Sensitivity of Rural Households' Livelihood Strategies to Livelihood Capital in Poor Mountainous Areas

sustainability

Article Sensitivity of Rural Households’ Livelihood Strategies to Livelihood Capital in Poor Mountainous Areas: An Empirical Analysis in the Upper Reaches of the Min River, China

Xiaolan Wang 1,*, Li Peng 2 , Dingde Xu 3 and Xuxi Wang 4 1 School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang 621010, China 2 Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China; [email protected] 3 Sichuan Center for Rural Development Research, College of Management of Sichuan Agricultural University, Chengdu 611130, China; [email protected] 4 College of Land and Resource, China West Normal University, Nanchong 637009, China; [email protected] * Correspondence: [email protected]

Received: 2 March 2019; Accepted: 4 April 2019; Published: 12 April 2019

Abstract: Exploring the sensitivity of rural households’ livelihood strategies to livelihood capital is of great significance for improving rural households’ livelihood levels. This paper selects 23 livelihood capital measurement indicators and conducts an in-depth survey of rural households. In addition, the entropy method and a weighted comprehensive model are used to explore the basic characteristics of rural households’ livelihood capital in the upper reaches of the Min River, China, in 2017. Furthermore, econometric models are used to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital. As indicated from the research, the livelihood capital levels of different types of rural households in the study area are not equivalent. The types of rural households with different livelihood strategies can be ordered in terms of quantity as follows: non-agricultural type > non-agricultural dominant type > agricultural dominant type > pure agricultural type. Livelihood strategies have different sensitivities to different livelihood capital measurement indicators. Among these indicators, cash income, the number of relatives and friends available for financial assistance, and the number of civil servants have positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. However, the average age of laborers, area of cultivated land and gardens, number of livestock and poultry, and present value of production tools have negative effects. These evaluation results can provide a scientific decision-making basis for the formulation of poverty alleviation policies by relevant government departments.

Keywords: sensitivity; livelihood capital; livelihood strategies; econometric models; upper reaches of the Min River; China

1. Introduction Livelihood is “a means or way of life” and a way of making a living based on ability, capital, and activity [1]. As the smallest livelihood unit in rural society, rural households bear multiple livelihood risks, such as nature, market, and policies [2]. The sustainability of rural households’ livelihood has a vital impact on the livelihood security of rural households, the sustainable development of rural areas, and even the future trends of rural human-land relationships [3]. Therefore, it is of great theoretical and practical signiﬁcance to explore the sustainability of rural households’ livelihood.

Sustainability 2019, 11, 2193; doi:10.3390/su11082193 www.mdpi.com/journal/sustainability Sustainability 2019, 11, 2193 2 of 16

For a long time, the issue of rural households’ livelihood has been a global focus, especially in developing countries [4–6]. With the deepening of research on livelihood issues conducted by relevant scholars, the sustainable livelihood approach (SLA) has gradually developed in theory and practice [7–10], and the framework for sustainable livelihood analysis proposed by the U.K.’s Department for International Development (DFID) is the most typical. This framework consists of five parts: vulnerability background, livelihood capital, organizational structure and policy system, livelihood strategy, and livelihood status; additionally, it regards rural households as the activity subjects in the vulnerability background and reflects the rural households’ livelihoods from the aspects of livelihood capital, livelihood strategies, and livelihood status [2,11]. Specifically, livelihood capital represents the elements that enhance people’s capacity to engage in different livelihood activities, and it not only plays a major role in making a living but also offers people the opportunity to influence the institutions and structures within which they operate [12,13]. However, livelihood strategies refer to different types of livelihood activities adopted by rural households, and the ability of rural households to implement different livelihood strategies depends on the status of their livelihood capital [14,15]. The framework provides a new research perspective for relevant scholars. On this basis, scholars have discussed and analyzed the structure and spatial characteristics of rural households’ livelihood capital as well as rural households’ livelihood strategy selection [16,17], the impact of livelihood capital and livelihood risk on livelihood strategies [18,19], the influence of climate change, labor migration and returning farmland to forests on rural households’ livelihood capital [20–22], and livelihood risk and sustainability [23–25] from different research scales. For example, Baffoe and Matsuda assessed rural livelihood assets from a gender perspective in Ghana [12]. Masud et al. evaluated community standards of living using the SLA as an analytical framework within the marine park areas (MPAs) in Peninsular Malaysia [17]. Liu et al. and Milad et al. estimated the influence of livelihood assets on livelihood strategies in the western mountainous area of China and the Hara Biosphere Reserve of Iran [18,19]. Sagynbekova examined the links among the environment, rural livelihoods, and labor migration in central Kyrgyzstan [21]. However, few studies have focused on the sensitivity of rural households’ livelihood strategies to livelihood capital. With the rapid development of urbanization, numerous surplus rural laborers have selected migrant work, and the proportions of non-agricultural laborers and part-time laborers among the total laborers in rural households are increasing, while the proportion of pure agricultural laborers is decreasing, which results in the differentiation of rural households. Corresponding to the differentiation process of rural households is the continuous adjustment of rural households’ livelihood capital structure and livelihood strategies; thus, the sensitivity of livelihood strategies to various types of livelihood capital is also continuously changing. As China’s largest Qiang population area, the upper reaches of the Min River is considered to be key to the socioeconomic development and national unity of Sichuan Province. Furthermore, this area is an ecological barrier of the upper reaches of the Yangtze River and an important water source for the Chengdu Plain. Due to the influence of the natural environment, socioeconomic development level, and other factors, China’s concentrated contiguous poverty-stricken areas, including the upper reaches of the Min River, have been trapped in a “poverty trap” for a long time [26,27]. In 2015, the Central Poverty Alleviation and Development Working Conference clearly stated that “China will achieve the goal of poverty alleviation for the rural poor and regional overall poverty alleviation under the current standards by 2020”; among these areas, 14 concentrated contiguous poverty-stricken areas identified by the Chinese government are the important areas for regional poverty alleviation [28]. “The Plan for Rural Revitalization Strategy in China (2018–2022)” has noted that it is necessary to take precise poverty alleviation as the priority task for the implementation of rural revitalization strategy to promote the organic integration and mutual promotion of poverty alleviation and rural revitalization. In the current critical period of poverty alleviation, it is of great practical significance to explore the sensitivity of rural households’ livelihood strategies to livelihood capital in the upper reaches of the Min River, China, from the perspective of livelihood and propose targeted policies of rural households’ SustainabilitySustainability 20192019,, 1111,, 2193x FOR PEER REVIEW 33 ofof 1615

