Law Reinforcement, Production Pattern and Enterprise Environmental Performance: Evidence from Environmental Courts in China
Abstract
:1. Introduction
2. Background and Theoretical Analysis
2.1. Environmental Court in China
2.2. Theoretical Analysis and Research Hypotheses
3. Methodology and Data
3.1. Methodology
3.1.1. Multiperiod DID Method
3.1.2. Parallel Trend Test (PTT)
3.1.3. Propensity Score Matching–Difference-in-Differences (PSM-DID) Strategy
3.2. Data
3.2.1. Variable Selection
3.2.2. Data Source
3.2.3. Data Processing
4. Results and Discussions
4.1. Preliminary Observation of Data
4.2. Baseline Results
4.3. Robustness Tests
4.3.1. The results of Parallel Trend Test
4.3.2. Placebo Test
4.3.3. Heterogeneous Effects on Different Air Pollutants
4.3.4. Results of PSM-DID Strategy
4.4. Heterogeneity Test
4.5. Mechanism Analysis
5. Discussion
6. Conclusions and Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Category | Variable | Index |
---|---|---|
Dependent variable | Log of air pollutant emission of industrial enterprises | |
Core explanatory variable | Environmental court | |
Control variable | Growth rate of industrial enterprises gross output value | |
Fixed capital stock of industrial enterprises (Absolute amount/one billion) | ||
Profit margin of industrial enterprises (Output value/ten thousand) | ||
Log of location entropy (Degree of industrial agglomeration) | ||
Proportion of added value of secondary and tertiary industries (Industrial upgrading) | ||
Log of urban railway passenger volume (Infrastructure) | ||
Log of urban foreign direct investment |
Variable | N | Mean | Std. Dev | Min | Max |
---|---|---|---|---|---|
406,527 | 10.52182 | 2.36711 | 0 | 21.50265 | |
534,972 | 0.07282 | 0.25965 | 0 | 1 | |
534,972 | 0.29096 | 0.28814 | −13.14930 | 6.92647 | |
534,972 | 0.03538 | 0.29765 | 0 | 48.66104 | |
534,972 | −0.00005 | 0.02985 | −12.57400 | 0.71640 | |
534,972 | −9.81529 | 3.30024 | −34.02110 | 8.85743 | |
534,972 | 83.54955 | 23.20705 | 0 | 99.97000 | |
534,972 | 8.12486 | 2.73743 | 0 | 11.75502 | |
534,972 | 9.11579 | 3.07823 | 0 | 13.31672 |
Explanatory Variables | (1) No Control Variables | (2) With Control Variables |
---|---|---|
−0.0599 *** (0.0223) | −0.0623 *** (0.0223) | |
0.0748 *** (0.0059) | ||
0.0736 ** (0.0282) | ||
−0.0070 (0.0078) | ||
0.0035 *** (0.0010) | ||
0.0007 ** (0.0003) | ||
−0.0138 *** (0.0032) | ||
0.0158 *** (0.0034) | ||
Time FE | Y | Y |
Individual FE | Y | Y |
0.0185 | 0.0196 | |
406,526 | 406,526 |
Variables | (1) Pre-One Period | (2) Pre-Five Period |
---|---|---|
−0.0030 (0.0184) | 0.0226 (0.0149) | |
Control variables | N | Y |
Time FE | Y | Y |
Individual FE | Y | Y |
0.0195 | 0.0195 | |
406,526 | 406,526 |
Explanatory Variables | (1) ln (SO2) | (2) ln (NOx) | (3) ln (Dust) | (4) ln (Smoke) |
---|---|---|---|---|
−0.0302 (0.0250) | −0.0420 * (0.0221) | 0.1471 * (0.0812) | −0.1293 *** (0.0287) | |
Control variables | Y | Y | Y | Y |
Time FE | Y | Y | Y | Y |
Individual FE | Y | Y | Y | Y |
0.0060 | 0.0326 | 0.0269 | 0.0082 | |
379,781 | 200,535 | 76,168 | 344,719 |
Variable | N | Means | Std. Dev | 95%CI | |||
---|---|---|---|---|---|---|---|
Treatment Group | Control Group | Treatment Group | Control Group | ||||
