The Impact of the Circular Economy Pilot Policy on Carbon Emissions in Chinese Cities and Its Underlying Mechanisms
Abstract
:1. Introduction
2. Policy Background and Research Hypotheses
2.1. Policy Background
2.2. Research Hypotheses
3. Research Methodology
3.1. Model Construction
3.1.1. Multi-Period DID Model
3.1.2. Mediation Effects Model
3.1.3. Moderation Effects Model
3.1.4. SDID Model
3.2. Variable Description
3.3. Sample Selection and Data Sources
4. Empirical Results and Robustness Testing
4.1. Baseline Regression
4.2. Parallel Trend Test
4.3. Robust Test
4.3.1. Placebo Test
4.3.2. Correction of Sample Selection Bias
4.3.3. Inclusion of Interaction Fixed Effects
4.3.4. Eliminate Interference from Other Policies
5. Mechanism Testing and Heterogeneity Analysis
5.1. Impact Mechanism Testing
5.1.1. Mechanism Effects of Government Technology Investment
5.1.2. Mechanism Effects of Per Capita Fixed Capital
5.1.3. The Regulatory Effect of Public Management
5.2. Heterogeneity Analysis
5.2.1. Diversity in Resource Endowment
5.2.2. Heterogeneity of Industrialization Levels
5.2.3. The Heterogeneity of Economic Foundations
6. Examination of the Spillover Effects of the Circular Economy Pilot Policy’s Spatial Dimensions
6.1. Spatial Autocorrelation Analysis
6.2. The Examination Results of the SDID Model
7. Discussion
8. Conclusions and Policy Implications
- First, it is recommended to gradually expand the content and coverage of the circular economy pilot policy systematically and progressively. Adhering strictly to the three major principles of “reduction, reuse, and recycling”, tailored 3–5 year development plans for circular economy and their phased objectives should be formulated based on the resource utilization efficiency and innovation foundation of circular economy enterprises, with regular monitoring of the progress and completion of the phased objectives of the plan. In the short term, the focus should mainly be on improving the structure of factor allocation, using renewable resources to replace non-renewable resources, and achieving resource reduction. Meanwhile, in the long term, continuous and in-depth promotion of recycling technologies is needed, specifically guiding innovative resource flows towards the innovation and application fields of new energy and renewable energy, strengthening the large-scale use of solar energy, wind energy, biomass energy, geothermal energy, hydrogen energy, and other energy sources to facilitate the green and low-carbon transformation of urban energy systems and curb carbon emissions. Furthermore, the standardized governance model of circular economy in national demonstration cities should be summarized, replicated, and promoted to surrounding areas, fostering innovative cooperation between national circular economy demonstration cities and surrounding areas in the field of energy generation to fully demonstrate the “demonstration effect” of the circular economy pilot policy.
- Second, it is recommended that, in the governance of the circular economy, active participation from entities at all levels be galvanized, with a focus on green and low-carbon technological innovation, adjustment of the factor allocation structure, and the local government’s management of circular economy development. Due to the reliance of the circular economy pilot policy on the support of circular economy industries, the high initial investment level and long recovery period of circular economy industries, as well as the relatively low equipment levels of key technologies such as mining technology, environmental protection technology, energy-saving technology, and comprehensive utilization technology, there is a bottleneck phenomenon. At the local government level, it is necessary to increase economic incentives for circular economy industries, enhance interest subsidies for key technology development and promotion loans from fiscal funds, broaden the financing channels for key technologies through green financial innovation products such as green bonds, encourage enterprises participating in carbon emission reduction accounting to enter the carbon market trading and obtain market incentives for carbon emission reduction benefits, and strengthen the attention of local governments to the construction of circular economy and the support for circular economy innovation. On the legal front, the government responsibility system within the circular economy legal framework should be perfected, clarifying local government responsibilities for circular economy development goals, management scope, focus, and the specific procedures and timelines for responsibility implementation, thus ensuring local government’s governance intensity in managing the circular economy from its root. At the corporate level, the focus should be on reducing excess capacity, deleveraging, and facilitating an orderly exit for ‘zombie’ enterprises, optimizing the structure of corporate factor allocation, and steering social capital towards new energy or enterprises with higher energy efficiency.
