EN中文

Journal of Resources and Ecology >

2025 , Vol. 16 >Issue 1: 62 - 72

DOI: https://doi.org/10.5814/j.issn.1674-764x.2025.01.006

Resource Economy

Can Anti-poverty Policies Improve Livelihood Sustainability? An Empirical Study from the Perspective of Farmers’ Perceptions

  • YANG Lun , *
Expand
  • Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
*YANG Lun, E-mail:

Received date: 2024-03-24

  Accepted date: 2024-09-20

  Online published: 2025-01-21

Supported by

National Natural Science Foundation of China(42001249)

Fold

Abstract

In recent years, an ambitious development policy named the targeted poverty alleviation policy has been implemented in China, and it has achieved remarkable success. But whether the smallholder farmers raised out of extreme poverty due to this policy have achieved sustainable livelihoods remains uncertain. This study developed a livelihood sustainability index that can comprehensively assess farmers’ livelihoods, constructed an analytical model of the direct and indirect impacts of policy measures on livelihood sustainability using the farmer’s perceptions of those policies as a mediator, and created a policy perception elasticity factor to screen the contributions of policy measures to the improvement of livelihood sustainability. Based on these theoretical advances, a case study of an indigenous community on the Tibetan Plateau was conducted. The results show that this policy has contributed to improving farmers’ livelihood sustainability in the case areas, especially in terms of livelihood assets and livelihood outcomes, through direct encouragement and indirect influences based on the vulnerability context. In China’s era of “post-targeted poverty alleviation”, the findings from this case study indicate that relevant future policies should attach importance to institutional reform and staff management, and establish practical actions to cope with the uncertainty of the vulnerability context.

Key words： targeted poverty alleviation policy; sustainable development goals; sustainable livelihoods; livelihood sustainability index; policy perception elasticity

Cite this article

YANG Lun . Can Anti-poverty Policies Improve Livelihood Sustainability? An Empirical Study from the Perspective of Farmers’ Perceptions[J]. Journal of Resources and Ecology, 2025 , 16(1) : 62 -72 . DOI: 10.5814/j.issn.1674-764x.2025.01.006

1 Introduction

Eradicating poverty in all its forms and dimensions is an indispensable requirement for sustainable development (UNESCO, 2022). Since the United Nations formally proposed the 2030 Sustainable Development Goals, poverty assessment has expanded from focusing on just income to multiple dimensions, such as education, human capital, good health, and well-being (Sachs et al., 2019). This coincides with the concept of sustainable livelihoods proposed by many scholars on poverty. A livelihood is sustainable when it can cope with and recover from stresses and shocks and maintain or enhance its capabilities and assets both now and in the future, while not undermining the natural resource base (DFID, 1999). These livelihood sustainability goals must be achieved for several million low-income people who always rely or depend on natural resources (such as farmland, grassland, and forestry) for their livelihoods in line with the principle of “leaving nobody behind” (Huang et al., 2022). As the most populous developing country, China has implemented an ambitious anti-poverty policy named the targeted poverty alleviation policy, which has achieved remarkable success since 2015. China’s poverty rate has dropped significantly from 10.2% to 0.6% in the past several years. Compared with previous poverty policies, the targeted poverty alleviation policy shifts poverty improvement from a strict income perspective to a multifaceted connotation that includes food, housing, education, and other components (Wang and Shu, 2021).
However, there is no all-encompassing perspective of livelihood sustainability for assessing how the targeted poverty alleviation policy impacts individuals. The reasons for this phenomenon are diverse. First, the targeted poverty alleviation policy is comprehensive. It is implemented through various group-oriented measures rather than individual-oriented subsidies, including institutional reform, staff management, government funding management, financial funding management, and social funding management measures. Therefore, assessing the extent and manner of its impact on farmers at the individual level may need to be mediated by farmers’ perceptions of the policy rather than through the effects of policy measures on individuals. Second, it must exclude the impacts of factors other than the anti-poverty policy on livelihood sustainability, which may come from biophysical, environmental, economic, and other domains, such as climate change, depression, and pandemics. For instance, the COVID-19 pandemic from 2019 to the present has forced 120 million people into or back into extreme poverty and increased the vulnerability of their livelihood sustainability in the world (Sachs et al., 2021). Third, numerous studies have shown that the improvement of farmers’ livelihood sustainability cannot quickly result from policies alone. Instead, it is a long-term goal that requires joint efforts through policy interventions and other action plans. Thus, assessing the impacts of anti-poverty policies on livelihood sustainability is a long-term and site-specific task that needs to follow up with samples of farmers. These farmers should be recipients of the policy, members of a low-income group, and able to live permanently on a fixed geographic site.
Among the 14 contiguous poverty-stricken areas in China, which is the most challenging area for poverty reduction in China, the largest is the Qinghai-Tibet Plateau. Most of the villages on the Qinghai-Tibet Plateau are indigenous communities. For a long historical period, the farmers in these communities could only rely on poor environmental resources (such as grassland and forest) to maintain their primary livelihood goals due to traffic inconvenience and a generally low education level (Yang et al., 2019). As a result, their incomes have been chronically low, and their livelihoods are unsustainable. Of greater concern, the increase in temperature and population growth in recent years have caused problematic regional changes, such as a reduction of the suitable area for ​​crops, grassland degradation, and an increase in food demand. So, the farmers in indigenous communities on the Qinghai-Tibet Plateau now face more severe livelihood pressure (Duan et al., 2019; Qi et al., 2020; Veh et al., 2020). This study explored two key questions through a 5-year fixed-point study in this region: 1) From the perspective of indigenous farmers, can the targeted poverty alleviation policy improve their livelihood sustainability? and 2) If the policy can improve their livelihood sustainability, what is the potential improvement mechanism?

