Bayesian Forecasting of Chinas Tourism Demand with VAR Models

摘要：

Tourism plays an important role in hastening the development of economy and society in China.This paper extends the existing forecasting accuracy debated in the tourism literature by examining the forecasting performance of various vector autoregressive models,analyze the statistical structure of VAR models,and design three Bayesian VAR models using the parameters Minnesota priors,which would lead to an improvement in forecasting performance.The empirical results based on a data set on the demand for China tourism show that the Bayesian VAR models invariably outperform their unrestricted VAR counterparts.It is noteworthy that the univariate BVAR was found to be the best performing model among all the competing models examined.

关键词： Tourism demand Forecasting analysis VAR models Bayesian method RMSF error

作者: ZHU Huiming YAN Jun

作者单位: School of Business Administration,Hunan University,P.R.China,410082

会议类型: 国际会议

会议名称: 2007 International Conference on Management Science and Engineering(2007管理科学与工程国际学术会议)

会议地点: 河南焦作

会议语种:英文

页码: 2116-2121

在线出版日期: 2007-08-20（万方平台首次上网日期，不代表论文的发表时间）