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Article
Research on the Intergenerational Transmission
of Poverty in Rural China Based on Sustainable
Livelihood Analysis Framework: A Case Study
of Six Poverty-Stricken Counties
Xiaoying Wu 1, Xinhua Qi 2,*, Shan Yang 1, Chao Ye 3 and Biao Sun 1
1 School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China;
WuXiaoying154642@163.com (X.W.); yangshan@njnu.edu.cn (S.Y.); sunbiaoyf@163.com (B.S.)
2 School of Geographic Sciences, Fujian Normal University, Fuzhou 350007, China
3 School of Geographic Sciences, East China Normal University, Shanghai 200241, China; yeover@163.com
* Correspondence: fjqxh@fjnu.edu.cn; Tel.: +86-166-0522-7682
Received: 13 March 2019; Accepted: 11 April 2019; Published: 18 April 2019
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Abstract: China’s complicated and diverse poverty problems gradually emerged as poverty alleviation
efforts deepened and rural urbanization progressed. Among these problems, the intergenerational
transmission of poverty (ITP) is the most prominent and is an entrenched issue in rural China.
This study selects six typical poverty-stricken counties in the eastern, central, and western regions
of China on the basis of geography and uses the transformation matrix method and a regression
model to analyze the regional differentiation characteristics of ITP. We further explore its impact
mechanisms based on a sustainable livelihood analysis framework with the following results: (1) ITP
in rural China exhibits the phenomenon of income-stratified transmission, and the groups at both
ends of the low-income spectrum are more prone to having ITP; (2) ITP and the intergenerational
mobility of income for different income levels have different spatial distribution characteristics, with
these intergenerational relationships exhibiting a reverse variation trend in the eastern region, while
exhibiting a codirectional variation trend in the central and western regions; (3) there are differences
in the subsistence livelihood capital, which affect ITP in different regions. Financial capital has a
significant impact on ITP across all of China. Natural capital has a significant impact on the eastern
region, and physical capital plays a significant role in the central region, while the western region is
greatly affected by both human and physical capital. In view of the differences in the influence of
livelihood capital on ITP in different regions, China should formulate policies to accurately address
ITP in order to narrow regional differences and accelerate the comprehensive construction of a
financially affluent society.
Keywords: sustainable livelihoods; participatory rural assessment; intergenerational transmission of
poverty; rural poverty in China
1. Introduction
Throughout the history of human development, poverty is consistently one of the problems
plaguing all countries of the world. According to the United Nations Millennium Development Goals
Report 2015, the total number of people living in extreme poverty around the world decreased by
1.064 billion from 1990 to 2015, with China’s contribution exceeding 70% of this total [1]. Since China’s
economic reform and opening, the Chinese government accomplished remarkable achievements in
anti-poverty. The number of rural poor people dropped from 770 million in 1978 to 43.35 million
in 2016 (the new poverty line standard: 2300 RMB per person per year basis as of 2010), and the
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Sustainability 2019, 11, 2341 2 of 22
incidence of poverty dropped from 97.5% to 4.5% [2,3], making China a model for promotion all
over the world. However, China remains a developing country. It still has the characteristics of a
broad poverty area, a deep poverty degree, and a complex overall poverty problem. The reduction of
the poverty population does not indicate that the poverty problem is completely solved. The most
intractable problem is that poverty-stricken families in rural China often descend into poverty for
generations. Poverty monitoring data indicate that the poverty of some rural households entered a
vicious circle, with intergenerational transmission of poverty (ITP) becoming increasingly apparent [4,5].
The Eighteenth National Congress of the Communist Party of China clearly put forward the grand
goal of building a financially affluent society in a comprehensive way by 2020, and the report of the
Nineteenth National Congress once again proclaimed that the period from now to 2020 is the decisive
time for building a financially affluent society in a comprehensive way. They stated that China should
“resolutely win the battle against poverty” and suggested new requirements for solving the problem of
rural poverty. To advance new urbanization, as well as promote urban–rural integration and rural
redevelopment and construction, we should pay special attention to the current situation of rural
construction and the poor populations in rural areas [6,7]. Solving the problem of ITP is the key to
achieving this goal.
Sen believes that the real meaning of poverty is poor people’s inability to generate income and
opportunities, meaning that poor people lack the ability to access and enjoy a normal life [8]. ITP is a
“solidification” phenomenon of poverty and represents a more entrenched problem. Research into
this phenomenon began in the early 1960s. When American sociologists studied the problem of the
poor, they first suggested the concept of “ITP”. This refers to poverty, as well as conditions and related
factors leading to poverty, being passed down from parents to children within the family, causing
children to repeat their parents’ poverty in adulthood and to pass this poverty on to future generations,
in a malignant genetic chain [9,10]. Some scholars believe that ITP has broad and narrow meanings.
In a broad sense, it refers to the idea that related factors that lead to poverty are transmitted from
the previous generation to the offspring in the family, community, geographical area (including the
country), and the hierarchy, such that the descendants repeat the poverty situation of the previous
generation in adulthood. In a narrow sense, it puts more emphasis on the related factors that are
passed on from the previous generation to the offspring at the family level, which result in the next
generations repeating the poverty situation of the previous generation in adulthood [11].
The early literature on ITP generally focused on developed countries [12–15]. These researchers
believed that children from poor families had relatively low levels of education, employment, and
health compared to those from wealthy families. The income level of parents also determined
the level of human capital of children to a certain extent, which then affected their employment
opportunities and improved the probability of falling into poverty [16–18]. Over the past decade,
the research perspective gradually shifted from developed to developing countries [19,20]. Drawing
lessons from developed countries, more attention was paid to children in low-income families in
developing countries. Based on the theory that the employment, income, marital status, and religious
beliefs of children’s parents at the time of their birth will have an impact on whether they will fall
into poverty as adults [21–23], improving children’s nutrition, health [24], and education [25,26] are
considered important ways to reduce poverty and inequality. Some researchers further pointed out
that, before offspring are born, poor pregnant mothers can help their children get a good start in life
through prenatal care, thus reducing ITP. Mothers also play an important role in the intergenerational
mobility of income among children [27–29].In the examination of ITP among adults, it is believed
that decisions of mothers, such as leaving school, working, and having children, play an important
role in the impoverishment of their children [30,31]. At the same time, these investigations were
concerned about the destructive impacts of regional conflicts and domestic violence on children’s
poverty [32,33]. It is worth mentioning that China’s research on ITP pays more attention to the
transmission of the economic level. It indicates that the income of rural residents in China exhibits
weak intergenerational mobility and strong inheritance, and that the economic situation of offspring is
Sustainability 2019, 11, 2341 3 of 22
vulnerable to economic disadvantages of their parents [34]. The offspring of poor families are affected
by their educational level, school opportunities, and employment status. They also have obvious
disadvantages in terms of medical insurance and other financial and social factors. Family income
exhibits strong intergenerational transmission [35,36]. Through research on ethnic minority areas and
underdeveloped areas in northwest China [37–39], it was found that ITP is very common in rural
China, especially at the relative poverty level; it is more prominent, tends to increase, and displays
biphasic, long-term, universality, concealment, and complexity characteristics within a district [34,40].
In terms of research methods, some scholars primarily studied income mobility by constructing
an income elasticity coefficient [41]. However, due to the differences in observations data and
processing methods, there are often a number of data errors, leading to inconsistent results [42–44].
These researchers did not clearly delineate which income class is involved in ITP or how to focus
on solving the problem of intergenerational transmission for this class. In addition to using panel
data, this research employed micro-data such as family history and life history to explore how the
allocation of key assets such as land, healthcare, nutrition, and education among family members
affects ITP [45–47].
In terms of the causes and mechanisms of ITP, the mainstream theories around the world include the
cultural poverty hypothesis, the policy poverty hypothesis (such as welfare dependence), the economic
structure poverty hypothesis (such as the labor market), the intergenerational genetic hypothesis,
the educational poverty hypothesis, the social exclusion hypothesis, the capacity poverty hypothesis,
and so on (such as Thomas [48], Herbert [49], Camp [50], and Sen [51]). The International Center
for Persistent Poverty Research points out that the main factors influencing ITP include population
and health, social network, education, and living environment [52]. Some scholars tended to focus
on economic [53], sociological [54], and physiological [55] characteristics, in particular the significant
impact of human and social capital, thus paying more attention to individual, parental, and social
system factors, while ignoring the systematic investigation of family comprehensive factors. Some
scholars found that the low level of education of the household and the family labor ability are the most
important factors [56–58]. At the same time, family assets have significant impact on the long-term
poverty situation [59].
In summary, this study argues that ITP mainly refers to the transmission and reproduction of
poverty, as well as the factors leading to poverty between two generations. It also asserts that the
intergenerational transmission of income is the most direct and fundamental manifestation of ITP.
