The Impact of Forestry Technological Innovation on the Welfare of Farm Households Managing Jujube Forests (Ziziphus jujuba Mill.) in the Lüliang Mountains of the Yellow River’s Middle Reaches
Abstract
:1. Introduction
2. Theoretical Analysis and Research Hypotheses
2.1. The Welfare Effects of the JFHGOP on Farm Households
2.2. The Pathways of the Welfare Effects of the JFHGOP on Farm Households
3. Materials and Methods
3.1. Data Sources
3.2. Key Variables and Their Measurement
3.2.1. Key Independent Variable
3.2.2. Dependent Variables
3.2.3. Moderating Variables
3.2.4. Matching Variables
3.3. Estimation Methods
3.3.1. Propensity Score Matching (PSM)
3.3.2. Ordinary Least Squares (OLS)
4. Results
4.1. Baseline Regression Results and Analysis
4.1.1. PSM Results
4.1.2. Common Support Domains and Equilibrium Test
4.1.3. Least Squares Regression Estimation Results
4.1.4. Robustness Tests
- (1)
- Panel Tobit Model
- (2)
- Multiple Ordered Logistic Regression Models
4.2. Heterogeneity Analysis
4.2.1. Heterogeneity Analysis of Economic Benefits
4.2.2. Heterogeneity Analysis of Ecological and Social Benefits
4.3. Analysis of the Pathway
5. Discussion
6. Conclusions
- (1)
- The Jujube Forest High Grafting and Optimization Program significantly impacts households’ overall welfare, including economic, ecological, and social benefits. These conclusions hold firm even after passing robustness tests.
- (2)
- Heterogeneity analysis reveals that households’ resource endowments are critical for improving welfare. Factors such as education level, labor force size, jujube forest plot size, and annual household income each play a significant role.
- (3)
- Path analysis shows that the program influences farm household welfare through government subsidies and cooperative support.
- (1)
- To achieve a balance between economic development and ecological protection in the middle reaches of the Yellow River, it is essential to advance forestry technological innovation and consolidate jujube forest areas.
- (2)
- Smaller farm households remain the backbone of jujube industry production and management. Therefore, governments should offer additional support through policies, funding, and technology.
- (3)
- Attention should also be given to labor force aging and migration in impoverished and remote mountainous areas. Providing forestry production and labor replacement services can support sustainable development in mountainous forestry and improve farm household welfare.
- (4)
- Emphasizing and optimizing subsidy mechanisms in remote mountainous areas is crucial. Additionally, industry assistance policies should be further implemented to supplement production factors. This will help fully leverage policy subsidies in supporting the production and management of smaller farm households.
- (5)
- Finally, further support cooperative organizations and other new business entities, cultivate leading enterprises, and promote collaboration among the government, these new entities, and farm households. This will advance green development in mountainous forestry and enhance farm household welfare.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Sample Town | Sample Village | Number of Farm Households | Percentage of Households (%) | Total (%) | ||
