不同地区城镇居民收入对食品消费水足迹的影响——基于QUAIDS模型
|
杨鑫, 穆月英
|
Impact of urban residential income on consumptive water footprints of food in different regions based on QUAIDS modeling
|
Xin YANG, Yueying MU
|
|
表4 不同地区食品水足迹的价格弹性和收入弹性 |
Table 4 Price elasticity and income elasticity of food water footprints in different regions |
|
地区 | 水足迹类型 | 食品水足迹价格弹性 | 食品水足迹收入弹性 | 粮食 | 油脂 | 肉类 | 蛋类 | 水产品 | 蔬菜 | 酒类 | 瓜果 | 乳品 | 东北部 | 总水足迹 | -0.234 | -0.053 | -0.186 | -0.089 | 0.024 | -0.098 | -0.029 | -0.134 | -0.089 | 0.708 | 绿水 | -0.262 | -0.048 | -0.193 | -0.087 | 0.043 | -0.083 | -0.032 | -0.130 | -0.070 | 0.688 | 蓝水 | 0.041 | -0.114 | -0.394 | -0.037 | -0.441 | -0.011 | 0.090 | -0.033 | -0.219 | 0.894 | 灰水 | -0.196 | -0.055 | -0.092 | -0.111 | 0.090 | -0.188 | -0.055 | -0.185 | -0.129 | 0.737 | 东部 | 总水足迹 | -0.172 | -0.038 | -0.236 | -0.084 | 0.004 | -0.110 | -0.036 | -0.120 | -0.114 | 0.670 | 绿水 | -0.192 | -0.034 | -0.253 | -0.085 | 0.033 | -0.103 | -0.033 | -0.114 | -0.097 | 0.649 | 蓝水 | 0.035 | -0.079 | -0.343 | -0.027 | -0.521 | -0.011 | 0.068 | -0.026 | -0.192 | 0.810 | 灰水 | -0.161 | -0.046 | -0.128 | -0.108 | 0.075 | -0.185 | -0.057 | -0.173 | -0.168 | 0.703 | 中部 | 总水足迹 | -0.267 | -0.063 | -0.208 | -0.076 | 0.036 | -0.070 | -0.047 | -0.107 | -0.080 | 0.726 | 绿水 | -0.298 | -0.057 | -0.207 | -0.074 | 0.054 | -0.053 | -0.052 | -0.109 | -0.057 | 0.703 | 蓝水 | 0.060 | -0.128 | -0.525 | -0.002 | -0.451 | -0.002 | 0.087 | 0.050 | -0.238 | 0.945 | 灰水 | -0.227 | -0.068 | -0.114 | -0.104 | 0.104 | -0.170 | -0.067 | -0.146 | -0.136 | 0.763 | 西部 | 总水足迹 | -0.258 | -0.067 | -0.218 | -0.060 | 0.022 | -0.047 | -0.048 | -0.148 | -0.065 | 0.754 | 绿水 | -0.287 | -0.062 | -0.220 | -0.059 | 0.032 | -0.025 | -0.054 | -0.150 | -0.039 | 0.733 | 蓝水 | 0.064 | -0.129 | -0.564 | -0.001 | -0.368 | -0.021 | 0.109 | 0.019 | -0.255 | 0.973 | 灰水 | -0.225 | -0.073 | -0.105 | -0.084 | 0.095 | -0.157 | -0.065 | -0.186 | -0.125 | 0.786 |
|
|
|