Previous studies paid less attention to ITP data from developing countries. An understanding of this
transmission in regions with obvious economic disparities needs to be obtained, and the mechanism
of ITP in different regions needs to be clearly explained. In addition, the vulnerability–sustainable
livelihood analysis framework is employed in this study to measure absolute poverty [60,61]. This is
followed by a gradual exploration of the relationship between the sustainable livelihood status of
poor farmers and poverty-causing factors, as well as poverty alleviation strategies [62–66]. If all five
types of livelihood capital (human, natural, physical, financial, and social) are introduced into the
mechanism analysis of poverty transmission, it will more comprehensively analyze the influence of
familial factors within the same region on ITP. Therefore, this study uses east China (Songxi and Xiapu
County of Fujian Province), central China (Pingyu and Xin County of Henan Province), and western
China (Gulang and Weiyuan County of Gansu Province) as examples, and, via the participatory rural
appraisal (PRA), method obtains 879 questionnaires in order to analyze the regional differentiation
characteristics of ITP in China. Based on the sustainable livelihood analysis framework, this study
analyzes the impact mechanisms of ITP in China using multiple logistic models and then suggests
policy recommendations designed to accurately block ITP.
Sustainability 2019, 11, 2341 4 of 22
2. Research Area, Methods, and Data Sources
2.1. Survey of the Study Area
China covers a vast domain, and the poverty situation varies significantly from one region to
another. In 2015, the respective numbers of rural poor in the eastern, central, and western regions of
China were 6.35 million, 20.07 million, and 29.14 million, accounting for 11.7%, 36%, and 52.3% of the
poverty-stricken population, with associated poverty incidence levels of 1.8%, 6.2%, and 10% [67].
Gansu Province in western China is one of the most backward provinces in terms of economic and
social development, and it has the highest proportion of rural poor, as well as the deepest degree of
poverty in all of China. There are still 3.25 million rural poor in Gansu Province and a total of 43 of its
counties are key counties in the national poverty alleviation and development effort [67]. Gulang and
Weiyuan Counties are located in Longzhong and Longnan, respectively (Figure 1). Their characteristics
include a poor natural environment, weak infrastructure, large numbers of poor inhabitants, and
diverse poverty-inducing factors. Both are dry farming counties in mountainous areas, mainly in the
primary industry. These areas are faced with the predicament of a single industrial structure, poor
self-development ability, an information blockade, and difficulties alleviating poverty.
Sustainability 2019, 11, 2341  5  of  22 
 
Figure 1. Location map of sample points. 
 
 
Figure  2.  Per  capita  disposable  income  of  rural  residents  in  six  sample  counties  and  provinces. 
Source: According to the Statistical Yearbook 2017 of each county. 
2.2. Data Sources 
In  July,  August,  and  December  2016,  three  periods  of  field  investigation  and  household 
questionnaire surveys were conducted over a total of 40 days in Fujian Province, Henan Province, 
and Gansu  Province,  respectively.  Firstly,  the  natural  and  social  statistics  of  each  county were 
collected from data found on the internet, and then cadres in the sample villages of each county were 
contacted  to  lead  investigative  groups  into  individual  households.  The  participatory  rural 
evaluation method was used to conduct pre‐surveys and questionnaire surveys. The investigators 
were professionally trained. Each investigator was assigned a local guide to provide directions and 
translate  the  language. All questionnaires were completed  in person. Due  to  the  large number of 
Figure 1. Location map of sample points.
Henan Province in central China, with a topography consisting of mostly plains, has the country’s
largest agricultural population and is one of the provinces with the largest rural poverty population, as
much as 4.63 million [67]. It includes 31 key counties in the poverty alleviation and development effort
at the national level. Among these, Pingyu County is a traditional plain agriculturalcounty, and Xin
County is a typical forestry county in the old revolutionary area located in the hinterlands of the Dabie
Mountains (Figure 1). Both counties are primarily involved in crop farming. Due to the low level of
agricultural production, inadequate production input, and poor ability to resist natural disasters [68],
as well as the serious constraint of a smallholder ideology lacking any sort of market economy concept
or competitive consciousness, poverty and poverty recurrence are prominent. Fujian Province in
eastern China is a typical coastal province with both mountains and seas, but its regional development
is unevenly distributed. The coastal areas in southeast Fujian are relatively developed, while the
mountains in northwest and eastern Fujian are relatively backward, with correspondingly prominent
poverty problems and serious non-income poverty [69]. At present, Fujian still includes 23 provincial
key poverty alleviation development counties [70]. Among them, Songxi and Xiapu Counties are
located in the concentrated areas of poverty-stricken counties in Fujian Province. The former is a
traditional agricultural county in the mountainous areas of northern Fujian Province, while the latter is
Sustainability 2019, 11, 2341 5 of 22
a typical coastal county with the longest coastline and most islands in the country (Figure 1). These
two counties are characterized by a large number of poor inhabitants who returned to poverty due to
illness, or to more severe poverty as a result of disasters [71].
Fujian, Henan, and Gansu Province are the typical representatives of the poverty-stricken areas
in the eastern, central, and western regions, respectively. The six typical counties mentioned above
have the basic characteristics of rural poverty in the eastern, central, and western regions, and they can
adequately reflect the current situation of rural poverty in their respective regions and have certain
representativeness (Figure 2).
Figure 2. Per capita disposable income of rural residents in six sample counties and provinces. Source:
According to the Statistical Yearbook 2017 of each county.
2.2. Data Sources
In July, August, and December 2016, three periods of field investigation and household
questionnaire surveys were conducted over a total of 40 days in Fujian Province, Henan Province, and
Gansu Province, respectively. Firstly, the natural and social statistics of each county were collected
from data found on the internet, and then cadres in the sample villages of each county were contacted
to lead investigative groups into individual households. The participatory rural evaluation method
was used to conduct pre-surveys and questionnaire surveys. The investigators were professionally
trained. Each investigator was assigned a local guide to provide directions and translate the language.
All questionnaires were completed in person. Due to the large number of questions, each questionnaire
took more than 30 min to fill out, and some families were visited and investigated in depth. Since the
problem studied in this paper is ITP, it was necessary to form a sample pairing between the father
and the child. In this study, the first adult child with income is selected as the research object of the
offspring, and the father with income and labor ability is the object of the father’s research. In this
survey, a total of 900 questionnaires were distributed in three provinces, and 879 valid questionnaires
were obtained, with an effectiveness rate of 97.7%. After the questionnaire contents were input into
a Microsoft Excel database, a mathematical statistical method and SPSS 22.0 software were used to
analyze the data. The sample attributes of the respondents are listed in Table 1.
Sustainability 2019, 11, 2341 6 of 22
Table 1. Demographic characteristics of the affected households.
Region Population Size(Person/Household)
Labor Capacity
(Person/Household)
Perennial Number of
Migrant Workers
(Person/Household)
Perennial Number of
Household Farmers
(Person/Household)
Chronic/Severe/
Disabled
Proportion (%)
Eastern (Fujian
Province) 5.74 4.33 1.16 1.56 42.43
Central
(Henan
Province)
6.01 4.17 1.61 1.80 60.85
Western
(Gansu
Province)
5.65 4.16 1.44 1.85 44.40
Note: labor capacity = non-labor population (under 14 years old, over 60 years old) × 0 + half labor force (women,
children and the elderly who can operate easily) × 0.5 + full labor force × 1.
2.3. Variable Selection and Analysis Methods
The population segment analyzed in this study was mainly the rural poor, whose income
intergenerational changes mainly consist of three types: when the income of the father is fixed and the
income of children is lower than that of parents, that is identified as the intergenerational downward
mobility of income; when the income of children is higher than that of their parents, that is identified
as the intergenerational upward mobility of income; and when the income level of children and
parents is the same, that is identified as the intergenerational transmission of income, which is the
most direct and fundamental manifestation characteristic of intergenerational poverty transmission
(Figure 3). The research approach mainly employed the transformation matrix method, and it explained
influence mechanisms using the logistic regression model of multiple classifications. For the selection
of dependent variables in the regression model, upward income flow was taken as the reference group,
and five indicators of livelihood capital were taken as independent variables. At the same time, the
factors influencing downward income flow and income intergenerational transmission were observed.
The main consideration was the downward flow of income, which indicates that the income of the
descendants is lower than that of the parents, and that they are falling into the poverty trap, thus
becoming a new generation of poverty. A deeper analysis of ITP, as well as an exploration of the factors
of downward income flow, will lead to a more in-depth interpretation of ITP. The structure of the
logistic regression model for multiple classifications is as follows:
ln
p
(
y = jx
)
p
(
y = Jx
)  = α j + n∑
k=1
β jkxk, (1)
where j is the dependent variable, J is the reference variable of the dependent variable, p represents the
probability of the intergenerational change type of j income, xk is the independent variable in the table,
α j is a constant, and β jk is the partial regression coefficient.Sustainability 2019, 11, 2341  7  of  22 
 
Figure 3. Three types of intergenerational income. 
