Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China
Abstract
:1. Introduction
2. Feature Fact Analysis and Theoretical Mechanisms
2.1. Characteristic Fact Analysis
2.2. Theoretical Mechanisms
3. Case Study and Discussion
3.1. Model Setting
3.2. Variable Descriptions
3.2.1. Dependent Variables and Independent Variables
3.2.2. Covariates
3.2.3. Mediators
3.3. Data Method
4. Results Discussion
4.1. Benchmark Regression Results
4.2. Robustness Tests
4.2.1. Parallel Trend Test
4.2.2. Removing the Control Group Sample Selection Bias: PSM-DID Model
4.2.3. Removing Other Policy Interference: DDD Model
4.2.4. Removing Random Factor Confounding: Placebo Test
4.3. Mechanism Analysis
5. Heterogeneity and Spatial Effect
5.1. Heterogeneity Analysis
5.1.1. Panel Quantile Regression
5.1.2. Grouping Regression
5.2. Spatial Effect Analysis
6. Concluding Remarks
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable Type. | Variables | Symbol | Measurement |
---|---|---|---|
Output Indicators | Real industrial output | y | The total industrial output value above the scale and deflated by the industrial producer ex-factory price index in the province where it is located, using 2003 as a benchmark |
Input Indicators | Industrial Capital Inputs | K | Fixed capital stock, which is measured using the perpetual inventory method and is deflated by the fixed asset investment price index of the province in which it is located using 2003 as a benchmark |
Industrial labor input | L | The number of employees in the secondary industry minus the number of employees in the construction industry gives | |
Industrial Energy Inputs | E | Use of industrial electricity consumption as a proxy variable |
Test Method | Statistic Type | Statistic Value | p-Value |
---|---|---|---|
Kao test | Modified Dickey–Fuller t | 3.188 | 0.001 |
Pedroni test | Modified Phillips–Perron t | 5.021 | 0.000 |
Westerlund test | Variance ratio | 3.125 | 0.001 |
Year | N | p25 | p50 | p75 | Mean | SD |
---|---|---|---|---|---|---|
2003 | 4522 | 0.620 | 0.768 | 0.955 | 0.751 | 0.217 |
2004 | 4522 | 0.599 | 0.735 | 0.864 | 0.715 | 0.199 |
2005 | 4522 | 0.600 | 0.716 | 0.920 | 0.726 | 0.208 |
2006 | 4522 | 0.601 | 0.751 | 0.975 | 0.745 | 0.221 |
2007 | 4522 | 0.600 | 0.792 | 0.952 | 0.755 | 0.216 |
2008 | 4522 | 0.550 | 0.750 | 0.939 | 0.725 | 0.224 |
2009 | 4522 | 0.613 | 0.720 | 0.849 | 0.717 | 0.182 |
2010 | 4522 | 0.488 | 0.650 | 0.788 | 0.638 | 0.207 |
2011 | 4522 | 0.549 | 0.702 | 0.837 | 0.686 | 0.191 |
2012 | 4522 | 0.549 | 0.690 | 0.813 | 0.666 | 0.188 |
2013 | 4522 | 0.467 | 0.612 | 0.736 | 0.596 | 0.180 |
2014 | 4522 | 0.238 | 0.422 | 0.599 | 0.435 | 0.233 |
2015 | 4522 | 0.427 | 0.581 | 0.732 | 0.579 | 0.196 |
2016 | 4522 | 0.401 | 0.507 | 0.653 | 0.526 | 0.175 |
2017 | 4522 | 0.360 | 0.472 | 0.631 | 0.497 | 0.179 |
2018 | 4522 | 0.339 | 0.468 | 0.594 | 0.474 | 0.180 |
2019 | 4522 | 0.352 | 0.485 | 0.604 | 0.483 | 0.184 |
Overall | 4522 | 0.468 | 0.636 | 0.798 | 0.630 | 0.226 |
Variable Type | Variables | Symbol | Obs | Min | Max | Mean | S.E. |
---|---|---|---|---|---|---|---|