- Third, it is advisable for the circular economy pilot policy to be tailored to the unique attributes of each city, identifying low-carbon transformation measures that align with the city’s specific traits. The circular economy pilot policy and regulations tend to be more macroscopic, lacking operational details, while the implementation of the circular economy pilot policy requires effective government supervision and public oversight. Therefore, to further refine the circular economy pilot policy and regulations, local governments can establish a circular economy carbon emission reduction accounting evaluation system, incorporate circular economy carbon emission reduction accounting into the local government assessment index system, and establish mechanisms and platforms for public participation in a circular economy. At the same time, there should be intensified policy guidance for key cities, implementing circular economy development strategies per differences in resource endowment, industrial structure, and economic foundation, such as currently prioritizing carbon reduction in resource-based cities, old industrial cities, and cities within the central region.
- Finally, the research findings indicate a significant “demonstration effect” of the circular economy pilot policy demonstration cities on the transformation of energy demand in surrounding areas. In response to this, this study suggests summarizing the standardized model of circular economy governance in national circular economy demonstration cities for replication and promotion in surrounding areas to enhance their demonstration effect, while also fostering innovative cooperation between national circular economy demonstration cities and surrounding areas in the field of energy generation.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
City Level | Eastern Region | Central Region | Western Region |
---|---|---|---|
Prefecture-level city | Suzhou, Weifang, Guangzhou, Quzhou, Nanping, Chengde | Hebi, Loudi, Tongling, Huangshi, Jilin, Jincheng | Wuzhou, Jinchang, Wuhai, Guangan, Pu’er, Chongqing Dazu, Shangluo |
County-level city | Ninghai, Yongkang, Xintai, Yanqing, Taixing, Shishi, Gaoyang | Jieshou, Guixi, Gucheng, Zixing, Diaobinshan, Boai, Xiaoyi | Tongwei, Tiandong, Longli, Huolinguole, Ge’ermu, Shanshanxian, Yimen |
City Level | Eastern Region | Central Region | Western Region |
---|---|---|---|
Prefecture-level city | Taizhou, Liaocheng, Xuzhou, Zhanjiang, Yangzhou, Qindao, Tianjin | Jinmen, Luoyang, Shenyang, Xinxiang, Anshan, Ji’an, Fuyang, Changsha | Baotou, Liupanshui, Baiyin, Shizuishan, Chongqing Qijiang, Lasa, Tongren, Luzhou, Chongqing, Hechuan, Qujing, Liuzhou |
County-level city | Pingyuan, Anji, Zhaoyuan, Guangning, Luoding, Haining, Danyang | Anhua, Fengyang, Fengcheng, Zhijiang, Zhangshu, Fanchang, Anxiang, Qianjiang, Tonghe, Jianping, Taonan, Changge | Hancheng, Cengong, Linxia, Pujiang, Fuchuanyaozhu, Jianshebintuan’ershi, Chongqing Liangping, Xichong, Tuoketuo, Jianshebintuanyishi, Rikazeshi, Manasi, Jingchuan, Yongning, Qingtongxia, Datong, Xiangyun |
