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CAER
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The effects of social capital
on farmers’ wellbeing in
China’s undeveloped
poverty-stricken areas
Xiaoqiang Ma
Received 22 June 2016
Revised 27 September 2017
8 June 2018
29 October 2018
Accepted 22 April 2019
Northwest University, Xi’an, China
Jiaqi Wang
Northwest Institute of Mechanical and Electrical Engineering, Xianyang, China, and
Ling Zhao and Jinmian Han
Northwest University, Xi’an, China
Abstract
Purpose – The purpose of this paper is to investigate empirically the effects of different dimensions of social
capital on the well-being of farmers in China’s undeveloped poverty-stricken areas, and study the equivalent
multiple of social capital and income compensation.
Design/methodology/approach – The paper opted for an exploratory study using the open-ended
approach of grounded theory, including 1,176 interviews with rural households in poverty-stricken areas in
China. The data were complemented by documentary analysis. Then an econometric model of social capital
and farmers’ well-being was applied to the data.
Findings – The results show that the number frequently visiting relatives, reciprocity, participation and
trust level are significantly positively related to the well-being of the farmers, and the level of participation in
social capital requires the most income compensation, while the level of trust comes second.
Originality/value – This paper can serve as a template for developing a useful tool that can be fitted to
national or regional data for studying the effects of social capital on the well-being of farmers in poor areas or
countries and for calculating the concrete equivalent multiple of social capital and income compensation.
Keywords Social capital, Equivalent multiple, Farmers’ well-being, Undeveloped poverty-stricken areas
Paper type Research paper
China Agricultural Economic
Review
Vol. 12 No. 1, 2020
pp. 108-121
© Emerald Publishing Limited
1756-137X
DOI 10.1108/CAER-06-2016-0087
1. Introduction
With today’s rapid in economic development, economic outcomes cannot be explained fully
by traditional factors of production such as labor, land, physical capital and
entrepreneurship. More and more attention has been given to “social capital” in
explaining the well-being of the household and the nation. Since reform and opening-up,
China’s rural economy has developed rapidly. In China, a number of factors have brought
real benefits to farmers, namely the implementation of the household contract responsibility
system along with various kinds of favorable policies to farmers, the progress of the new
rural cooperative medical system, the establishment of the rural subsistence security system
as well as social special care, the construction of rural public utilities and the cancellation of
agricultural taxes. As a consequence, farmers’ well-being has obviously improved. However,
there are some problems which restrict the process of rural development, such as limitations
on the increase of farmers’ income, a continued large income disparity, less choice of
financial instruments and low efficiency of the rural credit market. Obstacles restricting the
further improvement of farmers’ well-being still exist.
This paper is funded by National Social Science Foundation Project (13CJY077), Shaanxi Provincial Social
Science Project (2018D09), Shaanxi Social Science Research Base Key Project (15JZ068), Shaanxi Provincial
Department of Education Project (18JK0762) and Social Science Prosperous Project of Northwest University.
The above problems have been studied from different perspectives, with fruitful
results. In studies on improving household well-being, “capital” has been paid great
attention. But early studies on household well-being have been mainly from the
perspective of human capital, physical capital, natural capital and other traditional
capital. Since the 1980s, the concept of social capital has been put forward (Bourdieu, 1983;
Coleman, 1990), which provides a new perspective for the research on household wellbeing. Like physical capital and human capital, social capital is also foundational for
people engaged in economic activities, and for gaining welfare. It can increase people’s
welfare level, especially in undeveloped poverty-stricken areas where physical capital and
human capital are relatively low. The most significant difference between social capital
and traditional capital is that social capital is a kind of informal institution, and is a kind of
resource which people acquire and use in social action and which is embedded in the social
network (Lin, 2001).
Correlation studies of social capital and economic well-being can be divided into three
levels: national and regional level; community and village level; and household level. At
present, most studies have focused on the national and regional levels, such as Tanzania
(Narayan and Pritchett, 1997), Indonesia (Grootaert, 1999), South Africa ( John et al., 2000),
Burkina Faso (Grootaert et al., 2002) and Bolivia (Grootaert and Narayan, 2004). In China,
only a handful of literature (Huang and Lin, 2010; Ye and Luo, 2011) has addressed the
effect of social capital on people’s income at the community and village levels. However,
research on the correlation between social capital and farmers’ household well-being is
even more deficient.