Dependent variable | Industrial capacity utilization | IUC | 4522 | 0.106 | 1.000 | 0.630 | 0.226 |
Independent variable | Low-carbon city policy variable | treat×post | 4522 | 0.000 | 1.000 | 0.196 | 0.397 |
Covariates | City size | pop_size | 4522 | −7.662 | −1.288 | −3.409 | 0.227 |
Fiscal deficit | deficit | 4522 | −9.544 | 0.584 | −2.776 | 0.872 | |
Education level | education | 4522 | −4.032 | −0.705 | −1.725 | 1.049 | |
Financial development level | financial | 4522 | −0.897 | 3.075 | 0.642 | 0.258 | |
Opening degree | opening | 4522 | −12.830 | −0.781 | −4.154 | 0.363 | |
Mediators | Integrated resource misallocation index | misallocation | 4522 | 0.000 | 0.999 | 0.918 | 1.448 |
Industrial structure upgrading index | upgrade | 4522 | 0.095 | 5.154 | 0.895 | 0.092 | |
Technological innovation index | innovation | 4522 | 0.000 | 0.207 | 0.013 | 0.471 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
ICU | ICU | ICU | ICU | |
BCC/SBM(VRS) | BCC/SBM(VRS) | Super-SBM(VRS) | Super-SBM(VRS) | |
treat × post | 0.033 *** | 0.032 *** | 0.037 *** | 0.033 *** |
(0.007) | (0.007) | (0.007) | (0.007) | |
pop_size | 0.291 *** | 0.382 *** | ||
(0.038) | (0.044) | |||
deficit | 0.001 | 0.003 | ||
(0.006) | (0.007) | |||
education | 0.059 *** | 0.078 *** | ||
(0.014) | (0.015) | |||
financial | 0.045 *** | 0.038 ** | ||
(0.014) | (0.015) | |||
opening | 0.005 * | 0.004 | ||
(0.002) | (0.003) | |||
_cons | 0.623 *** | 1.705 *** | 0.614 *** | 2.049 *** |
(0.002) | (0.136) | (0.002) | (0.162) | |
Covariant | No | Yes | No | Yes |
Year-FE | Yes | Yes | Yes | Yes |
City-FE | Yes | Yes | Yes | Yes |
N | 4522 | 4522 | 4522 | 4522 |
R-squared | 0.757 | 0.763 | 0.740 | 0.750 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
ICU | ICU | ICU | ICU | |
PSM-DID | PSM-DID | DDD | DDD | |
treat × post | 0.034 *** | 0.033 *** | ||
(0.007) | (0.007) | |||
treat × post × group | 0.118 *** | 0.105 *** | ||
(0.010) | (0.010) | |||
pop_size | 0.309 *** | 0.253 *** | ||
(0.039) | (0.040) | |||
deficit | 0.002 | −0.002 | ||
(0.006) | (0.005) | |||
education | 0.061 *** | 0.047 *** | ||
(0.015) | (0.014) | |||
financial | 0.042 *** | 0.047 *** | ||
(0.015) | (0.014) | |||
opening | 0.003 | 0.004 * | ||
(0.002) | (0.002) | |||
_cons | 0.624 *** | 1.755 *** | 0.623 *** | 1.547 *** |
(0.002) | (0.137) | (0.002) | (0.139) | |
Covariant | No | Yes | No | Yes |
Year-FE | Yes | Yes | Yes | Yes |
City-FE | Yes | Yes | Yes | Yes |
Group-FE | No | No | Yes | Yes |
N | 4461 | 4461 | 4522 | 4522 |
R-squared | 0.757 | 0.764 | 0.761 | 0.766 |
Variable | Alleviating Resource Misallocation | Industrial Structure Upgrading | Technology Innovation | |||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Misallocation | ICU | Upgrade | ICU | Innovation | ICU | |
treat × post | −0.011 *** | 0.026 *** | 0.046 *** | 0.031 *** | 0.003 *** | 0.028 *** |
(0.001) | (0.007) | (0.012) | (0.007) | (0.001) | (0.007) | |
misallocation | −0.558 *** | |||||
(0.069) | ||||||
upgrade | 0.026 *** | |||||
(0.009) | ||||||
innovation | 1.312 *** | |||||
(0.331) | ||||||