2 Literature review

Livelihood has been widely used or practiced as a term, an approach or framework, and an epistemology since its introduction in the early 1990s (Natarajan et al., 2022). Many scholars have adopted the Sustainable Livelihood Framework (DFID, 1999) when conducting empirical studies on improving livelihood sustainability in rural areas of the Global South. These studies have attempted to answer two key questions.
1) What are sustainable livelihoods?
In most empirical studies, discussions on defining sustainable livelihoods have considered the strategies, assets, and outcomes. Farmers with abundant and harmonious livelihood assets and outcomes can easily maintain the preferable livelihood sustainability (DFID, 1999; Peng et al., 2022). But from the perspective of livelihood strategies, a debate between diverse and specialized strategies remains. Diverse strategies (such as integrating agriculture and agritourism) are generally valuable for improving the livelihood sustainability of poor farmers (Paul et al., 2020). But more specialized strategies (such as scale farming) are more sustainable in highly developed markets (Wang et al., 2016). Recently, the well-being of farmers has been a concern in many studies. Empowerment for rights of the poor (Berhanu et al., 2022), effective community-based participation in the co-management of natural resources (de la Puente et al., 2022; Ullah et al., 2022), and local conservation engagement in rural tourism (Aazami and Shanazi, 2020) are crucial for reinforcing sustainable livelihoods, especially in low-income communities. Meanwhile, the study of livelihood resilience and vulnerability has considered how to evaluate sustainability theoretically (Bauer et al., 2022). Although many aspects of livelihood sustainability have been discussed, there are no indexes, methodologies, or standards that can more succinctly and directly describe livelihood sustainability. In the context of humanity’s increasing uncertainties, a quick, concise but comprehensive approach may be worth exploring.
2) How can livelihood sustainability be improved?
Farmers’ livelihoods are the result of many factors, including external environment factors (such as government policies, social cohesion, and village organizational ability) and internal family factors (such as income sources, social networks, access to resources, and individual characteristics) (Ding et al., 2020; Pu and Chang-Richards, 2022). These factors are the basis for developing actions that can improve their sustainable livelihoods. Aside from cash transfers and immediate financial support (Hajdu et al., 2020; Rathnayake et al., 2022), successful efforts can be classified into three categories. The first is enhancing farmers’ capacity, such as through proper knowledge transfer (such as training and novel community services), agricultural technology popularization, and investment in rural education (Wu et al., 2021; Ulukan et al., 2022). The second is ensuring the health of farmers by promoting the development of social insurance, social relief, and medical services (Wang et al., 2016). The third is improving farmers’ productivity by paying for ecosystem services, investing in rural infrastructure (such as irrigation, drainage, and power facilities), improving social services for agricultural mechanization, and other asset investments (Dang et al., 2020; Wu et al., 2021). Among those actions, policy intervention is the most common choice because it can unite various stakeholders, including governments, international organizations, non-governmental organizations, and local farmers (Liu and Lan, 2015; Mdee et al., 2021). Furthermore, some recent empirical studies have shown that the perceptions of policy recipients are essential factors affecting policy effectiveness (Malakar et al., 2018; Abukari and Mwalyosi, 2020; Wekesa et al., 2023).

3 Methodology

3.1 Data sources and study area

This study selected Zhagana Village (34°09ʹ40ʺ-34°11ʹ20ʺN, 103°08ʹ49ʺ-103°10ʹ15ʺE), which is located in Diebu County, Gansu Province, China, as the case study group. This area has a high population density and more human activity for the Qinghai-Tibet Plateau, and it is a crucial area for integrating forestry, planting, and animal husbandry. Furthermore, since many farmers there employ environmental resource use and management practices from great antiquity, the Food and Agriculture Organization of the United Nations officially designated the Diebu Zhagana Agriculture-Forestry-Animal Husbandry Composite System, which includes Zhagana Village, as the first Globally Important Agricultural Heritage System site on the Qinghai-Tibet Plateau in 2017.
Zhagana Village is a typical indigenous Tibetan community, with 210 households in 2021. In 2017, 154 randomly selected households were pre-surveyed for this study. Based on the results, 77 households were randomly chosen to begin a 5-year follow-up survey from 2017 to 2021, representing 36.32% of the total households. The data collected included the household’s livelihood status, policy perceptions, and productive behaviors.

3.2 Evaluation of the livelihood sustainability index

Based on the Sustainable Livelihood Framework and relevant studies, we argue that farmers’ livelihoods are sustainable in the Qinghai-Tibet Plateau when they have abundant livelihood assets, diverse livelihood strategies, and favorable livelihood outcomes (DFID, 1999; Paul et al., 2020; Peng et al., 2022). Thus, this study established the livelihood sustainability index (Lsustainability) to quantitatively assess the livelihood sustainability of farmers (Table 1).
Table 1 The evaluation indexes of livelihood sustainability
First-level index Second-level index Second-level index definition
Livelihood strategies
sustainability index (LS)		 Agriculture-oriented strategy (LSa) Number of households that engage in agriculture-oriented activities (farming) for more than two-thirds of their working hours
Part-time strategy (LSp) Number of households that engage in agriculture-oriented activities or non-agriculture-oriented activities for no more than two-thirds of their working hours
Non-agriculture-oriented strategy (LSn) Number of households that engage in non-agriculture-oriented activities (such as going out for non- farming jobs, taking part in rural tourism reception) for more than two-thirds of their working hours
Livelihood
assets
sustainability index (LA)		 Human capital (LAh) Quantity of available labor force per household
Social capital (LAs) Number of available relatives in the village per household
Natural capital (LAn) Area of available land resources per household (ha)
Physical capital (LAp) Quantity of available instruments of production per household
Financial capital (LAf) Quantity of financial or alternative savings per household (yuan)
Livelihood
outcomes
sustainability index (LO)		 Family health condition (LOh) Prevalence of severe/moderate/mild diseases of family members per household (%)
Family education condition (LOe) Average years of education of family members per household (year)
Family financial condition (LOf) Average annual income per household (yuan)

Note: Due to the significant differences in the dimensions between the indexes, this study adopted the maximum difference normalization method to standardize the data for each index.

