Resources Science ›› 2020, Vol. 42 ›› Issue (7): 1348-1360.doi: 10.18402/resci.2020.07.11
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XIONG Hang(), JING Zheng, ZHAN Jintao(
)
Received:
2019-12-09
Revised:
2020-05-14
Online:
2020-07-25
Published:
2020-09-25
Contact:
ZHAN Jintao
E-mail:xionghang@njau.edu.cn;jintao.zhan@njau.edu.cn
XIONG Hang, JING Zheng, ZHAN Jintao. Impact of different environmental regulatory tools on technological innovation of Chinese industrial enterprises above designated size[J].Resources Science, 2020, 42(7): 1348-1360.
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Table 2
Key variable description"
一级指标 | 二级指标 | 二级指标说明 |
---|---|---|
企业创新行为 | 自主创新 | 规模以上的工业企业的R&D内部投入/百亿元 |
技术引进 | 规模以上的工业企业的R&D外部投入/百亿元 | |
市场激励型环境工具 | 环保税(排污费) | 排污费与各省GDP的比值/% |
可再生能源发电补贴 | 光伏发电平均上网电价与燃煤平均上网电价的比值/% 风力发电平均上网电价与燃煤平均上网电价的比值/% | |
环境权交易制度 | 是否实施SO2废气排污权制度(1为是,0为否) 碳交易量/t | |
命令控制型环境工具 | 法律法规、行政手段 | 累积有效的环保法规数 累积有效的行政规章数 受理行政处罚数 |
Table 3
Descriptive statistics of regression variables"
变量 | 变量解释 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|
rdin | 规模以上工业企业的R&D内部支出/百亿元 | 3.369 | 4.207 | 0.065 | 18.650 |
rdout | 规模以上工业企业的R&D外部支出/百亿元 | 0.181 | 0.241 | 0.003 | 1.595 |
rd | 规模以上工业企业的R&D总支出/百亿元 | 3.550 | 4.417 | 0.068 | 20.240 |
scjl | 市场激励型工具综合指标 | 0.378 | 0.254 | 0.000 | 1.220 |
mlkz | 命令控制型工具综合指标 | 0.231 | 0.140 | 0.030 | 0.761 |
ins | 实际工业增加值/百亿元 | 97.930 | 81.220 | 5.170 | 359.000 |
acindust | 工业增加值占GDP比重/% | 0.364 | 0.082 | 0.118 | 0.496 |
perGDP | 人均实际GDP/(万元/人) | 4.263 | 1.874 | 1.970 | 9.159 |
perGDP2 | 人均实际GDP平方 | 21.660 | 20.330 | 3.880 | 83.890 |
fdi | 外商实际直接投资/百亿美元 | 0.918 | 0.769 | 0.001 | 3.326 |
Table 4
National regression results"
(1) | (2) | (3) | (4) | (5) | (6) | |
---|---|---|---|---|---|---|
rdin | rdout | rd | rdin | rdout | rd | |
mlkz | 0.288 | -0.199 | 0.089 | 0.288 | -0.199*** | 0.089 |
(0.417) | (0.158) | (0.844) | (0.170) | (0.007) | (0.567) | |
2014×mlkz | -0.031 | -0.020 | -0.050 | -0.031 | -0.020 | -0.050 |
(0.743) | (0.613) | (0.665) | (0.644) | (0.362) | (0.562) | |
2015×mlkz | -0.207 | -0.040 | -0.247 | -0.207* | -0.040** | -0.247* |
(0.197) | (0.500) | (0.222) | (0.058) | (0.042) | (0.054) | |
2016×mlkz | -0.417* | -0.126 | -0.543* | -0.417** | -0.126*** | -0.543** |
(0.085) | (0.222) | (0.080) | (0.031) | (0.000) | (0.017) | |
2017×mlkz | -0.244 | -0.055 | -0.299 | -0.244 | -0.055*** | -0.299* |
(0.346) | (0.536) | (0.330) | (0.115) | (0.001) | (0.078) | |
scjl | -0.173 | -0.095 | -0.268 | -0.173 | -0.095 | -0.268 |
(0.434) | (0.630) | (0.433) | (0.467) | (0.383) | (0.437) | |
2014×scjl | -0.602 | -0.009 | -0.611 | -0.602 | -0.009 | -0.611 |
(0.248) | (0.938) | (0.292) | (0.169) | (0.844) | (0.196) | |
2015×scjl | -0.160 | 0.362 | 0.202 | -0.160 | 0.362*** | 0.202 |
(0.730) | (0.203) | (0.733) | (0.668) | (0.004) | (0.642) | |
2016×scjl | 1.534* | 0.146 | 1.680* | 1.534*** | 0.146* | 1.680*** |
(0.078) | (0.318) | (0.071) | (0.004) | (0.088) | (0.003) | |
2017×scjl | 1.395*** | 0.360* | 1.755*** | 1.395** | 0.360*** | 1.755*** |
(0.001) | (0.065) | (0.001) | (0.010) | (0.006) | (0.009) | |
ins | -0.325*** | 0.024 | -0.301** | -0.325*** | 0.024 | -0.301*** |
(0.002) | (0.713) | (0.018) | (0.000) | (0.132) | (0.000) | |
