全国和区域蔬菜价格走势特征及影响因素

Analysis of the features of vegetable price trend and its influencing factors at national and regional scale in China

关键词:  农产品  蔬菜  市场信息  市场价格  价格波动  时间序列分析

Key words:  agricultural production  vegetable  market information  market price  price volatility  time series analysis

摘要:

以上海蔬菜价格为例，采用时间序列分析和建模方法，研究全国和区域蔬菜价格的走势特征及其影响因素。结果表明:1)1995—2002年全国蔬菜年均价呈缓慢降低走势，2003年开始呈现快速上升走势，2017年以后有所下降，2010—2018年上海蔬菜年均价与全国蔬菜年均价走势一致，但低于全国蔬菜价格水平；2)全国和上海的月均价和日均价表现出明显的季节性、不规则性，上海蔬菜价格的不规则波动性高于全国蔬菜价格；3)全国和上海蔬菜月均价的时间序列分析模型结果表明，全国蔬菜价格与前3年同月价格、当年前1月价格有较高的关联性，而上海蔬菜价格与当年前4个月价格的关联性最高，与前2年同月价格也有较高关联性；4)全国和上海蔬菜年均价均与上期价格、生产成本、居民消费价格指数、人均可支配收入有较高的正相关关系，一元回归分析表明，蔬菜价格受居民消费价格指数影响最大。根据研究结果，建议加强区域尺度农产品市场信息的研究，从而据此调控生产，使产品供应更好满足市场需求。

Abstract:

Research on the market information of agricultural products is helpful to adjust the produce and supply to better meet market demand, and the price change of agricultural products is the wind vane reflecting the market situation. The vegetable price trend characteristics and its influencing factors at national and regional scale in China were analyzed. The vegetable price in Shanghai is selected as study object. The result showed that the price of vegetables in China decreased slowly from 1995 to 2002, and it began to rise from 2003, and declined again after 2017. The vegetable prices in Shanghai were consistent with the national vegetable prices, but they are lower than the national vegetable prices during 2010-2018. The monthly and daily vegetable prices in China and Shanghai showed obvious seasonality and irregularity, and the irregular volatility of vegetable prices in Shanghai was higher than that in China. The results of the time series analysis model of vegetables price in China and Shanghai displayed that the price of vegetable in China was highly correlated with the price of the same period over last 3 years and the price in the earlier month of that year, while the price of vegetable in Shanghai was highly correlated with the price of the same period of last 2 years and the price in the earlier 4 months of that year. Among all influencing factors, the national vegetable price and Shanghai vegetable price had higher positive correlation with last year's price, production cost, consumer price index and per capita disposable income. The results of univariate regression analysis with each factor showed that the vegetable price had the highest relevance with consumer price index. According to the research results, it is suggested to strengthen the research on the market information of agricultural products at the regional level, that is possible for the production management to make the product supply better meet the market demand.