An Empirical Analysis of the Impact of Digital Economy on Manufacturing Green and Low-Carbon Transformation under the Dual-Carbon Background in China
Abstract
:1. Introduction
2. Theoretical Analysis
3. Measurement of the Digital Economy
3.1. Evaluation Index
3.2. Data
3.3. Result
4. Measurement of the Manufacturing Transformation Efficiency
4.1. Evaluation Index
4.2. Data
4.3. Result
5. Study Design
5.1. Theoretical Mechanism and Research Hypothesis
5.2. Model
5.3. Result and Analysis
6. Discussion
6.1. Mediation Effect Test
6.2. Heterogeneity Test
6.3. Robustness Test
- (1)
- The core explanatory variable digital economy development level is analysed with a one-period lag, and the results are presented in Column (7) of Table 10. The regression coefficient of digital economy development in period t-1 is significantly positive at the 1% level, which again confirms the robustness of the benchmark regression results.
- (2)
- Instrumental variable method
7. Conclusions and Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Target Level | Criterion Level | Index Level | Unit | Indicator Direction |
---|---|---|---|---|
Digital Economy | Basic indicators | Number of IPV4 addresses | 10,000 | + |
Base stations of mobile phones | CNY 10,000 | + | ||
Length of optical cable lines | km | + | ||
Number of internet broadband subscriber ports | 10,000 ports | + | ||
Popularisation rate of mobile phones | % | + | ||
Industry indicators | Business volume of telecommunications services | CNY 100 million | + | |
Income from related software business | CNY 10,000 | + | ||
Number of top 100 internet companies | unit | + | ||
Environmental indicators | Number of software developers | unit | + | |
Number of invention patent applications | piece | + | ||
Full-time equivalent of R&D personnel | 10,000 man-years | + | ||
Transaction value in technical market | CNY 100 million | + | ||
Convergence indicators | Sales and purchases through e-commerce | CNY 100 million | + | |
The proportion with e-commerce transactions enterprises | % | + | ||
Digital financial inclusion index | / | + |
Region | 2016 | 2017 | 2018 | 2019 | 2020 | Average Annual Growth Rate (%) | |
---|---|---|---|---|---|---|---|
Eastern Region | Beijing | 0.4123 | 0.5447 | 0.5977 | 0.6451 | 0.7380 | 16.04 |
Tianjin | 0.0670 | 0.0682 | 0.0796 | 0.0927 | 0.1047 | 11.98 | |
Hebei | 0.0671 | 0.0884 | 0.1037 | 0.1208 | 0.1366 | 19.63 | |
Shanghai | 0.2562 | 0.2686 | 0.3089 | 0.3385 | 0.3558 | 8.64 | |
Jiangsu | 0.3704 | 0.3880 | 0.4389 | 0.4540 | 0.5106 | 8.45 | |
Zhejiang | 0.2667 | 0.2884 | 0.3326 | 0.3636 | 0.4003 | 10.72 | |
Fujian | 0.1395 | 0.1571 | 0.1849 | 0.1946 | 0.1848 | 7.64 | |
Shandong | 0.2089 | 0.2436 | 0.3036 | 0.3179 | 0.3512 | 14.11 | |
Guangdong | 0.4786 | 0.5292 | 0.6208 | 0.6893 | 0.7465 | 11.80 | |
Hainan | 0.0289 | 0.0353 | 0.0360 | 0.0406 | 0.0427 | 10.59 | |
Average | 0.2296 | 0.2612 | 0.3007 | 0.3257 | 0.3571 | 11.72 | |
Central Region | Shanxi | 0.0369 | 0.0467 | 0.0577 | 0.0653 | 0.0727 | 18.62 |
Anhui | 0.1035 | 0.1199 | 0.1502 | 0.1530 | 0.1759 | 14.49 | |
