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中国旅游经济增长动态路径的阶段性变迁识别——基于马尔科夫区制转移模型的实证分析
引用本文:隋建利,刘金全,闫超.中国旅游经济增长动态路径的阶段性变迁识别——基于马尔科夫区制转移模型的实证分析[J].旅游学刊,2013,28(7):22-32.
作者姓名:隋建利  刘金全  闫超
作者单位:吉林大学数量经济研究中心,吉林长春,130012
基金项目:国家社科基金重大项目,国家自然科学基金项目,教育部人文社会科学研究项目,中国博士后科学基金特别资助项目,中国博士后科学基金面上项目
摘    要:文章基于我国国内和国际旅游收入年度数据,在分别对其总量和增长率序列进行定量探讨后,运用双阶段马尔科夫区制转移模型,对我国旅游经济增长动态过程进行阶段性变迁识别和转移分析。结论表明:(1)随着时间的推移,国内和国际旅游收入均大体呈不断攀升的态势,国内旅游收入增长率呈U形变化,而国际旅游收入增长率呈周期性变化特征。(2)国内(国际)旅游收入维系快速(低速)增长的可能性要强于其保持低速(快速)增长的可能性,国内(国际)旅游收入维系快速(低速)增长的可能性要强于国际(国内)旅游收入。(3)无论是国内旅游收入还是国际旅游收入,当其增长率较高时,通常都会存在潜在的较大不确定性,当其增长率较低时,所面临风险冲击的可能性也较小,国际旅游收入快速(低速)增长时的波动性显著强于国内旅游收入快速(低速)增长时的波动性。(4)从近年来的发展趋势看,国内旅游收入增长率仍然具有持续攀升的强劲势头,同时也将会伴随较大的波动性,国际旅游收入增长率维持平缓低位推进的可能性较大,与此相对应的波动性较小。

关 键 词:旅游经济  国内旅游收入  国际旅游收入  马尔科夫区制转移模型

Phase Transfer Identification of China's Tourism Economy Dynamic Path:Based on Markov Regime Switching Model
SUI Jianli , LIU Jinquan , YAN Chao.Phase Transfer Identification of China's Tourism Economy Dynamic Path:Based on Markov Regime Switching Model[J].Tourism Tribune,2013,28(7):22-32.
Authors:SUI Jianli  LIU Jinquan  YAN Chao
Institution:( Quantitative Research Center of Economics, Jilin University, Changchun 130012, China)
Abstract:Drawing on domestic tourism revenue data from 1994 to 2011 and international tourism revenue data from 1978 to 2021, we will use a dual-stage Markov regime switching model to identify and characterize the multi-stage process of growth in China's tourism industry. Our objective in this study is to measure and consider the growth rate of China's tourism revenue, and to analyze the transition probability of changes between different stages. We identified and performed a transfer analysis of phased changes in the dynamic process of the growth of China's tourism economy, and ultimately reached the following conclusions: First, domestic and international tourism revenue both generally show a rising trend over time. The data from the growth rate of domestic tourism form a U-shaped curve. Domestic tourism revenue growth is still strong and momentum has continued to increase, but it may be accompanied by greater volatility. The international tourism growth rate has been cyclical in recent years. The growth rate of international tourism revenue is likely to maintain a steady trend, that is, its potential for volatility is likely to be smaller. Second, domestic tourism revenue in a stage of slow growth is significantly weaker than when it is in a stage of rapid growth. Domestic tourism revenue is more likely to maintain its rapid growth. International tourism revenue in its ongoing slow-growth stage is significantly stronger than when it is in its rapid-growth phase. International tourism, therefore, is more likely to maintain a slow growth rate. For both domestic and international tourism revenue, a higher rate of growth usually means a greater potential for uncertainty and volatility. When the growth rate is lower, the possibility of risk is correspondingly smaller. Third, international tourism revenue entered a stage of rapid growth that was still weaker than the rapid growth experienced by domestic tourism revenue, which demonstrates that domestic tourism revenue is more likely to maintain the potential for rapid growth than international tourism revenue. In addition, the volatility of international tourism revenue in its rapid-growth phase was significantly stronger than that of domestic tourism revenue, and the volatility of international tourism revenue in the slow-growth stage was stronger than that of domestic tourism revenue. Fourth, along with the ongoing development of China's tourism economy, both domestic and international tourism revenue growth have resulted in significant structural changes between the stages of slow growth and rapid growth. Judging from the trends of recent years, the rising growth rate of domestic tourism revenue will gain momentum, but may also be accompanied by a greater volatility; international tourism revenue growth rate will maintain a steady trend.
Keywords:tourism economy  domestic tourism revenue  international tourism revenue  Markov regime switchmodel
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