At the beginning of the twenty-first century, as the goal of China’s Rural Poverty
Alleviation and Development Program (2011–2020) was reached, the distribution of China’s
population of absolute poverty was concentrated in the ethnic communities, remote
mountainous areas, provincial border areas and old revolutionary base areas. These areas
are called “undeveloped poverty-stricken areas with special difficulties,” hereinafter referred
to as undeveloped poverty-stricken areas. To adapt to this change in China’s poverty
pattern, in 2011, China’s Rural Poverty Alleviation and Development Program (2011–2020)
addressed 14 undeveloped poverty-stricken areas, which were considered the crucial
battlefield of China’s new stage poverty alleviation. Ding (2014) and Liu et al. (2014) studied
the poverty measurement and alleviation in these areas. From this background, the present
paper uses the 2015 farmers’ household field survey data of Qinba, LiuPanShan, Lv-liang
Mountains and the Yanshan – Taihang Mountains, and investigates empirically the effect of
farmers’ social capital on household economic well-being. It also discusses how to increase
farmers’ household social capital in order to improve the performance of the poverty
alleviation policy. This paper can provide a new direction for improving the farmers’ wellbeing in China’s undeveloped poverty- stricken areas.
2. Literature review
2.1 Social capital and its mechanism in affecting household welfare
In the past two decades, social capital has emerged as one of the most salient and
controversial concepts in social science studies. Different scholars have tried to identify
social capital from different perspectives and approaches. Through its development,
this concept has been widely used in the fields of economics, political science,
management, science and other disciplines, but such far a common definition has yet to be
agreed upon.
Until the late 1980s and early 1990s, Bourdieu’s (1986), Coleman’s (1988) and Putnam’s
et al. (1993) studies had become the starting point of social capital research discussion.
Bourdieu (1986) distinguished between three forms of capital: economic capital, cultural
Effects of
social capital
on farmers’
wellbeing
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capital and social capital. He defines social capital as “the aggregate of the actual or
potential resources which are linked to possession of a durable network of more or less
institutionalized relationships of mutual acquaintance and recognition.” Fukuyama (2000)
explained it as “shared norms or values that promote social cooperation, instantiated in
actual social relationships,” and posits that social capital is based on trust. Lin (2001)
considered social capital as the expected returns of social relations in the marketplace.
In accordance with the above research, this paper defines social capital as a kind of
social resource which exists in social networks in the form of capital, through the
accumulation of the owner, and which can bring convenience and benefits. As a special
kind of capital, social capital, compared with human capital and physical capital, has the
characteristic of incomplete substitution, is self-value-added and not transferable, and is
consisted as public goods and has externalities. Social capital is helpful for people to
achieve a certain goal, and to improve both themselves and the surrounding environment.
Creating and accumulating social capital contributes to the improvement of people’s
well-being.
Scholars use various indicators to measure social capital. Narayan and Pritchett (1997)
measured three dimensions of social capital: first, their membership in groups; second, the
characteristics of those groups in which the households were members; and third, the
individual’s values and attitudes, particularly their definition and expressed levels of trust
in various groups and their perception of social cohesion. Grootaert (1999) used six
measurement indicators: density of membership (measured by the number of
memberships per household), heterogeneity index (rated according to eight criteria),
meeting attendance (measured by average number times over a three-month period
someone from the household attend group meetings), active participation index
(through questionnaires subjectively evaluate this index), membership dues (willing to
pay membership dues) and community orientation (whether they perceive the association
of which they are members to have been imitated by the community). Grootaert et al.
(2002) used seven measurement indicators. The first six are almost the same as those
Grootaert (1999) used. They added one more indicator, which is mode of organization
(measured by formally or informally organized). Grootaert and Narayan (2004) also
used the first six measurement indicators. Yusuf (2008) argued that the social capital
includes density of membership, heterogeneity index, meeting attendance index, cash
contribution, labor contribution and decision making index. We can see that some of the
indicators are the same as those Grootaert and Narayan (2004) once used. Portela et al.
(2013) used trust, networks and norms to capture social capital and proposed different
measurement indicators.
The mechanism by which capital affects household economic welfare can be divided
into two categories: direct effect and indirect effect. For the direct effect, in the new
classical economics, social capital can be considered as a dimension of welfare, and the
accumulation of the social capital itself can improve welfare. In addition, social capital not
only promotes the accumulation of human capital of teenagers (Coleman, 1988), but also is
one of the important contributors to personal production activities. A person with higher
social capital will improve his physical standard of living; spiritual needs will also be
satisfied, and accordingly, welfare level will grow higher (Lin, 2010). As for the indirect
effects, from the perspective of informal institution, social capital can affect people’s
expectations, influence their behavior (Xu, 2014) and thus indirectly affect their income,
health and employment, so as to improve household welfare. The mechanism is as follows:
first, social capital can improve the flow of information, promote the diffusion and
adoption of new technology, and reduce transaction cost through information
communication channels (Ding et al., 2013). Second, social capital provides members of
the cooperative with network support, trust and mutually beneficial norms and incentive
supervision mechanism, promotes decision making and collective action, and reduces
opportunistic behavior, so as to minimize negative externalities and promote the
production of public goods. Third, as Grootaert indicated in 1999, social capital can
effectively improve the efficiency of resource allocation and promote mutually beneficial
trade by the spreading mechanism such as citizens’ action norms, trust and reputation.