and propose targeted policies of rural households’ livelihood sustainability to achieve the goal of livelihoodregional poverty sustainability alleviation to achieveand rural the re goalvitalization of regional strategy poverty in the alleviation region. and rural revitalization strategyBased in theon the region. above analysis, this paper takes the upper reaches of the Min River as the research area.Based First, onthe the basic above characteristics analysis, this of paper rural takeshouseholds’ the upper livelihood reaches ofcapital the Min in 2017 River are as theanalyzed research in area.accordance First, thewith basic the microsurvey characteristics data of of rural rural households’ households. livelihood Moreover, capital econometric in 2017 models are analyzed are used in accordanceto explore the with sensitivity the microsurvey of different data oftypes rural of households. rural households’ Moreover, livelihood econometric strategies models to arelivelihood used to explorecapital. theThe sensitivity analysis ofresults different can typesprovide of rural the households’scientific decision-making livelihood strategies basis tofor livelihood the sustainable capital. Thedevelopment analysis results of rural can households provide the in scientific the upper decision-making reaches of Min basis River, for theChina, sustainable and the development formulation of ruralpoverty households alleviation in policies the upper by reaches relevant of government Min River, China, departments. and the formulation of poverty alleviation policies by relevant government departments. 2. Overview of the Research Area 2. Overview of the Research Area Located in Sichuan Province, the upper reaches of the Min River (31°26′–33°16′ N, 102°59′– 104°14Located′ E) represent in Sichuan the Province, transitional the upperzone between reaches of th thee Qinghai-Tibet Min River (31◦ Plateau260–33◦16 and0 N, the 102 Sichuan◦590–104 ◦Basin.140 E) representWith a basin the transitionalarea of approximately zone between 22,000 the Qinghai-Tibet km2, this region Plateau coincides and the with Sichuan the administrative Basin. With a 2 basinjurisdictions area of of approximately Li County, Mao 22,000 County, km , Wenchua this regionn County, coincides Songpan with the County, administrative and Heishui jurisdictions County of LiTibetan County, Qiang Mao Autonomous County, Wenchuan Prefecture County, of SongpanNgawa in County, Sichuan and Province Heishui (Figure County 1). of TibetanMainly Qianginhabited Autonomous by Tibetan, Prefecture Qiang, of Ngawaand Hui in Sichuanethnic Provinceminorities, (Figure this1 ).region Mainly is inhabited a poverty-stricken by Tibetan, Qiang,mountainous and Hui area ethnic with minorities, a relati thisvely region backward is a poverty-stricken economy, and mountainous it belongs areato the with scope a relatively of 14 backwardconcentrated economy, contiguous and it belongspoverty-stricken to the scope areas of 14stipulated concentrated in “The contiguous Outline poverty-stricken for Rural Poverty areas stipulatedAlleviation in and “The Development Outline for Ruralin China Poverty (2011–2020)” Alleviation [29]. and Development in China (2011–2020)” [29]. InIn recentrecent years, years, various various poverty poverty alleviation alleviation projects projects have have been been vigorously vigorously promoted promoted in the upperin the reachesupper reaches of the Minof the River, Min China,River, China, and farmers’ and farmer livess’ have lives been have greatly been greatly improved; improved; however, however, many ruralmany people rural people are still are in still poverty. in poverty. According According to statistics, to statistics, in 2017, in the 2017, resident the resident population population of the upperof the reachesupper reaches of the Min of the River, Min China, River, was China, 398,200, was including 398,200, approximatelyincluding approximately 137,500 agricultural 137,500 populationsagricultural andpopulations approximately and approximately 14,100 absolutely 14,100 poverty-stricken absolutely poverty-stricken populations; furthermore,populations; furthermore, the poverty ratethe reachedpoverty 3.54%,rate reached which 3.54%, was 0.44 which percentage was 0.44 points percentage higher points than thehigher national than povertythe national rate poverty in the same rate yearin the [30 same]. According year [30]. to theAccording grouping to of the per grouping capita disposable of per capita income disposable of cities and income counties of incities Sichuan and Provincecounties inin 2017Sichuan (which Province can be divided in 2017 into (which four groups, can be namely, divided the into high-income four groups, group, namely, middle andthe high-income group,group, middle middle and and low-income high-income group, group, and low-income middle and group), low-income the five counties group, in and the upperlow-income reaches group), of the the Min five River, counties China, in belonged the upper to reaches the low-income of the Min group River, (Heishui China, County) belonged and to the middlelow-income and low-incomegroup (Heishui group County) (the other and four the counties), middle andand the low-income per capita disposablegroup (theincome other wasfour onlycounties), 10,766 and yuan the/year. per capita In the disposable same year, income the per was capita only disposable 10,766 yuan/year. incomeof In Chinese the same residents year, the was per 25,974capita yuandisposable/year. income of Chinese residents was 25,974 yuan/year.