---|---|---|---|---|---|---|
Participating Household | Non-Participating Household | Participating Household | Non-Participating Household | |||
Shibaitou Township | Baizhai Village | 13 | 0 | 8.28 | 0 | 4.30 |
Gaojiaju Village | 26 | 8 | 16.56 | 5.52 | 11.26 | |
Linjiaping Town | Xuejiagetai Village | 30 | 20 | 19.11 | 13.79 | 16.56 |
Haojiata Village | 0 | 21 | 0 | 14.48 | 6.95 | |
Sanjiao Town | Luojiashan Village | 0 | 35 | 0 | 24.14 | 11.59 |
Qikou Town | Zhaizeping Village | 40 | 35 | 25.48 | 24.14 | 24.83 |
Xiwancun Village | 8 | 21 | 5.10 | 14.48 | 9.60 | |
Qikou Town | Houtai Town Village | 40 | 5 | 25.48 | 3.45 | 14.90 |
Total | 157 | 145 | 100 | 100 | 100 |
Variable | Variable Definition and Unit | 2017 | 2021 | 2017 | ||
---|---|---|---|---|---|---|
Control Group (n = 145) | Treatment Group (n = 157) | Control Group (n = 145) | Treatment Group (n = 157) | Mean Difference (t-test) | ||
Involvement in programs | 0 = not involved 1 = Participation | 0 | 1 | 0 | 1 | |
Jujube forest operation income | CNY | 355.262 | 698.072 | 12.721 | 110.214 | −342.810 ** |
Jujube forest understory operation income | CNY | 178.386 | 327.809 | 122.616 | 1471.700 | −149.423 |
Other agricultural and forestry operation income | CNY | 1036.245 | 3786.892 | 904.728 | 3796.473 | −2750.647 ** |
Jujube forest land transfer income | CNY | 0 | 0 | 106.577 | 886.669 | |
Jujube employment income | CNY | 0 | 0 | 175.747 | 119.179 | |
Biodiversity | 1 = significant decrease 2 = minor decrease. 3 = no change 4 = minor increase 5 = significant increase | 3.469 | 3.522 | |||
Land resource conservation | Same as above | 3.221 | 3.350 | |||
Forest landscape | Same as above | 3.221 | 3.350 | |||
Employment opportunities | Same as above | 3.186 | 3.312 | |||
Life satisfaction | Same as above | 3.834 | 3.911 | |||
Gender | 0 = Female, 1 = Male | 0.497 | 0.656 | 0.497 | 0.656 | −0.159 ** |
Age | year | 60.138 | 58.076 | 64.138 | 62.076 | 2.061 * |
Education level | 0 = Illiterate 1 = Primary school 2 = Junior high school 3 = High school 4 = Associate degree and above | 1.297 | 1.522 | 1.297 | 1.522 | −0.226** |
Leader | 0 = No, 1 = Yes | 0.021 | 0.057 | 0.021 | 0.057 | −0.037 |
Internet | 0 = No, 1 = Yes | 0.552 | 0.701 | 0.552 | 0.701 | −0.149 *** |
Household size | Individuals | 1.993 | 2.236 | 1.993 | 2.236 | −0.243 * |
Labor force size | Count | 0.921 | 1.232 | 0.917 | 1.242 | −0.312 *** |
Migrant labor force size | Count | 0.434 | 0.478 | 0.490 | 0.465 | −0.043 |
Arable land area | Hectares | 0.490 | 0.576 | 0.490 | 0.577 | −1.342 |
Rural land contract management certificate | 0 = no, 1 = yes | 0.910 | 0.975 | 0.910 | 0.975 | −0.064 ** |
Jujube technical training | 0 = no, 1 = yes | 0.151 | 0.318 | 0.151 | 0.318 | −0.167 *** |
Government subsidy | Yuan | 0 | 0 | 20.514 | 35.377 |
Variable Name | Estimated Coefficient | Standard Error | Z-Value |
---|---|---|---|
Gender | 0.567 | 0.184 | 3.08 *** |
Age | 0.249 | 0.576 | 0.43 |
Education | 0.226 | 0.113 | 2.00 ** |
Leader | 0.113 | 0.526 | 0.21 |
Internet | 0.430 | 0.194 | 2.21 ** |
Household size | −0.144 | 0.254 | −0.57 |
Labor force size | 0.755 | 0.238 | 3.18 *** |
