New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency
Abstract
:1. Introduction
2. The Background of CFRR
2.1. The “Three Fixed” Reform Stage from 1978 to 1992
2.2. The Pilot Stage of Forest Right Reform from 1993 to 2003
2.3. A New Round of CFRR in 2003
3. Theoretical Analysis
3.1. Theoretical Analysis of the Promotion Effect of the New Round of CFRR on Farmers’ Forest Land Transfer Behavior
3.2. Analysis on the Maximization of Profit at Household Level after the Occurrence of Farmers’ Forestland Transfer Behavior
3.3. Estimation of Production Efficiency Based on Rural Household Level
4. Data Sources and Empirical Models
4.1. Data Sources
4.2. An Empirical Test of the Promotion Effect of the New Round of CFRR on Forestland Transfer Behavior
Panel Logit Model
4.3. Empirical Model Selection of the Influence of Forestland Transfer on Rural Household Production Efficiency
- (1)
- Agricultural labor input of rural households: the sum of labor days invested by rural households in forestry and planting industry (days).
- (2)
- Agricultural capital investment of rural households: the sum of funds invested by rural households in forestry and planting industry (yuan), including the purchase of chemical fertilizers, pesticides, seeds, and other inputs.
- (3)
- Agricultural land input of rural household: the sum of forestland and agricultural land managed by households but not the forestland and agricultural land owned by farmers.
- (4)
- Non-agricultural labor input of rural households: the number of working days that rural households put into non-agricultural employment (days).
4.3.1. DID Model
4.3.2. Quantile Model Regression
Quantile Model
5. Result and Discussion
5.1. Panel Logit Model
5.2. DID Regression and Quantile Regression
5.2.1. DID Regression and Quantile Regression for Technical Efficiency
5.2.2. DID Regression and Quantile Regression for Scale Efficiency
5.2.3. DID Regression and Quantile Regression for Comprehensive Efficiency
6. Conclusions and Policy Recommendations
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable | Explain | Mean | Standard Error | Expected Direction |
---|---|---|---|---|
Dependent variable | ||||
transferif | Yes = 1, No = 1 | 0.07 | 0.25 | |
CFRR | ||||
R | The score of factor analysis is calculated according to the index of the new round of CFRR | 5.9 × 10−9 | 0.91 | + |
Characteristics of household head | ||||
age | The age of household head (year); | 49.68 | 10.69 | +/− |
cadre | Yes = 1, No = 0 | 0.25 | 0.43 | +/− |
education | The number of years of formal education received by the head of household (years) | 7.07 | 2.55 | +/− |
laberif | Whether the head of household is a household labor force; Yes = 1, No = 0 | 0.94 | 0.23 | +/− |
Characteristics of household | ||||
distance | Distance from sample farmers’ families to their county towns (miles) | 33.66 | 32.09 | +/− |
offfarmlabor | Days of non-agricultural working/total working days of the family | 0.32 | 0.36 | - |
farmlabor | Days of family engaged in planting/total working days of family | 0.19 | 0.24 | +/− |
offfarmincome | Non-agricultural employment income/total household income | 0.57 | 0.33 | +/− |
farmincome | Planting income/total household income | 0.43 | 0.33 | +/− |