pop_size | −0.075 *** | 0.249 *** | 0.151 * | 0.287 *** | 0.018 *** | 0.267 *** |
(0.016) | (0.038) | (0.087) | (0.039) | (0.006) | (0.040) | |
deficit | 0.001 | 0.001 | −0.010 | 0.000 | −0.001 | 0.002 |
(0.002) | (0.006) | (0.009) | (0.006) | (0.001) | (0.006) | |
education | −0.021 *** | 0.047 *** | 0.140 *** | 0.055 *** | 0.006 * | 0.051 *** |
(0.004) | (0.014) | (0.025) | (0.015) | (0.003) | (0.016) | |
financial | −0.004 | 0.043 *** | 0.389 *** | 0.035 ** | −0.005 *** | 0.051 *** |
(0.004) | (0.014) | (0.035) | (0.015) | (0.001) | (0.014) | |
opening | −0.000 | 0.004 * | −0.005 | 0.005 * | 0.000 * | 0.004 * |
(0.000) | (0.002) | (0.006) | (0.002) | (0.000) | (0.002) | |
_cons | 0.635 *** | 2.060 *** | 1.342 *** | 1.671 *** | 0.086 *** | 1.592 *** |
(0.054) | (0.137) | (0.315) | (0.138) | (0.021) | (0.144) | |
Covariant | Yes | Yes | Yes | Yes | Yes | Yes |
Year−FE | Yes | Yes | Yes | Yes | Yes | Yes |
City−FE | Yes | Yes | Yes | Yes | Yes | Yes |
N | 4522 | 4522 | 4522 | 4522 | 4522 | 4522 |
R−squared | 0.933 | 0.766 | 0.822 | 0.763 | 0.670 | 0.765 |
Variable | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
P10 | P25 | P50 | P75 | P90 | |
ICU | ICU | ICU | ICU | ICU | |
treat × post | 0.023 | 0.026 ** | 0.032 *** | 0.038 ** | 0.041 * |
(0.017) | (0.013) | (0.011) | (0.017) | (0.022) | |
pop_size | 0.379 *** | 0.345 *** | 0.289 *** | 0.236 *** | 0.204 * |
(0.093) | (0.069) | (0.059) | (0.091) | (0.119) | |
deficit | 0.002 | 0.001 | 0.000 | −0.001 | −0.002 |
(0.013) | (0.010) | (0.009) | (0.013) | (0.017) | |
education | 0.048 | 0.052 ** | 0.059 *** | 0.066 * | 0.070 |
(0.034) | (0.026) | (0.022) | (0.034) | (0.044) | |
financial | 0.055 | 0.051 * | 0.045 ** | 0.039 | 0.036 |
(0.035) | (0.026) | (0.023) | (0.035) | (0.045) | |
opening | 0.003 | 0.003 | 0.005 | 0.006 | 0.006 |
(0.006) | (0.005) | (0.004) | (0.006) | (0.008) | |
Covariant | Yes | Yes | Yes | Yes | Yes |
Year-FE | Yes | Yes | Yes | Yes | Yes |
City-FE | Yes | Yes | Yes | Yes | Yes |
N | 4522 | 4522 | 4522 | 4522 | 4522 |
Variable | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
OIB | Non-OIB | B&R | Non-B&R | FTZ | Non-FTZ | |
ICU | ICU | ICU | ICU | ICU | ICU | |
treat×post | 0.051 *** | 0.026 *** | 0.067 *** | 0.010 | 0.066 *** | 0.016 ** |
(0.009) | (0.009) | (0.010) | (0.009) | (0.013) | (0.008) | |
pop_size | 0.457 *** | 0.104 ** | 0.312 *** | 0.231 *** | 0.101 ** | 0.326 *** |
(0.058) | (0.048) | (0.049) | (0.063) | (0.045) | (0.055) | |
deficit | 0.002 | 0.005 | −0.005 | 0.009 | 0.003 | −0.002 |
(0.008) | (0.008) | (0.008) | (0.007) | (0.007) | (0.008) | |
education | 0.092 *** | 0.085 *** | 0.054 ** | 0.032 ** | 0.041 | 0.052 *** |
(0.018) | (0.020) | (0.025) | (0.016) | (0.032) | (0.016) | |
financial | −0.013 | 0.059 *** | 0.041 ** | 0.033 * | −0.004 | 0.067 *** |
(0.019) | (0.021) | (0.020) | (0.019) | (0.038) | (0.017) | |
opening | 0.002 | 0.010 *** | 0.004 | 0.003 | 0.016 * | 0.002 |
(0.003) | (0.004) | (0.003) | (0.004) | (0.010) | (0.002) | |
_cons | 2.427 *** | 1.090 *** | 1.868 *** | 1.414 *** | 1.060 *** | 1.817 *** |