Numerous studies in poverty-stricken areas have shown that either diverse livelihood strategies, higher levels of livelihood capital, or more prosperous livelihood outcomes mean higher livelihood sustainability (Kuang et al., 2019; Rosalien et al., 2019; Richard et al., 2020). Among the three, LS denotes the sustainability of the range and combination of activities and choices (agricultural production, out-migration for work, and rural tourism) that people make/undertake to achieve their livelihood goals. LA represents the sustainability of the material and non-material basis (human, social, natural, physical, and financial capital) for maintaining farmers’ livelihoods. LO is the sustainability of livelihood strategy achievements or outputs (family health, education, and financial conditions). Therefore, the Lsustainability index consists of three parts: livelihood strategies sustainability index (LS), livelihood assets sustainability index (LA), and livelihood outcomes sustainability index (LO). This study sourced the indicators recommended by DFID for evaluation index selection (DFID, 1999). Based on our preliminary survey of the research area, the most representative evaluation index was selected for analysis (Table 1).
The calculation formulas of Lsustainability are:
${{L}_{\text{sustainability}}}=LS+LA+LO$
$LS=1-\underset{i=1}{\overset{N}{\mathop \sum }}\,Time_{i}^{2}$
$LA=\left( L{{A}_{h}}+L{{A}_{s}}+L{{A}_{n}}+L{{A}_{p}}+L{{A}_{f}} \right)/5$
$LO=\left( L{{O}_{h}}+L{{O}_{e}}+L{{O}_{f}} \right)/3$
Among the variables, i is the type of farmers’ livelihood activities (farming, going out for a non-farming job, or taking part in rural tourism reception), and N is the total number of types. Timei is the ratio of the livelihood activity time of type i to the total working time of farmers, and its value is between 0 and 1.00. The numeric range of Lsustainability is 0-3.00. When the evaluation value of a sample farmer is between 0-1.00, 1.00-2.00, or 2.00-3.00, it indicates that the sample’s livelihood sustainability is at a poor, medium, or good level, respectively. The numeric ranges of LS, LA and LO are all 0-1.00. When the evaluation value of either LS or LA or LO of a sample farmer is between 0-0.33, 0.34-0.66, or 0.67-1.00, it indicates the livelihood strategies sustainability, or livelihood assets sustainability, or livelihood outcomes sustainability is at a poor, medium, or good level, respectively.

3.3 Evaluation of farmers’ perceptions of the anti-poverty policy

Over the past five years, the local government in Zhagana Village has implemented various measures of the targeted poverty alleviation policy to alleviate and improve the poverty situation of smallholder farmers (Table 2). However, our field survey found that local farmers received the benefits of almost all five measures to different degrees, so the farm household types could not be classified in terms of whether they objectively participated in one particular measure or not. Therefore, this study used the arithmetic mean of the sum of the perception evaluation values of these five measures as the farmers’ perception value of the targeted poverty alleviation policy (Ppoverty). A single farmer’s perception evaluation value of a single policy measure was a number from 1.00 to 5.00, where 1.00 is a very low perceptual rating, 2.00 is low, 3.00 is medium, 4.00 is high, and 5.00 is very high. Thus, the value range for a single farmer’s perception of the Targeted Poverty Alleviation Policy is 1.00-5.00.
Table 2 The five measures of the targeted poverty alleviation policy
Policy measure Actions of the policy measure
Institutional
reform measure		 1) The government encourages farmers to participate in land transfer. 2) The government guides poor households to invest their resource assets in agricultural projects. 3) The government equitably distributes the compensation funds to poor households in agricultural projects. 4) The government integrates agricultural-related funds. 5) The government publicly regularly announces the progress of various policy measures. 6) The provincial government dynamically adjusts the amount of poverty alleviation funds based on the poverty alleviation situation of each county. 7) The government uses interest discounts, guarantees, risk compensation, and premium subsidies to invest in the agricultural industry. 8) The government recruits enterprises capable of absorbing poor laborers. 9) The government reforms the policy of the poor people to settle in cities and towns
Staff management measure 1) The government assigns personnel to the village to carry out the targeted poverty alleviation policy. 2) The staff formulates an operational poverty alleviation work plan. 3) The government regularly evaluates the work results of the staff. 4) The staff in the village regularly meets with the upper-level management personnel. 5) The government establishes long-term workstations in impoverished villages. 6) The government dynamically adjusts the number of staff according to the situation of impoverished villages
Government fund management measure 1) The government sets a particular targeted poverty alleviation policy funding budget. 2) The government separately sets up poverty alleviation funding subjects. 3) The government regularly audits the use of poverty alleviation funds. 4) The government supervises the use of poverty alleviation funds and establishes a lifelong accountability system for poverty alleviation projects
Financial fund management measure 1) Financial institutions increase financial service outlets in poor villages. 2) Financial institutions reduce loan interest rates for poor households. 3) Financial institutions establish special loan projects for the targeted poverty alleviation policy. 4) Financial institutions establish loan risk compensation measures for poor households. 5) Financial institutions simplify the loan process for poor households. 6) Financial institutions prioritize promoting micro-loan insurance to poor households. 7) Financial institutions increase the amount of agricultural insurance premium subsidies for poor households. 8) Financial institutions prioritize promoting personal accident insurance to poor households. 9) Financial institutions lead in establishing and evenly distributing village-level mutual aid funds
Social fund
management measure		 1) The government encourages social organizations and individuals to participate in poverty alleviation work. 2) Social organizations carry out volunteer actions for poverty alleviation. 3) The government encourages government personnel to participate in the poverty alleviation activities of various NGOs. 4) Local governments actively seek “one-to-one” poverty alleviation support from central agencies. 5) Local governments seek “one-to-one” poverty alleviation support from the governments in developed regions. 6) Medical institutions carry out medical assistance in poor villages. 7) The government encourages enterprises to participate in poverty alleviation through preferential tax policies. 8) The government commends social organizations and individuals for their poverty alleviation work