Migrant labor force size | 0.088 | 0.503 | 0.17 |
Arable land area | −0.594 | 0.503 | −0.17 |
Rural land contract management right certificate | 1.011 | 0.4342 | 2.34 ** |
Jujube technical training | 1.233 | 0.262 | 4.70 *** |
Jujube forests operating subsidy | 0.170 | 0.062 | 2.76 *** |
constant term | −2.959 | 2.411 | −1.23 |
LR ch2(12) | 88.69 *** | ||
Pseudo R2 | 0.107 | ||
Sample size | 604 |
Variable Name | Matching Method | Treatment Group Mean | Control Group Mean | ATT | t-Value |
---|---|---|---|---|---|
Jujube forest operations income | K-nearest neighbor matching | 2.263 | 0.978 | 1.285 | 4.61 *** |
Caliper matching | 2.263 | 1.155 | 1.108 | 4.03 *** | |
1-to-4 match in Calipers | 2.263 | 1.089 | 1.174 | 4.13 *** | |
Nuclear matching | 2.263 | 1.118 | 1.145 | 4.30 *** | |
Local linear Regression Matching | 2.263 | 1.117 | 1.146 | 3.39 *** | |
Average value | 2.263 | 1.091 | 1.172 | ||
Jujube forest understory operations income | K-nearest neighbor matching | 1.342 | 0.579 | 0.764 | 3.31 *** |
Caliper matching | 1.342 | 0.564 | 0.778 | 3.45 *** | |
1-to-4 match in Calipers | 1.342 | 0.579 | 0.764 | 3.25 *** | |
Nuclear matching | 1.342 | 0.605 | 0.737 | 3.37 *** | |
Local linear Regression Matching | 1.342 | 0.617 | 0.725 | 2.68 *** | |
Average value | 1.342 | 0.589 | 0.754 | ||
Other agricultural and forestry operations Income | K-nearest neighbor matching | 4.090 | 3.016 | 1.074 | 2.85 *** |
Caliper matching | 4.090 | 2.843 | 1.247 | 3.41 *** | |
1-to-4 match in Calipers | 4.090 | 2.892 | 1.197 | 3.11 *** | |
Nuclear matching | 4.090 | 2.879 | 1.211 | 3.43 *** | |
Local linear Regression Matching | 4.090 | 2.828 | 1.261 | 2.72 *** | |
Average value | 4.090 | 2.892 | 1.198 | ||
Jujube forests land transfer income | K-nearest neighbor matching | 2.102 | 0.415 | 1.687 | 8.500 *** |
Caliper matching | 2.102 | 0.277 | 1.825 | 9.37 *** | |
1-to-4 match in Calipers | 2.102 | 0.317 | 1.785 | 8.88 *** | |
Nuclear matching | 2.102 | 0.322 | 1.780 | 9.30 *** | |
Local linear Regression Matching | 2.102 | 0.326 | 1.775 | 7.19 *** | |
Average value | 2.102 | 0.331 | 1.770 | ||
Jujube employment income | K-nearest neighbor matching | 0.260 | 0.532 | −0.272 | −1.76 * |
Caliper matching | 0.260 | 0.504 | −0.244 | −1.67 * | |
1-to-4 match in Calipers | 0.260 | 0.504 | −0.244 | −1.67 * | |
Nuclear matching | 0.260 | 0.501 | −0.240 | −1.70 * | |
Local linear Regression Matching | 0.260 | 0.492 | −0.231 | −1.03 | |
Average value | 0.260 | 0.507 | −0.246 |
Matching Method | Pseudo R2 | LR Statistic | p-Value | Mean Bias | Med Bias |
---|---|---|---|---|---|
Prematch | 0.108 | 90.30 | 0.000 | 25.6 | 27.0 |
K-nearest neighbor Matching | 0.010 | 8.28 | 0.763 | 6.3 | 6.2 |
Caliper matching | 0.010 | 8.19 | 0.770 | 6.2 | 6.5 |
1-to-4 match in calipers | 0.011 | 9.47 | 0.663 | 7.3 | 7.6 |
Nuclear matching | 0.008 | 7.22 | 0.843 | 5.7 | 6.7 |
Local linear regression Matching | 0.018 | 15.86 | 0.198 | 9.5 | 9.8 |
Variable Name | Ecological Benefit | Social Benefit | |||
---|---|---|---|---|---|
Biodiversity | Land Resource Conservation | Forest Landscape | Employment Opportunities | Life Satisfaction | |
Involvement in programs | 0.131 (0.125) | 0.243 * (0.127) | 0.289 *** (0.103) | 0.288 ** (0.129) | 0.300 ** (0.116) |
