Combination of long term and short term forecasts, with application to tourism demand forecasting

International Journal of Forecasting

Volumn 27, Issue 3, 2011, Pages 870-886

  Andrawis, Robert R ^a   Atiya, Amir F ^a   El Shishiny, Hisham ^b  

^a CAIRO UNIVERSITY   (Egypt)

^b IBM Center for Advanced Studies in Cairo   (Egypt)

Author keywords

Bayesian forecasting ; Exponential smoothing; Forecast combination; Forecasting tourism in Egypt; Holt's model; Time series forecasting; Tourism demand; Tourism forecasting

Indexed keywords

EID: 79956344554     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2010.05.019     Document Type: Article

References (62)

1. Aiolfi M., Timmermann A. Persistence in forecasting performance and conditional combination strategies. Journal of Econometrics 2006, 135:31-53.
2. Andrawis R.R., Atiya A.F. A new Bayesian formulation for Holt's exponential smoothing. Journal of Forecasting 2009, 28:218-234.
3. Armstrong J.S. Combining forecasts. Principles of forecasting: a handbook for researchers and practitioners 2001, Kluwer Academic Publishers, Norwell, MA. J.S. Armstrong (Ed.).
4. Athanasopoulos G., Ahmed R.A., Hyndman R.J. Hierarchical forecasts for Australian domestic tourism. International Journal of Forecasting 2009, 25:146-166.
5. Athanasopoulos G., Hyndman R.J. Modelling and forecasting Australian domestic tourism. Tourism Management 2008, 29:19-31.
6. Bermudez J.D., Segura J.V., Vercher E. Holt-Winters forecasting: an alternative formulation applied to UK air passenger data. Journal of Applied Statistics 2007, 34:1075-1090.
7. Box G., Jenkins G. Time series analysis, forecasting and control 1976, Holden-Day Inc.
8. Casals J., Jerez M., Sotoca S. Modelling and forecasting time series sampled at different frequencies. Journal of Forecasting 2009, 28:316-342.
9. Chang C.-L., Sriboonchitta S., Wiboonpongse A. Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation. Mathematics and Computers in Simulation 2009, 79:1730-1744.
10. Chang I., Tiao G.C., Chen C. Estimation of time series parameters in the presence of outliers. Technometrics 1988, 30:193-204.
11. Chen, H., Ding, K., & Zhang, J. (2007). Properties of weighted geometric means combination forecasting model based on degree of logarithm grey incidence. In Proceedings of the IEEE international conference on grey systems and intelligent services (pp. 673-677).
12. Cholette P.A. Prior information and ARIMA forecasting. Journal of Forecasting 1982, 1:375-384.
13. Chu F.-L. Forecasting tourism: a combined approach. Tourism Management 1998, 19:515-520.
14. Chu F.-L. A fractionally integrated autoregressive moving average approach to forecasting tourism demand. Tourism Management 2008, 29:79-88.
15. Chu F.-L. Forecasting tourism demand with ARMA-based methods. Tourism Management 2009, 30:740-751.
16. Clemen R.T. Combining forecasts: a review and annotated bibliography. International Journal of Forecasting 1989, 5:559-583.
17. De Menezes L.M., Bunn D.W., Taylor J.W. Review of guidelines for the use of combined forecasts. European Journal of Operational Research 2000, 120:190-204.
18. Diebold F.X., Pauly P. The use of prior information in forecast combinations. International Journal of Forecasting 1990, 6:503-508.
19. du Preez J., Witt S.F. Univariate versus multivariate time series forecasting: an application to international tourism demand. International Journal of Forecasting 2003, 19:435-451.
20. Engle R.F., Granger C.W.J., Hallman J.J. Merging short- and long-run forecasts: an application of seasonal co-integration to monthly electricity sales forecasting. Journal of Econometrics 1989, 40:45-62.
21. Faria A.E., Mubwandarikwa E. The geometric combination of Bayesian forecasting models. Journal of Forecasting 2008, 27:519-535.
22. Frechtling D.C. Practical tourism forecasting 1996, Elsevier Publ.
23. Fritz R.G., Brandon C., Xander J. Combining time-series and econometric forecast of tourism activity. Annals of Tourism Research 1984, 11:219-229.
24. Gardner E.S. Exponential smoothing: the state of the art-part II. International Journal of Forecasting 2006, 22:637-666.
25. Gil-Alana A.L., Cunado J., de Gracia F.P. Tourism in the Canary Islands: forecasting using several seasonal time series models. Journal of Forecasting 2008, 27:621-636.
26. Goh C., Law R. Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention. Tourism Management 2002, 23:499-510.
27. Goodwin P., Lawton R. On the asymmetry of symmetric MAPE. International Journal of Forecasting 1999, 15:405-408.
28. Granger C.W.J. Implications of seeing economic variables through an aggregation window. Ricerche Economiche 1993, 47:269-279.
29. Granger C.W.J., Ramanathan R. Improved methods of combining forecasts. Journal of Forecasting 1984, 3:197-204.