3.4 Analysis of the impact of the policy on livelihood sustainability

Each of the five policy measures of the targeted poverty alleviation policy includes actions aimed at improving the poverty situation of farmers and the natural and social environments of the regions where farmers are located. Meanwhile, in studies of livelihoods, people’s livelihoods and the wider availability of assets are fundamentally affected by critical trends, shocks, and seasonality of the natural and economic environments where they live (Zhang et al., 2019; Lisa et al., 2020; Xu et al., 2020). These external natural and economic environments in which people exist have been framed as the vulnerability context (DFID, 1999). In general, they can be divided into the natural background, economic background, and community background factors (Table 3).
Table 3 The system of vulnerability context
First-level index Second-level index Second-level index definition
Natural
background		 Climate change The initial value is 0. Then, if the regional annual temperature increases, add 1; if there is no increase, it remains 0
Soil erosion The initial value is 0. Then, if the regional annual incidence of soil erosion increases, add 1; if there is no increase, it remains 0
Drought The initial value is 0. Then, if the regional annual incidence of drought increases, add 1; if there is no increase, it remains 0
Economic background Gross domestic product The initial value is 0. Then, if the gross domestic product increases, add 1; if there is no increase, it remains 0
Gross output value of agriculture The initial value is 0. Then, if the gross output value of agriculture increases, add 1; if there is no increase, it remains 0
Fixed asset investment The initial value is 0. Then, if the regional fixed asset investment increases, add 1; if there is no increase, it remains 0
Community background Community population size The initial value is 0. Then, if the community population size increases, add 1; if there is no increase, it remains 0
Community infrastructure The initial value is 0. Then, if the community infrastructure increases, add 1; if there is no increase, it remains 0
Communal activity The initial value is 0. Then, if the communal activity increases, add 1; if there is no increase, it remains 0
Therefore, a hypothesis can be proposed that the targeted poverty alleviation policy can affect the livelihood sustainability of farmers directly and/or indirectly via the vulnerability context. This study conducted two rounds of regression analysis to test this hypothesis, including a regression analysis between the livelihood sustainability indexes and the policy perception values and another regression analysis using the vulnerability context indexes as a mediator. The sample data of farmers consisted of short panel data with diversified dimensions and orders of magnitude. After the statistical test, the pooled regression was used for analysis:
${{y}_{it}}=\alpha +{{{x}'}_{it}}\beta +{{{z}'}_{i}}\delta +{{\varepsilon }_{it}}\begin{matrix} {} & (i=1,\cdots,n;\begin{matrix} {} \\ \end{matrix} \\ \end{matrix}t=1,\cdots,T)$
Among the variables,${{y}_{it}}$is the dependent variable;${{x}_{it}}$is the time-varying variable;${{z}_{i}}$is the time invariant variable; ${{{x}'}_{it}}$and${{{z}'}_{i}}$are the first derivatives of ${{x}_{it}}$and${{z}_{i}}$, respectively; $\alpha $is a constant term, and${{\varepsilon }_{it}}$is the error term.

3.5 Analysis of the contribution of the policy to livelihood sustainability

Any improvement in the farmers’ livelihood sustainability may not result from a single policy or action alone. Since the targeted poverty alleviation policy is a national policy implemented simultaneously in all regions of China, it is impossible to identify communities that did not implement the policy as a control group for assessing its contribution to improving livelihood sustainability. This study drew on the concept of “elasticity” in economics to answer this question. The response of changes in the livelihood sustainability index value (Lsustainability) to changes in the policy perception evaluation value (Ppoverty) was analyzed by establishing the Policy Perception Elasticity (PPE).
$PPE=\frac{PP{{E}_{\text{sustainability}}}}{PP{{E}_{\text{poverty}}}}$
$PP{{E}_{\text{sustainability}}}=\frac{\Delta {{L}_{\text{sustainability}}}}{{{L}_{\text{sustainability}}}}$
$PP{{E}_{\text{poverty}}}=\frac{\text{ }\!\!\Delta\!\!\text{ }{{P}_{\text{poverty}}}}{{{P}_{\text{poverty}}}}$
If the response is elastic (PPE>1.00), then the change in livelihood sustainability is faster than that of policy perception. That is, the targeted poverty alleviation policy significantly contributes to improving farmers’ livelihood sustainability. On the other hand, if it is inelastic (PPE<1.00), this indicates only a small contribution. If it is inelastic (PPE=1.00), this indicates no contribution.