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Variable | Description | Sample Size | Standard Deviation | Minimum Value | Median Value | Maximum Value |
---|---|---|---|---|---|---|
Logarithm of carbon emissions as a percentage of GDP | 4050 | 0.798 | −12.956 | −10.290 | −4.785 | |
Logarithm of total carbon emissions | 4050 | 1.123 | 2.521 | 6.072 | 10.060 | |
Dummy variable for pilot cities post-policy implementation (1 if yes, 0 if no) | 4050 | 0.252 | 0.000 | 0.068 | 1.000 | |
Logarithm of per capita GDP | 4050 | 0.999 | 13.461 | 16.362 | 19.774 | |
Proportion of urban population to total city population | 4050 | 0.234 | 0.075 | 0.401 | 1.926 | |
Ratio of financial institution loans to GDP | 4050 | 0.576 | 0.075 | 0.917 | 9.622 | |
Proportion of actual foreign capital used to GDP | 4050 | 0.019 | 0.001 | 0.018 | 0.212 | |
Comprehensive utilization rate of industrial waste | 4050 | 0.224 | 0.002 | 0.794 | 1.000 |
Variable | ||||
---|---|---|---|---|
−0.058 ** | −0.062 ** | −0.061 ** | −0.060 ** | |
(0.039) | (0.020) | (0.025) | (0.026) | |
−0.601 *** | 0.398 *** | |||
(0.000) | (0.000) | |||
0.165 ** | 0.169 ** | |||
(0.034) | (0.029) | |||
0.061 *** | 0.061 *** | |||
(0.001) | (0.001) | |||
−1.016 ** | −1.025 ** | |||
(0.016) | (0.015) | |||
0.096 *** | 0.096 *** | |||
(0.009) | (0.009) | |||
Constant | −9.804 *** | −0.672 | 5.648 *** | −0.660 |
(0.000) | (0.213) | (0.000) | (0.220) | |
Control | N | Y | N | Y |
Year FE | Y | Y | Y | Y |
City FE | Y | Y | Y | Y |
Observations | 4050 | 4050 | 4050 | 4050 |
R-squared | 0.391 | 0.450 | 0.340 | 0.365 |
Variables | PSM-DID | Introducing Interaction Effects | Excluding Interference from Related Policies | |||
---|---|---|---|---|---|---|
−0.055 ** | −0.053 ** | −0.058 ** | −0.055 ** | −0.092 ** | −0.090 ** | |
(0.032) | (0.040) | (0.036) | (0.045) | (0.028) | (0.032) | |
−0.540 *** | 0.459 *** | −0.284 *** | 0.714 *** | −0.498 *** | 0.503 *** | |
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |
0.093 | 0.096 | 0.042 | 0.046 | 0.172 * | 0.176 * | |
(0.226) | (0.209) | (0.607) | (0.577) | (0.098) | (0.089) | |
0.114 *** | 0.115 *** | 0.023 | 0.024 | 0.091 *** | 0.092 *** | |
(0.000) | (0.000) | (0.275) | (0.254) | (0.000) | (0.000) | |
−1.096 *** | −1.089 *** | −0.001 | 0.008 | −0.537 | −0.559 | |
(0.008) | (0.009) | (0.999) | (0.989) | (0.399) | (0.379) | |
0.082 ** | 0.082 ** | 0.137 *** | 0.137 *** | 0.084 * | 0.084 * | |
(0.026) | (0.026) | (0.001) | (0.001) | (0.092) | (0.092) | |
Constant | −1.601 *** | −1.587 *** | −5.026 *** | −5.042 *** | −2.410 *** | −2.419 *** |
(0.005) | (0.005) | (0.000) | (0.000) | (0.000) | (0.000) | |
Control | Y | Y | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y | Y | Y |
City FE | Y | Y | Y | Y | Y | Y |
Province × Year FE | Y | Y | ||||
Observations | 3828 | 3828 | 4050 | 4050 | 2310 | 2310 |
R-squared | 0.471 | 0.373 | 0.525 | 0.451 | 0.349 | 0.364 |
Variables | Government’s S and T Funding | Per Capita Fixed Capital | ||||
---|---|---|---|---|---|---|
