Does the Upgrading of Development Zones Improve Land Use Efficiency under the Net-Zero Carbon City Goal? Prefectural-Level Evidence from Quasi-Natural Experiments in China
Abstract
:1. Introduction
2. Research Background and Theoretical Mechanisms
2.1. The Upgrade Policy and High-Quality Transformation in DZ Construction
2.2. Theoretical Mechanisms
3. Materials and Methods
3.1. Sample Selection and Data Description
3.2. Variable Settings
3.2.1. Dependent Variable
3.2.2. Independent Variable
3.2.3. Control Variables
3.3. Methods
3.3.1. Carbon Budget Accounting
3.3.2. Global Super-Efficiency Epsilon-Based Measure Model
3.3.3. Staggered Differences-in-Differences Model
4. Results
4.1. Stylized Facts of Urban Net Carbon Emissions and Land Use Efficiency
4.1.1. Stylized Facts of Urban Net Carbon Emissions
4.1.2. Stylized Facts of Urban Land Use Efficiency
4.2. Benchmark Results
4.3. Robustness Tests
4.3.1. Parallel Trends Test and Dynamic Effects Analysis
4.3.2. Synthetic Differences-in-Differences Estimation
4.3.3. Tests for Heterogeneous Treatment Effects
4.3.4. Placebo Tests
4.4. Dual Effects of Emission Reduction and Sink Enhancement
4.5. Mechanism Tests
4.5.1. Land-Use and Environmental Regulations
4.5.2. Resource Allocation Optimization
4.5.3. Green Technological Innovation
4.6. Heterogeneity Analyses
4.6.1. Heterogeneity of National DZs
4.6.2. Heterogeneity of Regions
5. Discussion
6. Conclusions and Policy Implication
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Variable | N | Mean | S.D. | Minimum | Maximum |
---|---|---|---|---|---|
ULUE | 2639 | 2.649 | 1.985 | 0.030 | 12.047 |
Pgdp | 2639 | 10.188 | 0.635 | 8.538 | 11.608 |
Gov | 2639 | 0.186 | 0.095 | 0.061 | 0.625 |
Fin | 2639 | 1.877 | 0.635 | 0.849 | 4.033 |
Indus | 2639 | 0.848 | 0.077 | 0.619 | 0.987 |
Fdi | 2639 | 0.031 | 0.026 | 0.003 | 0.141 |
Num | 2639 | 1.555 | 0.660 | 0 | 2.890 |
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Layer of Criteria | Layer of Factors | Layer of Indicators | Unit |
---|---|---|---|
inputs | labor | number of employees in the primary, secondary, and tertiary | 104 persons |
land | area of built districts | km2 | |
capital | capital stock | 108 CNY | |
outputs | desirable output | GDP | 108 CNY |
undesirable output | net carbon emissions | million tones (mt) |
Variable | Definition | Code | Unit |
---|---|---|---|
economic development | natural logarithm of GDP per capita | Pgdp | - |
government intervention | (local fiscal expenditure)/regional GDP | Gov | % |
financial development | deposits and loans of financial institutions/regional GDP | Fin | % |
industrial structure | secondary and tertiary industry added value/regional GDP | Indus | % |
foreign direct investment | number of foreign-invested enterprises/number of industrial enterprises | Fdi | % |
number of provincial DZs | natural logarithm of number of provincial DZs | Num | - |
ULUE | ||
---|---|---|
(1) | (2) | |
UPDZ | 0.053 ** (0.024) | 0.047 *** (0.011) |
control variables | no | yes |
constant term | yes | yes |
time fixed effect | yes | yes |
city fixed effect | yes | yes |
sample size | 2639 | 2639 |
R-squared | 0.009 | 0.011 |
ULUE | ||
---|---|---|
(1) | (2) | |
UPDZ | 0.043 *** (0.014) | 0.045 *** (0.016) |
control variables | no | yes |
time fixed effect | yes | yes |
city fixed effect | yes | yes |
Panel A: Robust Estimations | ULUE | |||
---|---|---|---|---|
Simple Weighted ATT | Dynamic ATT | Calendar ATT | Group ATT | |
(1) | (2) | (3) | (4) | |
Simple ATT | 0.041 ** (0.019) | |||
