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7 Hurdle模型第二阶段OLS回归结果
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Tab. 7 OLS regression results of the second stage in the Hurdle model
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| 变量 | 2004—2008年 | 2004—2013年 | | 模型(1) | 模型(2) | 模型(3) | 模型(4) | 模型(5) | 模型(6) | 模型(7) | 模型(8) | | 50 km | 100 km | 150 km | 194 km | | 50 km | 100 km | 150 km | 194 km | | RES_AGR | -0.001 (0.196) | -0.009 (0.210) | -0.025 (0.223) | -0.027 (0.225) | -0.086 (0.217) | -0.041 (0.220) | -0.055 (0.228) | -0.058 (0.227) | | RES_MIN | 0.413 (0.263) | 0.439 (0.285) | 0.389 (0.299) | 0.402 (0.290) | -0.120 (0.184) | -0.089 (0.191) | -0.133 (0.197) | -0.126 (0.198) | | RES_ENE | -4.905*** (1.191) | -4.938*** (1.290) | -5.619*** (1.289) | -5.443*** (1.307) | -3.143*** (0.925) | -3.165*** (0.962) | -3.724*** (0.972) | -3.403*** (0.998) | | AGG_EMP | -0.011 (0.013) | -0.001 (0.014) | 0.002 (0.014) | 0.005 (0.013) | -0.015 (0.009) | -0.005 (0.010) | -0.001 (0.010) | -0.001 (0.010) | | AGG_INI | 0.746*** (0.199) | 0.800*** (0.209) | 0.829*** (0.211) | 0.857*** (0.207) | 0.365** (0.182) | 0.470*** (0.180) | 0.498*** (0.181) | 0.524*** (0.179) | | AGG_INT | 0.350** (0.163) | 0.414** (0.177) | 0.481*** (0.183) | 0.527*** (0.184) | 0.155 (0.189) | 0.288 (0.187) | 0.338* (0.189) | 0.385** (0.188) | | AGG_TEC | 0.008 (0.009) | 0.004 (0.010) | 0.013 (0.010) | 0.014 (0.010) | -0.002 (0.007) | -0.005 (0.007) | -0.000 (0.007) | -0.001 (0.007) | | GOV_NAT | 0.248 (0.504) | 0.070 (0.533) | 0.074 (0.453) | 0.090 (0.443) | 0.140 (0.477) | -0.127 (0.532) | -0.102 (0.496) | -0.121 (0.497) | | GOV_LEV | -0.001 (0.001) | -0.002* (0.001) | -0.002** (0.001) | -0.002** (0.001) | -0.001 (0.001) | -0.001** (0.001) | -0.002*** (0.001) | -0.002*** (0.001) | | GLO_EXP | -0.043 (0.086) | -0.028 (0.096) | -0.027 (0.096) | -0.018 (0.094) | | | | | | GLO_ FOR | 0.581 (0.379) | 0.421 (0.416) | 0.411 (0.412) | 0.445 (0.410) | 0.611** (0.290) | 0.443 (0.309) | 0.443 (0.312) | 0.499 (0.312) | | SPA_BJ | 0.224* (0.123) | 0.311** (0.136) | 0.342** (0.136) | 0.325** (0.135) | 0.198* (0.103) | 0.274** (0.109) | 0.315*** (0.110) | 0.305*** (0.110) | | SPA_TJ | 0.259 (0.171) | 0.413** (0.178) | 0.462*** (0.165) | 0.441*** (0.162) | 0.223 (0.139) | 0.349** (0.146) | 0.395*** (0.139) | 0.384*** (0.137) | | RES_TRA | -1.484 (1.608) | -2.003 (1.688) | -1.807 (1.682) | -1.899 (1.663) | -0.196 (1.204) | -0.846 (1.268) | -0.554 (1.284) | -0.580 (1.311) | | 常数项 | 0.061 (0.134) | -0.039 (0.142) | -0.080 (0.146) | -0.115 (0.143) | 0.190 (0.122) | 0.074 (0.127) | 0.027 (0.128) | -0.001 (0.125) | | 年份固定效应 | 是 | 是 | 是 | 是 | 是 | 是 | 是 | 是 | | 样本量 | 248 | 253 | 255 | 267 | 377 | 382 | 384 | 398 | | R2 | 0.345 | 0.307 | 0.346 | 0.348 | 0.240 | 0.231 | 0.264 | 0.262 |
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