Effects of
social capital
on farmers’
wellbeing
2.2 The relationship between social capital and people’s welfare
In the literature which analyzes the impact of social capital on welfare, scholars hold
different viewpoints; some are even opposite. Whether on the national, regional or
household levels, a large number of studies show that social capital has a positive impact on
economic welfare. Narayan and Pritchett (1997) found that higher social capital led to higher
household welfare, and the impact social capital had on household welfare was greater than
that of human capital and physical capital. Rose (1998) found that social capital was helpful
in promoting the economic welfare using the multiple regression method. Grootaert (1999)
used data from Indonesia and found that social capital could significantly increase farmers’
household welfare; and that the return on social capital gained by the poor was higher than
that of the rich. Grootaert and Narayan (2004) did research on Bolivian farmers, drawing the
following conclusion: the return on social capital gained by the poor was higher than other
forms of capital. Therefore, Grootaert considered social capital as “the capital of the poor.”
Jiang (2006) argued that the accumulation of social capital had a significantly positive
impact on household welfare level.
However, some scholars have the opposite viewpoints. Maluccio et al. (2000), based on
an empirical analysis of South Africa, found that the economic return of social capital was
less than that of human capital. Adato et al. (2007) using micro panel data of 1993–2001
from South Africa argued that the effect of social capital on increasing individual income
was more efficient for non-poor people. Huang and Yang (2008) also believed that the
marginal effect of social capital on income was less than that of human capital. Zhao and
Lu (2009) did empirical research on Chinese rural areas and found that the poor had
limited ability to obtain social capital and that the return of their social capital was also
relatively lower than that of the rich. Social capital was “the capital of the rich,” according
to their findings.
In addition, some studies have shown no significant correlation between social capital
and economic welfare. Putnam et al. (1993), who analyzed the development of the USA
from the 1850s, found that although there was a significant decline in social capital, the
country’s economic welfare had no significant decline. Gertler et al. (2006), by using panel
data in Indonesia, found that that there was no significant correlation between social
capital and family welfare level after risk shocks. Liu and Chang (2007) studied migrant
workers’ income in the Yangtze River delta region from the perspective of social capital
and found that the relationship between social capital and migrant workers’ income was
not significant.
The above literature provides a good foundation for this study. However, the results of
the impact of social capital on household welfare are inconsistent. In the 14 undeveloped
poverty-stricken areas in China, little research has been done in this aspect. Using field
survey data, this paper attempts to investigate empirically the effect of farmers’ social
capital on household economic well-being to see if the correlation is positive, negative or
even unrelated. It studies different dimensions of social capital and puts forward more
evidence of such effects. This paper is organized as follows: the following section
describes the research method and econometric model; Section 4 gives the empirical
analysis of social capital on the well-being of farmers and estimates the two-way causality,
and then studies the equivalent multiple of social capital and income compensation; and
the last section puts forward the conclusion and policy recommendations.
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3. Methodology
3.1 Selection of variables
This paper investigates empirically the effects of farmers’ social capital on their household
economic well-being in China’s undeveloped poverty-stricken areas. Household economic
well-being is the explained variable. It can be measured by household income, consumption
expenditure, assets or other forms of household wealth. This paper chooses the natural
logarithm of per capita household consumption expenditure as the explained variable for
measuring farmers’ household well-being. The reason why it is chosen is that household
income in a year varies widely. Moreover, farmers usually smooth their consumption in the
year, and consumption expenditure can better characterize the farmers’ well-being.
In employing the explanatory variables to measure social capital, this study has
chosen to use farmers’ social network, participation, trust and reciprocity, which are
specified as follows:
(1) Social network: in China’s undeveloped poverty-stricken areas, social network is
measured by the number of persons with whom the household mainly connects who
can also bring benefit to them. It includes the number of frequently visiting relatives,
and whether the household has migrant workers. In rural areas, the migrant
workers’ network is an important form of social network. It can provide the rural
surplus labor force with the information and opportunities to go out for work, and
then increase the non-agricultural income. Whether the household has migrant
workers reflects the extensive property of social network, while the number of
frequently visiting relatives measures the affinity degree of the local social network.