3. ITP’s Characteristics and Regional Differentiation 
3.1. General Characteristics of ITP 
The transformation matrix was proposed by Shorrocks in 1978 [72]. This method demonstrates 
liquidity by measuring the changes in the relative position of income, which is the most consistent 
method of definition of income mobility and the least controversial [42,73]. The greatest advantage 
of  this model  is  that  it can make a corresponding study on  the  income or class of  the  father and 
children of different  income  levels or strata. Defining  the  transformation matrix of  father‐to‐child 
income from ya to yb, we get the following equation: 
 
𝑃 𝑦 , 𝑦 𝑃 𝑦 , 𝑦 ∈ 𝑅 ∗   (2) 
where  𝑃 𝑦 , 𝑦 is the father, i is the income class, the children are in the proportion of the income 
class j, and n is the income level classification class. The diagonal value in the matrix indicates the 
proportion of the father and the child’s income in the same class. The bigger the ratio is, the higher 
the income inheritance of the child to the father is. It also means that the higher the intergenerational 
transmission is, the smaller the mobility is. The value at the non‐diagonal position indicates that the 
child and the father at different income levels. 
Based on the field survey data and referring to the absolute poverty line standard in the China 
Rural Poverty Detection Report 2016, the World Bank’spoverty index for developing countries, and 
the disposable income per capita of rural permanent residents in poverty‐stricken areas of China in 
2015, the annual income data nodes were defined as 2,300, 2,900, 8,000, 15,000, and 30,000 renminbi 
(RMB). It should be noted that families with annual incomes greater than 30,000 RMB are generally 
considered to be non‐poor, while the research group in this study consisted primarily of the poor. 
Therefore,  the  intergenerational  transmission of  income  for  the population segment making more 
than 30,000 RMB per year was not  compared and analyzed. Using  the  above  categories,  the  879 
observations  were  divided  into  income  ranks  ranging  from  1  to  6  (Table  2).  A  6  ×  6  income 
conversion matrix was then formed. 
Table 2. Six‐part grouping of parental generation income. RMB—renminbi. 
Index 
Low‐Income 
Group   
Middle–
Low‐Income 
Group 
Middle‐Income 
Group   
Middle–
High‐Income 
Group   
High‐Income 
Group   
— 
Annual income 
(RMB) 
<2,300  2,301–2,900  2,901–8,000  8,001–15,000  15,001–30,000  >30,000 
Conversion 
matrix 
corresponding 
to income rank 
1  2  3  4  5  6 
To  explore  the  intergenerational  transmission  of  income  between  fathers  and  children,  the 
distribution  of  income  level  between  them  was  differentiated  (Figure  4).  Across  the  entire 
observation group, there was a higher proportion of fathers having lower income levels than their 
Figure 3. Three types of intergenerational income.
Sustainability 2019, 11, 2341 7 of 22
3. ITP’s Characteristics and Regional Differentiation
3.1. General Characteristics of ITP
The transformation matrix was proposed by Shorrocks in 1978 [72]. This method demonstrates
liquidity by measuring the changes in the relative position of income, which is the most consistent
method of definition of income mobility and the least controversial [42,73]. The greatest advantage of
this model is that it can make a corresponding study on the income or class of the father and children
of different income levels or strata. Defining the transformation matrix of father-to-child income from
ya to yb, we get the following equation:
P(ya, yb) =
[
Pi j(ya, yb)
]
∈ Rn∗n (2)
where P(ya, yb) is the father, i is the income class, the children are in the proportion of the income
class j, and n is the income level classification class. The diagonal value in the matrix indicates the
proportion of the father and the child’s income in the same class. The bigger the ratio is, the higher
the income inheritance of the child to the father is. It also means that the higher the intergenerational
transmission is, the smaller the mobility is. The value at the non-diagonal position indicates that the
child and the father at different income levels.
Based on the field survey data and referring to the absolute poverty line standard in the China
Rural Poverty Detection Report 2016, the World Bank’s poverty index for developing countries, and
the disposable income per capita of rural permanent residents in poverty-stricken areas of China in
2015, the annual income data nodes were defined as 2300, 2900, 8000, 15,000, and 30,000 renminbi
(RMB). It should be noted that families with annual incomes greater than 30,000 RMB are generally
considered to be non-poor, while the research group in this study consisted primarily of the poor.
Therefore, the intergenerational transmission of income for the population segment making more than
30,000 RMB per year was not compared and analyzed. Using the above categories, the 879 observations
were divided into income ranks ranging from 1 to 6 (Table 2). A 6 × 6 income conversion matrix was
then formed.
Table 2. Six-part grouping of parental generation income. RMB—renminbi.
Index Low-IncomeGroup
Middle–Low-Income
Group
Middle-Income
Group
Middle–High-Income
Group
High-Income
Group —
Annual income
(RMB) <2300 2301–2900 2901–8000 8001–15,000 15,001–30,000 >30,000
Conversion
matrix
corresponding
to income rank
1 2 3 4 5 6
To explore the intergenerational transmission of income between fathers and children,
the distribution of income level between them was differentiated (Figure 4). Across the entire
observation group, there was a higher proportion of fathers having lower income levels than their
children. The proportion of fathers whose incomes were less than or equal to 2900 RMB was as high
as 41.87%, and only 17.52% had income levels greater than 15,000 RMB. The proportion of children’s
incomes exceeding 15,000 RMB was greater than 50%, but 20% of them still had incomes below 2900
RMB. The above analysis shows that there was a large gap between the income levels of fathers and
children. Regionally, the highest proportion of fathers’ incomes was less than or equal to 2900 RMB
and exhibited a decreasing trend from west to central to east, while the highest proportion of children’s
incomes was greater than 15,000 RMB, and exhibited a decreasing trend from east to central to west,
which is consistent with the gradient pattern of China’s economic development.
Sustainability 2019, 11, 2341 8 of 22
Sustainability 2019, 11, 2341  8  of  22 
children. The proportion of fathers whose incomes were less than or equal to 2,900 RMB was as high 
as 41.87%, and only 17.52% had income levels greater than 15,000 RMB. The proportion of children’s 
incomes exceeding 15,000 RMB was greater than 50%, but 20% of them still had incomes below 2,900 
RMB. The above analysis shows that there was a large gap between the income levels of fathers and 
children. Regionally, the highest proportion of fathers’ incomes was less than or equal to 2,900 RMB 
and  exhibited  a  decreasing  trend  from west  to  central  to  east, while  the  highest  proportion  of 
children’s  incomes was  greater  than  15,000 RMB,  and  exhibited  a decreasing  trend  from  east  to 
central to west, which is consistent with the gradient pattern of China’s economic development. 
  
(a) All observations.  (b) Eastern region. 
 
(c) Central region.  (d) Western region. 
Figure 4. (a) All observations. (b) Eastern region. (c) Central region. (d) Western region. 
From Table 3 and Figure 5, it can be observed intuitively that the intergenerational transmission 
of income across the entire observations group was higher in the high‐income, middle–high‐income, 
and  low‐income  groups,  and  exhibited  obvious  intergenerational  transmission  characteristics  of 
poverty. Specifically, the highest intergenerational transmission rate was 45.71% in the high‐income 
group, followed by 27.83% in the middle–high‐income group, and 19.84% in the low‐income group. 
In terms of income upward mobility, the descendants of a particular income class exhibit an upward 
mobility trend that gradually strengthens from high income to low, indicating an increasing desire 
for upward mobility as income decreases. In the process of achieving upward mobility, the lower the 
income class is, the easier it is to achieve class spanning. Higher income groups, meanwhile, have a 
lower  possibility  of  achieving  class  spanning.  In  terms  of  income  downward  mobility,  the 
descendant  income class shows a  tortuous downward  trend  from  the high‐income  to  low‐income 
41.87%
11.38%
16.15%
13.08%11.95%
5.57%
16.04%
4.10%
9.56%
14.11%
28.90%
27.30%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 2 3 4 5 6
All observations (father)
All observations (children)
40.00%
6.44%
10.51%
14.58%
18.98%
9.49%
11.19%
3.39%
5.76%
13.56%
39.32%
26.78%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 2 3 4 5 6
Eastern region (father)
Eastern region (children)
38.41%
11.76%
23.53%
11.42%
9.34%
5.54%
16.96%
3.46%
7.96% 8.65%
26.64%
36.33%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 2 3 4 5 6
Central region (father)
Central region (children)
47.12%
15.93%
14.58%
13.22%
7.46%
1.69%
20.00%
5.42%
14.92%
20.00%
20.68%
18.98%
0%
5%
10%15%
20%
25%
30%
35%
40%
45%
50%
1 2 3 4 5 6
Western region (father)
Western region (children)
Figure 4. (a) All observations. (b) Eastern region. (c) Central region. (d) Western region.
From Table 3 and Figure 5, it can be observed intuitively that the intergenerational transmission of
income across the entire observations group was higher in the high-income, middle–high-income, and
low-income groups, and exhibited obvious intergenerational transmission characteristics of poverty.