4 Results

4.1 Evaluation of livelihood sustainability and policy perception

In the past five years, the indigenous farmers’ livelihood sustainability in Zhagana Village has generally improved (Figure 1). However, it has always been at the medium level and high sustainability was never achieved. Specifically, the 5-year average value of 77 typical farmers’ livelihood sustainability index was 1.20. The index rose slightly from 2016 until it peaked in 2019, with an increase of 9.25%. In 2020, the index decreased slightly, but it was still higher than the estimated value in 2016 (Figure 1).
Figure 1 Changes in livelihood sustainability indexes and the policy perception value from 2016 to 2020
Like livelihood sustainability, farmers’ livelihood asset and livelihood outcome sustainability levels have increased slightly in the past five years but were always at the medium level. The farmers’ physical and social capital for maintaining their livelihoods has increased significantly, and the educational condition of households has improved considerably. However, the sustainability of farmers’ livelihood strategies showed a downward trend, and was at a poor level in each year. Their livelihood strategies have gradually simplified and become more non-agricultural. One possible reason is the harsh natural environment and inconvenient traffic conditions on the Qinghai-Tibet Plateau, which led to the initial livelihood strategies of local farmers that primarily rely on environmental resources (such as grassland and forests). However, the farmers have generally shifted in recent years from diversifying agricultural production (such as raising livestock and planting crops) to non-agricultural production strategies with higher returns on investment (such as highland tourism reception). Specifically, the 5-year average values ​​of the sample farmers’ livelihood strategies sustainability index, livelihood assets sustainability index, and livelihood outcomes sustainability index were 0.24, 0.49, and 0.47, respectively. Among them, the livelihood strategies sustainability index decreased in 2016 and reached its lowest level in 2018, with a reduction of 14.98%. Then it rose slightly after 2018, which continued into 2020. On the other hand, the livelihood assets sustainability index and livelihood outcomes sustainability index increased slightly from 2016 until 2019, increasing by 9.75% and 23.75%, respectively. They were both lower in 2020, but both were still higher than their 2016 assessments.
The farmers’ perception of the targeted poverty alleviation policy has fluctuated in the past five years, but it has always remained at the upper-middle level. This shows that farmers have always had a high awareness of this policy. Specifically, the farmers’ average perceived evaluation value of the targeted poverty alleviation policy was 3.95. It started to rise in 2016 and reached its peak in 2018, with an increase of 13.92%. It then decreased significantly in 2019 but increased in 2020.

4.2 Relationship between livelihood sustainability and policy perception

From the perspective of the indigenous farmers in Zhagana Village, the targeted poverty alleviation policy has positively contributed to improving their livelihood sustainability. Namely, the livelihood sustainability index and the policy perception evaluation value were positively correlated when the time variable was excluded. Therefore, the first key question raised in this study, whether the targeted poverty alleviation Policy can improve farmers’ livelihood sustainability, has been answered in the affirmative.
Specifically, the policy evaluation value of farmers can be taken as the independent variable, and the livelihood sustainability index, livelihood strategies sustainability index, livelihood assets sustainability index, and livelihood outcomes sustainability index of farmers can be taken as the dependent variables to draw scatter plot diagrams (Figure 2). The results show that the dispersion of the livelihood sustainability index (including the indexes of livelihood strategies, livelihood assets, and livelihood outcomes) and policy perceived evaluation value are relatively high. In other words, the distributions of scatter points are chaotic. But there is a specific correlation between the two groups. The livelihood sustainability index, livelihood assets sustainability index, and livelihood outcomes sustainability index are each positively correlated with the policy perception evaluation value. When a farmer’s targeted poverty alleviation policy evaluation value is higher, their value for either the livelihood sustainability index, or livelihood assets sustainability index, or livelihood outcomes sustainability index is also higher. On the other hand, the livelihood strategies sustainability index is negatively correlated with the policy perceived evaluation value. So when a farmer’s targeted poverty alleviation policy evaluation value is higher, their livelihood strategies sustainability index is lower.
Figure 2 The scatter plot diagrams of the livelihood sustainability index, livelihood strategies sustainability index, livelihood assets sustainability index, and livelihood outcomes sustainability index versus the policy perception evaluation value

4.3 Impacts of the targeted poverty alleviation policy on farmers’ livelihood sustainability

Based on the empirical analysis from the farmers’ perspective, the mechanism of the impact of targeted poverty alleviation policy on farmers’ livelihood sustainability is both direct and indirect (Figure 3). The policy’s institutional reform and staff management measures are vital for improving farmers’ livelihood sustainability. Furthermore, they all contribute to improving farmers’ livelihood sustainability in general. In addition, this improvement effect not only directly affects farmers’ livelihood strategies sustainability, livelihood assets sustainability, and livelihood outcomes sustainability but also indirectly affects the farmers’ livelihood sustainability by significantly affecting their vulnerability context (climate change, drought, fixed asset investment, and community infrastructure).
Figure 3 Schematic diagram of the impacts of the targeted poverty alleviation policy on farmers’ livelihood sustainability

4.3.1 The direct impacts

Based on the regression analysis results, only two of the five measures of the targeted poverty alleviation policy, the institutional reform measure and staff management measure, significantly directly impact the farmers’ livelihood sustainability (Figure 3). Among the measures, the institutional reform measure and staff management measure have significant positive correlations with farmers’ livelihood assets sustainability and livelihood outcomes sustainability, but only the institutional reform measure has a significant negative correlation with farmers’ livelihood strategies sustainability. These correlations indicate that when the government increases the intervention intensity of these two measures, the sustainability of farmers’ livelihood assets and livelihood outcomes may increase.

