文章摘要
价格支持政策背景下中国小麦市场区域动态关联分析
Dynamic integration analysis of wheat markets in China under the background of price support policy
投稿时间:2017-11-01  修订日期:2018-01-17
DOI:10.13872/j.1000-0275.2018.0007
中文关键词: 小麦  价格波动  价格支持政策  动态关联性  贝叶斯DCC-GARCH模型
英文关键词: wheat  price volatility  price support policy  dynamic correlation  the Bayesian DCC-GARCH model
基金项目:国家社会科学基金重点项目(17AJY019);国家现代农业产业技术体系资助项目(CARS-03-08B)
作者单位E-mail
李雪 中国农业大学经济管理学院 北京 100083 lx.lixue@163.com 
韩一军 中国农业大学经济管理学院 北京 100083 hyjcau@126.com 
付文阁 中国农业大学经济管理学院 北京 100083 fuwenge@cau.edu.cn 
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中文摘要:
      区域市场间的关联程度能够反映市场一体化程度,衡量市场运行效率,分析价格支持政策背景下中国不同地区小麦市场间的关联程度及其动态变化,对于提高小麦市场运行效率具有现实意义。基于7个地区小麦市场价格周数据,运用贝叶斯DCC-GARCH模型,分析不同地区间价格波动特征及其动态关联性,并结合政策的执行探讨地区间价格波动和关联程度变化的原因。结果表明,政策执行区小麦市场价格的波动程度更平缓,受上期的影响更大。地区市场间的关联程度仍有待提高,关联度均值最高的河北和山东、河北和天津小麦市场分别为0.265和0.257,超过0.2的占全部市场组的1/3。价格支持政策启动时期市场间的关联度明显高于其他时期,政策的执行有利于提高市场的整合程度。地理位置、交通便利条件、生产区域集中程度、政策干预等因素都对市场关联度有重要影响。因此,建议短期内继续保留最低收购价政策框架,确定合理的政策价格水平;改善主产区和主销区小麦物流设施,提高流通效率;不断完善国内市场体系,促进粮食生产和加工的专业化分工与规模化发展。
英文摘要:
      The degree of correlation among regional markets can delegate the degree of market integration, and it is an important indicator to illustrate overall market performance. It has great significance to improve the market efficiency through well understanding the correlation and dynamic volatility of wheat markets in different regions of China under the background of price support policy. Based on regional weekly wheat price data and applying the Bayesian DCC-GARCH Model, this paper empirically analyzed the price fluctuation characteristics and dynamic integration among different regional wheat markets and discussed the behind causes and the influencing factors. Results show that the price volatilities in policy implemented areas were more stable and also more susceptible to the previous period. The correlation among different regional wheat markets still need to be improved in China. The correlation index between Hebei and Shandong and the one between Hebei and Tianjin were relatively higher compared to others, which were 0.265 and 0.257, respectively. Over 1/3 of the correlation indices were above 0.2. The implementation of the price support policy did increase the correlation among different regional markets and improved wheat market integration. In addition, location, geographic proximity, the relative concentration of production areas and government intervenes were also important influencing factors for market integration. Therefore, this paper suggests: to continue the minimum purchasing price policy in the short term with a reasonable target price level, to improve the logistic facilities of wheat markets to increase circulation efficiency, and to continuously improve market mechanism to promote the specialization and scale development of grain production and processing.
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