Tourism demand forecasting: A time varying parameter error correction model

Gang Li, Kevin K.F. Wong, Haiyan Song, Stephen F. Witt

Research output: Journal article publicationJournal articleAcademic researchpeer-review

136 Citations (Scopus)


The advantages of error correction models (ECMs) and time varying parameter (TVP) models have been discussed in the tourism forecasting literature. These models are now combined to give a new single-equation model, the time varying parameter error correction model (TVP-ECM), which is applied for the first time in the context of tourism demand forecasting. The empirical study focuses on tourism demand, measured by tourism spending per capita, by U.K. residents for five key Western European destinations. The empirical results show that the TVP-ECM can be expected to outperform a number of alternative econometric and time-series models in forecasting the demand for tourism, especially in forecasting the growth rate of tourism demand. A practical implication of this result is that the TVP-ECM approach should be used when forecasting tourism growth is concerned.
Original languageEnglish
Pages (from-to)175-185
Number of pages11
JournalJournal of Travel Research
Issue number2
Publication statusPublished - 1 Jan 2006


  • Error correction model
  • Ex post forecasting
  • Kalman filter
  • Time-varying parameter
  • Tourism demand

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Tourism, Leisure and Hospitality Management


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