This paper assumes that there is no quality difference among the frequently visiting
relatives of the household.
(2) Participation: farmers’ participation in organizations and community groups can
help them to obtain scarce resources in social life. This indicator is measured by
farmers’ interest in public affairs, participation in village cadre elections and
whether a Chinese Communist Party member or not. It is indicated by four levels:
frequent participation, infrequent participation, rare participation and no
participation, and is given the points of 4, 3, 2 and 1, respectively.
(3) Trust: farmers’ trust toward each other can bring benefits to them. This indicator is
measured by the level of farmers’ trust toward the outside world, such as toward
acquaintances and strangers. The specific degree from extreme trust to no trust is
given points from 10 to 1, respectively, in our data survey. In a sense, the harmony of
the neighborhood reflects the degree of trust among farmers.
(4) Reciprocity: this refers to the degree of mutual help between farmers and those
with whom they daily interact. It can promote communication and cooperation
among rural households, constrain opportunistic behavior and solve the
“free-rider” problem of collective action. This indicator is measured by the role
of relatives and friends when farmers fall in trouble. It is indicated by four levels:
large, comparably large, normal and none, and is given the points of 4, 3, 2
and 1, respectively.
3.2 Model
3.2.1 Econometric model. We assume that after introducing the variable of social capital,
the farmers’ utility function is as follows:
U ¼ U ðI ; SC; X Þ;
(1)
where U denotes the farmer’s utility, namely the farmers’ well-being level, expressed by
annual per capita consumption. I is the farmer’s net income for the year. SC is the farmer’s
social capital and X is the farmer’s other characteristic variables. This function assumes that
utility is a function of income, social capital and farmers’ other characteristic variables.
At the same time, SC1, SC2, SC3, SC4 and SC5 represent the five different dimensions of social
capital, that is, number of frequently visiting relatives, whether the family has migrant
workers, reciprocity, trust and participation. Within this, a farmer’s social network scale is
represented from two perspectives, namely the number of frequently visiting relatives and
whether the family has migrant workers.
Accordingly, we establish the following econometric model of social capital and farmers’
well-being:
U ¼ b0 þby LogðI Þþbi SCi þbx X þx
i ¼ 1; 2; 3; 4; 5:
(2)
3.2.2 The equivalent multiple of social capital and income compensation. Assuming that C
(X); U, SCi0) denotes the necessary income level that a famer with social capital SCi0 and
characteristics of X needs to achieve the well-being level U. C(X; U, SCi1) stands for the
necessary income level of a famer with social capital SCi1 and characteristics of X.
We also define the equivalent multiple ES of social capital as follows:
ES ¼
C ðX ; U ; SCi0 Þ
;
C ðX ; U ; SCi1 Þ
(3)
where ES denotes the changing rate of the farmer’s income after the change in social capital,
in order that make his utility remain unchanged. Taking the logarithm on both sides of
Equation (3), we get the following equation:
LogES ¼ Log C ðX ; U ; SCi1 Þ Log C ðX ; U ; SCi0 Þ ¼
bi
DSC;
by
(4)
where ΔSC ¼ SCi1−SCi0. This paper investigates what the equivalent multiple of social
capital will be when the social capital changes by one unit, that is to say, SCi1−SCi0 ¼ 1,
ΔSC ¼ 1, thereby LogES ¼ (βi)/(βy), so that the income compensation of social capital is
CV ¼ ES I .
In the equation, CV ¼ ES I , I stands for the farmer’s per capita income. CV stands for the
income compensation of social capital. At average social income level, this indicator measures
the extra minimum income the farmer needs to obtain if his social capital loses while his
well-being level remains unchanged. Therefore, CV represents the farmers’ evaluation of the
importance of different dimensions of social capital. The greater the CV, the more important
the farmer considers the social capital and the higher his evaluation will be. On the other hand,
the less important the farmer considers the social capital, the lower his evaluation will be.
4. Empirical analysis
4.1 Data
4.1.1 Data source. The data of this paper are from our social investigation in the Qinba,
Liupanshan, Luliang and Yanshan undeveloped poverty-stricken areas in China in 2015.
We obtained 1,259 household questionnaires, out of which 1,176 were valid. By adopting the
method of random sampling investigation, investigators had face-to-face interviews with
the head of the households, and administered questionnaires involving household
characteristics, income and expenditure, social capital and other items.
4.1.2 Descriptive statistics of the main variables. Table I
Effects of
social capital
on farmers’
wellbeing
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Table I.