acindust | -0.660** | -0.098 | -0.758** | -0.660*** | -0.098*** | -0.758*** |
(0.012) | (0.111) | (0.011) | (0.001) | (0.001) | (0.001) | |
perGDP | -0.871** | -0.156 | -1.027** | -0.871*** | -0.156*** | -1.027*** |
(0.016) | (0.226) | (0.016) | (0.001) | (0.004) | (0.002) | |
perGDP2 | -1.587*** | -0.140 | -1.727*** | -1.587*** | -0.140** | -1.727*** |
(0.007) | (0.170) | (0.006) | (0.001) | (0.027) | (0.001) | |
fdi | 0.059*** | 0.005 | 0.064*** | 0.059*** | 0.005*** | 0.064*** |
(0.000) | (0.118) | (0.000) | (0.000) | (0.000) | (0.000) | |
dummy2014 | -8.452** | -0.989 | -9.442** | -8.452*** | -0.989*** | -9.442*** |
(0.012) | (0.199) | (0.012) | (0.001) | (0.002) | (0.001) | |
dummy2015 | -1.725 | -0.154 | -1.879 | -1.725*** | -0.154 | -1.879*** |
(0.174) | (0.308) | (0.153) | (0.001) | (0.291) | (0.002) | |
dummy2016 | 0.086 | 0.009 | 0.095 | 0.086** | 0.009 | 0.095** |
(0.350) | (0.296) | (0.308) | (0.021) | (0.436) | (0.030) | |
dummy2017 | 0.055 | -0.030 | 0.026 | 0.055 | -0.030* | 0.026 |
(0.559) | (0.410) | (0.796) | (0.499) | (0.052) | (0.777) | |
常数项 | 5.917** | 0.487 | 6.405** | 5.917*** | 0.487 | 6.405*** |
(0.043) | (0.223) | (0.040) | (0.000) | (0.105) | (0.000) | |
N | 150 | 150 | 150 | 150 | 150 | 150 |
标准误估计方法 | White | White | White | D&K | D&K | D&K |
Table 5
Difference in differences (DID) regression results for carbon trading market"
(1) | (2) | (3) | |
---|---|---|---|
rdin | rdout | rd | |
ctrade | 0.222 | 0.092** | 0.315* |
(0.160) | (0.030) | (0.076) | |
mlkz | 0.468 | -0.107 | 0.361 |
(0.160) | (0.228) | (0.332) | |
ins | 0.060*** | 0.005*** | 0.066*** |
(0.000) | (0.000) | (0.000) | |
acindust | -6.183** | -0.382 | -6.565** |
(0.016) | (0.572) | (0.022) | |
perGDP | -2.026*** | -0.187 | -2.213*** |
(0.003) | (0.300) | (0.004) | |
perGDP2 | 0.124** | 0.013 | 0.137** |
(0.013) | (0.319) | (0.014) | |
fdi | -0.070 | -0.064** | -0.134 |
(0.542) | (0.040) | (0.299) | |
dummy2014 | -0.184* | -0.036 | -0.220* |
(0.092) | (0.212) | (0.072) | |
dummy2015 | -0.517*** | -0.066 | -0.583*** |
(0.002) | (0.131) | (0.002) | |
dummy2016 | -0.654*** | -0.080 | -0.734*** |
(0.002) | (0.147) | (0.002) | |
dummy2017 | -0.317 | -0.039 | -0.356 |
(0.172) | (0.529) | (0.171) | |
常数项 | 5.908*** | 0.434 | 6.342*** |
(0.000) | (0.311) | (0.001) | |
N | 150 | 150 | 150 |
Table 6
Regional regression results"
东部地区 | 中部地区 | 西部地区 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
rdin | rdout | rd | rdin | rdout | rd | rdin | rdout | rd | |||||
mlkz | -0.315 | -1.064** | -1.380 | 0.330 | -0.140 | 0.191 | 0.323 | 0.017 | 0.340 | ||||
(0.716) | (0.013) | (0.255) | (0.142) | (0.118) | (0.267) | (0.188) | (0.545) | (0.206) | |||||
2014×mlkz | -0.241 | -0.274*** | -0.514* | -0.336** | -0.122*** | -0.458*** | 0.063** | 0.016* | 0.079*** | ||||
(0.242) | (0.002) | (0.071) | (0.014) | (0.005) | (0.005) | (0.032) | (0.099) | (0.004) | |||||
2015×mlkz | -0.221 | -0.292*** | -0.513 | -0.275 | -0.181*** | -0.455* | 0.061 | 0.031* | 0.092 | ||||
(0.440) | (0.003) | (0.131) | (0.198) | (0.003) | (0.077) | (0.595) | (0.071) | (0.390) | |||||
2016×mlkz | -0.370 | -0.489*** | -0.859 | -0.582* | -0.234** | -0.815** | -0.080 | 0.002 | -0.078** | ||||
(0.588) | (0.000) | (0.236) | (0.077) | (0.012) | (0.035) | (0.113) | (0.924) | (0.047) | |||||