Figure 1. The location map of the upper reachesreaches of the Min River, China.China.

Sustainability 2019, 11, 2193 4 of 16

3. Data Sources and Research Methods

3.1. Data Sources In this paper, Wenchuan County and Heishui County were selected from the middle and low-income group and the low-income group, respectively, as the sample counties according to the grouping of the per capita disposable income of cities and counties in Sichuan Province in 2017. Then, three townships with high, medium, and low economic levels were selected from each sample county as the sample townships. Finally, administrative villages with high, medium, and low economic levels were selected from each sample township as the sample villages, and 30 rural households were selected as the sample rural households through the random sampling method in each sample village. On this basis, a questionnaire survey and semistructured interviews were used to conduct an in-depth survey of rural households. Questionnaires and interviews mainly included the basic situation of family members, livelihood capital, and livelihood activities of rural households. The formal survey was carried out in January 2018. A total of 406 questionnaires were distributed, and 395 valid questionnaires were collected; thus, the valid rate was 97.29%. The distribution of sample villages and the number of valid questionnaires are detailed in Table1.

Table 1. The distribution of sample villages and the number of valid questionnaires.

Number of Valid Sample County Sample Township Sample Village Questionnaires Shashiduo Yangrong, Jiazu 52 Heishui Zhawo Kebie, Ruoduo 49 Seergu Seergu 38 Shuimo Laoren, Xianfengyan, Chenjiashan 80 Wenchuan Miansi Sanguanmiao, Lianghe, Gaodian 90 Yanmen Koushan, Qingpo, Tongshan 86

3.2. Selection of Livelihood Capital Measurement Indicators According to the way of classifying rural households’ livelihood capital in the framework for sustainable livelihood analysis proposed by the DFID and referring to the existing research on the quantification of rural households’ livelihood capital [12,18–21,31–34], this paper divides rural households’ livelihood capital into five types—human capital, natural capital, physical capital, financial capital, and social capital—and 23 specific rural household livelihood capital measurement indicators were selected (Table2). Human capital mainly includes an individual’s health condition, knowledge, and skills, and the lack of human capital is an important factor that leads to poverty among rural households. Based on the survey data, in this paper, human capital is quantified by seven indicators: age of household head, education level of household head, number of laborers, average age of laborers, health status of laborers, education level of laborers, and vocational skills of laborers. Natural capital refers to the land, water, and other natural resources used by rural households to survive. In this paper, two indicators, namely, cultivated land area and garden plot area, were selected to characterize the natural capital of rural households. Physical capital refers to the infrastructure and material equipment needed by rural households to maintain their livelihoods. In this paper, six indicators, namely, number of livestock and poultry, quality of housing, present value of housing, present value of production tools, present value of vehicles, and present value of durable goods, were selected to measure the physical capital of rural households. Financial capital refers to the disposable and financing cash of rural households. In this paper, five indicators, namely, cash income, opportunity to borrow, loans, usurious loans, and donations, were selected to measure the financial capital of rural households. Social capital refers to the social resources used by rural households in pursuit of livelihood goals. In this paper, three indicators, namely, number of relatives and friends providing employment Sustainability 2019, 11, 2193 5 of 16 opportunities, number of relatives and friends providing financial assistance, and number of civil servants, were selected to characterize the social capital of rural households.

Table 2. Rural households’ livelihood capital measurement indicators and the assignments and weight values.

Types of Capital Measurement Indicators Assignments Weight Values Actual age of household head of rural households Age of household head 0.0547 (years) Illiteracy = 0, Primary school = 0.25, Junior middle Education level of household Human capital (HC) school = 0.5, Senior middle school = 0.75, Technical 0.0897 head secondary school and above = 1. Number of family members aged 16–64, excluding Number of laborers students in school and family members who are 0.0653 incapacitated to work Average age of laborers Average age of all laborers in a household (years) 0.0708 Average health status of all laborers in a household: Health status of laborers 1 = Very poor, 2 = Poor, 3 = Average, 4 = Good, 0.0939 5 = Very good Education level of laborers Mean value of education level of all laborers 0.0922 Total number of laborers with certain vocational Vocational skills of laborers 0.0482 skills in a household Cultivated land area Per capita cultivated land area (hm2/person) 0.0624 Natural capital (NC) Garden plot area Per capita garden plot area (hm2/person) 0.0732 Cattle (horses) = 1, Sheep = 0.8, Pigs = 0.5, Chickens Number of livestock and poultry 0.0031 (rabbits, ducks) = 0.2, Bees = 0.1 Keekwilee-house = 0.1, Civil house = 0.2, Wood Physical capital (PC) house (brick and wood house, stone and wood Quality of housing 0.0376 house) = 0.4, Stone house (brick and tile house) = 0.7, Reinforced concrete house = 1 Sum of the present value of all housing in a Present value of housing 0.0169 household (10,000 Yuan a) Present value of production Sum of the present value of all production tools in a 0.0117 tools household (10,000 Yuan a) Sum of the present value of all vehicles in a Present value of vehicles 0.0025 household (10,000 Yuan a) Sum of the present value of all durable goods in a Present value of durable goods 0.0061 household (10,000 Yuan a) Cash income Per capita annual cash income (10,000 Yuan a/person) 0.0078 Whether rural households borrow money from Opportunity of obtaining relatives and friends 0.0264 borrowing Financial capital (FC) No = 0, Yes = 1 Whether rural households borrow money from Opportunity of obtaining loans banks and credit cooperatives 0.0313 No = 0, Yes = 1 Opportunity of obtaining Whether rural households have usurious loans 0.0441 usurious loans No = 0, Yes = 1 Whether rural households receive donations or Opportunity of obtaining remittances 0.0985 donations No = 0, Yes = 1 Number of relatives and friends Number of relatives and friends available for providing employment assistance when seeking migrant working 0.048 Social capital (SC) opportunities opportunities Number of relatives and friends Number of relatives and friends available for 0.0077 providing ﬁnancial assistance assistance when in urgent need of a lot of money Number of civil servants Number of civil servants in a clan 0.0079 Note: a During the study period, 1 U.S. dollar was equal to 6.62 Chinese Yuan. Sustainability 2019, 11, 2193 6 of 16

