郭娜, 闫英杰. 天气因素对蔬菜价格恢复力的影响——以石家庄市本地黄瓜为例[J]. 中国生态农业学报(中英文), 2015, 23(6): 785-792. DOI: 10.13930/j.cnki.cjea.150456
引用本文: 郭娜, 闫英杰. 天气因素对蔬菜价格恢复力的影响——以石家庄市本地黄瓜为例[J]. 中国生态农业学报(中英文), 2015, 23(6): 785-792. DOI: 10.13930/j.cnki.cjea.150456
GUO Na, YAN Yingjie. Impact of weather on vegetable price resilience— A case study of the local cucumber in Shijiazhuang City[J]. Chinese Journal of Eco-Agriculture, 2015, 23(6): 785-792. DOI: 10.13930/j.cnki.cjea.150456
Citation: GUO Na, YAN Yingjie. Impact of weather on vegetable price resilience— A case study of the local cucumber in Shijiazhuang City[J]. Chinese Journal of Eco-Agriculture, 2015, 23(6): 785-792. DOI: 10.13930/j.cnki.cjea.150456

天气因素对蔬菜价格恢复力的影响——以石家庄市本地黄瓜为例

Impact of weather on vegetable price resilience— A case study of the local cucumber in Shijiazhuang City

  • 摘要: 蔬菜价格的波动影响到经济和社会生活的诸多方面, 减小各种因素影响,稳定蔬菜价格已成为社会关注的焦点之一。为了研究天气因素对蔬菜价格恢复力的影响, 本文以石家庄市本地黄瓜为例, 采用2011年10月至2014年5月石家庄市月度降水量、气温和日照时数的时间序列数据, 通过向量自回归(VAR)模型的格兰杰(Granger)因果关系检验, 证实了降水量、气温和日照时数等天气因素的变动会引起黄瓜价格的波动。在此基础上构建了蔬菜价格恢复力模型, 测度了天气因素对黄瓜价格的干扰压力及黄瓜价格对各天气因素的敏感程度, 并计算了各天气因素影响下的黄瓜价格恢复力。Granger因果关系检验结果表明, 在5%显著性水平下, 降水量和气温是黄瓜价格波动的Granger原因; 在10%显著性水平下, 日照时数是黄瓜价格波动的Granger原因, 即降水量、气温和日照时数等天气因素的变动会引起黄瓜价格的波动。价格敏感系数计算结果表明, 黄瓜价格对降水量和温度变化的敏感程度相对较小, 而对日照时数的敏感程度较高; 日照时数、气温、降水量都会影响黄瓜价格恢复力, 其中日照时数的影响最明显, 当日照时数发生变化时, 黄瓜价格恢复力较小; 当降水量或气温发生变化时, 黄瓜价格恢复力相对较大。考虑到各种天气因素主要是通过影响蔬菜供给而导致其价格波动, 研究提出, 针对天气因素提升蔬菜价格恢复力应主要从供给角度采取相应措施, 以降低这些不利天气因素的影响, 具体包括加强雾霾治理力度, 缓解日照时数降低对蔬菜供给的影响; 加快发展设施农业, 提高蔬菜生产对天气变化的抵御能力; 加强农业基础设施建设, 提高蔬菜生产对天气变化的应对能力; 强化技术创新, 缓解天气变化对蔬菜供应的负面影响等方面。

     

    Abstract: Controlling fluctuation of vegetables prices, which influences many aspects of economy and society, have been one of focuses of social attention. To clarify the effect of weather factors on vegetables price volatility and resilience, with the local cucumber of Shijiazhuang City as an example, the paper used monthly time-series data of precipitation, temperature and sunshine hours of Shijiazhuang from October 2011 to May 2014, and confirmed that cucumber price volatility could be caused by fluctuations of weather factors, such as, precipitation, temperature and sunshine hours by using Granger causality test of vector auto regression (VAR) model. On this basis, the paper constructed vegetable price resilience model, measured the interference pressure of weather factors on cucumber price and the sensitivity of cucumber price to weather factors, and calculated the cucumber price resilience under weather factors disturbance. Granger causality test results showed significant relationship of cucumber price volatility with precipitation and temperature at < 5% probability and with sunshine hours at < 10% probability. The sensitivity coefficient of cucumber price to sunshine hours change was higher than those to precipitation and temperature changes. Fluctuations of precipitation, temperature and sunshine hours affected cucumber price resilience, of which sunshine hours was most obvious. The price resilience of cucumber price under changed sunshine hours was weaker than those under changed precipitation and temperature. Considering that weather factors affected vegetable prices resilience primarily through affecting vegetables supply, the study proposed that appropriate measures enhancing the vegetable prices resilience under changed whether factors should aim at adjusting vegetable production. Specific measures included reducing impact of sunshine hours decreasing on vegetables production through combating haze, developing agricultural facilities and infrastructure to improve vegetable production resisting ability to weather changes, strengthening agricultural technology innovation to mitigate the negative impact of weather changes on vegetables production.

     

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