(0.208) | (0.168) | (0.192) | (0.198) | (0.156) | (0.200) | |
Covariant | Yes | Yes | Yes | Yes | Yes | Yes |
Year−FE | Yes | Yes | Yes | Yes | Yes | Yes |
City−FE | Yes | Yes | Yes | Yes | Yes | Yes |
N | 1884 | 2581 | 2024 | 2441 | 756 | 3709 |
R-squared | 0.785 | 0.737 | 0.759 | 0.777 | 0.813 | 0.764 |
Year | Local Moran’s I | E.V. | S.E. | Z-Statistic | p-Value |
---|---|---|---|---|---|
2003 | 0.198 | −0.004 | 0.042 | 4.762 | 0.000 |
2004 | 0.195 | −0.004 | 0.042 | 4.706 | 0.000 |
2005 | 0.173 | −0.004 | 0.042 | 4.180 | 0.000 |
2006 | 0.203 | −0.004 | 0.042 | 4.887 | 0.000 |
2007 | 0.153 | −0.004 | 0.042 | 3.702 | 0.000 |
2008 | 0.148 | −0.004 | 0.042 | 3.582 | 0.000 |
2009 | 0.087 | −0.004 | 0.042 | 2.133 | 0.033 |
2010 | 0.123 | −0.004 | 0.042 | 2.997 | 0.003 |
2011 | 0.175 | −0.004 | 0.042 | 4.224 | 0.000 |
2012 | 0.203 | −0.004 | 0.042 | 4.887 | 0.000 |
2013 | 0.302 | −0.004 | 0.042 | 7.232 | 0.000 |
2014 | 0.340 | −0.004 | 0.042 | 8.123 | 0.000 |
2015 | 0.204 | −0.004 | 0.042 | 4.913 | 0.000 |
2016 | 0.252 | −0.004 | 0.042 | 6.054 | 0.000 |
2017 | 0.256 | −0.004 | 0.042 | 6.131 | 0.000 |
2018 | 0.256 | −0.004 | 0.042 | 6.150 | 0.000 |
2019 | 0.275 | −0.004 | 0.042 | 6.595 | 0.000 |
Global Moran’s I | 0.358 | −0.000 | 0.010 | 36.878 | 0.000 |
Effect Type | Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|---|
ICU | ICU | ICU | ICU | ||
Adjacency Matrix | Adjacency Matrix | Economic Matrix | Economic Matrix | ||
Direct effect | treat × post | 0.025 ** | 0.025 ** | 0.030 ** | 0.029 ** |
pop_size | 0.250 *** | 0.289 *** | |||
deficit | 0.001 | 0.001 | |||
education | 0.039 | 0.056 ** | |||
financial | 0.029 | 0.039 | |||
opening | 0.005 * | 0.005 * | |||
Indirect effect | treat × post | 0.012 * | 0.011 * | 0.009 * | 0.009 * |
pop_size | 0.113 | 0.090 ** | |||
deficit | 0.001 | 0.001 | |||
education | 0.018 * | 0.017 * | |||
financial | 0.013 | 0.012 | |||
opening | 0.002 * | 0.001 | |||
Total effect | treat × post | 0.037 ** | 0.036 ** | 0.039 ** | 0.038 ** |
pop_size | 0.362 *** | 0.379 *** | |||
deficit | 0.002 | 0.002 | |||
education | 0.056 * | 0.074 ** | |||
financial | 0.043 | 0.052 | |||
opening | 0.008 * | 0.007 * | |||
Covariant | No | Yes | No | Yes | |
Year-FE | Yes | Yes | Yes | Yes | |
City-FE | Yes | Yes | Yes | Yes | |
N | 4461 | 4461 | 4522 | 4522 |
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Han, Z.; Wang, L.; Zhao, F.; Mao, Z. Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China. Sustainability 2022, 14, 10941. https://doi.org/10.3390/su141710941
Han Z, Wang L, Zhao F, Mao Z. Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China. Sustainability. 2022; 14(17):10941. https://doi.org/10.3390/su141710941
Chicago/Turabian StyleHan, Zhipeng, Liguo Wang, Feifei Zhao, and Zijun Mao. 2022. "Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China" Sustainability 14, no. 17: 10941. https://doi.org/10.3390/su141710941
APA StyleHan, Z., Wang, L., Zhao, F., & Mao, Z. (2022). Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China. Sustainability, 14(17), 10941. https://doi.org/10.3390/su141710941