30. Greene M.N., Howrey E.P., Hymans S.W. The use of outside information in econometric forecasting. Model reliability 1986, MIT Press, Cambridge, MA. E. Kuh, D.A. Belsley (Eds.).
31. Hilaly, H., & El-Shishiny, H. (2008). Recent advances in econometric modeling and forecasting techniques for tourism demand prediction. In Proceedings of Eurochrie Conference.
32. Hollander M., Wolfe D.A. Nonparametric statistical methods 1973, Wiley.
33. Hyndman R.J. Another look at forecast-accuracy metrics for intermittent demand. Foresight 2006, 4:43-46.
34. Hyndman R.J., Koehler A.B. Another look at measures of forecast accuracy. International Journal of Forecasting 2006, 22:679-688.
35. Hyndman R., Koehler A., Ord K., Snyder R., Grose S. A state space formulation for automatic forecasting using exponential smoothing methods. International Journal of Forecasting 2002, 18:439-454.
36. Kamel N., Atiya A.F., El Gayar N., El-Shishiny H. Tourism demand forecasting using machine learning methods. ICGST International Journal on Artificial Intelligence and Machine Learning 2008, 8:1-7.
37. Kon S.C., Turner L.W. Neural network forecasting of tourism demand. Tourism Economics 2005, 11:301-328.
38. Li G., Song H., Witt S.F. Recent developments in econometric modelling and forecasting. Journal of Travel Research 2005, 44:82-99.
39. Lim C., McAleer M. Forecasting tourist arrivals. Annals of Tourism Research 2001, 28:965-977.
40. Makridakis S., Hibon M. The M3-competition: results, conclusions, and implications. International Journal of Forecasting 2000, 16:451-476.
41. Makridakis S., Wheelwright S.C., Hyndman R.J. Forecasting: methods and applications 1998, Wiley. 3rd ed.
42. Medeiros M.C., McAleer M., Slottje D., Ramos V., Rey-Maquieira J. An alternative approach to estimating demand: neural network regression with conditional volatility for high frequency air passenger arrivals. Journal of Econometrics 2008, 147:372-383.
43. Oh C.O., Morzuch B.J. Evaluating time-series models to forecast the demand for tourism in Singapore: comparing within-sample and post-sample results. Journal of Travel Research 2005, 43:404-413.
44. Patton A.J., Sheppard K. Optimal combinations of realised volatility estimators. International Journal of Forecasting 2009, 25:218-238.
45. Petropoulos C., Nikolopoulos K., Patelis A., Assimakopoulos V. A technical analysis approach to tourism demand forecasting. Applied Economics Letters 2005, 12:327-333.
46. Riedel S., Gabrys B. Combination of multi level forecasts. Journal of VLSI Signal Processing Systems 2007, 49:265-280.
47. Shen S., Li G., Song H. An assessment of combining tourism demand forecasts over different time horizons. Journal of Travel Research 2008, 47:197-207.
48. Song H., Li G. Tourism demand modelling and forecasting-a review of recent research. Tourism Management 2008, 29:203-220.
49. Song H., Witt S.F. Forecasting international tourist flows to Macau. Tourism Management 2004, 27:214-224.
50. Song H., Witt S.F., Wong K.F., Wu D.C. An empirical study of forecast combination in tourism. Journal of Hospitality and Tourism Research 2009, 33:3-29.
51. Stock J.H., Watson M.W. A comparison of linear and nonlinear univariate models for forecasting macroeconomic time series. Cointegration, causality, and forecasting: a festschrift in honour of Clive W.J. Granger 1999, Cambridge University Press, Cambridge, UK. R.F. Engle, H. White (Eds.).
52. Stock J.H., Watson M. Combination forecasts of output growth in a seven-country data set. Journal of Forecasting 2004, 23:405-430.
53. Tashman L. Out-of-sample tests of forecasting accuracy: an analysis and review. International Journal of Forecasting 2000, 16:437-450.
54. Timmermann A. Forecast combinations. Handbook of economic forecasting 2006, 135-196. Elsevier Publ. G. Elliott, C.W.J. Granger, A. Timmermann (Eds.).
55. Trabelsi A., Hillmer S.C. A benchmarking approach to forecast combination. Journal of Business and Economic Statistics 1989, 7:353-362.
56. Tsay R.S. Outliers, level shifts, and variance changes in time series. Journal of Forecasting 1988, 7:1-20.
57. Witt S.F., Newbould G.D., Watkins A.J. Forecasting domestic tourism demand: application to Las Vegas arrivals data. Journal of Travel Research 1992, 31:36-41.
58. Witt S.F., Witt C.A. Forecasting tourism demand: a review of empirical research. International Journal of Forecasting 1995, 11:447-475.
59. Wong K., Song H. Tourism forecasting and marketing 2002, The Haworth Hospitality Press, New York.
60. Wong K.F., Song H., Chon K. Bayesian models for tourism demand forecasting. Tourism Management 2006, 27:773-780.
61. Wong K.F., Song H., Witt S.F., Wu D.C. Tourism forecasting: to combine or not to combine?. Tourism Management 2007, 28:1068-1078.
62. Zaki A. An econometric model forecasting Egypt's aggregate international tourism demand and revenues. Tourism and Hospitality Planning and Development 2008, 5:215-232.