主产区柑橘价格的空间关联效应研究——基于VAR模型与社会网络分析法

STUDY ON SPATIAL CORRELATION EFFECT OF CITRUS PRICE IN MAIN PRODUCING AREAS——BASED ON VAR MODEL AND SNA MODEL

关键词:  主产区  柑橘价格  空间关联效应  VAR模型  社会网络分析

Key words:  main production area  citrus price  spatial correlation effect  VAR model  social network analysis

摘要:

目的 柑橘产区价格处于价格链前端，既对果农收入产生直接影响又直接作用于销区价格，对柑橘全产业链发展具有深远影响。探究主产区柑橘价格的空间关联效应，对明晰柑橘价格的空间传递机制，降低柑橘价格异常波动风险和保障果农收入具有重要的现实意义。方法 文章采用1999—2018年主产区柑橘价格数据，基于向量自回归模型对主产区柑橘价格的空间关联关系进行了分析，运用社会网络分析法刻画、解构了我国主产区柑橘价格空间关联网络。结果 （1）格兰杰因果检验结果表明我国6个柑橘主产区存在14条价格空间关联关系，具有显著的空间关联效应。（2）主产区柑橘价格空间关联网络密度为0.433 3，关联度为1，等级度为0.692 3，效率为0.7，网络具有良好的稳定性和互惠性。（3）主产区柑橘价格存在明显的空间传递，各主产区的传导地位和作用不同。湖北与其他主产省份关联最多，在网络中扮演着“中心行动者”的角色；湖南、江西和广东在网络中扮演着“边缘行动者”的角色，对网络边缘地区柑橘价格存在较大影响；湖北、重庆、广东在网络中扮演了“中介行动者”的角色，在价格信息传递过程中起到“桥梁”作用。结论 各主产区地方政府应针对自身产区在柑橘价格空间关联网络中的地位和作用，提高柑橘价格市场信息服务能力和风险管理水平，有效平抑产区柑橘价格的异常波动和空间滞后。

Abstract:

The price of citrus production areas is in the front end of the price chain, which has a direct impact on the income of farmers and the price of the marketing areas, and has a profound impact on the development of the whole citrus industry chain. Exploring the spatial correlation effect of citrus prices in the main production areas is of great practical significance to clarify the spatial transmission mechanism of citrus prices, reduce the risk of abnormal fluctuations in citrus prices and ensure the income of fruit farmers. Based on the citrus price data from 1999 to 2018, spatial correlations of citrus prices in the main producing areas were analyzed with vector autoregressive (VAR) models, and social network analysis (SNA) method was used to portray and deconstruct the spatial correlation network of citrus prices in the main producing areas in China. The results were listed as follows. (1) The results of Granger's causality test showed that there were 14 price spatial correlations with significant spatial correlation effects in the main citrus producing areas of China. (2) The spatial correlation network density of citrus prices in the main producing areas was 0.433 3, the correlation degree was 1, the rank degree was 0.692 3, the efficiency was 0.7, and the network had good stability and reciprocity. (3) There existed an obvious spatial transmission of citrus prices in the main producing areas of China, and the transmission status and role of each main producing area were different. Hubei province had the most connections with other main producing provinces and played the role of "central actor" in the network; Hunan province, Jiangxi province and Guangdong province played the role of "peripheral actor" in the network and had a greater influence on the citrus prices in the peripheral areas of the network; Hubei province, Chongqing and Guangdong province played the role of "intermediary actor" in the network, undertaking a "bridge" role in the process of price information transmission. In summary, the local government of each main producing area should improve the citrus price market information service capability and risk management level for the status and role of their own producing areas in the citrus price spatial correlation network, so as to effectively suppress the abnormal fluctuation and spatial lag of citrus prices in the producing areas.