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International Journal of Forecasting 27 (2011) 870886 www.elsevier.com/locate/ijforecast
 

Summary: International Journal of Forecasting 27 (2011) 870886
www.elsevier.com/locate/ijforecast
Combination of long term and short term forecasts, with
application to tourism demand forecasting
Robert R. Andrawisa, Amir F. Atiyaa,, Hisham El-Shishinyb
a Department of Computer Engineering, Cairo University, Giza, Egypt
b IBM Center for Advanced Studies in Cairo, IBM Cairo Technology Development Center, Giza, Egypt
Available online 15 September 2010
Abstract
Forecast combination is a well-established and well-tested approach for improving the forecasting accuracy. One beneficial
strategy is to use constituent forecasts that have diverse information. In this paper we consider the idea of diversity being
accomplished by using different time aggregations. For example, we could create a yearly time series from a monthly time series
and produce forecasts for both, then combine the forecasts. These forecasts would each be tracking the dynamics of different
time scales, and would therefore add diverse types of information. A comparison of several forecast combination methods,
performed in the context of this setup, shows that this is indeed a beneficial strategy and generally provides a forecasting
performance that is better than the performances of the individual forecasts that are combined.
As a case study, we consider the problem of forecasting monthly tourism numbers for inbound tourism to Egypt. Specifically,
we consider 33 individual source countries, as well as the aggregate. The novel combination strategy also produces a generally
improved forecasting accuracy.
c 2010 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

  

Source: Atiya, Amir - Computer Engineering Department, Cairo University

 

Collections: Computer Technologies and Information Sciences