3.3. Division of the Types of Rural Households Based on previous research results on the division of rural household types and the actual situation of the research area [35–37], according to the proportion of non-agricultural income among total household income, this paper divides rural households into four types: pure agricultural rural households, agricultural dominant rural households, non-agricultural dominant rural households, and non-agricultural rural households. Speciﬁcally, pure agricultural rural households refer to rural households without non-agricultural income, agricultural dominant rural households refer to rural households whose non-agricultural income accounts for 0–50% of total household income, non-agricultural dominant rural households represent rural households whose non-agricultural income accounts for 50–90% (including 50% and 90%) of total household income, and non-agricultural rural households denote rural households whose non-agricultural income accounts for more than 90% of total household income. An analysis of valid questionnaires showed that in the research area, there were 255 non-agricultural rural households, 61 non-agricultural dominant rural households, 58 agricultural dominant rural households, and 21 pure agricultural rural households, which accounted for 64.56%, 15.44%, 14.68%, and 5.32% of households, respectively.

3.4. Research Methods

3.4.1. The Entropy Method and the Weighted Comprehensive Model The entropy method is an objective weighting method. Compared with the analytic hierarchy process (AHP) and other subjective weighting methods, the entropy method avoids interference from human factors and the obtained weight value of the indicator has a higher reliability and accuracy [38]. Thus, this paper uses the entropy method to determine the weight value of each livelihood capital measurement indicator. The calculation process is shown in Equations (1)–(5) and implemented in MATLAB 7.0 software (MathWorks, Inc., Natick, MA, USA). The calculation results are detailed in Table2. O1 Data are standardized as follows: " # Fij min(Fij) X = − 100% (1) ij max(F ) min(F ) × ij − ij where Fij refers to the original value of the j-th indicator of the i-th rural household, Xij indicates the standardized value of Fij, and max(Fij) and min(Fij) refer to the maximum and minimum values of the j-th indicator of all rural households, respectively (i = 1, 2, ... , 395; j = 1, 2, ... , 23). O2 The proportion Pij of the i-th rural household under the j-th indicator is calculated as follows:

X395 Pij = Xij/ Xij (2) i=1

O3 The entropy Ej of the j-th indicator is calculated as follows:

395 1 X E = (P ln P ) (3) j −ln 395 ij × ij i=1

O4 The utility value Dj of the j-th indicator is calculated as follows:

D = 1 E (4) j − j Sustainability 2019, 11, 2193 7 of 16

O5 The weight value wj of the j-th indicator is calculated as follows:

X23 wj = Dj/ Dj (5) j=1

The weight value of each measurement indicator is determined and combined with the standardized indicator data to develop the weighted comprehensive model, which is used to calculate the indexes of the ﬁve types of livelihood capital of rural households and the total index of the livelihood capital of diﬀerent types of rural households [39]. The details are shown in Equation (6).

X5 Xm LCI = wjXij (6) k=1 j=1 where LCI represents the total index of livelihood capital, with a higher value corresponding to a higher rural household livelihood capital, and wj and Xij denote the weight value and standardized value of the j-th indicator (k = 1, 2, ... , 5; m = 1, 2, ... , 7), respectively.

3.4.2. The Ordinal Logistic Regression Model Rural households’ livelihood strategies are an ordered multi-classified variable; hence, in this paper, the ordinal logistic regression model is constructed to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital [40]. The independent variables of the model are the livelihood capital measurement indicators, and the dependent variable of the model is the rural households’ livelihood strategies. The process is implemented in SPSS 18.0 software (IBM Corporation, Armonk, NY, USA). The specific model is presented in Equation (7): p ln( ) =α + β X + β X + + β X (7) 1 p 1 i1 2 i2 ··· j ij − where p refers to the probability of the occurrence of livelihood strategies, α indicates the intercept term, and βj indicates the regression coefficient. p Assuming Ω = 1 p , Ω stands for the occurrence ratio: −

p α+β X +β X + +β X Ω = = e 1 i1 2 i2 ··· j ij (8) 1 p −

When Xij increases by one unit, Ω will increase or decrease by exp(βj) units. Therefore, in this paper, exp(βj) is used to represent the degree of the sensitivity of rural households’ livelihood strategies to livelihood capital measurement indicators.

4. Results

4.1. Statistical Characteristics of Livelihood Capital Measurement Indicators The descriptive statistical analysis of the data was conducted in SPSS 18.0 software, and the mean value and standard deviation (SD) of each livelihood capital measurement indicator for the diﬀerent types of rural households were obtained (Table3). Sustainability 2019, 11, 2193 8 of 16

Table 3. Statistical characteristics of livelihood capital measurement indicators.