Jiangxi | 0.0412 | 0.0634 | 0.0743 | 0.0933 | 0.1056 | 27.48 | |
Henan | 0.1001 | 0.1095 | 0.1318 | 0.1418 | 0.1559 | 11.82 | |
Hubei | 0.1261 | 0.1514 | 0.1858 | 0.2033 | 0.2130 | 14.23 | |
Hunan | 0.0861 | 0.1029 | 0.1193 | 0.1431 | 0.1630 | 17.31 | |
Average | 0.0823 | 0.0990 | 0.1198 | 0.1333 | 0.1477 | 15.83 | |
Western Region | Mongolia | 0.0298 | 0.0389 | 0.0431 | 0.0540 | 0.0633 | 20.92 |
Guangxi | 0.0524 | 0.0589 | 0.0715 | 0.0834 | 0.0981 | 17.00 | |
Chongqing | 0.0773 | 0.0852 | 0.1138 | 0.1182 | 0.1244 | 13.21 | |
Sichuan | 0.1196 | 0.1581 | 0.1898 | 0.2153 | 0.2374 | 19.00 | |
Guizhou | 0.0393 | 0.0514 | 0.0648 | 0.0795 | 0.0884 | 22.68 | |
Yunnan | 0.0562 | 0.0530 | 0.0670 | 0.0826 | 0.0953 | 14.85 | |
Shaanxi | 0.0950 | 0.1264 | 0.1345 | 0.1578 | 0.1530 | 13.44 | |
Gansu | 0.0280 | 0.0321 | 0.0405 | 0.0479 | 0.0543 | 18.05 | |
Qinghai | 0.0135 | 0.0159 | 0.0212 | 0.0234 | 0.0274 | 19.70 | |
Ningxia | 0.0163 | 0.0195 | 0.0244 | 0.0265 | 0.0291 | 15.74 | |
Xinjiang | 0.0240 | 0.0286 | 0.0416 | 0.0478 | 0.0565 | 24.46 | |
Average | 0.0501 | 0.0607 | 0.0738 | 0.0851 | 0.0934 | 16.93 | |
Northeast Region | Liaoning | 0.1099 | 0.1398 | 0.1287 | 0.1439 | 0.1378 | 06.71 |
Jilin | 0.0303 | 0.0414 | 0.0542 | 0.0555 | 0.0619 | 20.32 | |
Heilongjiang | 0.0411 | 0.0508 | 0.0509 | 0.0601 | 0.0680 | 13.77 | |
Average | 0.0604 | 0.0773 | 0.0779 | 0.0865 | 0.0892 | 10.72 | |
National | Average | 0.1174 | 0.1368 | 0.1591 | 0.1751 | 0.1917 | 13.09 |
Target Level | Criterion Level | Index Level | Unit | Indicator Direction |
---|---|---|---|---|
Manufacturing transformation efficiency | Economic benefits | Total profits of industrial enterprises above designated size_Manufacturing | CNY 100 million | + |
Green development | Energy consumption per unit of industrial added value | 10,000 tons of standard coal/CNY 100 million | − | |
Total industrial wastewater discharge | ton | − | ||
Common industrial solid wastes generated | 10,000 tons | − | ||
Total industrial waste gas emissions | ton | − | ||
Technology innovation | R&D expenditure of industrial enterprises above designated size | CNY 10,000 | + | |
Number of valid invention patents for industrial enterprises above designated size | piece | + | ||
Digital convergence | Digital economy development level | / | + |
Region | 2016 | 2017 | 2018 | 2019 | 2020 | Average Annual Growth Rate (%) | |
---|---|---|---|---|---|---|---|
Eastern Region | Beijing | 0.1839 | 0.2210 | 0.2258 | 0.2395 | 0.2610 | 9.36 |
Tianjin | 0.0678 | 0.0624 | 0.0651 | 0.0638 | 0.0684 | 0.40 | |
Hebei | 0.0420 | 0.0516 | 0.0591 | 0.0669 | 0.0770 | 16.41 | |
Shanghai | 0.1442 | 0.1593 | 0.1818 | 0.1902 | 0.2143 | 10.48 | |
Jiangsu | 0.1695 | 0.1907 | 0.2160 | 0.2351 | 0.2668 | 12.03 | |
Zhejiang | 0.1300 | 0.1430 | 0.1594 | 0.1706 | 0.1911 | 10.12 | |
Fujian | 0.0643 | 0.0757 | 0.0836 | 0.0887 | 0.0978 | 11.14 | |
Shandong | 0.6556 | 0.5603 | 0.4499 | 0.3293 | 0.4136 | −8.87 | |
Guangdong | 0.1790 | 0.1996 | 0.2261 | 0.2484 | 0.2716 | 10.10 | |
Hainan | 0.0503 | 0.0553 | 0.0587 | 0.0617 | 0.0652 | 6.73 | |
