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Practical Tourism Forecasting : the Example of Asia Pacific. Stephen F. Witt Emeritus Professor (Tourism Forecasting). My Background. Mathematics Mathematical statistics Economics Econometrics PhD – econometric study of UK outbound tourism demand.
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Practical Tourism Forecasting : the Example of Asia Pacific Stephen F. Witt Emeritus Professor (Tourism Forecasting)
My Background Mathematics Mathematical statistics Economics Econometrics PhD – econometric study of UK outbound tourism demand
Academic Research – Books & Journal Papers Econometric modelling of international tourism demand Assessment of accuracy of different forecasting methods within tourism context, i.e. which methods work best under what circumstances (time horizon, data frequency, ….)
Application of Academic Research Results Take results from academic research on tourism forecasting and apply to practical tourism forecasting situations Various consultancy studies for companies and destinations NTOs Ongoing annual publication of tourism forecasts for Pacific Asia Travel Association (PATA)
Asia Pacific Tourism Forecasts Lindsay W. Turner, Victoria University, Melbourne Stephen F. Witt, University of Surrey Publisher: PATA, Bangkok
Initial publisher Travel and Tourism Intelligence, London ( part of Corporate Intelligence Group) Asia Pacific Tourism Forecasts 2000-2004, published in 2000 Subsequently switched to PATA, publishing with them every year since 2001 Asia Pacific Tourism Forecasts 2012-2014, published in 2012
40 Asia Pacific destinations • Forecasts by country of origin • 1,400 forecast series • International arrivals forecast to grow 5% to Asia Pacific to reach ½ billion by 2014 6% to Asia 3% to North America 2% to Pacific
Methodology Model Selection • Time series models estimated from data series and give mathematical projection of seasonal, cyclical and trend components BSM (basic structural model) • Add dummy variables where appropriate to allow for political instability, terrorist activity, natural disasters (cyclones, tsunamis), financial crises, health threats (SARS, H1N1) or other events expected to influence time series BSM + interventions
Add economic variables: decision to keep/remove variable based on correct sign according to economic theory and statistical significance CSM (causal structural model) • Within sample 8 quarters forecasting accuracy testing • If results not good try another method such as ECM (error correction model) or TVP (time varying parameter) model
Forecast Adjustment • Forecasts generated by quantitative process assessed by experts (PATA, NTOs …) as to likely inaccuracies given any unmeasured factors the experts consider may raise or lower numbers • Quantitative model derived forecasts are adjusted to take expert to opinion into account
Economic Variables • Income (per capita PDI or GDP) • Destination price (destination CPI divided by origin CPI adjusted by origin – destination exchange rate) • Air fare index
International Tourist Arrivals to Asia Pacific Markets Total North America