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 , published in 2000 Subsequently switched to PATA, publishing with them every year since 2001 Asia Pacific Tourism Forecasts , 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 % 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

Top 10 Forecast Asia Pacific Destinations

THAILAND Forecast Arrivals

Top 5 Departures Forecasts from Asia Pacific Main Markets Australia to AAGR (%) New Zealand1,119,8791,140, USA904,2471,315, Singapore880,4861,212, Thailand698,0461,073, China661,300846, China to Hong Kong22,684,38835,234, Macau13,229,05822,522, Korea (ROK)1,875,1572,837, Chinese Taipei1,630,7351,907, Japan1,412,8751,169,

Hong Kong to AAGR (%) China79,321,90083,882, Macau7,466,1397,804, Chinese Taipei794,362827, Japan508,691320, Singapore387,552700, India to Singapore828,9031,006, Thailand760,3711,360, Malaysia690,8491,044, USA650,935712, China549,300738,

Japan to AAGR (%) USA3,386,0763,492, China3,731,2003,836, Korea (ROK)3,023,0093,437, Hong Kong1,316,6181,304, Chinese Taipei1,080,1531,478, Korea (ROK) to China4,076,4004,647, Japan2,439,8162,444, USA1,107,5181,320, Hong Kong891,0241,356, Thailand805,4451,473,

USA to AAGR (%) Mexico17,967,69119,241, Canada11,746,36612,413, China2,009,6002,351, Hong Kong1,171,4191,267, India915,5791,256,

Tourist Arrivals from SA to Asia Pacific Destinations North America AAGR (%) Mexico4,8616, USA80,17497, Northeast Asia Chinese Taipei4,0664, Hong Kong77,65891, Korea (ROK)9,63311, Macau4,6246, South Asia Bhutan India55,68869, Maldives3,1575, Pakistan5,84611, Sri Lanka1,4152,

Southeast Asia AAGR (%) Indonesia12,69116, Malaysia26,39530, Philippines2,7744, Singapore32,42837, Thailand57,10090, Pacific Australia62,17069, New Zealand17,40125,