Monash University
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The tourism forecasting competition

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journal contribution
posted on 2022-09-29, 03:25 authored by George Athanasopoulos, Rob J Hyndman, Haiyan Song, Doris C Wu
We evaluate the performance of various methods for forecasting tourism demand. The data used include 380 monthly series, 427 quarterly series and 530 yearly series, all supplied to us by tourism bodies or by academics from previous tourism forecasting studies. The forecasting methods implemented in the competition are univariate time series approaches, and also econometric models. This forecasting completion differs from previous competitions in several ways: (i) we concentrate only on tourism demand data; (ii) we include econometric approaches; (iii) we evaluate forecast interval coverage as well as point forecast accuracy; (iv) we observe the effect of temporal aggregation on forecasting accuracy; and (v) we consider the mean absolute scaled error as an alternative forecasting accuracy measure.

History

Classification-JEL

C22,C52,C53

Creation date

2008-12

Revision date

2009-10

Working Paper Series Number

10/08

Length

34 pages

File-Format

application/pdf

Handle

RePEc:msh:ebswps:2008-10

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