Definition and
description of
variables
Overall
classification
Variable
name
Variable explanation
Social capital
SC1
Mean
SD
Minimum Maximum
Number of frequently visiting
12.070
8.820
1
60
relatives
SC2
One of HH’s members is a
0.640
0.481
0
1
migrant worker (yes ¼ 1, no ¼ 0)
SC3
Participation level (range 1–4)
1.820
0.926
1
4
SC4
Trust level (range 1–10)
3.464
2.713
0
9.100
SC5
Reciprocity level (range 1–4)
2.543
0.899
1
4
Household
i
HH income per capita
11,301.289 10,222.730 500.000 98,000.000
characteristics c
HH consumption expenditure
7,759.347 8,308.955 400.000 78,000.000
per capita
Ln i
The natural logarithm of HH
9.026
0.823
6.210
11.49
income per capita
Ln c
The natural logarithm of
8.549
0.867
5.990
11.26
HH consumption expenditure
per capita
Scale
Size of household
4.588
1.463
1
13
Area
HH total contracted land area
6.680
6.459
1
40
Type
Quality of Housing (scale 1–3)
2.000
0.722
1
3
Mach
Number of pieces agricultural
0.337
0.481
0
2
machinery
Car
HH having car (yes ¼ 1, no ¼ 0)
0.158
0.365
0
1
Head of
Age
Age of HH head
46.682
10.180
19
73
2
Age square of HH head
2,282.5
942.05
361
5,329
household
Age
HH head is healthy (yes ¼ 1,
0.926
0.263
0
1
characteristics Health
no ¼ 0)
Edu
HH head education (range 1 to 4)
1.970
0.767
1
4
Gender Head gender (male ¼ 1,
0.949
0.221
0
1
female ¼ 0)
Note: HH refers to household
Source: Authors’ calculation based on field survey data in China’s undeveloped poverty-stricken areas in 2015
From our field survey, the surveyed households’ social capital conditions are as follows.
4.1.2.1 Social network size. The maximum, minimum, mean and standard deviation of
the number of frequently visiting relatives of the surveyed households are, respectively,
60, 1, 12.070 and 8.820, which indicates the social network size ranges widely and has a
high discrete degree. From the mean, standard deviation, maximum and minimum of the
number of migrant workers, we can see that in the undeveloped poverty-stricken areas of
China, the households having migrant workers are more than those not having migrant
workers and the dispersion degree of the number of migrant workers among the
households is small.
To analyze further, among the surveyed households having less than five persons, 61
percent have migrant workers; while among the surveyed households having more than five
persons, the proportion is 74 percent. When the age of the head of the household is between
30 and 40, the proportion of migrant workers is only 35 percent. When the head’s age is less
than 30 or greater than 60, the proportion of migrant workers is, respectively, 62 and 70
percent. When the head of the household is male, the mean of the frequently visiting
relatives is 12.87, but when the head of the household is female, the mean is 7.82. It means
the number of daily interactions of male-headed households is much greater than femaleheaded households, because the males’ social status and activity levels are higher than those
of the females.
4.1.2.2 Participation level. From the descriptive statistics, the mean of the participation
level of the surveyed households is 1.820. The maximum, minimum and standard deviation,
respectively, are 4, 1 and 0.926. This means the surveyed households’ participation level in
public activities and affairs is low, and the dispersion degree of the participation level
among households is small.
The statistics show that when the head’s age is less than 30, the average level of
participation in public affairs is 1.39, while the average level is 1.66 when the head’s age is
between 31 and 45. The average level of participation is 1.91 when the head’s age is
between 46 and 60, and the average is 2.33 when the head’s age is greater than 60.
This means that with increasing age, the prestige and social status of the household
head gradually increases. They receive more respect, and increase their participation in
public affairs.
4.1.2.3 Trust level. From the descriptive statistics, the mean, maximum, minimum and
standard deviation of the trust level of surveyed households, respectively, are 3.464, 9.1, 0
and 2.713. This indicates that the trust level of the surveyed households is low, and the
dispersion degree of the participation level among households is not big.
Statistical analysis shows that the trust level of those household heads who have only
primary or secondary education levels is higher than those with university education,
because with a higher education level, people’s thoughts encompass a wider range of factors
and they are more cautious when getting along with others; thus, their level of trust in
others is lower.
4.1.2.4 Reciprocity level. From the descriptive statistics, the surveyed households’ average
reciprocity level is 2.543. The standard deviation, maximum and minimum are, respectively,
0.899, 4 and 1. This indicates that the surveyed households have a high reciprocity level, and
the dispersion degree of the reciprocity level among the households is small.
