Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China
Abstract
:1. Introduction
2. Theoretical Basis and Quantitative Analysis Model
2.1. Theoretical Basis
2.2. Livelihood Stability System Model
3. The Empirical Study
3.1. Study Area
3.2. Data Acquisition and Data Management
3.2.1. Data Sources
3.2.2. Establishment of the Index System of Livelihood Stability
3.2.3. Data Processing
3.3. Results
3.3.1. Livelihood Capitals
3.3.2. Livelihood Strategy
3.3.3. Response Capacity
3.3.4. Land-Use Efficiency
3.3.5. The Livelihood Stability Values
4. Discussion and Conclusion
4.1. Discussion
4.1.1. Policy Implementations
4.1.2. Diversity-Stability Relationship
4.1.3. Study Limitations
4.2. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Category | Variable Name (Short Forms) | Definition (Unit) | Mean | Standard Deviation | Mean Deviation | Standard Error | ||||
---|---|---|---|---|---|---|---|---|---|---|
Natives | Immigrants | Natives | Immigrants | Natives | Immigrants | Natives | Immigrants | |||
Natural Capital (N) | Cropland (N1) | cropland per household, including drylands and paddy field (mu) | 7.09 | 7.76 | 8.33 | 7.57 | 5.47 | 4.91 | 1.28 | 0.69 |
Orchard (H5) | garden land per household (mu) | 4.26 | 1.27 | 4.00 | 3.26 | 2.83 | 1.97 | 0.62 | 0.3 | |
Forestland (N3) | forest area per household (mu) | 13.52 | 6.69 | 20.46 | 11.49 | 12.58 | 6.79 | 3.16 | 1.04 | |
Land blocks (N4) | negative number of land blocks per household cultivated (blocks) | 8.1 | 5.16 | 4.56 | 5.69 | 3.74 | 3.23 | 0.7 | 0.51 | |
Crop strains (N5) | food crops and cash crops per household (types) | 4.14 | 3.23 | 1.37 | 1.41 | 1.04 | 1.10 | 0.21 | 0.13 | |
Physical Capital (P) | Housing (P1) | number of rooms per household | 4.29 | 3.5 | 2.02 | 1.77 | 1.54 | 1.37 | 0.31 | 0.16 |
Electricity consumption (P2) | electricity consumption per month per household (W) | 82.5 | 81.33 | 72.22 | 91.50 | 37.38 | 39.42 | 11.14 | 8.28 | |
Distance to road (P3) | distance to the nearest road (negative indicator) (meters) | 33.9 | 100.91 | 83.18 | 532.20 | 41.94 | 158.77 | 12.83 | 48.18 | |
Production tools (P4) | number of farm machines and durable goods per household | 4.71 | 3.76 | 1.90 | 1.97 | 1.54 | 1.66 | 0.29 | 0.18 | |
Livestock (P5) | all kinds of livestock in research area: 1 = cattle, 0.8 = horses, 0.3 sheep, 0.2 = pigs, 0.01 chickens, 0.02 = ducks, 0.03 = geese, 0.2 = silkworms, 0.001 = eggs | 1.35 | 1.26 | 1.08 | 2.61 | 0.75 | 1.28 | 0.17 | 0.24 | |
Fertilizer (P6) | total fertilizer and pesticide amounts applied for the year (negative indicator) (kilograms) | 581.48 | 1033.7 | 509.20 | 1434.35 | 328.42 | 880.80 | 78.57 | 129.86 | |
Financial Capital (F) | Agricultural income (F1) | household total income from agricultural work per year (RMB) | 14,726.07 | 9315.49 | 9377.64 | 11,586.16 | 7307.36 | 7626.69 | 1447 | 1048.96 |
Wages (F2) | wage income per year per household (RMB) | 12,845.24 | 19709.49 | 20,757.16 | 37,070.33 | 16,136.05 | 21,531.04 | 3202.9 | 3356.19 | |
Remittance (F3) | remittance income per year per household (RMB) | 7973.83 | 3178.08 | 21,890.46 | 6878.39 | 9988.38 | 4033.22 | 3377.77 | 627.91 | |
Property (F4) | property income per year per household (RMB) | 0.02 | 95.45 | 0.15 | 552.42 | 0.00 | 0.00 | 0.02 | 50.01 | |
Non-agricultural income (F5) | household total income from non-agricultural work per year (RMB) | 5842.86 | 5696.81 | 14,762.56 | 15,715.82 | 9121.77 | 9302.89 | 2277.91 | 1422.84 | |
Loans (F6) | whether household can loan from the bank: 1 = Yes; 0 = No | 0.6 | 0.61 | 0.50 | 0.49 | 0.48 | 0.47 | 0.8 | 0.04 | |
Borrowings (F7) | whether household can borrow from others: 1 = Yes; 0 = No | 0.79 | 0.9 | 0.42 | 0.30 | 0.34 | 0.16 | 0.06 | 0.03 | |
Human Capital (H) | Labor members (H1) | number of household workers refers to able-bodied workers aged 14 to 65 | 3.93 | 4.18 | 0.97 | 1.83 | 0.67 | 1.38 | 0.15 | 0.17 |
Non-farming laborers (H2) | number of workers in non-agricultural industries | 1.05 | 1.23 | 0.91 | 1.16 | 0.73 | 0.92 | 0.14 | 0.11 | |
Labor capacity (H3) | including all household members: 1 = sound labor capacity, 0.5 = semi-labor ability, 0 = incapacity | 0.73 | 0.71 | 0.21 | 0.25 | 0.17 | 0.20 | 0.03 | 0.02 | |
