基于企业大数据的京津冀制造业集聚的影响因素
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黄宇金, 盛科荣, 孙威
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Influencing factors of manufacturing agglomeration in the Beijing-Tianjin-Hebei region based on enterprise big data
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HUANG Yujin, SHENG Kerong, SUN Wei
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表4 变量描述性统计
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Tab. 4 Descriptive statistics of variables
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| 变量类型 | 变量 | 样本量 | 平均值 | 标准差 | 最小值 | 最大值 | | 因变量 | DO(50) | 492 | 0.170 | 0.222 | 0 | 1.201 | | DO(100) | 492 | 0.204 | 0.248 | 0 | 1.203 | | DO(150) | 492 | 0.224 | 0.262 | 0 | 1.224 | | DO(194) | 492 | 0.231 | 0.264 | 0 | 1.224 | | 自变量 | RES_AGR | 492 | 0.053 | 0.094 | 0 | 0.311 | | RES_MIN | 492 | 0.039 | 0.078 | 0 | 0.601 | | RES_ENE | 492 | 0.030 | 0.0178 | 0 | 0.077 | | AGG_EMP | 492 | 36953 | 56086 | 167 | 520480 | | AGG_INI | 492 | 0.249 | 0.114 | 0 | 0.528 | | AGG_INT | 492 | 0.254 | 0.147 | 0 | 0.543 | | AGG_TEC | 492 | 167.4 | 537.8 | 0 | 5600 | | GOV_NAT | 492 | 0.015 | 0.026 | 0 | 0.333 | | GOV_LEV | 492 | 28.68 | 40.29 | 0 | 138 | | GLO_EXP | 492 | 0.165 | 0.180 | 0 | 0.898 | | GLO_FOR | 492 | 0.062 | 0.052 | 0 | 0.339 | | SPA_BJ | 492 | 0.231 | 0.165 | 0 | 0.870 | | SPA_TJ | 492 | 0.256 | 0.137 | 0.022 | 0.775 | | RES_TRA | 492 | 0.036 | 0.014 | 0 | 0.115 |
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