Our statistical analysis also shows that when the head’s age is less than 30 or greater
than 60, households have a low level of reciprocity, but when the head’s age is between
30 and 60, households have a high level of reciprocity. This may be due to the fact
that households with young heads accumulate limited social resources, and households
with old heads gradually reduce their daily communicative activities, but households
with middle-aged heads have considerable social resources and more frequent
communicative activities.
4.2 Regression results and analysis (Table II)
The coefficient of each variable of Equation (2) can be obtained from the regression above.
From the results, the variables measuring social capital are statistically significant. The
coefficients of SC1: the number of frequently visiting relatives, SC3: participation level,
SC4: trust level and SC5: reciprocity level are all positive, indicating a positive correlation
between these dimensions of social capital and the households’ well-being. Other
researchers found similar results (Narayan and Pritchett, 1997; Rose, 1998; Grootaert,
1999; Grootaert and Narayan, 2004; Jiang, 2006; Huang and Lin, 2010; Ye and Luo, 2011).
The coefficient of SC2 is negative, indicating that this type of social capital is negatively
related to the household well-being. The usual understanding is that migrant workers can
increase the household income and improve household well-being, so the coefficient
should be positive. But this paper posits that migrant workers do not live in their villages
and this may weaken their links with other households in their own village, decreasing
their household social capital stock and their household well-being. The other reason is
that the migrant workers’ consumption is not included in the total consumption of the
households. The influence of participation level on household welfare is 0.088, and the
influence of trust level is 0.073. This suggests that the higher the level of the households’
Effects of
social capital
on farmers’
wellbeing
115
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Table II.
Social capital and
results of farmers’
estimated level
of well-being
Variable name
Variable explanation
Coefficient
SE
Intercept
β0
4.373***
(1.018)
Ln i
The natural logarithm of HH income per capita
0.436***
(0.073)
Gender
Head gender (male ¼ 1, female ¼ 0)
0.113*
(0.063)
Age
Age of HH head
0.066**
(0.032)
Age square of HH head
−0.001**
(0.00)
Age2
Edu
HH head education (range 1–4)
0.069
(0.066)
Scale
Size of household
−0.080**
(0.038)
Area
HH total contracted land area
0.018*
(0.009)
Type
Quality of housing (scale 1–3)
0.0030***
(0.001)
Mach
Number of pieces of agricultural machinery
0.056
(0.110)
SC1
Number of frequently visiting relatives
0.009*
(0.005)
SC2
One of HH’s members is a migrant worker (yes ¼ 1, no ¼ 0)
−0.085*
(0.048)
SC3
Participation level (range 1–4)
0.088*
(0.047)
SC4
Trust level (range 1–10)
0.073***
(0.023)
SC5
Reciprocity level (range 1–4)
0.035*
(0.020)
2
2
Adjusted R
0.394
Adj. R
n
Sample size
1,176
Notes: *po 0.1; **p o0.05; ***p o0.01
Source: Authors’ calculation based on the field survey data in China’s undeveloped poverty-stricken
areas in 2015
participation in rural public affairs, the more significantly this affects their own wellbeing. In the same way, the higher the level of trust in others in their village, the more
significantly this affects their own well-being. Thus, improving participation in public
affairs and strengthening trust levels can improve the level of household well-being in the
undeveloped poverty-stricken areas in China.
The age of the household head and annual income per capita have statistically significant
effects on farmers’ well-being. The influence of heads’ education level on farmers’ well-being is
not significant, and one possible reason is that such areas in China are naturally fragile and
people in those areas face more risk shocks. There is a tendency toward saving to deal with
future uncertainty, and their patterns of consumption are also similar, tending to only just meet
their daily needs. The other possible reason is that the sources of income and standards of
living in undeveloped poverty-stricken areas in China are quite similar, so it is hard to increase
the well-being of the household even if the heads have a higher education level. It is obvious
that male-headed households’ well-being is higher than that of female-headed households,
and the results are statistically significant. This is in line with the understanding, in a general
sense, that female-headed households are mostly single parents. The effect of household size on
farmers’ household welfare is negative, and it is also statistically significant. This means that
the more members of the household, the lower their overall welfare. This is because the larger
the household, the greater the household burden and consequent costs and the lower the level
of well-being. The quality of house and the contracted land area are positively related to wellbeing. This is because the house is often the most important asset of Chinese rural households
in poverty-stricken areas; the better the quality of the house, the higher the living standard of
the households. Part of the farmers’ income is from farming, and their income will increase with
increasing size of the contracted land area, leading to a higher level of well-being.