Average | 0.1687 | 0.1719 | 0.1726 | 0.1694 | 0.1927 | 3.56 | |
Central Region | Shanxi | 0.0266 | 0.0540 | 0.0688 | 0.0592 | 0.0675 | 32.56 |
Anhui | 0.0584 | 0.0714 | 0.0820 | 0.0881 | 0.1043 | 15.73 | |
Jiangxi | 0.0517 | 0.0646 | 0.0736 | 0.0816 | 0.0938 | 16.19 | |
Henan | 0.0671 | 0.0764 | 0.0863 | 0.0948 | 0.1080 | 12.65 | |
Hubei | 0.0757 | 0.0840 | 0.0955 | 0.1035 | 0.1087 | 9.52 | |
Hunan | 0.1578 | 0.1892 | 0.2130 | 0.2416 | 0.2775 | 15.19 | |
Average | 0.0729 | 0.0899 | 0.1032 | 0.1115 | 0.1266 | 14.94 | |
Western Region | Mongolia | 0.0538 | 0.0566 | 0.0569 | 0.0589 | 0.0647 | 4.75 |
Guangxi | 0.0335 | 0.0347 | 0.0367 | 0.0385 | 0.0434 | 6.79 | |
Chongqing | 0.0603 | 0.0675 | 0.0752 | 0.0798 | 0.0857 | 9.20 | |
Sichuan | 0.0430 | 0.0507 | 0.0564 | 0.0615 | 0.0687 | 12.51 | |
Guizhou | 0.0319 | 0.0359 | 0.0391 | 0.0457 | 0.0487 | 11.26 | |
Yunnan | 0.0420 | 0.0466 | 0.0504 | 0.0552 | 0.0618 | 10.13 | |
Shaanxi | 0.0394 | 0.0460 | 0.0487 | 0.0524 | 0.0533 | 8.03 | |
Gansu | 0.0253 | 0.0272 | 0.0289 | 0.0301 | 0.0347 | 8.23 | |
Qinghai | 0.0376 | 0.0377 | 0.0394 | 0.0429 | 0.0457 | 5.02 | |
Ningxia | 0.0288 | 0.0304 | 0.0322 | 0.0333 | 0.0354 | 5.27 | |
Xinjiang | 0.0370 | 0.0435 | 0.0487 | 0.0523 | 0.0623 | 14.03 | |
Average | 0.0393 | 0.0434 | 0.0466 | 0.0500 | 0.0550 | 8.73 | |
Northeast Region | Liaoning | 0.0445 | 0.0507 | 0.0519 | 0.0546 | 0.0624 | 8.98 |
Jilin | 0.0366 | 0.0380 | 0.0392 | 0.0408 | 0.0439 | 4.70 | |
Heilongjiang | 0.0495 | 0.0542 | 0.0554 | 0.0605 | 0.0678 | 8.24 | |
Average | 0.0435 | 0.0476 | 0.0488 | 0.0520 | 0.0580 | 7.53 | |
National | Average | 0.0896 | 0.0960 | 0.1001 | 0.1023 | 0.1155 | 6.64 |
Variable | Symbol | Type | Measurement Method | Unit |
---|---|---|---|---|
Green and low-carbon transformation efficiency in manufacturing | Explained variables | Economic benefits, green development, technological innovation, and digital integration | / | |
Digital economy development level | Core explanatory variables | Basic indicators, industrial indicators, environmental indicators, and integration indicators are composed | / | |
Technology innovation | Intermediate variable | R&D expenditure of industrial enterprises above designated size | CNY 100 million | |
Human capital | Control variables | Average number of years of schooling index for people over 6 years old | person/year | |
Operating costs | The main business cost of industrial enterprises above designated size | CNY 100 million | ||
Industry scale | Industrial value added as a percentage of GDP | % |
Variables | Observations | Mean | Median | Std. Dev. | Minimum | Maximum |
---|---|---|---|---|---|---|
150 | −2.583 | −2.774 | 0.697 | −3.675 | −0.422 | |
150 | −2.278 | −2.288 | 0.917 | −4.309 | −0.292 | |
150 | 14.53 | 14.80 | 1.373 | 11.12 | 17.03 | |
150 | −1.218 | −1.149 | 0.857 | −3.803 | 0.707 | |
150 | 9.862 | 9.882 | 1.055 | 7.175 | 11.81 | |
150 | 2.231 | 2.227 | 0.0930 | 2.045 | 2.548 |
Variables | (1) | (2) |
---|---|---|
0.559 *** (0.041) | 0.477 *** (0.055) | |
−0.081 (0.211) | ||
0.314 *** (0.068) | ||
1.555 *** (0.578) | ||