Characteristics of land | ||||
farmland | Total area of household contracted agricultural land (mu = 1/15 hectare) | 5.01 | 4.58 | +/− |
forestland | Total area of household contracted forest land (mu) | 58.36 | 98.48 | +/− |
forestfragment | Household contracted forest land area/number of forest land plots | 14.85 | 22.79 | - |
roadif | Whether there is a road leading to the contracted forest land; Yes = 1, No = 0 | 0.58 | 0.49 | - |
Title 1 | Variables | Explain |
---|---|---|
the New Round of CFRR | R1 | Does the forestland have a forest warrant after the new round of CFRR? 1 = Yes, 0 = No |
R2 | Whether it is easy to obtain a forest right harvesting certificate permit from the local forestry department after the new round of CFRR? 1 = easy, 0 = not easy | |
R3 | Average number of years of the implementation of supporting measures such as tax and fee waivers and subsidies (years) |
Common Factor | Characteristic Root | Variance Contribution Rate | Cumulative Variance Contribution Rate |
---|---|---|---|
F1 | 1.6212 | 0.5404 | 0.5404 |
F2 | 0.7705 | 0.2568 | 0.7973 |
Variable | Explain | Mean | Standard Error | Expected Direction |
---|---|---|---|---|
Dependent variable | ||||
Comprehensive technical efficiency (CRSTE) | Technical efficiency of farmers under the assumption of constant return to scale | 0.13 | 0.18 | |
Pure technical efficiency (VRSTE) | Technical efficiency of farmers under the assumption of variable return of scale | 0.26 | 0.24 | |
Scale efficiency (SE) | Farmers’ scale efficiency under the assumption of constant scale reward | 0.42 | 0.28 | |
Forestland transfer | ||||
P | 2007–2011 = 1, 2003 = 0 | 0.50 | 0.50 | + |
rentin | Yes = 1, No = 0 | 0.10 | 0.30 | + |
rentout | Yes = 1, No = 0 | 0.05 | 0.21 | + |
Characteristics of household head | ||||
Age | The age of household head (year) | 49.68 | 10.69 | +/− |
Cadre | Yes = 1, No = 0 | 0.25 | 0.43 | +/− |
Education | The number of years of formal education received by the head of household (years) | 7.07 | 2.55 | + |
Access to capital market | ||||
offfarmincome | Non-agricultural employment income/total household income | 0.57 | 0.30 | + |
forestmortage | Yes = 1, No = 0 | 0.00 | 0.05 | + |
The degree of fragmentation of forestland | ||||
forestfragment | Household contracted forest land area/number of forest land plots | 14.85 | 22.79 | - |
Variables | Panel Logit Regression |
---|---|
R | 0.323 ***1 |
(0.106) | |
age | −0.030 |
(0.020) | |
cadre | 0.617 |
(0.427) | |
education | 0.168 ** |
(0.083) | |
laborif | 1.438 |
(1.354) | |
distance | 0.006 |
(0.006) | |
offfarmlabor | −0.301 |
(0.386) | |
farmlabor | 0.006 |
(0.623) | |
offfarmincome | 1025 |
(912.9) | |
farmincome | 1025 |
(913.0) | |
farmland | 0.019 |
(0.026) | |
forestland | 0.003 * |
(0.002) | |
forestfragment | −0.012 * |
(0.008) | |
roadif | −0.689 * |
(0.389) | |
Constant | −1033 |
(912.8) | |
Observation | 4116 |
Variable | DID Regression | Quantile Regression | ||||
---|---|---|---|---|---|---|
θ = 10 | θ = 25 | θ = 50 | θ = 75 | θ = 90 | ||
P | 0.0664 ***1 | 0.0470 *** | 0.0599 *** | 0.0806 *** | 0.1020 *** | 0.0507 |
(0.0123) 2 | (0.0057) | (0.0082) | (0.0115) | (0.0209) | (0.0494) | |