4.3.2 The indirect impacts

Compared with the direct impacts, the indirect impacts of the targeted poverty alleviation policy on farmers’ livelihood sustainability are more complicated (Figure 3). Three of the five measures, institutional reform, staff management, and financial funds management, indirectly affect farmers’ livelihood sustainability. Moreover, the “bridges” that have the indirect effects are natural background (climate change and drought), economic background (fixed asset investment), and community background (community infrastructure).
Based on the significant degree of the correlation analysis and the aggregation degree of the influencing relationship, the paths of indirect influence could be simplified down to three.
(1) Through the direct positive correlation of climate change with the institutional reform measure and staff management measure, these two measures can have indirect correlations with livelihood strategies sustainability (positive), livelihood assets sustainability (negative), and livelihood outcomes sustainability (negative). This means that when the government increases the intensity of its climate change actions, this will undermine the livelihood assets sustainability and livelihood outcomes sustainability but improve the livelihood strategies sustainability.
(2) Through the direct positive correlation of drought with both the institutional reform measure and staff management measure, these two measures can have indirect correlations with livelihood strategies sustainability (negative), livelihood assets sustainability (positive), and livelihood outcomes sustainability (positive). This means that when government increases the intensity of its drought actions, this will improve the livelihood assets sustainability and livelihood outcomes sustainability but undermine the livelihood strategies sustainability.
(3) Through the direct positive correlation of community infrastructure with the institutional reform measure and staff management measure, these two measures can have indirect correlations with livelihood assets sustainability (positive) and livelihood outcomes sustainability (positive). This means that when the government increases the intensity of its community infrastructure actions, this will improve the livelihood assets sustainability and livelihood outcomes sustainability.
Comparing the direct and indirect impacts, the direct impact of the institutional reform measure and staff management measure on farmers’ livelihood sustainability and the indirect impact through climate change are opposite. One possible reason is that these two measures’ actions in response to climate change (such as institutionally reducing regional carbon emissions and setting up personnel to monitor carbon emissions) may limit the activities of farmers. As a result, farmers would need to seek alternative livelihood strategies (such as establishing agricultural production constrained by carbon emissions compliance), and the diversity of livelihood strategies will rise in the short term. But the adoption of these alternative livelihood strategies by farmers requires an adaptation period, so the sustainability of livelihood assets and outcomes are bound to decline in the short term. However, such an outcome does not necessarily mean improving farmers’ livelihood sustainability and tackling climate change are opposed to their long-term goals. On the contrary, in the long run, when farmers gradually adapt to restrictive actions to cope with climate change, the reduction of farmers’ livelihood sustainability during the adaptation period will slow down. At the same time, this will improve the livelihood sustainability as their livelihood activities will be more adaptable to climate change.

4.4 Contribution of the targeted poverty alleviation policy to livelihood sustainability

Overall, although the targeted poverty alleviation policy’s contribution to the improvement of livelihood sustainability is relatively limited, it made a much larger contribution in the later stage of the policy. The mean elasticity between the livelihood sustainability index and farmers’ perception of the targeted poverty alleviation policy is less than 1, indicating a lack of elasticity between the two. Nevertheless, the mean elasticity increased continuously from 2016 to 2020, especially between 2018 and 2019, when it was greater than 1 (Table 4).
Table 4 Policy perception elasticity of the sampled farmers from 2016 to 2020
Policy measure Livelihood sustainability Period Average
2016-2017 2017-2018 2018-2019 2019-2020
Farmers’ perception of the targeted poverty alleviation Policy Livelihood sustainability index 0.28 0.08 1.12* 0.96 0.43
Farmers’ perception of the institutional reform measures Livelihood strategies sustainability index 1.33* 1.03* 2.13* 1.45* 0.31
Livelihood assets sustainability index 0.28 0.40 14.56* 0.60 3.66*
Livelihood outcomes sustainability index 2.36* 0.20 30.80* 2.09* 7.82*
Farmers’ perception of the staff management measure Livelihood strategies sustainability index 0.38 4.24* 2.13* 1.04* 1.95*
Livelihood assets sustainability index 0.08 1.66* 14.56* 0.43 3.10*
Livelihood outcomes sustainability index 0.67 0.84 30.80* 1.49* 6.95*
Farmers’ perception of the financial funds management measure Livelihood strategies sustainability index 0.53 0 0.09 0.95 0.08
Livelihood assets sustainability index 0.11 0 0.60 0.39 0.22
Livelihood outcomes sustainability index 0.94 0 1.26* 1.36* 0.42

Note: Elastic values greater than 1 are marked with an asterisk (*).

Among the three policy measures that have significant impacts on livelihood sustainability directly or indirectly, the contributions of staff management and institutional reform measures to the improvement of livelihood sustainability are relatively substantial. In contrast, the contribution of the financial funds management measure is limited. This indicates that the targeted poverty alleviation policy’s contribution to improving farmers’ livelihood sustainability mainly comes from its staff management and institutional reform measures. Specifically, the average elasticity values between the farmers’ perception of the staff management measure and the three livelihood sustainability indexes are all greater than 1 (Table 4), indicating that the measure and the three livelihood sustainability indexes are all elastic. In addition, the average elasticity values between the farmers’ perception of the institutional reform measure and the indexes of livelihood assets sustainability and livelihood outcomes sustainability are greater than 1 (Table 4), indicating that the measure and these two livelihood sustainability indexes are elastic. On the other hand, the mean elasticity values between the farmers’ perception of the financial funds management measure and the three livelihood sustainability indexes are less than 1 (Table 4), indicating a lack of elasticity.

5 Discussion

China is now in an era of “post-targeted poverty alleviation”, where the rural revitalization strategy has replaced the targeted poverty alleviation policy since 2021. However, there may still be plenty of room for improvement in the livelihood sustainability of most Chinese farmers that have been raised out of extreme poverty. Therefore, figuring out how to continuously improve the farmers’ livelihood sustainability through practical measures is a development issue worthy of attention in China and around the world.
Based on the empirical analysis of this study, the institutional reform and staff management measures in the targeted poverty alleviation policy were the two measures that had the most significant impacts and contributed the most to the livelihood sustainability improvement of farmers. The finding that the financial, governmental, and social funds management measures failed to demonstrate substantial effects was surprising in the context of many previous studies which reported that fiscal transfers or subsidies are probably the most direct and effective measures for improving livelihood sustainability.
There are two possible reasons for this discrepancy. First, this study assessed policy impacts from the perspective of farmers’ subjective policy evaluations. Institutional reform and staff management measures are more revealing over time than financial, governmental, and social fund management measures. For example, poverty alleviation personnel arrangements from the staff management measure and land transfer systems from the institutional reform measure have been in place for a long time, so farmers naturally have high perceptions of them. Second, the livelihood sustainability index established in this study focuses more on farmers’ well-being, capacity, and development potential rather than simply on economic income, and thus it may be more relevant to institutional reform and staff management measures. However, this discrepancy does not mean that the results of this study lack credibility or scientific validity, but rather that they have some limitations. These limitations are reflected in the index criteria and the index design orientation discussed above. In the livelihood sustainability index constructed in this study, the livelihood strategies sustainability index characterizes higher diversification as higher sustainability. Meanwhile, the livelihood assets sustainability index and livelihood outcomes sustainability index interpret higher livelihood asset and outcome assessment values as higher sustainability, respectively. In the case of this study, such criteria are reasonable because the case study area is in a chronically poor region, and this region’s demographic, social, and economic development are relatively poor. However, if the livelihood sustainability index was extended to other moderately developed areas, the criteria for the index would need to be re-established. For example, in developed regions the diversified livelihood strategies may not be as sustainable as specialized livelihood strategies due to the highly developed market settings.
Although the findings of this study may have some limitations, they can at least provide the insight that improving the farmers’ livelihood sustainability may not require excessive financial support in the form of transfer payments, but rather more attention should be given to institutional reforms and the management of policy implementers in future policy formulations. Furthermore, in achieving sustainable livelihoods for smallholder farmers, decision-makers may need to set development goals in stages and take specific actions in terms of the smallholder farmers’ well-being, capacity, health, and productivity.