Pure Agricultural Agricultural Dominant Non-Agricultural Non-Agricultural Total Sample Total Sample Type Measurement Indicators Type (n = 21) Type (n = 58) Dominant Type (n = 61) Type (n = 255) (n = 395) (n = 395) Age of household head 51.67 10.99 49.72 13.35 47.69 12.20 48.61 13.28 48.71 13.00 81.00 19.00 ± ± ± ± ± ± Education level of household head 0.29 0.30 0.40 0.23 0.34 0.23 0.33 0.24 0.34 0.24 1.00 0.00 ± ± ± ± ± ± Number of laborers 3.00 1.65 2.96 1.66 3.40 1.58 2.96 1.74 3.05 1.69 8.00 0.00 ± ± ± ± ± ± HC Average age of laborers 29.73 23.80 32.23 18.96 37.74 11.50 34.73 13.97 34.76 14.92 63.50 0.00 ± ± ± ± ± ± Health status of laborers 2.58 2.02 2.91 1.70 3.62 1.06 3.47 1.38 3.38 1.42 5.00 0.00 ± ± ± ± ± ± Education level of laborers 0.25 0.24 0.32 0.27 0.37 0.22 0.35 0.24 0.34 0.24 1.00 0.00 ± ± ± ± ± ± Vocational skills of laborers 0.08 0.29 0.33 0.86 0.36 0.60 0.24 0.53 0.28 0.61 4.00 0.00 ± ± ± ± ± ± Cultivated land area 0.06 0.03 0.08 0.06 0.06 0.05 0.05 0.06 0.06 0.06 0.33 0.00 NC ± ± ± ± ± ± Garden plot area 0.02 0.03 0.04 0.05 0.03 0.04 0.01 0.03 0.02 0.04 0.20 0.00 ± ± ± ± ± ± Number of livestock and poultry 14.07 23.99 2.66 5.37 6.72 22.41 2.23 7.90 3.57 12.86 180.00 0.00 ± ± ± ± ± ± Quality of housing 0.73 0.20 0.76 0.18 0.73 0.16 0.72 0.19 0.73 0.18 1.00 0.10 ± ± ± ± ± ± Present value of housing 21.33 30.27 18.48 17.76 25.99 36.25 28.18 32.52 25.88 31.40 300.00 0.20 PC ± ± ± ± ± ± Present value of production tools 0.32 0.62 0.43 0.87 0.95 3.09 0.62 4.24 0.64 3.58 60.00 0.00 ± ± ± ± ± ± Present value of vehicles 1.46 3.73 4.92 8.05 2.84 5.42 2.60 9.31 3.01 8.34 120.00 0.00 ± ± ± ± ± ± Present value of durable goods 0.71 0.64 0.87 1.05 0.79 0.76 0.79 1.15 0.80 1.05 13.08 0.00 ± ± ± ± ± ± Cash income 0.34 0.38 1.25 1.20 1.08 0.94 1.06 1.11 1.08 1.09 8.27 2.42 ± ± ± ± ± ± Opportunity of obtaining borrowing 0.33 0.49 0.31 0.47 0.44 0.50 0.34 0.48 0.36 0.48 1.00 0.00 ± ± ± ± ± ± FC Opportunity of obtaining loans 0.33 0.49 0.16 0.37 0.33 0.47 0.17 0.38 0.21 0.41 1.00 0.00 ± ± ± ± ± ± Opportunity of obtaining usurious loans 0.00 0.00 0.00 0.00 0.04 0.19 0.03 0.16 0.02 0.15 1.00 0.00 ± ± ± ± ± ± Opportunity of obtaining donations 0.08 0.29 0.00 0.00 0.04 0.19 0.06 0.24 0.05 0.21 1.00 0.00 ± ± ± ± ± ± Number of relatives and friends 1.92 2.71 3.90 6.27 4.26 6.02 3.59 6.33 3.73 6.17 40.00 0.00 providing employment opportunities ± ± ± ± ± ± SC Number of relatives and friends 3.08 2.11 7.60 16.90 4.85 5.24 3.74 4.21 4.60 8.13 100.00 0.00 providing ﬁnancial assistance ± ± ± ± ± ± Number of civil servants 0.33 0.49 0.69 1.18 1.34 3.00 0.75 1.42 0.85 1.82 22.00 0.00 ± ± ± ± ± ± Note: The results in lines 3–7 in the table are the mean value standard deviation, and the results in line 8 in the table are the maximum value minimum value. ± ± Sustainability 2019, 11, 2193 9 of 16

Table3 shows that in terms of human capital, and regardless of the total sample or rural households with different livelihood strategies, the household heads were mainly middle-aged and the mean age of household heads of pure agricultural rural households was the highest; in contrast, the mean age of household heads of other types of rural households differed little from that of the total sample. The education level of household heads was mostly primary school. The mean number of laborers in a household was approximately 3. The laborers were generally young and presented an average health status, and the education level was mostly primary school, with a very small proportion of laborers with vocational skills (approximately 9%). With regard to natural capital, the per capita cultivated land area and per capita garden plot area of rural households were very small (0.06 hm2/person and 0.02 hm2/person, respectively), and these values were much smaller than the per capita cultivated land area of China in 2017 (0.10 hm2/person). Concerning physical capital, the mean number of livestock and poultry in the total sample was 3.57, and the mean value of the pure agricultural sample was the largest (14.07), which was much larger than the overall mean value, although they generally belonged to small-scale poultry raising operations. In addition, housing mainly consisted of stone houses and brick-and-tile houses, and the mean present value of housing was 258,800 yuan. The mean value of the agricultural dominant type was the lowest, while that of the non-agricultural type was the highest. Regarding financial capital, the mean per capita annual cash income in the total sample was 10,800 yuan, and that of the pure agricultural type was the smallest (only 3400 yuan), while that of the agricultural dominant type was the largest (12,500 yuan). Moreover, approximately 36% of rural households borrowed money from relatives and friends, 21% of rural households borrow money from banks and credit cooperatives, and only 2% and 5% of rural households had usurious loans and receive donations, respectively. Specifically, pure agricultural rural households did not have usurious loans, while agricultural dominant rural households neither had usurious loans nor received donations. With regard to social capital, in the total sample, the mean number of relatives and friends available for assistance when seeking migrant working opportunities was 3.73, the mean number of relatives and friends available for assistance when in urgent need of considerable funds was 4.6, and the mean number of civil servants in a clan was 0.85. Of these values, the mean values of all three indicators were smallest for pure agricultural rural households.

