Effect of seasonality treatment on the forecasting performance of tourism demand models

Shen, S., Li, G. and Song, H. 2009. Effect of seasonality treatment on the forecasting performance of tourism demand models. Tourism Economics. 15 (4), pp. 693-708.

TitleEffect of seasonality treatment on the forecasting performance of tourism demand models
AuthorsShen, S., Li, G. and Song, H.
Abstract

This study provides a comprehensive comparison of the performance

of the commonly used econometric and time-series models in forecasting

seasonal tourism demand. The empirical study is carried out

based on the demand for outbound leisure tourism by UK residents

to seven destination countries: Australia, Canada, France, Greece,

Italy, Spain and the USA. In the modelling exercise, the seasonality

of the data is treated using the deterministic seasonal dummies,

seasonal unit root test techniques and the unobservable component

method. The empirical results suggest that no single forecasting

technique is superior to the others in all situations. As far as overall

forecast accuracy is concerned, the Johansen maximum likelihood

error correction model outperforms the other models. The time-series

models also show superior performance in dealing with seasonality.

However, the time-varying parameter model performs relatively poorly

in forecasting seasonal tourism demand. This empirical evidence

suggests that the methods of seasonality treatment affect the forecasting

performance of the models and that the pre-test for seasonal

unit roots is necessary and can improve forecast accuracy.

JournalTourism Economics
Journal citation15 (4), pp. 693-708
ISSN1354-8166
YearDec 2009
PublisherIP Publishing
Digital Object Identifier (DOI)doi:10.5367/000000009789955116
Publication dates
PublishedDec 2009

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