−8.164 *** (1.535) | ||
150 | 150 | |
0.606 | 0.689 | |
0.507 | 0.600 |
Variables | (1) | (2) | (3) |
---|---|---|---|
0.452 *** (0.0419) | 0.516 *** (0.0518) | 0.331 *** (0.0505) | |
0.246 *** (0.0637) | |||
−0.292 *** (0.0797) | 0.0160 (0.0727) | −0.303 *** (0.0816) | |
0.289 *** (0.0527) | 0.756 *** (0.0579) | 0.143 ** (0.0642) | |
1.119 ** (0.478) | 0.744 (0.527) | 0.822 * (0.472) | |
−7.252 *** (1.251) | 6.619 *** (1.407) | −9.022 *** (1.277) | |
Mediating effect | Presence | ||
Mediating effect percentage | 0.281 | ||
150 | 150 | 150 |
Variables | Eastern Region | Central Region | Western Region | Northeast Region |
---|---|---|---|---|
0.684 *** (0.182) | 0.806 *** (0.164) | 0.340 *** (0.032) | 0.392 *** (0.109) | |
0.910 (0.580) | 0.013 (0.493) | −0.546 *** (0.138) | −0.584 (0.443) | |
0.545 *** (0.134) | 0.162 (0.202) | 0.154 *** (0.053) | 0.282 *** (0.082) | |
1.881 * (1.034) | 1.149 (2.402) | 0.830 ** (0.330) | 1.360 (1.333) | |
−9.844 *** (3.048) | −4.815 (6.526) | −5.979 *** (0.933) | −8.457 ** (2.912) | |
50.000 | 30.000 | 55.000 | 15.000 | |
0.659 | 0.830 | 0.923 | 0.882 | |
0.536 | 0.754 | 0.896 | 0.794 |
Variable | (1) | (2)–(5) | (6) | (7) | (8) | |||
---|---|---|---|---|---|---|---|---|
1.239 *** (0.108) | 0.559 *** (0.041) | 0.587 *** (0.054) | 0.546 *** (0.050) | 0.477 *** (0.055) | 0.522 *** (0.071) | 0.329 *** (0.055) | 0.881 *** (0.213) | |
0.350 (0.255) | 0.177 (0.221) | −0.142 (0.215) | −0.081 (0.211) | 0.018 (0.309) | −0.275 (0.221) | −0.310 *** (0.038) | ||
0.275 *** (0.077) | 0.323 *** (0.070) | 0.314 *** (0.068) | 0.271 *** (0.086) | 0.213 *** (0.074) | −0.013 (0.137) | |||
1.584 ** (0.677) | 1.555 *** (0.578) | 1.733 ** (0.785) | 1.245 ** (0.519) | −1.006 (0.865) | ||||
−15.436 *** (1.457) | −1.309 *** (0.095) | −1.030 *** (0.360) | −4.701 *** (0.857) | −8.164 *** (1.535) | −7.865 *** (2.125) | −6.985 *** (1.555) | 1.421 (3.605) | |
150 | 150 | 150 | 150 | 150 | 120 | 120 | 150 | |
0.786 | 0.606 | 0.608 | 0.669 | 0.689 | 0.615 | 0.639 | 0.707 | |
0.725 | 0.507 | 0.505 | 0.579 | 0.600 | 0.467 | 0.500 | 0.698 |
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Zhang, W.; Zhou, H.; Chen, J.; Fan, Z. An Empirical Analysis of the Impact of Digital Economy on Manufacturing Green and Low-Carbon Transformation under the Dual-Carbon Background in China. Int. J. Environ. Res. Public Health 2022, 19, 13192. https://doi.org/10.3390/ijerph192013192
Zhang W, Zhou H, Chen J, Fan Z. An Empirical Analysis of the Impact of Digital Economy on Manufacturing Green and Low-Carbon Transformation under the Dual-Carbon Background in China. International Journal of Environmental Research and Public Health. 2022; 19(20):13192. https://doi.org/10.3390/ijerph192013192
Chicago/Turabian StyleZhang, Wei, Hao Zhou, Jie Chen, and Zifu Fan. 2022. "An Empirical Analysis of the Impact of Digital Economy on Manufacturing Green and Low-Carbon Transformation under the Dual-Carbon Background in China" International Journal of Environmental Research and Public Health 19, no. 20: 13192. https://doi.org/10.3390/ijerph192013192