4.3 Two-way causality: instrument variable estimation
This paper treats social capital an input of household production function. However,
Grootaert (1999) and Grootaert and Narayan (2004) argued that social capital, like human
capital, can be, at least partly, a consumption good. Therefore, there could be a reverse
causality from well-being level to social capital. If so, the estimated coefficient of social
capital is biased. In econometrics, instrument variable estimation can be used to solve this
two-way causality. Grootaert (1999), Grootaert and Narayan (2004) and Yusuf (2008) also
adopted this estimation to estimate reverse causality. So we need to find valid instrumental
variables. Such variables induce changes in the social capital but have no independent effect
on farmers’ well-being, allowing a researcher to uncover the causal effect of social capital on
farmers’ well-being. We argue that the following instrument variables are suitable for
social capital in China’s poverty-stricken areas: frequency of relatives’ and friends’ visiting
the household during Spring Festival, number of churches and temples in the
village, frequency of helping others in the same village when a household encounters
a big event such as house-building, number of organizations in the village and proportion
of migrant workers in the village.
After introducing the above instrumental variables, we apply the 2SLS regression.
The following results obtained are compared with the previous results. From this table,
we can see the adjusted R2 has increased from 0.394 to 0.396 and the coefficients of
social capital all have a slight change. Yusuf (2008) indicated that a reverse causality
could have been accepted if there is no improvement or reduction in R2 as well as
reduction/lack of improvement in the instrumented variable. Moreover, for example,
the coefficient of SC1 with instrumental variable estimation has changed into 0.010
which was 0.009 in the OLS estimation, indicating a one unit increase in the instrumented
SC1 leading to a 1 percent increase in household well-being. Such changes in R2 as
well as the coefficients of social capital suggest the absence of significant reverse
causality, and thus confirms social capital is and exogenous determinant of household
well-being (Table III).
In addition, Hausman’s test is performed on the regression of the instrumental
variables and the ordinary least squares regression. Table IV shows the results.
Variable name
Without instrumental variable (OLS)
Effects of
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on farmers’
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117
With instrumental variable (2SLS)
4.373*** (1.018)
4.371*** (1.015)
β0
Ln i
0.436*** (0.073)
0.433*** (0.069)
Gender
0.113* (0.063)
0.114* (0.065)
Age
0.066** (0.032)
0.064** (0.030)
Age2
−0.001** (0.00)
−0.001** (0.00)
Edu
0.069 (0.066)
0.070 (0.067)
Scale
−0.080** (0.038)
−0.083** (0.039)
Area
0.018* (0.009)
0.017* (0.009)
Type
0.0030*** (0.001)
0.0031*** (0.001)
Mach
0.056 (0.110)
0.057 (0.111)
SC1
0.009* (0.005)
0.010* (0.006)
SC2
−0.085* (0.048)
−0.087* (0.050)
SC3
0.088* (0.047)
0.089* (0.049)
SC4
0.073*** (0.023)
0.074*** (0.025)
SC5
0.035* (0.020)
0.037* (0.022)
Adj. R2
0.394
0.396
n
1,176
1,176
F-statistics
23.28
24.75
Notes: *p o0.1; **p o0.05; ***p o0.01
Source: Authors’ calculation based on the field survey data in China’s undeveloped poverty-stricken
areas in 2015
Table III.
Social capital:
Instrumental variable
estimation
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The p-values obtained by the test are all greater than 0.7, and the null hypothesis
that there is no systematic difference between the OLS result and the 2SLS result
cannot be rejected. Therefore, based on the results of the Hausman’s test, we found that
there is no significant endogeneity in the social capital variables, that is, using the OLS
results to estimate the impact of social capital on the income of farmers will not have
systematic bias.
118
4.4 The equivalent multiple of social capital and income compensation
Table V is calculated by Equations (3) and (4). As can be seen from the results, the
equivalent multiple of the number of frequently visiting relatives is 1.021, and
income compensation is RMB 2,323.47 per year, indicating that on the premise of no
difference in the quality of relatives, households should receive an annual income of
RMB 2,323.47 as compensation to ensure the same level of welfare when the number
of frequently visiting relatives reduces by one unit. The equivalent multiple of
households having migrant workers is less than one, because the social capital is
negatively related to households’ well-being. Its income compensation is RMB 1,872.86 per
year, indicating that households should get an annual income of RMB 1,872.86 to ensure
the same level of welfare when the number of migrant workers increases by one unit.
This is different from the other four indicators of social capital. Households should get
income compensation when relatives, participation, trust level and reciprocity level
decrease, but households should get annual income compensation when the number of
migrant workers increases.