2017×mlkz | -0.437 | -0.327** | -0.764 | -0.287 | -0.204** | -0.492 | -0.074 | 0.022 | -0.052 | ||||
(0.556) | (0.014) | (0.298) | (0.413) | (0.039) | (0.209) | (0.131) | (0.322) | (0.186) | |||||
scjl | 0.150 | 0.181 | 0.330 | 0.971** | 0.240 | 1.210*** | -0.165 | -0.044* | -0.210 | ||||
(0.357) | (0.411) | (0.128) | (0.021) | (0.193) | (0.002) | (0.181) | (0.076) | (0.156) | |||||
2014×scjl | 0.042 | 0.494** | 0.536 | -0.373 | 0.081 | -0.292 | -0.377 | -0.036 | -0.413 | ||||
(0.868) | (0.027) | (0.201) | (0.286) | (0.380) | (0.327) | (0.190) | (0.191) | (0.169) | |||||
2015×scjl | 0.498** | 1.298*** | 1.796*** | -0.050 | 0.229* | 0.179 | -1.003*** | -0.133*** | -1.135*** | ||||
(0.044) | (0.003) | (0.001) | (0.929) | (0.057) | (0.733) | (0.001) | (0.002) | (0.000) | |||||
2016×scjl | 2.197 | 0.843* | 3.041* | -2.231*** | 0.236** | -1.995*** | -1.185*** | -0.211*** | -1.396*** | ||||
(0.107) | (0.075) | (0.097) | (0.005) | (0.023) | (0.006) | (0.000) | (0.003) | (0.000) | |||||
2017×scjl | 1.590** | 0.783*** | 2.373*** | 1.598* | 0.256 | 1.855** | 0.608*** | 0.017 | 0.625*** | ||||
(0.040) | (0.006) | (0.005) | (0.067) | (0.197) | (0.026) | (0.000) | (0.543) | (0.000) | |||||
ins | -0.276 | 0.484*** | 0.208 | -0.157 | 0.027 | -0.130* | -0.030 | 0.011 | -0.019 | ||||
(0.215) | (0.001) | (0.418) | (0.147) | (0.683) | (0.097) | (0.438) | (0.400) | (0.668) | |||||
acindust | -2.089** | -0.263** | -2.352** | -0.387* | 0.113* | -0.275* | 0.279 | -0.006 | 0.273 | ||||
(0.029) | (0.013) | (0.023) | (0.055) | (0.066) | (0.068) | (0.130) | (0.807) | (0.133) | |||||
perGDP | -2.582*** | -0.482** | -3.064*** | -0.504* | 0.069 | -0.435* | 0.944*** | 0.093* | 1.037*** | ||||
(0.006) | (0.013) | (0.006) | (0.080) | (0.275) | (0.065) | (0.007) | (0.054) | (0.005) | |||||
perGDP2 | -2.657*** | -0.541** | -3.199*** | 0.312 | 0.030 | 0.342* | 1.371*** | 0.156** | 1.528*** | ||||
(0.002) | (0.014) | (0.003) | (0.100) | (0.554) | (0.056) | (0.003) | (0.028) | (0.001) | |||||
fdi | 0.064*** | 0.006** | 0.070*** | 0.036*** | 0.003 | 0.040*** | 0.016* | 0.001 | 0.018* | ||||
(0.002) | (0.013) | (0.002) | (0.001) | (0.120) | (0.001) | (0.079) | (0.334) | (0.071) | |||||
dummy2014 | -14.097 | -4.463*** | -18.560 | -9.885** | -0.401 | -10.287*** | -4.790*** | -0.021 | -4.810*** | ||||
(0.268) | (0.007) | (0.146) | (0.026) | (0.697) | (0.008) | (0.008) | (0.932) | (0.003) | |||||
dummy2015 | -3.107*** | 0.048 | -3.059** | -0.182 | -0.861 | -1.042 | 0.944 | 0.079** | 1.024 | ||||
(0.006) | (0.910) | (0.029) | (0.846) | (0.151) | (0.346) | (0.137) | (0.035) | (0.122) | |||||
dummy2016 | 0.160** | -0.007 | 0.153* | 0.202 | 0.104 | 0.307* | 0.000 | -0.003 | -0.002 | ||||
(0.029) | (0.778) | (0.092) | (0.193) | (0.202) | (0.093) | (0.995) | (0.609) | (0.977) | |||||
dummy2017 | 0.266 | 0.030 | 0.297 | 1.644** | 0.210** | 1.855*** | -1.410** | -0.128*** | -1.538** | ||||
(0.308) | (0.228) | (0.255) | (0.012) | (0.037) | (0.007) | (0.032) | (0.004) | (0.023) | |||||
常数项 | 14.142** | 1.131 | 15.274** | -0.642 | 1.465 | 0.823 | -1.155 | -0.211* | -1.366 | ||||
(0.017) | (0.289) | (0.024) | (0.753) | (0.150) | (0.710) | (0.281) | (0.061) | (0.230) | |||||
N | 55 | 55 | 55 | 40 | 40 | 40 | 55 | 55 | 55 |
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