rentin | −0.0066 | −0.0214 * | −0.0343 * | −0.0791 *** | −0.0468 | 0.1380 |
(0.0380) | (0.0124) | (0.0176) | (0.0250) | (0.0457) | (0.1080) | |
rentout | 0.1000 * | 0.0153 | 0.0145 | 0.0414 | 0.2180 *** | 0.4230 *** |
(0.0554) | (0.0170) | (0.0240) | (0.0342) | (0.0625) | (0.1470) | |
rentin∗P | 0.0057 | 0.0320 * | 0.0190 | 0.0503 | 0.0335 | −0.0489 |
(0.0474) | (0.0171) | (0.0241) | (0.0344) | (0.0627) | (0.1480) | |
rentout∗P | −0.0439 | 0.0162 | 0.0261 | −0.0161 | −0.1750 ** | −0.1920 |
(0.0687) | (0.0236) | (0.0334) | (0.0476) | (0.0869) | (0.2050) | |
age | −0.0012 * | 0.0002 | 0.0002 | −0.0006 | −0.0014 | −0.0024 |
(0.0006) | (0.0003) | (0.0004) | (0.0005) | (0.0010) | (0.0023) | |
cadre | −0.0281 ** | −0.0059 | −0.0055 | −0.0187 | −0.0269 | −0.0690 |
(0.0134) | (0.0062) | (0.0087) | (0.0124) | (0.0227) | (0.0535) | |
education | −0.0004 | −0.0001 | −0.0001 | 0.0008 | −0.0017 | 0.0036 |
(0.0019) | (0.0010) | (0.0014) | (0.0019) | (0.0035) | (0.0083) | |
offfarmincome | 0.0371 | 0.0514 *** | 0.0762 *** | 0.0812 *** | 0.0952 *** | −0.0443 |
(0.0248) | (0.0086) | (0.0122) | (0.0174) | (0.0317) | (0.0747) | |
forestmortage | 0.4260 * | 0.1980 *** | 0.1680 * | 0.1180 | 0.7830 *** | 0.4540 |
(0.2570) | (0.0653) | (0.0924) | (0.1320) | (0.2400) | (0.5670) | |
forestfragment | −0.0016 *** | −0.0007 *** | −0.0012 *** | −0.0015 *** | −0.0015 *** | −0.0022 * |
(0.0003) | (0.0001) | (0.0002) | (0.0003) | (0.0005) | (0.0011) | |
Constant | 0.2780 *** | 0.0171 | 0.0476 ** | 0.1540 *** | 0.3070 *** | 0.6360 *** |
(0.0408) | (0.0167) | (0.0236) | (0.0336) | (0.0613) | (0.1450) | |
Observation | 1309 | 1309 | 1309 | 1309 | 1309 | 1309 |
R-squared | 0.060 |
Variable | DID Regression | Quantile Regression | ||||
---|---|---|---|---|---|---|
θ = 10 | θ = 25 | θ = 50 | θ = 75 | θ = 90 | ||
P | 0.0843 ***1 | 0.2010 *** | 0.2540 *** | 0.1500 *** | −0.0802 ** | −0.2380 *** |
(0.0166) 2 | (0.0075) | (0.0171) | (0.0214) | (0.0376) | (0.0292) | |
rentin | −0.0393 | 0.0045 | 0.0580 | 0.0130 | −0.2190 *** | −0.0820 |
(0.0389) | (0.0165) | (0.0374) | (0.0467) | (0.0822) | (0.0638) | |
rentout | −0.1750 *** | −0.0046 | −0.0627 | −0.2360 *** | −0.3610 *** | −0.1330 |
(0.0600) | (0.0225) | (0.0511) | (0.0637) | (0.1120) | (0.0872) | |
rentin∗P | 0.1500 *** | −0.0649 *** | 0.0072 | 0.1340 ** | 0.4640 *** | 0.2340 *** |
(0.0510) | (0.0226) | (0.0514) | (0.0640) | (0.1130) | (0.0875) | |
rentout∗P | 0.0887 | −0.0370 | −0.0379 | 0.1940** | 0.3020* | 0.0152 |
(0.0665) | (0.0313) | (0.0711) | (0.0887) | (0.1560) | (0.1210) | |
age | −0.0024 *** | −0.0004 | −0.0018 ** | −0.0030 *** | −0.0020 | 0.0000 |
(0.0007) | (0.0004) | (0.0008) | (0.0010) | (0.0017) | (0.0013) | |
cadre | −0.0728 *** | −0.0088 | −0.0585 *** | −0.0802 *** | −0.0542 | −0.0680 ** |
(0.0178) | (0.0082) | (0.0186) | (0.0231) | (0.0407) | (0.0316) | |
education | −0.0001 | −0.0002 | 0.0001 | −0.0026 | 0.0054 | 0.0137 *** |
(0.0027) | (0.0013) | (0.0029) | (0.0036) | (0.0063) | (0.0049) | |
offfarmincome | 0.0470 * | 0.0118 | 0.0183 | 0.0423 | 0.0543 | 0.0368 |
(0.0270) | (0.0114) | (0.0259) | (0.0323) | (0.0570) | (0.0442) | |
forestmortage | −0.2100 *** | 0.0092 | 0.0012 | −0.0361 | −0.3700 | −0.6700 ** |