When the level of participation increases by one unit, the income increases to 1.224 times,
and income compensation is RMB 2,785.018 per year to maintain the original level of wellbeing. Similarly, when the levels of trust or reciprocity change by one unit, equivalent
multiples are 1.182 and 1.084, respectively, and income compensation is RMB 2,690.833 and
2,466.24, respectively. Thus, when the level of well-being and the characteristic conditions of
households are held equal, participation level requires the most income compensation, and
the level of trust comes second.
Instrumental variables
Table IV.
Hausman’s test:
p-value
Table V.
The Equivalent
multiple of social
capital and income
compensation
SC1
SC2
SC3
SC4
SC5
Frequency of relatives’ and friends’ visiting the household during
Spring festival
0.853
Number of churches and temples in the village
0.743
Frequency of helping others in the same village when a household
0.772
encounters a big event such as house-building
Number of organizations in the village
0.838
Proportion of migrant workers in the village
0.794
Source: Authors’ calculation based on the field survey data in China’s undeveloped poverty- stricken areas in 2015
Number of frequently visiting
relatives
Households having migrant
workers
Participation
level
Trust
level
Reciprocity
level
1.021
0.823
1.224
1.182
1.084
2,323.47
1,872.86
2,785.018
2,690.833
2,466.24
Source: Authors’ calculation based on field survey data in China’s undeveloped poverty-stricken areas in 2015
5. Conclusion, policy recommendations and limitations
Using survey data of 1,176 farmers’ households from Qinba, LiuPanShan, Lu-liang
and the Yanshan –Taihang mountains, which are 4 of the 14 undeveloped
poverty-stricken areas in China, this paper studies the effects of different dimensions of
social capital on the well-being of farmers’ households. The conclusions are summarized
as follows: first, using statistical methods in data classification, we found that social
network from the respect of the number of frequently visiting relatives among the
households ranges widely and has a high discrete degree. In such areas, most households
have a member migrating out of their village to work outside, and social network can also
be measured from this respect. The households’ participation in organizations and
community groups and their trust toward the outside world are low. The households in
these poverty-stricken areas depend on mutual help among the persons they daily interact
and have a high reciprocity level. Second, the regression results show that the four
dimensions of social capital have statistically significant effects on household well-being,
and the number of frequently visiting relatives, reciprocity, participation and trust level of
the household contribute positively to the household well-being. Among these, the
strongest effect on household well-being is the participation level. The number of migrant
workers of the household has a negative impact on the household well-being. In addition,
the age and gender of the head of the household has a statistically significant influence on
household well-being. The well-being of male-headed households is higher than that of
female-headed households. The quality of house and the contracted land area are
positively related to farmers’ well-being. The influence of heads’ education level on
farmers’ well-being is not significant. Third, using instrumental variable estimation to test
reserve causality between social capital and household well-being, we find that the direct
effect of social capital on well-being outweighs the reverse effect. Fourth, analysis of
results of the equivalent multiple of social capital and its income compensation indicate
that when the level of participation increases by one unit, the income increases to 1.224
times and participation level requires the most income compensation, and the level of trust
comes the second.
From the above results, this paper proposes that farmers’ well-being can be improved by
improving the social capital in undeveloped poverty-stricken areas in China. It gives the
following corresponding policy recommendations: first, social capital acquisition and
investment are very important in undeveloped poverty-stricken areas. Households in such
areas should pay attention to their social capital accumulation. The government may also
establish and enhance the credibility of the rural social credit system to help the households
in such areas build social networks and trust systems. Second, since participation level
requires the most income compensation, the community and local government need to
encourage the development of various ethical, religious and cultural entertainment
organizations and promote community construction. The households themselves need to
actively participate in public activities and affairs to build their prestige and social status in
their villages, for they live in remote areas and have the free time to do so. Third, poverty
alleviation can be achieved by investing in social capital in such areas in China.
Constructing effective networks of social participation, fostering farmer’s participation
awareness and increasing farmers’ opportunity to participate in public activities can help to
improve farmers’ well-being and alleviate their poverty.
The limitation of this paper is that the measurement of social capital is complex,
and this paper selected only four core indicators of social capital, namely, social
network size, level of reciprocity, trust level and participation level. Future research could
try to expand the dimensions of indicators, cooperate with other subjects and establish a
multi-dimensional social capital measurement model to measure the welfare of farmers
more comprehensively.
Effects of
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Corresponding author
Jinmian Han can be contacted at: rubyhan228@gmail.com
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Effects of
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