Control variable | Yes | Yes | Yes | Yes | Yes |
Regional variables | Yes | Yes | Yes | Yes | Yes |
Observed value | 302 | 302 | 302 | 302 | 302 |
Constant term | 3.912 *** | 0.291 *** | 4.571 *** | 4.525 *** | 1.498 |
Adjusted R2 | 0.081 | 0.170 | 0.111 | 0.096 | 0.114 |
Variables | Jujube Forests and Operations Income (1) | Jujube Forests Understory Operations Income (2) | Other Agriculture and Forestry Income (3) | Jujube Forests Land Transfer Income (4) | Jujube Employment Income (5) |
---|---|---|---|---|---|
Involvement in programs | 3.357 *** (0.853) | 6.055 *** (1.886) | 2.051 ** (0.889) | 8.647 *** (0.676) | −5.309 ** (2.412) |
Control variables | Yes | Yes | Yes | Yes | Yes |
Time variables | Yes | Yes | Yes | Yes | Yes |
Observed value | 604 | 604 | 604 | 604 | 604 |
Wald chi2 | 149.88 | 35.27 | 36.19 | ||
Pseudo-R2 | 0.335 | 0.260 |
Variables | Ecological Benefits | Social Benefits | |||
---|---|---|---|---|---|
Biodiversity | Land Resource Conservation | Forest Landscape | Employment Opportunities | Life Satisfaction | |
Involvement in programs | 0321 (0.326) | 0.553 * (0.288) | 0.810 *** (0.308) | 0.764 *** (0.309) | 0.770 ** (0.304) |
Control variable | Yes | Yes | Yes | Yes | Yes |
Regional variables | Yes | Yes | Yes | Yes | Yes |
Observed value | 302 | 302 | 302 | 302 | 302 |
Pseudo R2 | 0.025 | 0.066 | 0.058 | 0.052 | 0.054 |
Grouping Variable | Jujube Forest Operations Income | Jujube Forest Understory Operations Income | Other Agriculture and Forestry Income | Jujube Forest Land Transfer Income | Jujube Employment Incomes | |
---|---|---|---|---|---|---|
ATT | ATT | ATT | ATT | ATT | ||
Education level | Above mean | 0.864 ** (2.31) | 0.862 ** (2.18) | 1.156 ** (2.19) | 1.931 *** (6.55) | −0.162 (−1.12) |
Below mean | 1.072 *** (2.71) | 0.639 ** (2.03) | 1.369 *** (2.77) | 1.758 *** (6.48) | −0.283 (−1.27) | |
Labor force size | Above mean | 1.587 *** (2.62) | 0.870 (1.30) | 2.410 *** (2.99) | 1.591 *** (3.75) | |
Below mean | 1.085 *** (3.45) | 0.724 *** (3.27) | 0.548 (1.34) | 1.730 *** (7.66) | −0.299 * (−1.65) | |
Average size of jujube forest plots | Above mean | 0.751 (1.25) | 1.105 * (1.86) | 1.393 *** (3.82) | −0.676 (−1.62) | |
Below mean | 1.223 *** (4.06) | 0.649 *** (2.98) | 1.939 *** (7.70) | −0.090 (−0.64) | ||
Annual household income | Above mean | 1.619 *** (3.93) | 1.135 *** (2.70) | 1.284 ** (2.01) | 1.969 *** (6.74) | −1.160 (−0.67) |
Below mean | 0.730 * (1.88) | 0.524 ** (2.07) | 0.306 (0.65) | 1.519 *** (5.75) | −0.181 (−0.86) |
Grouping Variable | Land Resource Conservation | Forest Landscape | Employment Opportunities | Life Satisfaction | |
---|---|---|---|---|---|
Education level | Above mean | 0.034 (0.219) | 0.314 ** (0.151) | 0.468 ** (0.220) | 0.208 (0.183) |
Below mean | 0.339 ** (0.147) | 0.313 ** (0.141) | 0.188 (0.166) | 0.393 ** (0.162) | |
Labor force size | Above mean | 0.548 * (0.312) | 0.318 (0.229) | 0.677 ** (0.290) | 0.468 ** (0.194) |
Below mean | 0.223 (0.139) | 0.273 ** (0.122) | 0.178 (0.153) | 0.203 (0.146) | |
Average size of jujube forest plots | Above mean | 0.062 (0.256) | 0.081 (0.204) | −0.254 (0.223) | 0.272 (0.244) |