Specifically, the highest intergenerational transmission rate was 45.71% in the high-income group,
followed by 27.83% in the middle–high-income group, and 19.84% in the low-income group. In terms
of income upward mobility, the descendants of a particular income class exhibit an upward mobility
trend that gradually strengthens from high income to low, indicating an increasing desire for upward
mobility as income decreases. In the process of achieving upward mobility, the lower the income
class is, the easier it is to achieve class spanning. Higher income groups, meanwhile, have a lower
possibility of achieving class spanning. In terms of income downward mobility, the descendant income
class shows a tortuous downward trend from the high-income to low-income groups. Among them,
the descendant income downward mobility ratio of the high-income group was as high as 30.48%
(not including incomes greater than 30,000 RMB). This reflects descendants whose parents were in
the high-income level but, due to income retrogression, are likely to fall into the “poverty trap” and
become a new “poor second generation”.
Sustainability 2019, 11, 2341 9 of 22
Table 3. Intergenerational revenue conversion frequency (all observations) (%).
Six Categories of
Father’s Income
Six Categories of Children Income
Total
1 2 3 4 5 6
1 19.84 4.08 9.24 14.13 30.16 22.55 100
2 15.00 4.00 13.00 16.00 20.00 32.00 100
3 14.08 8.45 11.97 9.86 28.17 27.46 100
4 9.57 2.61 6.96 27.83 20.87 32.17 100
5 14.29 0.95 8.57 6.67 45.71 23.81 100
6 14.29 2.04 6.12 6.12 22.45 48.98 100
Note: The white cell indicates that the income of the father is on the same order as that of the children, the dark-gray
cell indicates that the income of the father is fixed and the income of the children is upward, and the light-gray cell
indicates a downward trend.
Sustainability 2019, 11, 2341  9  of  22 
groups. Among them, the descendant  income downward mobility ratio of the high‐income group 
was as high as 30.48% (not including incomes greater than 30,000 RMB). This reflects descendants 
whose parents were in the high‐income level but, due to income retrogression, are likely to fall into 
the “poverty trap” and become a new “poor second generation”. 
Table 3. Intergenerational revenue conversion frequency (all observations) (%). 
Six 
Categories 
of Father’s 
Income 
Six Categories of Children Income 
Total 
1  2  3  4  5  6 
1  19.84  4.08  9.24  14.13  30.16  22.55  100 
2  15.00  4.00  13.00  16.00  20.00  32.00  100 
3  14.08  8.45  11.97  9.86  28.17  27.46  100 
4  9.57  2.61  6.96  27.83  20.87  32.17  100 
5  14.29  0.95  8.57  6.67  45.71  23.81  100 
6  14.29  2.04  6.12  6.12  22.45  48.98  100 
Note:  The white  cell  indicates  that  the  income  of  the  father  is  on  the  same  order  as  that  of  the 
children,  the dark‐gray  cell  indicates  that  the  income of  the  father  is  fixed and  the  income of  the 
children is upward, and the light‐gray cell indicates a downward trend. 
 
Figure 5.  Intergenerational mobility of  income for generations (all observations). Note: The dotted 
line  in  the  table  is an observation of  income exceeding 30,000  renminbi  (RMB), which  is only  for 
reference and not for specific analysis. 
3.2. Regional Differences of ITP in the Eastern, Central, and Western Regions 
The corresponding numbers of observations of fathers and children in the eastern, central, and 
western regions were 295, 289, and 295 pairs, respectively. From Figure 6b, it can be concluded that 
the  intergenerational  transmission  rate  of  income  in  the  high‐income  group was  highest  in  the 
eastern region, while the rate in the middle–low‐income and low‐income groups were highest in the 
central  region.  In  the western  region,  the  intergenerational  transmission  rates  in  the  low‐income, 
middle–high‐income, and middle‐income groups were higher  than  those  in  the other  two regions 
(Table 4, Table 5). From the perspective of internal differences (Table 4, Figure 6), in the high‐income 
group,  the  intergenerational  transmission  of  income decreased  from  east  to west.  In  the  eastern 
region, more than half of the children’s and fathers’ income levels were in the same class (53.57%). 
This  income  class  exhibited  obvious  characteristics  of  ITP,  and  the  intergenerational mobility  of 
income was low. In the low‐, middle‐, and high‐income groups, the intergenerational transmission 
rates of income increased from east to west. The intergenerational transmission rate of income in the 
western region was found to be higher than the rates in the central and eastern regions. That is to 
say,  the  social mobility  in  the western  region was  lower  than  that  in  the other  two  regions,  thus 
indicating that the degree of social openness in this region needs to be further improved. It is also 
Figure 5. Intergenerational mobility of income for generations (all observations). Note: The dotted line
in the table is an observation of income exceeding 30,000 renminbi (RMB), which is only for reference
and not for specific analysis.
3.2. Regional Differences of ITP in the Eastern, Central, and Western Regions
The corresponding numbers of observations of fathers and children in the eastern, central, and
western regions were 295, 289, and 295 pairs, respectively. From Figure 6b, it can be concluded
that the intergenerational transmission rate of income in the high-income group was highest in the
eastern region, while the rate in the middle–low-income and low-income groups were highest in the
central region. In the western region, the intergenerational transmission rates in the low-income,
middle–high-income, and middle-income groups were higher than those in the other two regions
(Tables 4 and 5). From the perspective of internal differences (Table 4, Figure 6), in the high-income
group, the intergenerational transmission of income decreased from east to west. In the eastern region,
more than half of the children’s and fathers’ income levels were in the same class (53.57%). This income
class exhibited obvious characteristics of ITP, and the intergenerational mobility of income was low.
In the low-, middle-, and high-income groups, the intergenerational transmission rates of income
increased from east to west. The intergenerational transmission rate of income in the western region
was found to be higher than the rates in the central and eastern regions. That is to say, the social
mobility in the western region was lower than that in the other two regions, thus indicating that the
degree of social openness in this region needs to be further improved. It is also more difficult for
children in these income groups to rise into the upper class. In the middle–low-income group, the
intergenerational transmission rates of income were generally low, with the rate in the central region
greater than the rates in the eastern and western regions. It is worth mentioning that, from Figure 6b,
Sustainability 2019, 11, 2341 10 of 22
it can be observed that the ratio between the highest- and lowest-income transmission groups was
higher in the eastern region than in the central and western regions, confirming the characteristic of
highly differentiated income in the rural poor groups of eastern China, a finding that is consistent with
the conclusions drawn by other researchers [74].
Sustainability 2019, 11, 2341  11  of  22 
Table  5.  Comparison  of  intergenerational  incometransfer  rates  in  eastern,  central,  and western 
regions in China. 
Category (RMB)  <2,300  2,301–2,900  2,901–8,000  8,001–15,000  15,001–30,000 
Intergenerational 
transmission rate of 
income 
Western > 
central > 
eastern 
Central > 
eastern > 
western 
Western > 
central > 
eastern 
Western > 
central > 
eastern 
Eastern > 
  central >   
western 
 
     
(a) Downward mobility of children 
income. 
(b) Intergenerational transmission rate 
of children income. 
(c) Upward mobility of children 
income. 
Figure 6. Intergenerational mobility of income for generations (Eastern, central, western regions). 
Note: The dotted line in the table is an observation of income exceeding 30,000 RMB, which is only 
for reference and not for specific analysis. 
4. Mechanisms of ITP 
4.1. Model Variable Selection and Specific Operation 
The  selection  of  independent  variables  in  this  study was mainly  based  on  the  sustainable 
livelihood analysis  framework of  the Department  for  International Development,  referring  to  the 
quantitative  research  on  livelihood  capital  performed  by  Sharp  (2003)  in  Africa  [61]  and  the 
vulnerability analysis method of farmers and its localization application by Li [75]. In this study, we 
designed  the  households  interviewed  in  terms  of  different  research  units  in  China  for  family 
livelihood capital quantitative numerical measurements (Table 6). 
Table 6. Livelihood capital indicators. 
Types of 
Capital 
Measurement Index 
Index 
Symbol 
Assignment 
Human 
capital (H) 
Labor capacity  L1 
Non‐labor population (under 14 years old, over 60 
years old) = 0, half labor force (women, children 
and the elderly who can operate easily) = 0.5, full 
labor force = 1 
Educational years of head of 
household 
L2  Educational years (take the logarithm) 
Natural 
capital (N) 
Per capita farmland/farming/grazing 
area of the family 
N1 
Family total cultivated land (cultivated 
land/farming/grazing area)/total family population 
(take the logarithm) 
Physical 
capital (P) 
Family housing situation  P1 
Owning property: fewer= 1, few = 2, general = 3, 
many = 4, a great many = 5 
Housing type: grass house = 1, civil house = 2, 
wood house = 3, brick house = 4, concrete house = 5
Household fixed capital  P2 
There are several kinds of large machines: none = 1, 
one = 2, two = 3, three = 4, four or more = 5 
There are several kinds of durable consumer 
goods: none = 1, one = 2, two = 3, three = 4, four or 
Figure 6. Intergenerational mobility of income for generations (Eastern, central, western regions).
