【作者】 刘媛媛；

【导师】 童光荣；

【作者基本信息】 武汉大学 ， 数量经济学， 2005， 硕士

【摘要】 中国入境旅游市场自1978年以来,一直保持稳步快速发展的趋势,并为我国外汇收入和国际收支平衡做出了巨大贡献。然而,入境旅游业又是一个极度敏感的行业,国际上政治、经济的动荡以及各种突发事件都有可能对入境旅游业产生重大的影响。本文旨在运用计量分析的方法来研究中国入境旅游市场的需求及其变化趋势,建立计量模型来预测中国入境旅游人数。 本文介绍了中国建国以来中国入境旅游市场的发展历程及其对中国国民经济做出的巨大贡献,详细分析了入境旅游业的各项影响因素以及1978年以来对中国入境旅游业造成重大影响的各种突发事件,以此作为模型的构建依据。然后构建了三个计量经济学模型以预测中国入境旅游人数的变化趋势。第一个模型是多元线性回归模型,选择的解释变量为中国居民消费价格指数、国外综合加权汇率、国外综合加权实际GDP以及一个虚拟变量。第二个模型为时间序列模型,采用1976年Box&Jenkins提出的ARIMA(p,d,q)(P,D,Q)_s模型。第三个模型则结合第一个模型与第二个模型的变量和参数,设计出一个线性混合回归模型。最后比较了三个模型预测能力的高低,认为结合了回归与时间序列的模型三为最优模型,建议政府相关单位或相关企业,在预测旅游人数需求时,可采用结合回归与时间序列的计量模型,预测能力应当比单纯时间序列模型或单纯线性回归模型更加准确。更多还原

【Abstract】 Since 1978, Chinese inbound tourism has kept a steadily fast development trend and has made enormous contribution to the foreign exchange revenue and the balance of payments of our country. However, inbound tourism is an extremely sensitive trade, and it may be greatly affected by political and economic turbulence or various kinds of accidents in the world. This thesis is trying to apply quantitative analysis to study the demand of Chinese inbound travel market and its variation tendency, and to create metrics models to predict the number of inbound visitors of China.This thesis introduces the development course of Chinese inbound travel market and its enormous contribution to Chinese national economy, and detailedly analyzes the factors which influence the inbound tourism and various kinds of accidents which have greatly affected Chinese inbound travel business since 1978. These are regarded as the base of the model. And then three econometrics models are structured in order to predict the variation tendency of the number of the inbound travelers of China. The first model is a multi-variable linear regression model. The explanatory variables are Chinese consumer price index, foreign comprehensive weighting exchange rate, foreign comprehensive weighting real GDP and a dummy variable. The second model is a time series model. It adopts the ARIMA(p,d,q)(P,D,Q)_s model which was put forward byBox&Jenkins in 1976. The third model combines the variables and parameters of the first and the second model to create a linear mixture regression model. At last, having compared the predicting ability of the three models, the third model, which combines the regression model and the time series model, is regarded as the optimum model. The thesis suggests the government or relevant enterprises to apply the linear mixture regression model in the forecasting of the number of travelers. It should be more accurate than the simple time series model or the simple linear regression model.更多还原