In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations i...In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.展开更多
运用共同趋势与共同周期（common trend and common cycles）理论，研究中国与东盟国家之间的经济周期在波动中是否存在同步性．以1994—2005年问中国与东盟的GDP季度时间序列为基础，建立了多变量向量误差修正模型．实证分析发现：中...运用共同趋势与共同周期（common trend and common cycles）理论，研究中国与东盟国家之间的经济周期在波动中是否存在同步性．以1994—2005年问中国与东盟的GDP季度时间序列为基础，建立了多变量向量误差修正模型．实证分析发现：中国与东盟国家GDP季度时间序列之间在短期内有共同周期，在长期里存在共同发展趋势；中国与东盟国家经济周期在考察样本期间具有同步性，满足金融合作最重要的前提条件；中国与东盟国家应当进一步强化彼此间的经贸交流和经济金融合作，真正发挥区域经济之间的相互带动作用，从而实现区域经济的共同繁荣．展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.71371160)the Program for Changjiang Youth Scholars(No.Q2016131)the Program for New Century Excellent Talents in University(No.NCET-13-0509)
文摘In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.
文摘运用共同趋势与共同周期（common trend and common cycles）理论，研究中国与东盟国家之间的经济周期在波动中是否存在同步性．以1994—2005年问中国与东盟的GDP季度时间序列为基础，建立了多变量向量误差修正模型．实证分析发现：中国与东盟国家GDP季度时间序列之间在短期内有共同周期，在长期里存在共同发展趋势；中国与东盟国家经济周期在考察样本期间具有同步性，满足金融合作最重要的前提条件；中国与东盟国家应当进一步强化彼此间的经贸交流和经济金融合作，真正发挥区域经济之间的相互带动作用，从而实现区域经济的共同繁荣．