Note: The dotted line in the table is an observation of income exceeding 30,000 RMB, which is only for
reference and not for specific analysis.
Table 4. The frequency of intergenerational income transfers in eastern, central, and western regions in
China (%).
(a)
Fujian
Province
Six Categories of
Father’s Income
Six Categories of Children Income
Total
1 2 3 4 5 6
1 13.56 4.24 5.93 15.25 38.14 22.88 100
2 5.26 5.26 26.32 5.26 31.58 26.32 100
3 9.68 9.68 3.23 16.13 35.48 25.81 100
4 4.65 2.33 0.00 20.93 37.21 34.88 100
5 8.93 0.00 3.57 8.93 53.57 25.00 100
6 21.43 0.00 7.14 7.14 28.57 35.71 100
(b)
Henan
Province
Six Categories of
Father’s Income
Six Categories of Children Income
Total
1 2 3 4 5 6
1 18.92 2.70 8.11 8.11 35.14 27.03 100
2 14.71 5.88 8.82 8.82 8.82 52.94 100
3 16.18 4.41 7.35 4.41 29.41 38.24 100
4 18.18 0.00 3.03 27.27 9.09 42.42 100
5 18.52 3.70 14.81 0.00 37.04 25.93 100
6 6.25 6.25 6.25 6.25 12.50 62.50 100
(c)
Gansu
Province
Six Categories of
Father’s Income
Six Categories of Children Income
Total
1 2 3 4 5 6
1 25.90 5.04 12.95 17.99 19.42 18.71 100
2 19.15 2.13 10.64 25.53 23.40 19.15 100
3 13.95 13.95 25.58 13.95 20.93 11.63 100
4 7.69 5.13 17.95 35.90 12.82 20.51 100
5 22.73 0.00 13.64 9.09 36.36 18.18 100
6 0.00 0.00 0.00 0.00 20.00 80.00 100
Note: The white cell indicates that the income of the father is on the same order as that of the children, the dark-gray
cell indicates that the income of the father is fixed and the income of the children is upward, and the light-gray cell
indicates a downward trend.
Sustainability 2019, 11, 2341 11 of 22
Table 5. Comparison of intergenerational income transfer rates in eastern, central, and western regions
in China.
Category (RMB) <2300 2301–2900 2901–8000 8001–15,000 15,001–30,000
Intergenerational
transmission rate of
income
Western >
central >
eastern
Central >
eastern >
western
Western >
central >
eastern
Western >
central >
eastern
Eastern >
central >
western
In terms of the intergenerational mobility of income (Figure 6a,c), the upward mobility rates of
all income classes in the eastern region were discovered to be higher than the rates in the central and
western regions, while the downward mobility rates of all income classes in the western region were
higher than those in the eastern and central regions. This trend indicates that the higher the income
level and the more developed the economy are, the higher the upward mobility of the children’s
income class will be. The lower the income level and the more backward the economy are, the more
significant the downward mobility of the income class of the children will be. The next generation will
enter the struggle to eliminate poverty, making the transmission cycle of poverty from generation to
generation longer and more difficult to eradicate.
4. Mechanisms of ITP
4.1. Model Variable Selection and Specific Operation
The selection of independent variables in this study was mainly based on the sustainable livelihood
analysis framework of the Department for International Development, referring to the quantitative
research on livelihood capital performed by Sharp (2003) in Africa [61] and the vulnerability analysis
method of farmers and its localization application by Li [75]. In this study, we designed the households
interviewed in terms of different research units in China for family livelihood capital quantitative
numerical measurements (Table 6).
Table 6. Livelihood capital indicators.
Types of Capital Measurement Index Index Symbol Assignment
Human capital (H)
Labor capacity L1
Non-labor population (under 14 years old, over
60 years old) = 0, half labor force (women, children
and the elderly who can operate easily) = 0.5,
full labor force = 1
Educational years of head of
household L2 Educational years (take the logarithm)
Natural capital (N)
Per capita
farmland/farming/grazing
area of the family
N1
Family total cultivated land (cultivated
land/farming/grazing area)/total family population
(take the logarithm)
Physical capital (P)
Family housing situation P1
Owning property: fewer= 1, few = 2, general = 3,
many = 4, a great many = 5
Housing type: grass house = 1, civil house = 2,
wood house = 3, brick house = 4,
concrete house = 5
Household fixed capital P2
There are several kinds of large machines: none =
1, one = 2, two = 3, three = 4, four or more = 5
There are several kinds of durable consumer goods:
none = 1, one = 2, two = 3, three = 4,
four or more = 5
Financial capital (F)
Per capita household income
(RMB) F1
2300 and below = 1, 2301–2900 = 2, 2901–8000 = 3,
8001–15,000 = 4, 15,001–30,000 = 5
Access to credit (both formal
and informal channels) F2 Yes = 1, no = 0
Social capital (S)
Whether or not any family
member holds the post of state
functionary or village cadre
S1 Yes = 1, no = 0
Whether or not families
receive assistance when they
are in trouble
S2 Yes = 1, no = 0
Sustainability 2019, 11, 2341 12 of 22
All variables were simultaneously input into multiple multi-classification logistic regression
models with Stata. The Hausman test showed that the model was suitable for random effects (the value
of p > χ2 are greater than 0.05) (Table 7); therefore, we could proceed by applying the multinomial
logistic model. We firstly conducted a regression analysis. However, due to the mentioned limitationsof the multinomial logistic regression model, marginal effects were used for a better interpretation of
the results [59] (Table 8).
Table 7. Suest-based Hausman test of independence of irrelevant alternatives (IIA) assumption.
HO: Odds (Outcome-J vs. Outcome-K) Are Independent of Other Alternatives
Outcome χ2 df p > χ2
Y1 10.965 11 0.360
Y2 8.362 11 0.681
Y3 15.566 11 0.212
Note: A significant test is evidence against Ho. Y1: intergenerational downward mobility of income;
Y2: intergenerational transmission of income; Y3: intergenerational upward mobility of income.
Sustainability 2019, 11, 2341 13 of 22
Table 8. Multivariate logistic regression estimates.
Types of Capital Variable Index
All Observations (Model 1) Eastern Region (Model 2) Central Region (Model 3) Western Region (Model 4)
Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2
Dy/dx Dy/dx Dy/dx Dy/dx Dy/dx Dy/dx Dy/dx Dy/dx
Human capital (H)
Labor capacity (L1) −0.074 0.105 −0.080 0.019 −0.134 0.046 −0.209 ** −0.102
Educational years of head of household (L2) −0.048 −0.047 −0.057 −0.162 −0.108 0.052 −0.024 −0.152 *
Natural capital (N) Per capita farmland/farming/grazing area (N1) −0.006 −0.001 −0.002 −0.023 ** −0.034 * 0.020 −0.022 0.022
Physical capital (P)
Household ownership of property (a great
many) (P11)
Fewer 0.048 *** 0.115 *** −0.028 0.033 0.061 0.100 *** 0.061 0.370 ***
Few 0.006 *** 0.151 *** −0.020 0.082 0.071 0.118 *** 0.010 0.370 ***
General 0.030 *** 0.195 *** −0.015 −0.053 0.081 0.286 0.056 0.331 ***
Many 0.101 0.341 - - - - 0.143 0.593
Housing type (concrete house) (P12)
Grass house 0.088 0.034 - - - - 0.010 0.099 ***
Civil house 0.093 0.045 ** - - - - 0.031 0.024 ***
Wood house 0.079 0.016 ** - - - - 0.012 0.013 ***
Brick house 0.031 0.058 * - - - - 0.167 0.280
The number of machines in the household (four
or more) (P21)
None −0.027 ** −0.045 0.020 0.089 −0.066 −0.065 ** −0.081 ** 0.260
One −0.065 ** −0.008 * 0.004 0.020 −0.130 * −0.028 ** −0.081 ** 0.233
Two −0.050 −0.044 0.008 0.165 −0.118 −0.005 * −0.036 ** 0.230
Three −0.112 −0.033 0.090 0.193 −0.170 −0.177 −0.354 ** 0.417
The number of durable consumer goods in the
household (four or more) (P22)
None 0.003 0.030 −0.066 0.207 0.301 0.019 0.224 0.171
One 0.065 ** 0.122 0.054 0.101 −0.403 ** −0.115 0.145 0.373
Two 0.081 ** 0.007 ** −0.021 0.322 0.440 ** 0.158 −0.107 * 0.196
Three 0.122 0.022 −0.001 −0.193 ** 0.054 ** 0.073* −0.388 ** 0.205
Sustainability 2019, 11, 2341 14 of 22
Table 8. Cont.
