Elsevier, vol. 13(4), pages 551-556, December.
  7. Adamowicz, Wiktor L., 1994. "Habit Formation And Variety Seeking In A Discrete Choice Model Of Recreation Demand," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(01), July.
  8. 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.
  9. Kulendran, N. & King, Maxwell L., 1997. "Forecasting international quarterly tourist flows using error-correction and time-series models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 319-327, September.
  10. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
  11. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1997. "A note on forecasting international tourism demand in Spain," International Journal of Forecasting, Elsevier, vol. 13(4), pages 539-549, December.
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Cited by:
  1. Kurt Brannas & A. M. M. Shahiduzzaman Quoreshi, 2010. "Integer-valued moving average modelling of the number of transactions in stocks," Applied Financial Economics, Taylor & Francis Journals, vol. 20(18), pages 1429-1440.
  2. Brännäs, Kurt & Lönnbark, Carl, 2006. "Effects of Explanatory Variables in Count Data Moving Average Models," UmeÃ¥ Economic Studies 679, Umeå University, Department of Economics.
  3. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer, vol. 92(3), pages 319-341, August.
  4. Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
  5. Quoreshi, Shahiduzzaman, 2005. "Modelling High Frequency Financial Count Data," UmeÃ¥ Economic Studies 656, Umeå University, Department of Economics.
  6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
  7. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
  8. Juan Luis Eugenio-Martín & Noelia Martín Morales & Riccardo Scarpa, 2004. "Tourism and Economic Growth in Latin American Countries: A Panel Data Approach," Working Papers 2004.26, Fondazione Eni Enrico Mattei.

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