4.2. Analysis of Rural Households’ Livelihood Capital In this paper, the weighted comprehensive model was used to calculate the indexes of the ﬁve types of livelihood capital and the total index of livelihood capital for diﬀerent types of rural households. The calculation results are shown in Table4.

Table 4. Livelihood capital indexes of diﬀerent types of rural households.

Types of Rural Households HC Index NC Index PC Index FC Index SC Index LCI Pure agricultural type 0.1024 0.0078 0.0173 0.1068 0.0015 0.2359 Agricultural dominant type 0.1340 0.0180 0.0152 0.1125 0.0036 0.2833 Non-agricultural dominant type 0.1381 0.0153 0.0175 0.1731 0.0039 0.3480 Non-agricultural type 0.1354 0.0074 0.0171 0.1216 0.0029 0.2845 Total sample 0.1341 0.0106 0.0173 0.1277 0.0031 0.2928

Table4 shows that among the di fferent types of rural households, non-agricultural dominant rural households had the highest level of livelihood capital, and they were followed by non-agricultural rural households and agricultural dominant rural households; in contrast, pure agricultural rural households had the lowest level of livelihood capital. From the perspective of the types of livelihood capital, regardless of the type of livelihood strategy adopted, there were great differences in the levels of five types of livelihood capital among rural households. The levels of human capital and financial capital were relatively high (accounting for 40–48% and 40–50% of the total livelihood capital level, respectively), followed by the levels of physical capital and natural capital (accounting for approximately 6% and 4%, respectively), and the level of social capital was the lowest (accounting for Sustainability 2019, 11, 2193 10 of 16 only 1%). The level of human capital was relatively high because there were several young laborers in rural households, whereas the education level of laborers was not high, and laborers with vocational skills were scarce. In recent years, rural households had gradually participated in different types of non-agricultural livelihood activities, and their incomes had increased; thus, the level of financial capital was relatively high. With the increase in income, rural households had higher quality of life requirements, and they also had the ability to buy or build better-quality houses and other durable goods; thus, the level of physical capital had improved to some extent. However, due to the influence of the policy of returning farmland to forests (a policy that requires ceasing cultivation of land with serious soil erosion, serious salinization and low grain yield in a planned way as well as carrying out afforestation, grass planting, and vegetation restoration in accordance with local conditions to protect and improve the ecological environment), rural households had few land resources. The social capital of rural households was mainly the social network of kinship or geography, which provided limited support for resisting risks to livelihood and improving livelihood activities.

4.3. Analysis on Rural Households’ Livelihood Strategies Using the survey data, the main livelihood activities of the diﬀerent types of rural households were counted. The statistical results are shown in Table5.

Table 5. The main livelihood activities of the diﬀerent types of rural households.

Livelihood Activities Types of Rural Households Self-Employed Planting Poultry Raising Migrant Work Wage Work Business Pure agricultural type + + Agricultural dominant type + + + + Non-agricultural dominant type + + + + + Non-agricultural type + + + + + Note: + indicates that rural households have adopted this type of livelihood activity.

As shown in Table5, the livelihood activities of pure agricultural rural households included fruit planting and poultry raising. The survey showed that these rural households depended on planting plums, cherries, and other economic crops, as well as raising chickens, pigs, sheep, and other livestock and poultry as the entire source of household income. These rural households’ livelihood activities were relatively simple, and the economic income was easily aﬀected by climate, product market price, and other factors; thus, the livelihood risks were relatively high. Agricultural dominant rural households mainly relied on planting plums, cherries, and red dates, as well as raising a few pigs as the main source of economic income. In addition, these rural households took migrant work and self-employed businesses as supplementary sources of household income. Non-agricultural-dominant rural households and non-agricultural rural households mainly depended on migrant work, self-employed businesses, and wage work to maintain their household livelihoods, and the proportion of the income from fruit planting and poultry raising was small or zero. Migrant workers were mainly employed as agricultural helpers, construction workers, and food and beverage waiters (or chefs), and migrant work included work in residential areas and trans-provincial work. Self-employed businesses mainly included running farmhouses, running small shops, and taking advantage of their location to provide water to passing vehicles (i.e., selling water). In general, except for pure agricultural rural households, the livelihood activities of agricultural-dominant rural households, non-agricultural dominant rural households, and non-agricultural rural households included both agricultural livelihood activities and non-agricultural livelihood activities. Therefore, these three types of rural households had both agricultural income and diﬀerent types of non-agricultural income, and compared with pure agricultural rural households, their livelihood risks were relatively low. Sustainability 2019, 11, 2193 11 of 16