Types of Capital Variable Index
All Observations (Model 1) Eastern Region (Model 2) Central Region (Model 3) Western Region (Model 4)
Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2
Financial capital (F)
Per capita household income
(RMB) (15,001–30,000) (F1)
2300 and below −0.142 −0.152 *** −0.038 −0.067 *** −0.191 −0.106 ** −0.200 −0.221 ***
2301–2900 −0.235 *** −0.713 *** −0.197 ** −0.095 *** −0.226 ** −0.126 ** −0.293 *** −0.006 ***
2901–8000 −0.211 *** −0.084 *** −0.086 −0.047 *** −0.025 ** −0.023 *** −0.033 * −0.082 **
8001–15,000 −0.324 *** −0.281 *** −0.019 ** −0.049 *** −0.403 −0.140 * −0.420 * −0.156 *
Access to credit (yes) (F2)
No 0.376 * 0.516 ** 0.044 0.032 0.023 0.059 0.074 ** 0.005
Social capital (S)
Are there any members of the family serving as
state cadres (yes) (S1)
No 0.055 * 0.320 0.030 −0.060 0.039 0.058 0.058 0.080
Are families in distress assisted (yes)(S2)
No −0.084 *** −0.046 ** −0.044 * −0.163 −0.115 ** −0.004 −0.095 * −0.039
Intercept −31.682 −15.283 −20.349 1.521 −14.178 −15.641 −24.207 −32.842
Chi-square value 324.88 *** 149.91 *** 135.71 *** 176.51 ***
Cox and Snell 0.342 0.473 0.422 0.537
Note: In parentheses, the reference group is provided; * p < 0.1, ** p < 0.05, *** p < 0.01. Y1: intergenerational downward mobility of income; Y2: intergenerational transmission of income.
Sustainability 2019, 11, 2341 15 of 22
4.2. Model Regression Results and Interpretation
Influencing factors of ITP include human capital, natural capital, physical capital, financial capital
and social capital in eastern, central, and western regions. These capitals have different ways of
influence and significance in various regions, as shown in Figure 7.
Sustainability 2019, 11, 2341  17  of  22 
returned to the village to drive the villagers to become wealthy”, the proportion of “yes” answers in 
the eastern region was much higher than the proportions in the central and western regions, while 
the proportion of “no” answers in the western region was the highest of the three study areas, which 
also reflected the fact that the eastern region was relatively developed. The higher the proportion of 
“rural elite”  is,  the  stronger  the  role of  the  clan  relationship network and  the higher  the  level of 
intergenerational  income  transmission  between  generations  are.  This  indicates  that  the 
intergenerational transmission of high income is predominant. It also tangentially indicates that, in 
the western region, where social capital is generally scarce, the available and accessible social capital 
is  extremely  limited,  increasing  the  likelihood  of  low‐income  intergenerational  poverty 
transmission. The extremely scarce social capital in the western region makes it more difficult to get 
rid of poverty, and we should pay close attention to it [80,81]. 
 
Figure 7. Influencing factors of intergenerational transmission of poverty (ITP) in eastern, central, 
and western regions. 
5. Conclusions, Discussions, and Policy Implications 
5.1. Conclusions and Discussion 
Based on 879 rural poverty questionnaires collected in survey, this study explored ITP in China 
and the factors affecting it. From this research, we can draw the following conclusions: 
(1) The income levels of rural fathers and their children are noticeably different. Fathers had the 
highest proportion of  lower  incomes  in our study observations, with  this proportion exhibiting a 
decreasing  “western–central–eastern”  trend, while  their  children  had  the  highest  proportion  of 
higher  incomes,  with  this  proportion  exhibiting  a  decreasing  “eastern–central–western”  trend, 
coinciding with the gradient pattern of China’s economic development. 
(2)  ITP  in  China  is  characterized  by  income  class  differentiation.  Among  the  low‐income 
groups, the groups at both ends of this income level are more likely to experience ITP. In terms of 
liquidity,  the  lower‐income  generation  shows  the  strongest  upward  mobility  trend,  while  the 
higher‐income generation shows a more obvious downward mobility trend. 
(3)  ITP  among  different  strata  highlights  the  solidification  of  income  in  the  poor  strata  of 
society. The  intergenerational mobility of  income  is an  important manifestation of  the mobility of 
social  income strata, which tends to change  in either the same direction or the opposite direction. 
Among these strata, the economically developed eastern region exhibits a reverse trend, especially 
for  ITP  in  the high‐income group, while  the upward mobility of children’s  income  in  the eastern 
region  is more  significant, which  is more  likely  to block  ITP. The  economically underdeveloped 
central and western regions have the most prominent ITP in the middle‐ and  low‐income groups, 
where  children’s  income  has  a  downstream  relationship with  the  income  of  their  fathers.  The 
dynamic trend is more obvious, and it is more likely for children to fall into the poverty trap in these 
regions. 
Figure 7. Influencing factors of intergenerational transmission of poverty (ITP) in eastern, central, and
western regions.
4.2.1. Impact of Human Capital on ITP
ITP is affected to a certain extent by the family labor capacity and the educational level of the head
of the family. Both of these factors play a more obvious role in the western part of China. In western
rural poor families, the smaller a family’s labor capacity and the lower its education level are, the
more likely its children’s incomeswill be downwardly mobile, thus increasing the likelihood that
the next generation will fall into the poverty trap. This makes it more difficult to interrupt ITP and
realize the upward flow of income. Families with large labor ability and a father’s high education level
will reduce 20.1% and 15.2% of the possibility of their child to fall into ITP, respectively. This is also
consistent with the conclusions reached by some scholars that human capital plays an important role
in ITP [76,77]. Gansu Province has the smallest population of the three provinces investigated in this
study, with an average of 5.652 people per household, as well as the weakest family labor capacity, with
an average of 4.155 people per household. Through the survey data, we also learned that the hollowing
out of rural areas in the western region is more serious than expected. The villages are filled with
empty nesters, left-behind children, and women. The main labor force decreased, while the number
of children increased. Heads of household are consumed with the heavy burden of making a living,
leaving them little time to care for their children or to improve their educational level. The inadequate
investment of educational capital combined with heavy family labor makes any family resources that
can be obtained and absorbed by the descendants in the western region extremely limited, and the lack
of human capital increases the likelihood of the intergenerational transmission of low income.
4.2.2. Impact of Natural Capital on ITP
The per capita amount of land owned by a family is the most important factor in a farmer’s
livelihood. The main source of the income of a farmer depends on the productivity per unit area
of land. This variable has a significant impact on ITP in the eastern and central regions. The less
natural capital and land income there is, the more prone a region is to ITP. Among these areas, Fujian
Province in the eastern region consists of hills and low mountains, with limited arable land. Due to
this topography, farms are located mainly on beaches or in shallow seas. Although their income
levels are higher than those of farmers in the central and western regions, they are vulnerable to
extreme weather events such as typhoons, floods, and heat waves. The instability factors of agricultural
Sustainability 2019, 11, 2341 16 of 22
output and income dominate in this region (the proportion of non-agricultural/aquatic income last
year was as high as 21.7%). This is also consistent with the conclusions reached by some scholars that
natural capital plays an important role in ITP in coastal areas [78]. Henan Province in central China
covers a large area and has a high output of agricultural products, but its main difficulty concerns
the low price of these products. The results of a farmer’s hard work over the course of a year are
sometimes insufficient to pay for land expenditure. In the eastern and central regions, where farming
and cultivation predominate, it is common for both parents and children to have farming-related
occupations. Their overall income will also be affected by family natural capital and its associated
income, resulting in a higher intergenerational transmission rate in the high-income groups of the
eastern region, while the intergenerational transmission rate in the middle- and low-income groups is
more prominent in the central region.
4.2.3. Impact of Physical Capital on ITP
Physical capital variables include two factors: one is the number and structural type of houses
owned by families; the other is the number of large-scale machines and durable consumer products
owned by families. The former is an important material way for farmers to obtain a stable life; the
latter is the means and methods for farmers to achieve diversified production. From the point of view
of the overall observations model, both of these factors played a particular role in ITP. Physical capital
had the most significant impact on the western region. In terms of housing structure, only 31.86% of
the rural homes in the western region are constructed of brick or steel concrete, while 39.32% are made
of adobe. The likelihood of a child with poor family housing falling into ITP will increase by 37%.
In terms of large-scale appliances and durable consumer goods, the most basic household durable
consumer goods (such as televisions and radios) are still the predominant ones in the western region,
while the farmers in the central and eastern regions have new-generation tools and modern production
equipment. This factor directly affects the diversification level of farmers’ livelihoods and will have
a certain impact on the income level of the two generations. Family children with fewer household
appliances and durable consumer goods are more likely to fall into ITP by 8.1%. In addition, family
housing conditions limit the convertible capital of peasant households available when facing risks,
further aggravating ITP among the low-income strata in the western region.