6 Conclusions

Improving smallholder farmers’ livelihood sustainability is a rural development issue closely related to the UN’s Sustainable Development Goals. Based on previous studies on sustainable livelihoods, this study developed a livelihood sustainability index that can comprehensively assess farmers’ livelihoods, constructed an analytical model for the direct and indirect impacts of policy measures on livelihood sustainability using the vulnerability context as a mediator, and created a policy perception elasticity measure to assess the contributions of individual policy measures to livelihood sustainability improvement.
Based on a case study of indigenous farmers on the Qinghai-Tibet Plateau, the targeted poverty alleviation policy implemented by China in the past five years has indeed promoted the improvement of their livelihood sustainability from the perspective of farmers, especially their livelihood assets sustainability and livelihood outcomes sustainability. Among the five basic measures of the targeted poverty alleviation policy, institutional reform and staff management measures have been crucial for improving farmers’ livelihood sustainability. These two measures can directly promote the improvement of the sustainability of farmers’ livelihood strategies, assets, and outcomes, and indirectly affect the improvement of farmers’ livelihood sustainability by directly affecting the vulnerability context. The case study shows that improving farmers’ livelihood sustainability is a goal that needs sustained policy attention and support in the long run. Based on the practical actions from the targeted poverty alleviation policy, relevant policies in the future should pay attention to institutional reform and staff management measures with sufficient time and intensity. At the same time, they should not only focus on the farmers’ livelihoods but also attach great importance to the vulnerability context that is closely related to farmers’ livelihoods, such as the natural environment, socio-economic conditions, and community development.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
Aazami M, Shanazi K. 2020. Tourism wetlands and rural sustainable livelihood: The case from Iran. Journal of Outdoor Recreation and Tourism, 30: 100284. DOI: 10.1016/j.jort.2020.100284.

[2]
Abukari H, Mwalyosi R B. 2020. Local communities’ perceptions about the impact of protected areas on livelihoods and community development. Global Ecology and Conservation, 22: e00909. DOI: 10.1016/j.gecco.2020.e00909.

[3]
Bauer T, de Jong W, Ingram V, et al. 2022. Thriving in turbulent times: Livelihood resilience and vulnerability assessment of Bolivian Indigenous forest households. Land Use Policy, 119: 106146. DOI: 10.1016/j.landusepol.2022.106146.

[4]
Berhanu G, Woldemikael S M, Beyene E G. 2022. The interrelationships of sustainable livelihood capital assets deprivations and asset based social policy interventions: The case of Addis Ababa informal settlement areas, Ethiopia. Research in Globalization, 4: 100081. DOI: 10.1016/j.resglo.2022.100081.

[5]
Dang X, Gao S, Tao R, et al. 2020. Do environmental conservation programs contribute to sustainable livelihoods? Evidence from China’s grain-for-green program in northern Shaanxi Province. Science of the Total Environment, 719: 137436. DOI: 10.1016/j.scitotenv.2020.137436.

[6]
de la Puente S, López de la Lama R, Llerena-Cayo C, et al. 2022. Adoption of sustainable low-impact fishing practices is not enough to secure sustainable livelihoods and social wellbeing in small-scale fishing communities. Marine Policy, 146: 105321. DOI: 10.1016/j.marpol.2022.105321.

[7]
DFID. 1999. Sustainable livelihoods guidance sheets. London, UK: Department for International Development.

[8]
Ding J, Wang Z, Liu Y, et al. 2020. Rural households’ livelihood responses to industry-based poverty alleviation as a sustainable route out of poverty. Regional Sustainability, (1): 68-81.

DOI

[9]
Duan J, Xu Y, Sun X. 2019. Spatial patterns and their changes of grain production, grain consumption and grain security in the Tibetan Plateau. Journal of Natural Resources, 34(4): 673-688.

DOI

[10]
Hajdu F, Granlund S, Neves D, et al. 2020. Cash transfers for sustainable rural livelihoods? Examining the long-term productive effects of the Child Support Grant in South Africa. World Development Perspectives, 19: 100227. DOI: 10.1016/j.wdp.2020.100227.

[11]
Huang J, Neufeld L M, Badiane O, et al. 2022. Equitable livelihoods must underpin food systems transformation. Nature Food, 6: 15-17.

[12]
Kuang F Y, Jin J J, He R, et al. 2019. Influence of livelihood capital on adaptation strategies: Evidence from rural households in Wushen Banner, China. Land Use Policy, 89: 104228. DOI: 10.1016/j.landusepol.2019.104228.