Education (H4) | educational level of all household members: 4 = junior college and above, 3 = high school, 2 = middle school, 1 = primary school, 0 = illiterate | 1.43 | 1.93 | 0.45 | 0.63 | 0.37 | 0.51 | 0.07 | 0.06 | |
Educational expenditure (H5) | educational expenditure per household in total (RMB) | 4133.81 | 4083.73 | 6752.51 | 6536.50 | 4479.07 | 4475.26 | 1041.94 | 591.79 | |
Male (H6) | proportion of males per household (%) | 0.54 | 0.55 | 0.17 | 0.19 | 0.14 | 0.15 | 0.03 | 0.02 | |
Health Status (H7) | medical expenditures (negative indicator) (Yuan) | 2416.67 | 4255.74 | 2730.76 | 8773.56 | 2133.33 | 4440.12 | 421.36 | 794.32 | |
Social Capital (S) | Transportation (S1) | annual transport expenditures (RMB) | 854.86 | 1498.1 | 4578.63 | 2566.25 | 1678.64 | 1398.00 | 706.5 | 232.34 |
Communication (S2) | annual communications expenditures (RMB) | 1405.24 | 962.95 | 1175.36 | 1251.49 | 895.06 | 830.04 | 181.36 | 113.3 | |
Relative network (S3) | number of farmers who work in the town for more than six months per year | 0.71 | 0.93 | 0.60 | 0.83 | 0.51 | 0.57 | 0.09 | 0.08 | |
Access to notification (S4) | number of ways farmers can obtain relative information | 0.05 | 1.19 | 0.22 | 0.80 | 0.09 | 0.51 | 0.03 | 0.07 |
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Indicators | Content | Formula | Explanation |
---|---|---|---|
Livelihood capitals | Natural, Physical, Financial, Human, Social Capital | f(t) stands for livelihood capitals values; Vp represents the values of natural, physical, financial, human, and social capitals, respectively (i.e., Z = 5). | |
Livelihood Strategy | Income Diversity | Based on the Shannon–Wiener diversity index, this suggests that the higher the income diversity, the more sources of income farmers will have. Thus, the proportion of these income tends to balance. Pn represents the rate of net income of farmers to total income from nth income source; S represents the number of income sources. | |
Response Capacity (Dependency) | Income Dependency | This involves the proportion of a farmer’s income from one source that is much higher than the sum of the others. (Precondition Xn > 1 and X > 1) Xn represents one net income per household from the nth income source; X represents total net income per household. | |
Resource Dependency | This reflects the farmers’ dependency on natural resources. These usually include grain and cash crops, livestock, fruit production, forestry, collected feed, and firewood. N represents agricultural income per household; T indicates total household income. | ||
Land-Use Efficiency | Land Intensification Level | Data envelopment analysis (DEA) (CCR (I) model) | It is important for farmers to assess land-use change and rational utilization as well as the potential economic effects. We developed the CCR (I) model (proposed by Charnes, Cooper and Rhodes in 1978) from the perspective of input and output using DEA-SOLVER PRO 5.0 software for data processing, which means from the perspective of input and the current level of output, comparing the proportion of ideal minimum input and actual input (Figure 3). |
Types | Livelihood Capitals | Livelihood Strategy | Response Capacity | Land-Use Efficiency | Livelihood Stability | ||
---|---|---|---|---|---|---|---|
Income Diversity | Income Dependency | Resource Dependency | Total | ||||
Immigrants | 0.6210 | 0.5050 | 0.6935 | 0.3918 | 0.5427 | 0.3922 | 0.5152 |
Natives | 0.6422 | 0.5528 | 0.6654 | 0.5178 | 0.5916 | 0.5881 | 0.5937 |
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Li, X.; Xu, S.; Hu, Y. Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China. Sustainability 2020, 12, 6374. https://doi.org/10.3390/su12166374
Li X, Xu S, Hu Y. Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China. Sustainability. 2020; 12(16):6374. https://doi.org/10.3390/su12166374
Chicago/Turabian StyleLi, Xiang, Shuang Xu, and Yecui Hu. 2020. "Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China" Sustainability 12, no. 16: 6374. https://doi.org/10.3390/su12166374
APA StyleLi, X., Xu, S., & Hu, Y. (2020). Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China. Sustainability, 12(16), 6374. https://doi.org/10.3390/su12166374