4.4. Analysis of the Sensitivity of Livelihood Strategies to Livelihood Capital Based on the analysis of rural households’ livelihood capital and livelihood strategies, and according to Equation (7), ordinal logistic regression analysis was conducted in SPSS 18.0 software to obtain various livelihood capital indicators that had significant impacts on the livelihood strategies of different types of rural households. The overall likelihood ratio test of the regression model was significant at the level of 0.001, indicating that the model was meaningful overall. The regression results are detailed in Table6. According to the regression results, eight indicators, i.e., average age of laborers in human capital, cultivated land area and garden plot area in natural capital, number of livestock and poultry and present value of production tools in physical capital, cash income in financial capital, and number of relativesSustainability and 2019 friends, 11, x FOR providing PEER REVIEW financial assistance, and number of civil servants in social11 of capital, 15 had a remarkable influence on the livelihood strategy selection of non-agricultural dominant rural householdsAfter and the non-agricultural indicators that have rural a households.significant impact on the selection of livelihood strategies are obtained, the degree to which these indicators influence livelihood strategies, namely, the degree of After the indicators that have a significant impact on the selection of livelihood strategies are sensitivity of these livelihood strategies to the eight indicators, must be determined. Thus, based on obtained, the degree to which these indicators influence livelihood strategies, namely, the degree of Equation (8), this paper measured the degree of sensitivity of Ω, the occurrence ratio of livelihood sensitivitystrategies, of these to the livelihood above indicators. strategies The tome theasurement eight indicators, results are shown must bein Figure determined. 2. Thus, based on Equation (8), this paper measured the degree of sensitivity of Ω, the occurrence ratio of livelihood strategies, toTable the 6. above Ordinal indicators. logistic regression The measurement analysis results of results livelihood are capital shown and in livelihood Figure2 .strategies.

Types of Measurement Indicators β SD Exp (β) TableCapital 6. Ordinal logistic regression analysis results of livelihood capital and livelihood strategies. HC Average age of laborers −0.016 ** 0.008 0.984 Types of Capital Measurement Indicators β SD Exp (β) Cultivated land area −4.607 ** 2.033 0.010 HCNC Average age of laborers 0.016 ** 0.008 0.984 Garden plot area −0.317 * − 0.045 0.728 Cultivated land area 4.607 ** 2.033 0.010 NC Number of livestock and poultry −0.110 *** − 0.026 0.896 PC Garden plot area 0.317 * 0.045 0.728 Present value of production tools −0.130 *** − 0.030 0.878 Number of livestock and poultry 0.110 *** 0.026 0.896 PC − FC CashPresent income value of production tools 0.381 *** 0.130 0.068 *** 0.030 1.464 0.878 Number of relatives and friends − FC Cash income0.086 *** 0.381 0.032 *** 0.068 1.090 1.464 SC Numberproviding of relatives financial and friendsassistance providing ﬁnancial assistance 0.086 *** 0.032 1.090 SC Number ofNumber civil servants of civil servants 0.055 ** 0.055 0.027 ** 0.027 1.057 1.057 Note:Note: The model The model used pure used agricultural pure agricult ruralural households rural households as the reference as the refe group,rence and group, *, **, andand ****, **, represent and *** that it was signiﬁcantrepresentat that the it 0.1, was 0.05, significant and 0.01 at levels, the 0.1, respectively. 0.05, and 0.01 levels, respectively.

FigureFigure 2. The 2. sensitivityThe sensitivity of non-agriculturalof non-agricultural dominant dominant rural households’ households’ and and non-agricultural non-agricultural rural rural households’households’ livelihood livelihood strategies strategies to to livelihood livelihood capital capital indicators.

As shown in Table 6 and Figure 2, among the eight indicators that had a remarkable influence on the livelihood strategy selection of non-agricultural-dominant rural households and non-agricultural rural households, three indicators—cash income, number of relatives and friends providing financial assistance, and number of civil servants—had a positive effect, and with every one unit increase in each indicator, the occurrence rates of selection of non-agricultural dominant or non-agricultural livelihood strategies by rural households increased by 1.464, 1.090, and 1.057 times, respectively. However, the other five indicators, namely, the average age of laborers, cultivated land area, garden plot area, number of livestock and poultry, and present value of production tools, had a negative effect; with every one unit increase in each indicator, the occurrence ratios of the Sustainability 2019, 11, 2193 12 of 16

As shown in Table6 and Figure2, among the eight indicators that had a remarkable influence on the livelihood strategy selection of non-agricultural-dominant rural households and non-agricultural rural households, three indicators—cash income, number of relatives and friends providing financial assistance, and number of civil servants—had a positive effect, and with every one unit increase in each indicator, the occurrence rates of selection of non-agricultural dominant or non-agricultural livelihood strategies by rural households increased by 1.464, 1.090, and 1.057 times, respectively. However, the other five indicators, namely, the average age of laborers, cultivated land area, garden plot area, number of livestock and poultry, and present value of production tools, had a negative effect; with every one unit increase in each indicator, the occurrence ratios of the non-agricultural dominant or non-agricultural livelihood strategy selected by rural households decreased by 0.984, 0.010, 0.728, 0.896, and 0.878 times, respectively. Due to the age limitation inherent in migrant working and other non-agricultural livelihood activities, older laborers are more inclined to select pure agricultural or agricultural-dominant livelihood strategies. If natural capital and physical capital are more abundant, then rural households will be less likely to select non-agricultural dominant or non-agricultural livelihood strategies. Cash income provides the conditions and possibilities for rural households to engage in non-agricultural livelihood activities; thus, if there is more cash income, rural households will be more likely to select non-agricultural dominant or non-agricultural livelihood strategies. If social capital is more abundant, rural households will have more opportunities and ways to obtain information about non-agricultural livelihood activities; thus, they will be more likely to select non-agricultural dominant or non-agricultural livelihood strategies.