[13]
Lisa C K, Nancy L P, Kimberly M C, et al. 2020. Circular labor migration and land-livelihood dynamics in southeast Asia’s concession landscapes. Journal of Rural Studies, 73: 21-33.

[14]
Liu Z, Lan J. 2015. The sloping land conversion program in China: Effect on the livelihood diversification of rural households. World Development, 70: 147-161.

[15]
Malakar K, Mishra T, Patwardhan A. 2018. Perceptions of multi-stresses impacting livelihoods of marine fishermen. Marine Policy, 97: 18-26.

[16]
Mdee A. Ofori A, Chasukwa M, et al. 2021. Neither sustainable nor inclusive: a political economy of agricultural policy and livelihoods in Malawi, Tanzania and Zambia. Journal of Peasant Studies, 48(6): 1260-1283.

[17]
Natarajan N, Newsham A, Rigg J, et al. 2022. A sustainable livelihoods framework for the 21st century. World Development, 155: 105898. DOI: 10.1016/j.worlddev.2022.105898.

[18]
Paul S, Das T K, Pharung R, et al. 2020. Development of an indicator based composite measure to assess livelihood sustainability of shifting cultivation dependent ethnic minorities in the disadvantageous northeastern region of India. Ecological Indicators, 110: 105934. DOI: 10.1016/j.ecolind.2019.105934.

[19]
Peng W, Robinson B E, Zheng H, et al. 2022. The limits of livelihood diversification and sustainable household well-being, evidence from China. Environmental Development, 43: 100736. DOI: 10.1016/j.envdev.2022.100736.

[20]
Pu G, Chang-Richards A Y. 2022. Livelihood recovery for sustainable development: A study of the Lushan Earthquake. International Journal of Disaster Risk Reduction, 82: 103317. DOI: 10.1016/j.ijdrr.2022.103317.

[21]
Qi W, Liu S, Zhou L. 2020. Regional differentiation of population in Tibetan Plateau: Insight from the ‘Hu Line’. Acta Geographica Sinica, 75(2): 255-267. (in Chinese)

[22]
Rathnayake S, Gray D, Reid J, et al. 2022. The impacts of the COVID-19 shock on sustainability and farmer livelihoods in Sri Lanka. Current Research in Environmental Sustainability, 4: 100131. DOI: 10.1016/j.crsust.2022.100131.

[23]
Richard B, Erin K F, Chris H. 2020. Leveraging existing household survey data to map livelihoods in Nigeria. World Development, 126: 104727. DOI: 10.1016/j.worlddev.2019.104727.

[24]
Rosalien E J, Pita A V, Rene G A B, et al. 2019. Influence of livelihood assets, experienced shocks and perceived risks on smallholder coffee farming practices in Peru. Journal of Environmental Management, 242: 496-506.

DOI PMID

[25]
Sachs J, Kroll C, Lafortune G, et al. 2021. Sustainable development report 2021. Cambridge, UK: Cambridge University Press.

[26]
Sachs J D, Schmidt-Traub G, Mazzucato M, et al. 2019. Six transformations to achieve the sustainable development goals. Nature Sustainability, 2(9): 805-814.

DOI

[27]
Ullah A, Zeb A, Saqib S E, et al. 2022. Landscape co-management and livelihood sustainability: Lessons learned from the billion trees afforestation project in Pakistan. Land Use Policy, 115: 106034. DOI: 10.1016/j.landusepol.2022.106034.

[28]
Ulukan D, Bergkvist G, Lana M, et al. 2022. Combining sustainable livelihood and farm sustainability approaches to identify relevant intensification options: Implications for households with crop-based and gathering-based livelihoods in Tanzania. Ecological Indicators, 144: 109518. DOI: 10.1016/j.ecolind.2022.109518.

[29]
UNESCO. 2022. Sites for sustainable development: Realizing the potential of UNESCO designated sites to advance agenda 2030. http://www.unesco.org.uk. Viewed on 2024-02-20.

[30]
Veh G, Korup O, Walz A. 2020. Hazard from Himalayan glacier lake outburst floods. The Proceedings of the National Academy of Sciences of the USA, 117(2): 907-912.

[31]
Wang C, Zhang Y, Yang Y, et al. 2016. Assessment of sustainable livelihoods of different farmers in hilly red soil erosion areas of southern China. Ecological Indicators, 64: 123-131.

[32]
Wang Y H, Shu Q F. 2021. The policy process and practical experience of the targeted poverty alleviation in China. Journal of Tsinghua University (Philosophy and Social Sciences), 36(1): 141-155, 201. (in Chinese)

[33]
Wekesa C, Mutta D, Larwanou M, et al. 2023. Effects of charcoal ban on value chains and livelihoods in Kenyan coast—Stakeholders’ perceptions. Environmental Development, 45: 100809. DOI: 10.1016/j.envdev.2023.100809.

[34]
Wu Z, Liu T, Xia M, et al. 2021. Sustainable livelihood security in the Poyang Lake Ecological Economic Zone: Identifying spatial-temporal pattern and constraints. Applied Geography, 135: 102553. DOI: 10.1016/j.apgeog.2021.102553.

[35]
Xu W, Jin X, Liu J, et al. 2020. Impact of cultivated land fragmentation on spatial heterogeneity of agricultural agglomeration in China. Journal of Geographical Sciences, 30(10): 1571-1589.

DOI

[36]
Yang L, Liu M C, Lun F, et al. 2019. The impacts of farmers’ livelihood capitals on planting decisions: A case study of Zhagana Agriculture- Forestry-Animal Husbandry Composite System. Land Use Policy, 86: 208-217.

[37]
Zhang J, Mishra A K, Zhu P X. 2019. Identifying livelihood strategies and transitions in rural China: Is land holding an obstacle? Land Use Policy, 80: 107-117.

DOI

Options
Outlines

/

〈 〉