资源科学 ›› 2021, Vol. 43 ›› Issue (2): 304-315.doi: 10.18402/resci.2021.02.09
收稿日期:
2020-02-26
修回日期:
2020-07-05
出版日期:
2021-02-25
发布日期:
2021-04-25
通讯作者:
江民星
作者简介:
翟志宏,男,江西九江人,博士研究生,高级工程师,研究方向为气候经济学。E-mail: 基金资助:
ZHAI Zhihong1,2(), JIANG Minxing3,4,5(
), CHANG Chunying6
Received:
2020-02-26
Revised:
2020-07-05
Online:
2021-02-25
Published:
2021-04-25
Contact:
JIANG Minxing
摘要:
降水对蔬菜价格波动有重要影响,分析降水的蔬菜价格冲击效应对菜价预测及市场供需调整具有重要意义。本文首先构建了一个包含降水因素的蔬菜供需动态模型,揭示逐日降水对菜价的影响机制,并阐明了降水对不同蔬菜冲击效应存在异质性的原因;然后基于广州市2004—2018年逐日的菜心、生菜和豆角3种蔬菜零售价格数据及降水数据,采用VAR模型、脉冲响应函数和预测方差分解方法来验证上述影响机制,并量化降水在月和日尺度上对3种蔬菜价格的冲击效应。研究发现:①一定条件下逐日过量降水对菜价具有正向冲击作用,即导致菜价上涨,且冲击效应与蔬菜需求价格弹性呈反向关系。②菜价受降水的冲击在不同时间尺度上异质性明显,日尺度的冲击效应表现更为敏感,降水对菜心、生菜和豆角价格冲击在日尺度上分别在第16、20和10 d达到最大,随后减弱;而月尺度的冲击效应具有明显滞后性(滞后一个月),冲击较强但持续性不强。③日降水对菜心、生菜和豆角价格波动的贡献率分别约8.3%、18.4%和1.0%;月尺度降水相对日尺度降水而言,对3种菜价的影响更大,贡献率分别约为24.0%、18.1%和10.7%。最后,本文提出了针对降水过量时期稳定蔬菜价格的政策建议。
翟志宏, 江民星, 常春英. 降水对蔬菜价格的冲击效应——以广州为例[J]. 资源科学, 2021, 43(2): 304-315.
ZHAI Zhihong, JIANG Minxing, CHANG Chunying. Impact of precipitation on vegetable prices: Taking Guangzhou City as an example[J]. Resources Science, 2021, 43(2): 304-315.
表1
变量描述性统计"
变量符号 | 变量名称 | 变量取值 | 均值 | 标准差 | 最小值 | 最大值 | |
---|---|---|---|---|---|---|---|
月度 | rain_m | 降水量 | 月降水量/mm | 169.8 | 161.6 | 0.0 | 834.6 |
lncx_m | 菜心价格 | 月菜心价格,取对数 | 1.675 | 0.376 | 0.800 | 2.867 | |
lnsc_m | 生菜价格 | 月生菜价格,取对数 | 1.398 | 0.444 | 0.311 | 2.773 | |
lndj_m | 豆角价格 | 月豆角价格,取对数 | 1.908 | 0.356 | 1.059 | 2.989 | |
日度 | rain_d | 降水量 | 日降水量/mm | 5.6 | 15.2 | 0.0 | 222.1 |
lncx_d | 菜心价格 | 日菜心价格,取对数 | 1.662 | 0.411 | 0.000 | 3.401 | |
lnsc_d | 生菜价格 | 日生菜价格,取对数 | 1.383 | 0.477 | 0.000 | 3.584 | |
lndj_d | 豆角价格 | 日豆角价格,取对数 | 1.895 | 0.381 | 0.956 | 3.178 |
表2
最优的滞后阶数"
变量 | Lag | LL | LR | FPE | AIC | HQIC | SBIC | |
---|---|---|---|---|---|---|---|---|
月度 | lncx_m | 12 | -915.278 | 19.903* | 646.366* | 12.142* | 12.534 | 13.107 |
lnsc_m | 8 | -971.266 | 10.183 | 1065.01* | 12.645* | 12.911 | 13.301 | |
lndj_m | 12 | -870.738 | 24.297* | 369.118* | 11.582* | 11.974 | 12.547 | |
日度 | lncx_d | 8 | -16726.4 | 42.168 | 1.673* | 6.190* | 6.205* | 6.232 |
lnsc_d | 12 | -16859.5 | 8.862 | 2.046* | 6.392* | 6.414 | 6.454 | |
lndj_d | 19 | -14614.0 | 15.592 | 1.638* | 6.169* | 6.206 | 6.275 |
表3
Granger因果关系检验结果"
原假设 | chi2 | df | Prob>chi2 | |
---|---|---|---|---|
月度数据 | rain_m不是lncx_m的格兰杰原因 | 69.341 | 12 | 0.000 |
lncx_m不是rain_m的格兰杰原因 | 22.946 | 12 | 0.028 | |
rain_m不是lnsc_m的格兰杰原因 | 67.123 | 8 | 0.000 | |
lnsc_m不是rain_m的格兰杰原因 | 21.523 | 8 | 0.006 | |
rain_m不是lndj_m的格兰杰原因 | 49.436 | 12 | 0.000 | |
lndj_m不是rain_m的格兰杰原因 | 39.801 | 12 | 0.000 | |
日度数据 | rain_d不是lncx_d的格兰杰原因 | 71.249 | 8 | 0.000 |
lncx_d不是rain_d的格兰杰原因 | 13.021 | 8 | 0.111 | |
rain_d不是lnsc_d的格兰杰原因 | 109.230 | 12 | 0.000 | |
lnsc_d不是rain_d的格兰杰原因 | 13.865 | 12 | 0.309 | |
rain_d不是lndj_d的格兰杰原因 | 52.739 | 19 | 0.000 | |
lndj_d不是rain_d的格兰杰原因 | 34.912 | 19 | 0.014 |
表4
月度数据方差分解结果"
