How Does Diversification of Producer Services Agglomeration Help Reduce Carbon Emissions Intensity? Evidence from 252 Chinese Cities, 2005–2018
Abstract
:1. Introduction
2. Theoretical Analyses
3. Empirical Framework
3.1. Econometric Models
3.2. Variables and Data
3.2.1. Measuring Carbon Emissions Intensity
3.2.2. Measuring Producer Services Agglomeration Diversification
3.2.3. Mechanism Variables
3.2.4. Controls
4. Baseline Results and Robustness Analyses
4.1. Baseline Results
4.2. Robustness
5. Mechanism Analyses
6. Heterogeneity
7. Discussion and Policy Implications
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Definitions | Observations | Mean | Std. Dev. |
---|---|---|---|---|
Log carbon emissions intensity per nominal GDP | 3772 | 8.520 | 0.697 | |
Log producer services agglomeration diversification | 3772 | 0.202 | 0.091 | |
Log producer services employment | 3772 | 6.554 | 0.858 | |
Log manufacturing employment | 3772 | 10.724 | 1.117 | |
Log real GDP | 3772 | 15.677 | 0.963 | |
Ratio of the tertiary industry output to secondary industry output | 3772 | 0.844 | 0.404 | |
Log average wages | 3772 | 10.263 | 0.575 | |
Log total green patent applications | 3772 | 17.896 | 5.480 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
−1.695 *** | −0.302 *** | −0.181 *** | −0.145 *** | |
(0.257) | (0.048) | (0.055) | (0.037) | |
−0.043 ** | −0.023 * | |||
(0.017) | (0.012) | |||
−0.081 *** | −0.057 *** | |||
(0.011) | (0.009) | |||
−0.621 *** | ||||
(0.036) | ||||
0.050 *** | ||||
(0.013) | ||||
−0.107 *** | ||||
(0.026) | ||||
−0.006 *** | ||||
(0.001) | ||||
City fixed effects | Yes | Yes | Yes | Yes |
Year fixed effects | No | Yes | Yes | Yes |
Constant | 8.861 *** | 8.580 *** | 9.707 *** | 20.201 *** |
(0.052) | (0.010) | (0.118) | (0.538) | |
Observations | 3780 | 3780 | 3780 | 3772 |
Adj. R-squared | 0.743 | 0.961 | 0.963 | 0.977 |
(1) | (2) | (3) | (4) | (5) | |
---|---|---|---|---|---|
−0.126 *** | −0.203 *** | −0.078 *** | −0.053 * | −0.143 *** | |
(0.039) | (0.054) | (0.029) | (0.028) | (0.047) | |
0.009 | −0.026 * | −0.003 | −0.008 | −0.016 | |
(0.014) | (0.015) | (0.010) | (0.009) | (0.015) | |
−0.054 *** | −0.074 *** | −0.047 *** | −0.054 *** | −0.075 *** | |
(0.010) | (0.011) | (0.008) | (0.007) | (0.011) | |
−0.715 *** | −0.679 *** | −0.642 *** | −0.828 *** | −0.385 *** | |
(0.042) | (0.041) | (0.036) | (0.018) | (0.031) | |
0.112 *** | 0.458 *** | 0.007 | 0.029 ** | 0.061 *** | |
(0.017) | (0.021) | (0.012) | (0.012) | (0.014) | |
−0.268 *** | −0.213 *** | −0.049 ** | −0.073 *** | −0.111 *** | |
(0.032) | (0.033) | (0.023) | (0.020) | (0.029) | |
−0.010 *** | −0.008 *** | 0.000 | −0.003 *** | −0.009 *** | |
(0.002) | (0.002) | (0.001) | (0.001) | (0.001) | |
City fixed effects | Yes | Yes | Yes | Yes | Yes |
Year fixed effects | Yes | Yes | Yes | Yes | Yes |
Constant | 24.473 *** | 22.869 *** | 19.942 *** | 23.011 *** | 16.677 *** |
(0.635) | (0.634) | (0.518) | (0.336) | (0.520) | |
Observations | 3772 | 3772 | 3772 | 4024 | 3522 |
Adj. R-squared | 0.974 | 0.967 | 0.979 | 0.983 | 0.972 |
(1) | (2) | (3) | (4) | (5) | |
---|---|---|---|---|---|
−0.470 ** | −0.545 *** | 4.991 *** | −0.377 ** | 0.414 ** | |
(0.196) | (0.208) | (1.710) | (0.158) | (0.202) | |
−0.353 *** | −0.222 *** | −0.570 | 0.014 | 0.253 *** | |
(0.043) | (0.041) | (0.378) | (0.043) | (0.046) | |
−0.128 *** | −0.389 *** | 2.973 *** | 0.067 ** | 0.011 | |
(0.024) | (0.026) | (0.219) | (0.034) | (0.031) | |
−0.213 *** | −0.248 *** | 1.794 *** | 0.161 ** | 0.217 *** | |
(0.044) | (0.046) | (0.455) | (0.072) | (0.077) | |
−0.053 * | 0.030 | −0.097 | 0.004 | −0.054 | |
(0.029) | (0.032) | (0.248) | (0.059) | (0.050) | |
0.636 *** | 0.529 *** | 1.147 | 0.157 * | −0.033 | |
(0.066) | (0.068) | (0.698) | (0.089) | (0.093) | |
0.001 | −0.005 | −0.002 | 0.003 | 0.135 *** | |
(0.003) | (0.004) | (0.034) | (0.005) | (0.005) | |
City fixed effects | Yes | Yes | Yes | Yes | Yes |
Year fixed effects | Yes | Yes | Yes | Yes | Yes |
Constant | 4.702 *** | 9.228 *** | −60.297 *** | −4.925 *** | −3.159 ** |
(0.814) | (0.881) | (8.922) | (1.406) | (1.447) | |
Observations | 3772 | 3772 | 3772 | 3772 | 3721 |
Adj. R-squared | 0.807 | 0.832 | 0.750 | 0.907 | 0.949 |
(1) | (2) | |
---|---|---|
−0.006 | ||
(0.035) | ||
−0.239 *** | ||
(0.066) | ||
−0.136 *** | ||
(0.038) | ||
−0.165 *** | ||
(0.043) | ||
All controls | Yes | Yes |
City fixed effects | Yes | Yes |
Province–year fixed effects | Yes | Yes |
Constant | 20.097 *** | 20.192 *** |
(0.538) | (0.539) | |
Observations | 3772 | 3772 |
Adj. R-squared | 0.977 | 0.977 |
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Luo, L.; Bi, T.; Yu, H. How Does Diversification of Producer Services Agglomeration Help Reduce Carbon Emissions Intensity? Evidence from 252 Chinese Cities, 2005–2018. Sustainability 2024, 16, 2125. https://doi.org/10.3390/su16052125
Luo L, Bi T, Yu H. How Does Diversification of Producer Services Agglomeration Help Reduce Carbon Emissions Intensity? Evidence from 252 Chinese Cities, 2005–2018. Sustainability. 2024; 16(5):2125. https://doi.org/10.3390/su16052125
Chicago/Turabian StyleLuo, Langsha, Tianyu Bi, and Haochen Yu. 2024. "How Does Diversification of Producer Services Agglomeration Help Reduce Carbon Emissions Intensity? Evidence from 252 Chinese Cities, 2005–2018" Sustainability 16, no. 5: 2125. https://doi.org/10.3390/su16052125