0.007 *** | −0.059 ** | −0.057 ** | −0.144 *** | −0.056 ** | −0.054 ** | |
(0.001) | (0.027) | (0.034) | (0.000) | (0.036) | (0.044) | |
−0.393 * | −0.389 * | |||||
(0.053) | (0.055) | |||||
0.041 *** | 0.041 *** | |||||
(0.003) | (0.003) | |||||
Constant | −0.126 *** | −0.721 | −0.709 | 6.522 *** | −0.939 * | −0.927 * |
(0.004) | (0.181) | (0.188) | (0.000) | (0.085) | (0.089) | |
Control | Y | Y | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y | Y | Y |
City FE | Y | Y | Y | Y | Y | Y |
Observations | 4050 | 4050 | 4050 | 4050 | 4050 | 4050 |
R-squared | 0.208 | 0.451 | 0.365 | 0.104 | 0.451 | 0.366 |
Variables | ||||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
−0.065 ** | −0.968 *** | −0.063 ** | −0.984 *** | |
(0.015) | (0.002) | (0.019) | (0.001) | |
0.097 ** | 0.111 *** | 0.098 ** | 0.112 *** | |
(0.023) | (0.010) | (0.022) | (0.009) | |
−0.205 *** | −0.209 *** | |||
(0.003) | (0.002) | |||
Constant | −0.218 | 0.054 | −0.202 | 0.075 |
(0.705) | (0.926) | (0.724) | (0.897) | |
Control | Y | Y | Y | Y |
Year fixed | Y | Y | Y | Y |
City FE | Y | Y | Y | Y |
Observations | 4050 | 4050 | 4050 | 4050 |
R-squared | 0.451 | 0.452 | 0.366 | 0.367 |
Variables | G-Resource | M-Resource | R-Resource | D-Resource | ||||
---|---|---|---|---|---|---|---|---|
−0.098 ** | −0.098 ** | −1.538 *** | −1.531 *** | −0.116 * | −0.112 * | 0.021 | 0.022 | |
(0.035) | (0.035) | (0.000) | (0.000) | (0.060) | (0.069) | (0.804) | (0.797) | |
Constant | 0.552 | 0.383 | −8.264 ** | −8.188 ** | −1.578 | −1.545 | −6.574 *** | −6.471 *** |
(0.671) | (0.768) | (0.010) | (0.010) | (0.190) | (0.200) | (0.002) | (0.002) | |
Control | Y | Y | Y | Y | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y | Y | Y | Y | Y |
City FE | Y | Y | Y | Y | Y | Y | Y | Y |
Observations | 345 | 345 | 195 | 195 | 885 | 885 | 225 | 225 |
R-squared | 0.797 | 0.289 | 0.300 | 0.521 | 0.424 | 0.313 | 0.586 | 0.437 |
Variables | High Industrialization Level | Low Industrialization Level | ||
---|---|---|---|---|
−0.133 *** | −0.130 *** | 0.008 | 0.010 | |
(0.002) | (0.002) | (0.808) | (0.759) | |
Constant | 0.737 | 0.698 | −0.588 | −0.563 |
(0.439) | (0.463) | (0.426) | (−0.446) | |
Control | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y |
City FE | Y | Y | Y | Y |
Observations | 1410 | 1410 | 2640 | 2640 |
R-squared | 0.537 | 0.211 | 0.418 | 0.455 |
Variables | Eastern Region | Central Region | Western Region | Northeastern Region | ||||
---|---|---|---|---|---|---|---|---|
−0.049 | −0.048 | −0.098 ** | −0.100 ** | −0.056 | −0.049 | −0.099 | −0.096 | |
(0.212) | (0.222) | (0.014) | (0.013) | (0.391) | (0.453) | (0.263) | (0.277) | |
Constant | 1.094 | 1.079 | −1.261 | −1.225 | −4.133 *** | −4.150 *** | 1.533 | 1.606 |
(0.365) | (0.370) | (0.277) | (0.290) | (0.003) | (0.003) | (0.294) | (0.271) | |
Control | Y | Y | Y | Y | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y | Y | Y | Y | Y |
City FE | Y | Y | Y | Y | Y | Y | Y | Y |
Observations | 1290 | 1290 | 1170 | 1170 | 1095 | 1095 | 495 | 495 |
R-squared | 0.445 | 0.512 | 0.660 | 0.431 | 0.337 | 0.304 | 0.484 | 0.248 |