Below mean | 0.345 ** (0.157) | 0.362 *** (0.121) | 0.462 *** (0.160) | 0.331 ** (0.144) | |
Annual household income | Above median | 0.325 * (0.197) | 0.307 * (0.166) | 0.490 ** (0.204) | 0.530 *** (0.170) |
Below median | 0.117 (0.162) | 0.287 ** (0.131) | −0.010 (0.167) | 0.066 (0.157) |
Variable Name | Jujube Forest Operations Income | Jujube Forests Understory Operation Income | Other Agriculture and Forestry Income | Jujube Forest Land Transfer Income | Jujube Employment Incomes | Land Resource Conservation | Forest Landscape | Employment Opportunities | Life Satisfaction |
---|---|---|---|---|---|---|---|---|---|
Program | −0.04 (−0.10) | 0.26 (0.28) | 2.06 *** (0.58) | 5.52 *** (0.23) | −2.80 × 10−14 (3.98 × 10−9) | 0.38 ** (0.15) | 0.26 *** (0.09) | 0.19 (0.15) | 0.29 ** (0.13) |
Program × subsidies | 0.53 *** (0.10) | 0.56 *** (0.12) | 0.36 ** (0.17) | −1.01 *** (0.06) | 0.06 *** (0.02) | 0.32 *** (0.04) | 0.14 *** (0.02) | −0.01 (0.04) | 0.27 *** (0.34) |
Subsidies | −0.47 (0.11) | −0.51 *** (0.16) | −0.51 *** (0.19) | 0.61 *** (0.11) | 0.03 *** (0.10) | −0.34 *** (−0.04) | −0.20 *** (0.01) | 0.06 * (0.04) | −0.33 *** (0.04) |
Control variable | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Regional variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Observed value | 302 | 302 | 302 | 302 | 302 | 302 | 302 | 302 | 302 |
R2 | 0.24 | 0.15 | 0.05 | 0.72 | 0.27 | 0.09 | 0.09 | 0.05 | 0.07 |
Variable Name | Jujube Forest Operations Income | Jujube Forests Understory Operation Income | Other Agriculture and Forestry Income | Jujube Forest Land Transfer Income | Jujube Employment Income | Land Resource Conservation | Forest Landscape | Employment Opportunities | Life Satisfaction |
---|---|---|---|---|---|---|---|---|---|
Program × Cooperatives | −0.11 (0.16) | 0.52 * (0.27) | 2.08 *** (0.45) | 4.87 *** (0.25) | 0.80 *** (0.21) | 0.37 *** (0.12) | 0.24 *** (0.09) | 0.33 *** (0.12) | 0.12 ** (0.10) |
Control variable | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Regional variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Observed value | 302 | 302 | 302 | 302 | 302 | 302 | 302 | 302 | 302 |
R2 | 0.24 | 0.15 | 0.07 | 0.71 | 0.22 | 0.08 | 0.05 | 0.05 | 0.04 |
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Wang, J.; Jiang, X.; Chen, X.; Zhang, J.; Dou, Y.; Zhang, J. The Impact of Forestry Technological Innovation on the Welfare of Farm Households Managing Jujube Forests (Ziziphus jujuba Mill.) in the Lüliang Mountains of the Yellow River’s Middle Reaches. Forests 2024, 15, 1592. https://doi.org/10.3390/f15091592
Wang J, Jiang X, Chen X, Zhang J, Dou Y, Zhang J. The Impact of Forestry Technological Innovation on the Welfare of Farm Households Managing Jujube Forests (Ziziphus jujuba Mill.) in the Lüliang Mountains of the Yellow River’s Middle Reaches. Forests. 2024; 15(9):1592. https://doi.org/10.3390/f15091592
Chicago/Turabian StyleWang, Jin, Xuemei Jiang, Xingliang Chen, Jingjing Zhang, Yaquan Dou, and Jing Zhang. 2024. "The Impact of Forestry Technological Innovation on the Welfare of Farm Households Managing Jujube Forests (Ziziphus jujuba Mill.) in the Lüliang Mountains of the Yellow River’s Middle Reaches" Forests 15, no. 9: 1592. https://doi.org/10.3390/f15091592