Abstract:

By using the price monitoring data from 94 agricultural wholesale markets and concurrent hail observation data from March to May during the period 2017 to 2024, the impact of hail weather on vegetable prices in Guizhou province was analyzed based on the VAR model, which revealed how hail intensity indicators (including hail frequency, average hail diameter and maximum hail diameter) affect vegetable price fluctuations. The study aimed to provide a scientific basis for forecasting vegetable prices and assessing the benefits of hail suppression in Guizhou. The results showed that: (1) the weekly average price of vegetables showed a significant positive correlation with days of hail, the correlation coefficient was 0.94 (P＜0.05), and the weekly average price of vegetables rose with the increasing number of days of hail in a week, each additional hail day per week increased the weekly average price of vegetables by 0.14yuan·kg⁻¹. (2) For the same number of hail days, the weekly average price of vegetables increased with larger hail diameters. Within the same hail diameter range, the weekly average price of vegetables increased as the number of hail days increases. (3) Granger causality tests indicated that neither days of hail, average hail diameter and maximum hail diameter significantly predicted the weekly average price of vegetables fluctuations as none of them passed the significance test at the 0.1 level. (4) Regarding the impact on the weekly average vegetable price fluctuation range, the influencing factors are ranked as follows: the days of hail>the average hail diameter>the maximum hail diameter. Regarding the impact on the duration of the weekly average vegetable price fluctuations, the influencing factors are ranked as follows: the days of hail<the average hail diameter≈maximum hail diameter. (5) The contribution of hail frequency to the weekly average vegetable price fluctuations exceeded that of average hail diameter, which was greater than that of maximum hail diameter. Collectively, these three factors accounted for 4.021% contribute to the weekly average vegetable price. 

Key words: VAR model, Hail weather, Vegetable prices, Price shocks