Variable | ||||||
---|---|---|---|---|---|---|
Moran’s I | z | p-Value | Moran’s I | z | p-Value | |
2006 | 0.168 | 4.127 | 0.000 | 0.209 | 5.125 | 0.000 |
2007 | 0.159 | 3.922 | 0.000 | 0.217 | 5.310 | 0.000 |
2008 | 0.155 | 3.827 | 0.000 | 0.213 | 5.206 | 0.000 |
2009 | 0.189 | 4.655 | 0.000 | 0.215 | 5.262 | 0.000 |
2010 | 0.234 | 5.716 | 0.000 | 0.241 | 5.890 | 0.000 |
2011 | 0.201 | 4.929 | 0.000 | 0.222 | 5.434 | 0.000 |
2012 | 0.148 | 3.645 | 0.000 | 0.235 | 5.753 | 0.000 |
2013 | 0.156 | 3.843 | 0.000 | 0.256 | 6.258 | 0.000 |
2014 | 0.203 | 4.993 | 0.000 | 0.244 | 5.963 | 0.000 |
2015 | 0.282 | 6.874 | 0.000 | 0.278 | 6.772 | 0.000 |
2016 | 0.310 | 7.565 | 0.000 | 0.271 | 6.605 | 0.000 |
2017 | 0.319 | 7.807 | 0.000 | 0.265 | 6.477 | 0.000 |
2018 | 0.327 | 8.023 | 0.000 | 0.257 | 6.285 | 0.000 |
2019 | 0.335 | 8.253 | 0.000 | 0.232 | 5.684 | 0.000 |
2020 | 0.328 | 8.084 | 0.000 | 0.229 | 5.612 | 0.000 |
Variable | SLM-DID | SEM-DID | ||
---|---|---|---|---|
LM-test | 3.743 ** | 26.402 *** | 23.921 *** | 5.307 ** |
LR-test | 90.35 *** | 106.66 *** | 99.39 *** | 100.03 *** |
Wald-test | 91.21 *** | 108.08 *** | 100.11 *** | 100.76 *** |
Variable | Spatial Adjacency | Geographic Distance | Economic Distance | |||
---|---|---|---|---|---|---|
−0.050 ** | −0.047 * | −0.062 ** | −0.059 ** | −0.053 ** | −0.050 ** | |
(0.046) | (0.060) | (0.015) | (0.020) | (0.036) | (0.048) | |
−0.382 *** | −0.382 *** | −0.340 ** | −0.339 ** | −0.348 *** | −0.345 *** | |
(0.000) | (0.000) | (0.016) | (0.016) | (0.000) | (0.000) | |
ρ | 0.143 *** | 0.143 *** | 0.534 *** | 0.539 *** | 0.271 *** | 0.273 *** |
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |
Direct Effect | −0.062 ** | −0.059 ** | −0.064 ** | −0.061 ** | −0.058 ** | −0.055 ** |
(0.018) | (0.023) | (0.016) | (0.020) | (0.028) | (0.035) | |
Indirect Effect | −0.430 *** | −0.428 *** | −0.819 ** | −0.819 ** | −0.491 *** | −0.487 *** |
(0.000) | (0.000) | (0.018) | (0.029) | (0.000) | (0.000) | |
Total Effect | −0.492 *** | −0.487 *** | −0.882 ** | −0.880 ** | −0.549 *** | −0.542 *** |
(0.000) | (0.000) | (0.012) | (0.020) | (0.000) | (0.000) | |
Control | Y | Y | Y | Y | Y | Y |
Year FE | Y | Y | Y | Y | Y | Y |
City FE | Y | Y | Y | Y | Y | Y |
Observations | 4050 | 4050 | 4050 | 4050 | 4050 | 4050 |
R-squared | 0.104 | 0.520 | 0.121 | 0.609 | 0.128 | 0.617 |
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Li, S.; Hu, Z. The Impact of the Circular Economy Pilot Policy on Carbon Emissions in Chinese Cities and Its Underlying Mechanisms. Sustainability 2024, 16, 7859. https://doi.org/10.3390/su16177859
Li S, Hu Z. The Impact of the Circular Economy Pilot Policy on Carbon Emissions in Chinese Cities and Its Underlying Mechanisms. Sustainability. 2024; 16(17):7859. https://doi.org/10.3390/su16177859
Chicago/Turabian StyleLi, Shanshan, and Zhengjun Hu. 2024. "The Impact of the Circular Economy Pilot Policy on Carbon Emissions in Chinese Cities and Its Underlying Mechanisms" Sustainability 16, no. 17: 7859. https://doi.org/10.3390/su16177859