4.2.4. Impact of Financial Capital on ITP
Financial capital had a significant impact on ITP in all three study regions, but there were some
differences among them. On one hand, 28.44% of the fathers and children in the eastern region were
engaged in fishery production activities, and most of their families’ per capita income was concentrated
in the 15,001–30,000 RMB range. Therefore, the eastern region, with its higher per capita income,
was more likely to have greater income transmission between generations, while the western region,
with poor income from land-farming activities, was more likely to have lower income transmission
from fathers and children, increasing the likelihood that the children will fall into a vicious circle
of poverty. For example, in the central and western regions, families with a per capita income of
2301–2900 RMB had a 22.6% and 29.3% increase, respectively, in the possibility of ITP among their
descendants. On the other hand, compared to farmers with credit opportunities, families without
credit opportunities were more likely to fall into the intergenerational downward mobility of income,
as well as the intergenerational transmission of income, a phenomenon that was more pronounced in
the western region. The main reason for this disparity is that the eastern region is located in relatively
developed coastal areas, where farmers have more business opportunities, more awareness, and
opportunities to obtain credit (71.19% in eastern China, 69.20% in central China, and 59.32% in western
China); thus, the ability to enhance financial capital is strong. Farmers in the western region mainly
farm the land and work part-time, making the demand for credit less than that in the central and
eastern regions. Some farmers who get credit on time just to obtain the interest cannot effectively
transform capital and increase income. These factors further contributed to the differences between the
Sustainability 2019, 11, 2341 17 of 22
levels of ITP in the eastern and western regions. The lack of financial capital led to the deepening of
long-term poverty and limited ability to fight poverty [79].
4.2.5. Impact of Social Capital on ITP
Social capital is mainly realized through family politicians and clan networks in rural society, and
plays a subtle regulatory role in rural acquaintance society. This variable also exhibited a significant
impact on ITP. The poorer a family’s social capital is, the greater the possibility of ITP is, which
highlights the suffering of poor families in rural areas. When disaster strikes, a poor family’s weak
social network is insufficient to benefit fully from the help of others and of social teams, leading to
more difficulties for poor families, more of a struggle for their descendants to escape the poverty
trap, and a greater likelihood of the transmission of poverty between generations. Our survey results
demonstrated that this phenomenon was most obvious in the western region. The likelihood of
children in western ruralfamilies who did not receive credit and social assistance fell into ITP by
7.4% and 9.5% respectively. In addition, when asked whether “the wealthiest people in the village
play a helping role with the villagers” and “whether the wealthiest people in the village returned to
the village to invest in the village, and whether officials or other successful people returned to the
village to drive the villagers to become wealthy”, the proportion of “yes” answers in the eastern region
was much higher than the proportions in the central and western regions, while the proportion of
“no” answers in the western region was the highest of the three study areas, which also reflected the
fact that the eastern region was relatively developed. The higher the proportion of “rural elite” is,
the stronger the role of the clan relationship network and the higher the level of intergenerational
income transmission between generations are. This indicates that the intergenerational transmission of
high income is predominant. It also tangentially indicates that, in the western region, where social
capital is generally scarce, the available and accessible social capital is extremely limited, increasing the
likelihood of low-income intergenerational poverty transmission. The extremely scarce social capital
in the western region makes it more difficult to get rid of poverty, and we should pay close attention to
it [80,81].
5. Conclusions, Discussions, and Policy Implications
5.1. Conclusions and Discussion
Based on 879 rural poverty questionnaires collected in survey, this study explored ITP in China
and the factors affecting it. From this research, we can draw the following conclusions:
(1) The income levels of rural fathers and their children are noticeably different. Fathers had
the highest proportion of lower incomes in our study observations, with this proportion exhibiting a
decreasing “western–central–eastern” trend, while their children had the highest proportion of higher
incomes, with this proportion exhibiting a decreasing “eastern–central–western” trend, coinciding
with the gradient pattern of China’s economic development.
(2) ITP in China is characterized by income class differentiation. Among the low-income groups,
the groups at both ends of this income level are more likely to experience ITP. In terms of liquidity,
the lower-income generation shows the strongest upward mobility trend, while the higher-income
generation shows a more obvious downward mobility trend.
(3) ITP among different strata highlights the solidification of income in the poor strata of society.
The intergenerational mobility of income is an important manifestation of the mobility of social income
strata, which tends to change in either the same direction or the opposite direction. Among these
strata, the economically developed eastern region exhibits a reverse trend, especially for ITP in the
high-income group, while the upward mobility of children’s income in the eastern region is more
significant, which is more likely to block ITP. The economically underdeveloped central and western
regions have the most prominent ITP in the middle- and low-income groups, where children’s income
Sustainability 2019, 11, 2341 18 of 22
has a downstream relationship with the income of their fathers. The dynamic trend is more obvious,
and it is more likely for children to fall into the poverty trap in these regions.
(4) The influence of human, natural, physical, financial, and social capital on ITP varies among
the eastern, central, and western regions, with financial capital exerting the most significant influence.
In addition, natural capital plays a significant role in the eastern region, where the intergenerational
transmission of high income is most prominent. Physical capital predominates in the central region,
where the intergenerational transmission of low- and middle–low-income groups is greatest, and both
human and physical capital play obvious roles in the western region, mainly characterized by the
intergenerational transmission of low income. At present, the influence of human and natural capital is
weakened in China’s ITP. Correspondingly, family material capital and financial capital will gradually
come to play greater roles. Social capital, as a delicate array of networks, plays an important role in
rural society, although it is often neglected. This type of capital requires additional attention.
As an important factor affecting ITP, China should explore and summarize the lack of livelihood
capital in its eastern, central, and western regions. More attention should be paid to the sustainable
construction of livelihood capital in poor peasant households; the diversification of livelihoods should
be enhanced, and the stock of “heredity” capital to offspring should be increased. In addition, the
problem of ITP is affected by numerous factors, not just the family’s five major livelihood capital factors,
but also the social system, economic environment, poverty alleviation policies, and other aspects.
Future research can strengthen the impact of medium- and macro-factors on ITP.
5.2. Policy Implications
Sustainable improvement and development of farmers’ livelihoods is an important channel
to ensure that farmers reduce poverty and promote livelihood diversification. On the basis of
comprehensive consideration of the shortage of capital elements in different regions, several policy
recommendations are put forward for ITP. Firstly, we should provide micro-credit to improve farmers’
financial capital stock. We should strengthen the guidance of getting rich in precise poverty alleviation,
and give full play to the original intention of the government to provide micro-credit. Then, the
government can regulate and manage the private credit market through innovation of financial and
perfection of systems to make the private lending more legitimate and reduce the ratio of poor farmers
borrowing “usury”, thereby reducing the possibility of poverty trap. The government can further
improve and broaden the financing channels of various financial institutions for household items,
gradually reducing the cost of household borrowing, so as to help the poor groups in rural areas
ultimately eliminate poverty. Secondly, we should enhance the interpersonal network of rural poor
groups and improve the level of information transmission. For example, we can provide social
organizations suitable for rural poor groups to help them or we can employ information assistance and
labor skill training assistance. Thirdly, the western region should focus on increasing investment in
education and basic medical care; particular attention should be paid to girls’ education and women’s
health, actively exerting the power of the government and society. At the same time, strengthening
vocational education, and developing vocational education and higher education to enhance the
personal ability of children from poor families can truly block ITP.
Author Contributions: X.Q. conceived and edited the paper; S.Y. contributed to the methodologies and modified
the text; X.W. made investigations, analyzed the data, and wrote the paper; B.S. provided the figure; C.Y. contributed
to the language modification. All authors read and approved the final manuscript.
Funding: This research was supported by the National Social Science Foundation of China (Grant No: 18BJL126).
Acknowledgments: The research team helped complete the questionnaire survey.
Conflicts of Interest: The authors declare no conflicts of interest.
Sustainability 2019, 11, 2341 19 of 22
References
1. United States. The Millennium Development Goals Report 2015. United States, 2015. Available
online: Http://www.undp.org/content/undp/en/home/librarypage/mdg/the-millennium-development-goals-
report-2015.html (accessed on 1 October 2017).
2. National Bureau of Statistics. Zhang Weimin: Accelerating the Pace of Poverty Alleviation Has Significantly
Reduced the Number of Poor People in China. Available online: Http://www.stats.gov.cn/tjsj/sjjd/201510/t20151016_1257098.html (accessed on 10 October 2017).
3. Li, K.Q. The Fifth Session of the Twelfth National People’s Congress opened in Beijing Great Hall of the
People in 2017. Available online: Http://www.npc.gov.cn/npc/dbdhhy/12_5/2017-03/05/content_2010928.htm
(accessed on 20 November 2018).
4. Yuan, W.P.; Wang, S.P.; Song, S.S.; Yang, Y.Y. Progress in intergenerational transmission of rural poverty.
Agric. Outlook 2015, 7, 25–27.
5. Chen, Q.G.; Cheng, X. Analysis of intergenerational transmission of poverty and interruption strategies from
the perspective of life process. J. South-Cent. Univ. Natl. (Humanit. Soc. Sci. Ed.) 2015, 4, 101–106.