Pre_Avg | 0.007 (0.005) | |||
Post_avg | 0.054 ** (0.025) | |||
CAverage | 0.034 ** (0.014) | |||
GAverage | 0.032 ** (0.014) | |||
Panel B: Decomposed estimations | Estimated coefficient | Weight | ||
Earlier treatment vs. Later control | 0.043 | 0.241 | ||
Later treatment vs. Earlier control | −0.015 | 0.073 | ||
Treatment vs. Never treated | 0.064 | 0.686 | ||
Weighted coefficient | 0.053 |
CE | CS | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
UPDZ | −0.092 *** (0.029) | −0.083 *** (0.029) | 0.003 ** (0.001) | 0.003 ** (0.001) |
control variables | no | yes | no | yes |
constant term | yes | yes | yes | yes |
time fixed effect | yes | yes | yes | yes |
city fixed effect | yes | yes | yes | yes |
sample size | 2639 | 2639 | 2639 | 2639 |
R-squared | 0.039 | 0.044 | 0.002 | 0.011 |
LR | ER | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
UPDZ | −0.095 *** (0.037) | −0.093 ** (0.037) | 0.251 *** (0.065) | 0.129 ** (0.065) |
control variables | no | yes | no | yes |
constant term | yes | yes | yes | yes |
time fixed effect | yes | yes | yes | yes |
city fixed effect | yes | yes | yes | yes |
sample size | 2028 | 2018 | 2421 | 2383 |
R-squared | 0.040 | 0.030 | 0.691 | 0.644 |
RM | SO | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
UPDZ | −0.020 *** (0.006) | −0.028 *** (0.006) | 0.018 ** (0.008) | 0.014 *** (0.005) |
control variables | no | yes | yes | yes |
constant term | yes | yes | yes | yes |
time fixed effect | yes | yes | yes | yes |
city fixed effect | yes | yes | yes | yes |
sample size | 2421 | 2383 | 2024 | 2018 |
R-squared | 0.047 | 0.199 | 0.033 | 0.038 |
TI | GTI | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
UPDZ | 0.062 ** (0.030) | 0.105 *** (0.029) | 0.153 *** (0.037) | 0.155 *** (0.037) |
control variables | no | yes | no | yes |
constant term | yes | yes | yes | yes |
time fixed effect | yes | yes | yes | yes |
city fixed effect | yes | yes | yes | yes |
sample size | 2421 | 2383 | 2421 | 2383 |
R-squared | 0.400 | 0.460 | 0.467 | 0.532 |
ULUE | ||
---|---|---|
EDZ | HTDZ | |
(1) | (2) | |
UPDZ | 0.034 ** (0.017) | 0.076 *** (0.015) |
control variables | yes | yes |
constant term | yes | yes |
time fixed effect | yes | yes |
city fixed effect | yes | yes |
sample size | 1651 | 1586 |
R-squared | 0.014 | 0.013 |
ULUE | |||
---|---|---|---|
Eastern | Central | Western | |
(1) | (2) | (3) | |
UPDZ | 0.023 *** (0.007) | 0.087 *** (0.018) | 0.003 (0.030) |
control variables | yes | yes | yes |
constant term | yes | yes | yes |
time fixed effect | yes | yes | yes |
city fixed effect | yes | yes | yes |
sample size | 793 | 1092 | 754 |
R-squared | 0.025 | 0.001 | 0.013 |
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Rao, J.; Zhang, X.; Zhai, D. Does the Upgrading of Development Zones Improve Land Use Efficiency under the Net-Zero Carbon City Goal? Prefectural-Level Evidence from Quasi-Natural Experiments in China. Land 2024, 13, 1245. https://doi.org/10.3390/land13081245
Rao J, Zhang X, Zhai D. Does the Upgrading of Development Zones Improve Land Use Efficiency under the Net-Zero Carbon City Goal? Prefectural-Level Evidence from Quasi-Natural Experiments in China. Land. 2024; 13(8):1245. https://doi.org/10.3390/land13081245
Chicago/Turabian StyleRao, Jinguo, Xiaosong Zhang, and Duanqiang Zhai. 2024. "Does the Upgrading of Development Zones Improve Land Use Efficiency under the Net-Zero Carbon City Goal? Prefectural-Level Evidence from Quasi-Natural Experiments in China" Land 13, no. 8: 1245. https://doi.org/10.3390/land13081245