地理学报 ›› 2021, Vol. 76 ›› Issue (10): 2585-2604.doi: 10.11821/dlxb202110017

• 减贫与乡村发展 • 上一篇    下一篇

价格支持政策改革背景下中国玉米市场空间关联

丁存振()   

  1. 山东农业大学经济管理学院,泰安 271018
  • 收稿日期:2020-08-18 修回日期:2021-07-27 出版日期:2021-10-25 发布日期:2021-12-25
  • 作者简介:丁存振(1988-), 男, 博士, 副教授, 研究方向为农产品市场与政策。E-mail: dingcunzhen2010@163.com
  • 基金资助:
    国家自然科学基金项目(72073084)

Spatial correlation of corn markets under the background of price support policy reform in China

DING Cunzhen()   

  1. College of Economics and Management, Shandong Agricultural University, Tai'an 271018, Shandong, China
  • Received:2020-08-18 Revised:2021-07-27 Published:2021-10-25 Online:2021-12-25
  • Supported by:
    National Natural Science Foundation of China(72073084)

摘要:

玉米市场空间关联是反映玉米市场运行效率的关键指标,价格支持政策的实施及改革对玉米市场空间关联产生重要影响。本文基于中国省际玉米市场价格数据,分析了价格支持政策改革背景下玉米市场空间关联及其时变情况,并运用社会网络分析法刻画了玉米市场空间关联网络特征,最后,通过QAP分析考察了影响玉米市场空间关联的主要因素。研究发现:① 中国玉米市场总体空间关联程度较高,且近年来整体呈上升趋势,玉米临时收储政策的实施并未改变其上升趋势,但导致政策实施省份玉米市场与其他地区玉米市场间关联程度下降。② 玉米市场空间关联呈现多线程、复杂的网络结构形态,网络结构较为紧密、整体关联性强且较为稳定;中东部地区玉米消费量较大的省份在玉米市场空间关联网络中处于中心位置,在网络中扮演着中心行动者角色,而实施玉米支持政策的区域以及西部地区在玉米市场空间关联网络中影响力较小,处于边缘和弱势地位,扮演着边缘行动者角色。③ 地理位置邻接、市场距离、销区市场势力、信息传递效应以及实施临时收储政策是决定和影响玉米市场空间关联的主要因素,其中,销区市场势力及信息传递效应对玉米市场空间关联的影响不断上升。

关键词: 价格支持政策, 空间关联, 社会网络分析(SNA), QAP分析, 玉米, 中国

Abstract:

Market spatial correlation is one of the key indicators that reflect the operation efficiency of corn markets. The implementation and reform of corn price support policy in China plays an important role in changing the spatial correlation of corn markets. Employing market price data at province level, this study first analyzed the change of corn market spatial correlations under the price support policy reform. Then, social network analysis was applied to describe the network characteristics of corn market spatial correlations, and quadratic assignment procedure (QAP) analysis was used to investigate key factors that affected the spatial correlation. The results indicated that, (1) overall, the spatial correlation of China's corn markets was relatively high, and there was an upward trend in recent years. The implementation of temporary corn storage policy exerted insignificant effect on this upward trend, but it led to a decrease in the spatial correlation between markets in policy-affected provinces and those in non-policy affected provinces. (2) The spatial correlation of corn markets presented a multi-threaded and complex network structure, which was closely related and stable as a whole. Provinces with large corn consumption in the central and eastern regions were at the center of the spatial correlation network and played as the central actor in the network. However, provinces in the western region and provinces implementing corn support policy had little effect on the spatial correlation network of corn markets, indicating their marginal and disadvantaged role in the network. (3) Geographical proximity, market distance, market power, information transmission effect and the implementation of temporary storage policy were the key factors that affected the spatial correlation of corn markets. Furthermore, the role of market power and information transmission effect in determining the spatial correlation has become increasingly important.

Key words: price support policy, spatial correlation, social network analysis method (SNA), quadratic assignment procedure (QAP), corn, China