(0.0721) | (0.0865) | (0.1970) | (0.2450) | (0.4320) | (0.3350) | |
forestfragment | −0.0009 * | −0.0004 ** | −0.0010 ** | −0.0017 *** | 0.00045 | 0.0019 *** |
(0.0005) | (0.0002) | (0.0004) | (0.0005) | (0.0009) | (0.0007) | |
Constant | 0.4840 *** | 0.0275 | 0.1600 *** | 0.4640 *** | 0.6720 *** | 0.7940 *** |
(0.0484) | (0.0221) | (0.0502) | (0.0626) | (0.1100) | (0.0856) | |
Observation | 1309 | 1309 | 1309 | 1309 | 1309 | 1309 |
R-squared | 0.069 |
Variable | DID Regression | Quantile Regression | ||||
---|---|---|---|---|---|---|
θ = 10 | θ = 25 | θ = 50 | θ = 75 | θ = 90 | ||
P | 0.0792 ***1 | 0.0382 *** | 0.0609 *** | 0.0756 *** | 0.0881 *** | 0.1410 *** |
(0.0083) 2 | (0.0023) | (0.0028) | (0.0071) | (0.0125) | (0.0292) | |
rentin | −0.0264 | 0.0014 | −0.0010 | −0.0191 | −0.0543 ** | −0.0687 |
(0.0202) | (0.0051) | (0.00619) | (0.0154) | (0.0273) | (0.0638) | |
rentout | −0.0347 | −0.0012 | −0.0056 | −0.0258 | −0.0412 | −0.0695 |
(0.0212) | (0.0069) | (0.0085) | (0.0211) | (0.0373) | (0.0872) | |
rentin∗P | 0.0664 ** | 0.0092 | 0.0123 | 0.0348 | 0.0965 ** | 0.1640 * |
(0.0304) | (0.0069) | (0.0085) | (0.0212) | (0.0374) | (0.0875) | |
rentout∗P | 0.0591 | 0.0114 | 0.0149 | 0.0380 | 0.0654 | 0.1020 |
(0.0366) | (0.0096) | (0.0118) | (0.0294) | (0.0519) | (0.1210) | |
age | −0.0016 *** | −0.0001 | −0.0004 *** | −0.0009 *** | −0.0020 *** | −0.0050 *** |
(0.0004) | (0.0001) | (0.0001) | (0.0003) | (0.0006) | (0.0013) | |
cadre | −0.0233 *** | −0.0031 | −0.0063 ** | −0.0145 * | −0.0291 ** | −0.0483 |
(0.0089) | (0.0025) | (0.0031) | (0.0077) | (0.0135) | (0.0316) | |
education | −0.0006 | −0.0001 | −0.0001 | −0.0006 | −0.0024 | −0.0051 |
(0.0014) | (0.0004) | (0.0005) | (0.0012) | (0.0021) | (0.0050) | |
offfarmincome | 0.0309 * | 0.0033 | 0.0075 * | 0.0308 *** | 0.0742 *** | 0.0611 |
(0.0159) | (0.0035) | (0.0043) | (0.0107) | (0.0189) | (0.0442) | |
forestmortage | 0.0650 | 0.0091 | 0.0058 | −0.0180 | 0.1820 | 0.0857 |
(0.0822) | (0.0265) | (0.0325) | (0.0811) | (0.1430) | (0.3350) | |
forestfragment | −0.0009 *** | −0.0003 *** | −0.0003 *** | −0.0006 *** | −0.0007 ** | −0.0009 |
(0.0002) | (0.0001) | (0.0001) | (0.0002) | (0.0003) | (0.0007) | |
Constant | 0.1620 *** | 0.0096 | 0.0249 *** | 0.0753 *** | 0.1950 *** | 0.4620 *** |
(0.0246) | (0.0068) | (0.0083) | (0.0207) | (0.0366) | (0.0856) | |
Observation | 1309 | 1309 | 1309 | 1309 | 1309 | 1309 |
R-squared | 0.113 |
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Yu, J.; Wei, Y.; Fang, W.; Liu, Z.; Zhang, Y.; Lan, J. New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency. Land 2021, 10, 988. https://doi.org/10.3390/land10090988
Yu J, Wei Y, Fang W, Liu Z, Zhang Y, Lan J. New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency. Land. 2021; 10(9):988. https://doi.org/10.3390/land10090988
Chicago/Turabian StyleYu, Jinna, Yiming Wei, Wei Fang, Zhen Liu, Yujie Zhang, and Jing Lan. 2021. "New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency" Land 10, no. 9: 988. https://doi.org/10.3390/land10090988
APA StyleYu, J., Wei, Y., Fang, W., Liu, Z., Zhang, Y., & Lan, J. (2021). New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency. Land, 10(9), 988. https://doi.org/10.3390/land10090988