before PSM | 84,307 | 322,219 | 10.2099 | 10.6030 | 0.0091 | −0.4114 | −0.3756 |
after PSM | 84,307 | 199,206 | 10.2099 | 10.1781 | 0.0106 | 0.0111 | 0.0525 |
Variables | (1) | (2) |
---|---|---|
−0.1428 *** (0.0198) | −0.1121 *** (0.0197) | |
Control variables | N | Y |
Time FE | Y | Y |
Individual FE | Y | Y |
0.0413 | 0.0447 | |
258,882 | 258,882 |
Variables | Panel A: Scale of Enterprises | Panel B: Profit of Enterprises | |||
---|---|---|---|---|---|
(1) Small | (2) Medium | (3) Large | (4) Low | (5) High | |
−0.0627 ** (0.0267) | 0.0301 (0.0480) | −0.0805 (0.0808) | 0.0156 (0.0302) | −0.0722 ** (0.0358) | |
Control variables | Y | Y | Y | Y | Y |
Time FE | Y | Y | Y | Y | Y |
Individual FE | Y | Y | Y | Y | Y |
0.0170 | 0.0319 | 0.0232 | 0.0243 | 0.0210 | |
281,293 | 98,056 | 27,177 | 203,800 | 201,097 |
Variables | Panel A: Ownership of Enterprises | Panel B: Pollution Intensity of Enterprises | ||
---|---|---|---|---|
(1) State-Owned | (2) Private-Owned | (3) Low | (4) High | |
−0.0550 (0.0530) | −0.0584 ** (0.0246) | −0.0236 (0.0468) | −0.0327 * (0.0195) | |
Control variables | Y | Y | Y | Y |
Time FE | Y | Y | Y | Y |
Individual FE | Y | Y | Y | Y |
0.0295 | 0.0194 | 0.0517 | 0.0452 | |
96,806 | 309,720 | 138,568 | 266,386 |
Variables | Degree of Marketization | |
---|---|---|
(1) Low | (2) High | |
0.0099 (0.0379) | −0.1064 *** (0.0299) | |
Control variables | Y | Y |
Time FE | Y | Y |
Individual FE | Y | Y |
0.0172 | 0.0269 | |
217,831 | 187,946 |
(1) Log (Purchasing Equipment) | (2) Log (Vertical Integration Index) | (3) Log (Secondary Energy Ratio) | (4) Log (Labor Productivity) | |
---|---|---|---|---|
0.0769 *** (0.0162) | −0.1216 *** (0.0089) | 0.0663 ** (0.0265) | 0.1081 *** (0.0085) | |
Control variables | Y | Y | Y | Y |
Time FE | Y | Y | Y | Y |
Individual FE | Y | Y | Y | Y |
0.0576 | 0.0073 | 0.0153 | 0.0321 | |
859,705 | 1,333,497 | 909,576 | 2,316,697 |
Variables | Panel A: Judicial Efficiency | Panel B: Deterrent Effect | ||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
−0.0579 *** (0.0222) | −0.0601 *** (0.0222) | −0.0580 *** (0.0222) | −0.0601 *** (0.0222) | |
−0.0404 (0.0496) | −0.0319 (0.0715) | |||
−0.3023 ** (0.1568) | −0.3080 * (0.1567) | |||
−0.0506 (0.0714) | −0.0423 (0.0714) | |||
−0.2920 * (0.1567) | −0.2975 * (0.1567) | |||
Control variables | N | Y | N | Y |
Time FE | Y | Y | Y | Y |
Individual FE | Y | Y | Y | Y |
0.0185 | 0.0197 | 0.0185 | 0.0197 | |
406,527 | 406,527 | 406,527 | 406,527 |
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Zhu, D.; Tao, X.; Huang, M. Law Reinforcement, Production Pattern and Enterprise Environmental Performance: Evidence from Environmental Courts in China. Sustainability 2023, 15, 4440. https://doi.org/10.3390/su15054440
Zhu D, Tao X, Huang M. Law Reinforcement, Production Pattern and Enterprise Environmental Performance: Evidence from Environmental Courts in China. Sustainability. 2023; 15(5):4440. https://doi.org/10.3390/su15054440
Chicago/Turabian StyleZhu, Dandan, Xinping Tao, and Meibo Huang. 2023. "Law Reinforcement, Production Pattern and Enterprise Environmental Performance: Evidence from Environmental Courts in China" Sustainability 15, no. 5: 4440. https://doi.org/10.3390/su15054440