Does Classification-Based Forest Management Promote Forest Restoration? Evidence from China’s Ecological Welfare Forestland Certification Program
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Methods
3. Results
3.1. Correlation Test
3.2. Benchmark Regression Results
3.3. Heterogeneity Analysis of Different Forest Regions
3.4. Endogeneity and Empirical Robustness Tests
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable Category | Variable Name | Calculation Method | Mean | Std. Dev. |
---|---|---|---|---|
Explained variable | Forest area | The logarithm of forest area | 5.74 | 1.56 |
Core explanatory variable | Proportion of EWF | EWF area/total forest area | 0.27 | 0.26 |
Other control variables | Economic development | The logarithm of GDP per capita | 2.79 | 0.79 |
Population size | The logarithm of population density | 5.30 | 1.31 | |
Forestry support services | The logarithm of the output value of forestry production services, professional technical services, public management, and other services was taken after summing | 4.67 | 2.36 | |
Livelihood | The logarithm of wood yield | 3.76 | 3.65 | |
Demand for wood products | The output of wood-based panels was logarithmic | 3.43 | 2.45 | |
Policy support | The afforestation area of key projects was logarithmic | 5.08 | 17.60 | |
Forest products trade | The logarithm of sawlog and veneer imports was taken after summing | 7.68 | 1.09 |
Variable | SAR | Dynamic SAR | SDM | Dynamic SDM |
---|---|---|---|---|
Proportion of EWF | 0.5811 *** | −0.0268 | 0.2704 * | −0.0299 |
(0.0942) | (0.0818) | (0.1511) | (0.0820) | |
Economic development | 0.0472 | 0.0395 | ||
(0.0403) | (0.0423) | |||
Population size | 0.2144 | 0.1717 | ||
(0.1446) | (0.1602) | |||
Livelihood | −0.0159 ** | −0.0174 ** | ||
(0.0078) | (0.0082) | |||
Demand for wood products | −0.0275 ** | −0.0269 ** | ||
(0.0110) | (0.0110) | |||
Policy support | 0.0752 *** | 0.0738 *** | ||
(0.0226) | (0.0227) | |||
Forestry support services | 0.2915 *** | 0.2810 *** | ||
(0.1001) | (0.1015) | |||
Forest products trade | 0.1381 ** | 0.1378 ** | ||
(0.0672) | (0.0672) | |||
L. Forest area | 0.9049 *** | 0.9068 *** | ||
(0.0550) | (0.0550) | |||
L. W * Forest area | −0.2071 | −0.2144 * | ||
(0.1294) | (0.1295) | |||
rho | 0.5450 *** | 0.2368 ** | 0.4509 *** | 0.2380 ** |
(0.0699) | (0.0983) | (0.0833) | (0.0983) | |
sigma2_e | 0.0419 *** | 0.0177 *** | 0.0417 *** | 0.0176 *** |
(0.0044) | (0.0017) | (0.0043) | (0.0017) | |
Regional fixed effects | control | control | control | control |
Time fixed effects | control | control | control | control |
BIC | −32.81088 | −158.2225 | −34.34823 | −153.3117 |
Variable | State Forest Province | Southern Collective Forest Province | ||
---|---|---|---|---|
SAR | Dynamic SAR | SAR | Dynamic SAR | |
Proportion of EWF | 0.4604 *** | −0.0436 | 0.4596 *** | −0.2577 * |
(0.1285) | (0.1104) | (0.1078) | (0.1362) | |
Economic development | 0.0048 | 0.4734 *** | ||
(0.0620) | (0.1217) | |||
Population size | 0.9333 ** | 0.5297 *** | ||
(0.3814) | (0.1640) | |||
Livelihood | 0.3490* | 0.0397 | ||
(0.1783) | (0.1269) | |||
Demand for wood products | −0.1083 *** | −0.0298 *** | ||
(0.0377) | (0.0071) | |||
Policy support | −0.0090 | −0.0360 ** | ||
(0.0232) | (0.0169) | |||
Forestry support services | 0.2273 *** | 0.1302 *** | ||
(0.0594) | (0.0232) | |||
Forest products trade | 0.1513 | 0.1242 | ||
(0.1285) | (0.0757) | |||
L. Forest area | 0.7268 *** | 1.0938 *** | ||
(0.1017) | (0.0663) | |||
L. W. * Forest area | −0.6651 *** | 2.3189 *** | ||
(0.2308) | (0.1982) | |||
rho | 0.4575 *** | −0.0147 | 0.6931 *** | 0.3576 ** |
(0.1164) | (0.1542) | (0.0781) | (0.1433) | |
sigma2_e | 0.0423 *** | 0.0140 *** | 0.0084 *** | 0.0115 *** |
(0.0078) | (0.0023) | (0.0015) | (0.0013) | |
Regional fixed effects | control | control | control | control |
Time fixed effects | control | control | control | control |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Proportion of EWF | −0.0370 | −0.0160 | 0.1166 | 0.1125 |
(0.0373) | (0.0761) | (0.0861) | (0.0816) | |
L. Forest area | 0.4568 *** | 1.2465 *** | ||
(0.0823) | (0.0568) | |||
L. W. * Forest area | 7.1177 *** | |||
(0.6573) | ||||
L. Forest accumulation | 0.5176 *** | 0.6965 *** | ||
(0.0509) | (0.2178) | |||
L. W. * Forest accumulation | 0.4435 *** | |||
(0.1020) | ||||
rho | −0.5280 | 0.3295 *** | ||
(0.4295) | (0.0906) | |||
sigma2_e | 0.0140 *** | 0.0260 *** | ||
(0.0013) | (0.0024) | |||
AR (1) | −2.0489 ** | −2.0330 ** | ||
AR (2) | 0.2441 | 0.5992 | ||
Sargan | 12.9575 | 8.9253 | ||
Control variables | control | control | control | control |
R-squared | - | 0.4784 | 0.8439 | - |
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Xu, C.; Lin, F.; Zhu, C.; Li, C.; Cheng, B. Does Classification-Based Forest Management Promote Forest Restoration? Evidence from China’s Ecological Welfare Forestland Certification Program. Forests 2022, 13, 573. https://doi.org/10.3390/f13040573
Xu C, Lin F, Zhu C, Li C, Cheng B. Does Classification-Based Forest Management Promote Forest Restoration? Evidence from China’s Ecological Welfare Forestland Certification Program. Forests. 2022; 13(4):573. https://doi.org/10.3390/f13040573
Chicago/Turabian StyleXu, Chang, Fanli Lin, Chenghao Zhu, Chaozhu Li, and Baodong Cheng. 2022. "Does Classification-Based Forest Management Promote Forest Restoration? Evidence from China’s Ecological Welfare Forestland Certification Program" Forests 13, no. 4: 573. https://doi.org/10.3390/f13040573
APA StyleXu, C., Lin, F., Zhu, C., Li, C., & Cheng, B. (2022). Does Classification-Based Forest Management Promote Forest Restoration? Evidence from China’s Ecological Welfare Forestland Certification Program. Forests, 13(4), 573. https://doi.org/10.3390/f13040573