时期 | lncx_m对lncx_m 的贡献 | rain_m对lncx_m 的贡献 | lnsc_m对lnsc_m 的贡献 | rain_m对lnsc_m 的贡献 | lndj_m对lndj_m 的贡献 | rain_m对lndj_m 的贡献 |
---|---|---|---|---|---|---|
1 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
2 | 0.879 | 0.121 | 0.883 | 0.117 | 0.969 | 0.031 |
3 | 0.879 | 0.121 | 0.880 | 0.121 | 0.959 | 0.041 |
4 | 0.870 | 0.130 | 0.875 | 0.125 | 0.945 | 0.056 |
5 | 0.873 | 0.127 | 0.873 | 0.128 | 0.935 | 0.065 |
6 | 0.840 | 0.160 | 0.881 | 0.119 | 0.937 | 0.063 |
7 | 0.804 | 0.196 | 0.871 | 0.129 | 0.937 | 0.063 |
8 | 0.791 | 0.209 | 0.850 | 0.150 | 0.929 | 0.071 |
9 | 0.779 | 0.221 | 0.833 | 0.167 | 0.928 | 0.072 |
10 | 0.773 | 0.227 | 0.834 | 0.166 | 0.922 | 0.078 |
11 | 0.774 | 0.226 | 0.838 | 0.162 | 0.910 | 0.091 |
12 | 0.760 | 0.240 | 0.841 | 0.160 | 0.911 | 0.089 |
13 | 0.758 | 0.242 | 0.839 | 0.161 | 0.893 | 0.107 |
14 | 0.759 | 0.241 | 0.829 | 0.172 | 0.900 | 0.101 |
15 | 0.761 | 0.239 | 0.819 | 0.181 | 0.903 | 0.097 |
16 | 0.764 | 0.236 | 0.815 | 0.185 | 0.903 | 0.097 |
17 | 0.759 | 0.241 | 0.815 | 0.185 | 0.903 | 0.097 |
18 | 0.749 | 0.251 | 0.816 | 0.184 | 0.901 | 0.099 |
19 | 0.747 | 0.253 | 0.814 | 0.186 | 0.900 | 0.100 |
20 | 0.746 | 0.254 | 0.808 | 0.192 | 0.892 | 0.108 |
表5
日度数据方差分解表"
时期 | lncx_d对lncx_d 的贡献 | rain_d对lncx_d 的贡献 | lnsc_d对lnsc_d 的贡献 | rain_d对lnsc_d 的贡献 | lndj_d对lndj_d 的贡献 | rain_d对lndj_d 的贡献 |
---|---|---|---|---|---|---|
1 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
2 | 1.000 | 0.000 | 0.999 | 0.001 | 1.000 | 0.000 |
3 | 1.000 | 0.000 | 0.999 | 0.001 | 0.999 | 0.001 |
4 | 1.000 | 0.000 | 0.997 | 0.003 | 1.000 | 0.001 |
5 | 0.999 | 0.001 | 0.995 | 0.005 | 1.000 | 0.000 |
6 | 0.998 | 0.002 | 0.991 | 0.009 | 0.999 | 0.001 |
7 | 0.995 | 0.005 | 0.986 | 0.014 | 0.998 | 0.002 |
8 | 0.991 | 0.009 | 0.979 | 0.021 | 0.996 | 0.004 |
9 | 0.983 | 0.017 | 0.968 | 0.032 | 0.994 | 0.006 |
10 | 0.977 | 0.023 | 0.957 | 0.043 | 0.992 | 0.008 |
11 | 0.971 | 0.029 | 0.946 | 0.054 | 0.990 | 0.010 |
12 | 0.965 | 0.035 | 0.935 | 0.066 | 0.989 | 0.012 |
13 | 0.961 | 0.039 | 0.923 | 0.077 | 0.988 | 0.012 |
14 | 0.956 | 0.044 | 0.912 | 0.088 | 0.988 | 0.012 |
15 | 0.952 | 0.048 | 0.903 | 0.097 | 0.988 | 0.012 |
16 | 0.948 | 0.052 | 0.894 | 0.106 | 0.988 | 0.012 |
17 | 0.945 | 0.055 | 0.886 | 0.114 | 0.988 | 0.012 |
18 | 0.942 | 0.059 | 0.878 | 0.122 | 0.989 | 0.011 |
19 | 0.938 | 0.062 | 0.871 | 0.129 | 0.989 | 0.011 |
20 | 0.936 | 0.064 | 0.864 | 0.136 | 0.989 | 0.011 |
21 | 0.933 | 0.067 | 0.858 | 0.142 | 0.990 | 0.010 |
22 | 0.931 | 0.069 | 0.852 | 0.148 | 0.990 | 0.010 |
23 | 0.929 | 0.072 | 0.847 | 0.154 | 0.990 | 0.010 |
24 | 0.927 | 0.074 | 0.841 | 0.159 | 0.990 | 0.010 |
25 | 0.925 | 0.075 | 0.836 | 0.164 | 0.991 | 0.009 |
26 | 0.923 | 0.077 | 0.832 | 0.168 | 0.991 | 0.009 |
27 | 0.921 | 0.079 | 0.827 | 0.173 | 0.991 | 0.009 |
28 | 0.920 | 0.080 | 0.823 | 0.177 | 0.991 | 0.009 |
29 | 0.918 | 0.082 | 0.819 | 0.181 | 0.991 | 0.009 |
30 | 0.917 | 0.083 | 0.816 | 0.184 | 0.992 | 0.008 |
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