5. Discussion and Conclusions This paper used the entropy method and the weighted comprehensive model to measure rural households’ livelihood capital level in the upper reaches of the Min River, China, in 2017. In addition, with the help of econometric models, the sensitivity of rural households’ livelihood strategies to livelihood capital was analyzed in the research area. The results showed that the livelihood capital levels of different types of rural households in the upper reaches of the Min River in 2017 were not equivalent and were ordered as follows: non-agricultural dominant type > non-agricultural type > agricultural dominant type > pure agricultural type. In addition, there were significant differences in the levels of the five types of livelihood capital of rural households. The levels of human capital and financial capital were relatively high, the levels of physical capital and natural capital were moderate, and the level of social capital was the lowest; these findings are inconsistent with the findings of other scholars [12,34]. According to the survey, rural households in the upper reaches of the Min River mainly adopted four types of livelihood strategies in 2017, namely, the pure agricultural type, agricultural dominant type, non-agricultural dominant type, and non-agricultural type. Among them, the number of non-agricultural rural households was the highest and the number of pure agricultural rural households was the lowest. According to the analysis of the sensitivity of livelihood strategies to livelihood capital, rural households’ livelihood strategies had different sensitivities to various livelihood measurement indicators, which were consistent with the findings from other scholars [13,39,41,42]. Specifically, three indicators, namely, cash income, number of relatives and friends providing financial assistance, and number of civil servants, had marked positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households, while five indicators, namely, average age of laborers, cultivated land area, garden plot area, number of livestock and poultry, and present value of production tools, had noticeable negative effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. The analysis of the livelihood capital levels of rural households revealed that the education level of laborers was relatively low as a whole, and the proportion of laborers with vocational skills was very Sustainability 2019, 11, 2193 13 of 16 small. This phenomenon led to a considerable surplus of low-cultural quality, unskilled or low-skilled laborers, as well as a serious shortage of the high-quality and skilled laborers required by the emerging technology industries, resulting in difficulties in urban recruitment and rural surplus labor force employment. In the new era of national poverty alleviation and urbanization development, it is necessary to gradually improve the quality of education, increase the intensity of farmers’ agricultural and non-agricultural training and enhance their vocational skills through governmental efforts to increase the economic income of rural households and achieve the goal of precise poverty alleviation and new urbanization. In addition, rural households should be encouraged to develop various professional cooperative economic organizations based on kinship, geography, and careers to improve the levels of financial capital and social capital of rural households and enhance the ability of rural households to collectively resist external risks. The analysis of livelihood strategies revealed that livelihood diversification was a common phenomenon among rural households in the study area and that households were rarely dependent on one source of livelihood for a living, and these results were consistent with the findings of other scholars [43]. This diversification occurred mainly because of the release of a large number of laborers from agriculture and forestry land after the implementation of the policy of returning farmland to forestry in the upper reaches of the Min River, China; thus, to maintain their livelihoods, these laborers had to seek new means of survival. At the same time, the rapid development of new urbanization in China provided employment opportunities and jobs for the rural surplus labor force. Hence, many laborers released from agriculture and forestry land have selected migrant working and other non-agricultural livelihood strategies. The underlying motive for livelihood diversification among the rural households was to provide safety nets for individual families and to smooth consumption. Livelihood diversification is crucial for reducing vulnerability and building sustainable livelihood for rural households. A diversified household stands a better chance of surviving than an undiversified one, such as during exposure to major climatic events [43–45]. Pure agricultural rural households and agricultural dominant rural households mainly obtained economic income by planting fruits and raising a small amount of poultry. Fruit planting in the region has begun to take shape, although the degree of industrialization is low. Local government departments should rely on existing tourism resources to expand the sales channels for fruits, and the industrialization management of fruits should be gradually achieved by increasing capital investment and other measures. Non-agricultural dominant rural households and non-agricultural rural households mainly depended on migrant work, self-employed businesses, wage work, and other non-agricultural livelihood activities to maintain their household livelihoods. However, migrant workers were mainly engaged in manual labor and cannot easily work in industries with high technical content; thus, the employment field is relatively narrow, and the income is relatively low. Therefore, the cultural level and vocational skills of farmers should be gradually improved to enhance the diversity of rural households’ livelihood activities, increase the economic income of rural households, and ultimately achieve the goal of poverty alleviation. This paper revealed the basic characteristics of rural households’ livelihood capital as well as the sensitivity of rural households’ livelihood strategies to livelihood capital in the upper reaches of the Min River, China, in 2017, and the research results can provide a reference for relevant government departments to implement poverty alleviation policies. Moreover, the research ideas and research methods of this paper can provide some reference for research on the livelihoods of rural households in other poverty-stricken mountainous areas of China. However, the study area of this article belongs to minority areas as well as to mountainous and hilly areas from a geomorphological perspective. Therefore, whether the research results of this paper are applicable to areas with larger Han populations, especially the plain areas, still needs to be further explored. In addition, the research results can only reflect the livelihood status of rural households in 2017, and according to the framework for sustainable livelihood analysis proposed by the DFID, the livelihood status of rural households may change because of some external risk shocks. Therefore, in future studies, we should conduct a dynamic follow-up survey of rural households in different years and analyze the changing processes Sustainability 2019, 11, 2193 14 of 16 and changing trends of their livelihood status to propose targeted suggestions for the sustainability of rural households’ livelihoods.

Author Contributions: Conceptualization, L.P.; Formal analysis, D.X. and X.W.; Investigation, X.W.; Methodology, L.P.; Resources, D.X.; Writing—review & editing, X.W. Funding: The research was supported by the National Natural Science Foundation of China (41601612), the Scientific research Fund of Sichuan Provincial Education Department (17ZB0440), the Economic Development Research Center of Sichuan National Mountain Areas (SDJJ1802), and the Longshan talents of Southwest University of Science and Technology (17LZX679, 18LZX660). Conflicts of Interest: The authors declare no conflict of interest.

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