6. Ye, C.; Ma, X.Y.; Cai, Y.L.; Gao, F. The countryside under multiple high-tension lines: A perspective on the
rural construction of Heping Village, Shanghai. J. Rural Stud. 2018, 62, 53–61. [CrossRef]
7. Zhuang, L.; Ye, C. Disorder or reorder? The Spatial Production of state-level new areas in China. Sustainability
2018, 10, 3628. [CrossRef]
8. Amartya, S. Poverty and Famine; Commerical Press: Beijing, China, 2011.
9. Li, X.M. Comments on the theory of intergenerational transmission of poverty. J. Guangxi Youth Cadre Coll.
2006, 2, 75.
10. Wang, J. Exploring the path of intergenerational transmission of poverty in China. Soc. Stud. 2008, 1, 119–122.
11. Wang, Y.; Chen, Y.Y. Study on the formation mechanism of intergenerational transmission Chain of rural
poverty. North Econ. 2013, 6, 10.
12. Corcoran, M.; Danziger, S.K.; Kalil, A.; Seefeldt, K.S. How welfare reform is affecting women’s work.
Annu. Rev. Sociol. 2000, 1, 241–269. [CrossRef]
13. Blanden, J.; Gibbons, S. The Persistence of Poverty Across Generations: A View from two British Cohorts; Policy
Press University of Bristol: Bristol, UK, 2006.
14. Airio, I.; Moisio, P.; Niemel, M. Intergenerational Transmission of Poverty in Finland in the 1990s; University of
Turku: Turku, Finland, 2004. [CrossRef]
15. Musick, K.; Mare, R.D. Recent Trends in the Inheritance of Poverty and Family Structure; University of California:
Los Angeles, CA, USA, 2004. [CrossRef]
16. Mayer, S.E. The Influence of Parental Income on Children’s Outcomes; Knowledge Management Group, Ministry
of Social Development: Wellington, New Zealand, 2002.
17. Currie, A.; Shields, M.A.; Price, W.S. Is the child health/family income gradient: Evidence from England.
J. Health Econ. 2007, 2, 213–232. [CrossRef] [PubMed]
18. Becker, G.S.; Tomes, N. Human capital and the rise and fall of families. J. Labor Econ. 1986, 4, S1–S39.
[CrossRef]
19. Jenkins, S.P.; Siedler, T. Using household panel data to understand the intergenerational transmission of
poverty. Discuss. Pap. Diw Berl. 2007, 5, 694. [CrossRef]
20. Voth, H.J.; Horell, S.; Humphries, J. Destined for Deprivation? Intergenerational Poverty Traps
in Eighteenth-Century Britain. Centre for History and Economics 00-03, 2000. Available online:
http://dx.doi.org/10.2139/ssrn.254329 (accessed on 18 April 2019).
21. Kabeer, N.; Mahmud, S. Imagining the future: Children, education and intergenerational transmission of
poverty in urban Bangladesh. IDS Bull. 2010, 1, 10–21. [CrossRef]
22. Behrman, J.R.; Schott, W.; Mani, S.; Benjamin, T.C.; Kirk, D.; Le, T.D.; Lia, C.H.F.; Aryeh, D.S. Intergenerational
transmission of poverty and inequality: Parental resources and schooling attainment and children’s human
capital in Ethiopia, India, Peru, and Vietnam. Econ. Dev. Cult. Change 2017, 4, 657–697. [CrossRef]
23. Harper, C.; Marcus, R. Enduring poverty and the conditions of childhood: Lifecourse and intergenerational
poverty transmissions. World Dev. 2003, 3, 535–554. [CrossRef]
24. Gordon, D.; Nandy, S. The extent, nature and distribution of child poverty in India. Indian J. Hum. Dev. 2016,
1, 64–84. [CrossRef]
Http://www.undp.org/content/undp/en/home/librarypage/mdg/the-millennium-development-goals-report-2015.html
Http://www.undp.org/content/undp/en/home/librarypage/mdg/the-millennium-development-goals-report-2015.html
Http://www.stats.gov.cn/tjsj/sjjd/201510/t20151016_1257098.html
Http://www.stats.gov.cn/tjsj/sjjd/201510/t20151016_1257098.html
Http://www.npc.gov.cn/npc/dbdhhy/12_5/2017-03/05/content_2010928.htm
http://dx.doi.org/10.1016/j.jrurstud.2018.07.003
http://dx.doi.org/10.3390/su10103628
http://dx.doi.org/10.1146/annurev.soc.26.1.241
http://dx.doi.org/10.1177/138826270500700304
http://dx.doi.org/10.1016/j.ssresearch.2004.11.006
http://dx.doi.org/10.1016/j.jhealeco.2006.08.003
http://www.ncbi.nlm.nih.gov/pubmed/16962191
http://dx.doi.org/10.1086/298118
http://dx.doi.org/10.2139/ssrn.1752996
http://dx.doi.org/10.2139/ssrn.254329
http://dx.doi.org/10.1111/j.1759-5436.2009.00003.x
http://dx.doi.org/10.1086/691971
http://dx.doi.org/10.1016/S0305-750X(03)00010-X
http://dx.doi.org/10.1177/0973703016654561
Sustainability 2019, 11, 2341 20 of 22
25. Ludwig, J.; Mayer, S. “Culture” and the intergenerational transmission of poverty: The prevention paradox.
Future Child. 2006, 2, 175–196. [CrossRef]
26. Bird, K.; Higgins, K. Intergenerational Transmission of Poverty: Research Brief 5. SSRN Electron. J. 2010, 162,
1–8. [CrossRef]
27. Quisumbing, A.R.; Behrman, J.; Murphy, A.; Yount, K. Mothers’ Human Capital and the Intergenerational
Transmission of Poverty: The Impact of Mothers’ Intellectual Human Capital and Long-run Nutritional
Status on Children’s Human Capital Guatemala. Chronic Poverty Research Centre Working Paper No. 160;
IFPRI Discussion Paper No. 12-4. Available online: http://dx.doi.org/10.2139/ssrn.1719646 (accessed on 28
February 2019).
28. Quisumbing, A.R. Intergenerational transfers and the intergenerational transmission of poverty in Bangladesh:
Preliminary results from a longitudinal study of rural households. Soc. Sci. Electron. Publ. 2010, 35, 875–899.
[CrossRef]
29. Buvinic, M.; Valenzuela, J.P.; Gonzalez, M.E. The fortunes of adolescent mothers and their children:
The transmission of poverty in Santiago, Chile. Popul. Dev. Rev. 1992, 2, 269–297. [CrossRef]
30. Davis, P. Passing on poverty: The intergenerational transmission of well-being and ill-being in rural
Bangladesh. SSRN Electron. J. 2011, 35, 1–30. [CrossRef]
31. Moore, K. Thinking about Youth Poverty through the Lenses of Chronic Poverty, Life-course Poverty and
Intergenerational Poverty. Chronic Poverty Research Centre Working Paper No. 57. Available online:
http://dx.doi.org/10.2139/ssrn.1753655 (accessed on 28 February 2019).
32. Bird, K.; Higgins, K.; Mckay, A. Conflict, education and the intergenerational transmission of poverty in
Northern Uganda. J. Int. Dev. 2010, 8, 1183–1196. [CrossRef]
33. Orero, M.B.; Heime, C.; Cutler, S.J.; Mohaupt, S. The Impact of Conflict on the Intergenerational Transmission
of Chronic Poverty: An Overview and Annotated Bibliography. Chronic Poverty Research Centre Working
Paper No. 71. Available online: http://dx.doi.org/10.2139/ssrn.1753025 (accessed on 28 February 2019).
34. Zhang, L.D. An empirical study on intergenerational transmission of rural poverty in China. Chin. J. Popul.
Resour. Environ. 2013, 6, 45–50.
35. Fang, M.; Ying, R.Y. Intergenerational income mobility of rural residents in China. J. Nanjing Agric. Univ.
(Soc. Sci. Ed.) 2010, 2, 14–18.
36. Lin, M.G.; Zhang, R.L. Study on intergenerational transmission of poor families in rural areas: Analysis
Based on CHNS Data. J. Agrotech. 2012, 1, 29–35.
37. Yang, A.W.; Zhang, J.W. Intergenerational transmission of poverty in agricultural and pastoral areas of Tibet.
J. Tibet Univ. (Soc. Sci. Ed.) 2016, 1, 162–169.
38. Li, Z.N.; Liu, Q.J.; Liu, Z.Q. Current situation of chronic poverty in ethnic minority areas and the ways to
control it: Taking Ningxia as an example. Gansu Soc. Sci. 2015, 1, 226–230.
39. Guo, L.F.; Chen, S.Q. Analysis on the influencing factors of intergenerational transmission of rural poverty in
Yi District: From the perspective of cultural theory. China Venture Cap. 2013, 26X, 242–244.
40. Li, X.M. Basic characteristics of intergenerational transmission of poverty among minority