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Is the Time-Varying Parameter Model the Preferred Approach to Tourism Demand Forecasting? Statistical Evidence

  • Shujie Shen
  • Gang Li
  • Haiyan Song
Chapter

Introduction

Over the past 50 years, tourism has become one of the largest and most rapidly growing sectors in the world economy (Eadington and Redman 1991). Accurate forecasts of tourism demand are critical to both private sectors and governments in providing useful information for business strategy formulation and public policy making, respectively. A large body of literature has been published on tourism demand forecasting using regression techniques, and studies in this research stream have made a significant contribution to the understanding of international tourism demand. However, these studies are based on the assumption that the values of the parameters in the demand models are constant over time, an assumption that has been challenged by a number of researchers for being too restrictive (Song and Witt 2000, Song and Wong 2003, Li et al. 2005). A more sophisticated and flexible econometric forecasting method – the time varying parameter (TVP) model – has been developed to...

Keywords

Mean Square Error Forecast Error Mean Absolute Percentage Error Forecast Accuracy Origin Country 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2009

Authors and Affiliations

  1. 1.Institute for Transport StudiesUniversity of LeedsLeedsUK
  2. 2.University of SurreySchool of ManagementGuilfordUK
  3. 3.Hong Kong Polytechnic UniversityHong Kong SARChina

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