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Forecasting tourist arrivals using time-varying parameter structural time series models

Author

Listed:
  • Song, Haiyan
  • Li, Gang
  • Witt, Stephen F.
  • Athanasopoulos, George

Abstract

Empirical evidence has shown that seasonal patterns of tourism demand and the effects of various influencing factors on this demand tend to change over time. To forecast future tourism demand accurately requires appropriate modelling of these changes. Based on the structural time series model (STSM) and the time-varying parameter (TVP) regression approach, this study develops the causal STSM further by introducing TVP estimation of the explanatory variable coefficients, and therefore combines the merits of the STSM and TVP models. This new model, the TVP-STSM, is employed for modelling and forecasting quarterly tourist arrivals to Hong Kong from four key source markets: China, South Korea, the UK and the USA. The empirical results show that the TVP-STSM outperforms all seven competitors, including the basic and causal STSMs and the TVP model for one- to four-quarter-ahead ex post forecasts and one-quarter-ahead ex ante forecasts.

Suggested Citation

  • Song, Haiyan & Li, Gang & Witt, Stephen F. & Athanasopoulos, George, 2011. "Forecasting tourist arrivals using time-varying parameter structural time series models," International Journal of Forecasting, Elsevier, vol. 27(3), pages 855-869, July.
  • Handle: RePEc:eee:intfor:v:27:y::i:3:p:855-869
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    References listed on IDEAS

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    1. repec:eee:touman:v:45:y:2014:i:c:p:181-193 is not listed on IDEAS
    2. repec:bla:jecsur:v:32:y:2018:i:2:p:302-334 is not listed on IDEAS
    3. repec:eee:eneeco:v:71:y:2018:i:c:p:114-127 is not listed on IDEAS
    4. Lengyel, Attila, 2016. "Tourism, meditation, sustainability," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 0(Number 1), pages 1-11, March.
    5. Zeynalov, Ayaz, 2014. "Nowcasting Tourist Arrivals to Prague: Google Econometrics," MPRA Paper 60945, University Library of Munich, Germany.
    6. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    7. repec:eee:touman:v:47:y:2015:i:c:p:213-223 is not listed on IDEAS
    8. repec:jtr:journl:v:10:y:2015:i:1:p:125-142 is not listed on IDEAS
    9. repec:eee:touman:v:46:y:2015:i:c:p:322-335 is not listed on IDEAS
    10. repec:ptu:bdpart:e201613 is not listed on IDEAS

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