Ralph SantosEDHD-320.0501 October 10, 2017 Effects of Par.docx

Ralph Santos
EDHD-320.0501
October 10, 2017
“Effects of Parents’ Migration on the Education of Children
Left Behind in Rural China” by Minhui Zhou, Rachel Murphy,
and Ran Tao
The first research question is: what is the impact of parents’
migration status on children’s educational outcomes? The
available literature shows a mixed picture concerning whether
children whose parents have moved are benefited in their
education, while others willhave fouind that they are
disadvantaged. The second research question involveconcerns
the impact of both the parental absence and also the post-
migration parental structures on children’s educational
outcomes. As evidenced by this questions, most of the family
structures research which has been undertaken by migration
studies scholars have scrutinized the impacts of single-parent
parenthood on children’s educational performance and
attainment. The third and last research question pertains to the
ways in which the effects of parental migration and the effects
of post-migration parenthood may vary depending on the
children’s sex. This literature also draws some insights into the
sex variations and the effects of parental migration on
children’s educational results.
Data for this study was collected by sampling method. The final
sample involved 1,010 children: 53% were from Anhui province
and 47% in Jiangxi province. In case of theFor 304 children,
both parents were at home while the other 706 children had a
least 15 who had migrated. Also, there were 997 primary school
students, which is, in grades 4 and 6 representing 69% and 313
junior high school students representing 31%. Boys were 533,
where 55% of the sample that shows the girls numbered 457.
Children in the sample were aged between 8 and 17, with an

average age of 12 years. The independent variables for this
study are parents’ migration status which was designated as one
of three status;types: both parents are at home, one parent is a
migrant, and both parents are migrants. Dependent variables are
the children’s educational performance, which is measured by
the average of children’s test scores for the year 2009 and 2010
in Chinese and mathematics. Comment by Susan: ? what type
of sampling method? Comment by Susan: ? (is the 5 a
typo?) Comment by Susan: unclear wording
This article draws on an original cross-sectional survey of 1,010
children and their parents in highly migratory locations of
Anhui and Jiangxi province located in China’s interior. It
employs inclination score matching, a skill which mitigates
indigeneity, to examine the impact of parental migration and
post-migration responsibility arrangements on the children’s
educational performance as measured by test scores for Chinese
and mathematics. One major finding is that the educational
performance of the children is adversely impacted by the
parental migration only when both the parents migrate or when
or in the instance that a non-parent guardian is a principal
caretaker. Consequentially, longer duration of the parental
absence is interlinked with poorer educational performance. The
migration of two parents’ significantly negatively impacts the
educational performance of boys, with no significant
performance of girls as based on the findings we argue that
rather than support left-behind children within the landscape,
the long-term strategy ought to remove the institutional
distractions which hinder resettlement in the cities. Comment by
Susan: could be deleted; already conveyed earlier Comment by
Susan: very close paraphrase from article!! need to be sure to
fully put into your own words (and, in this case, this wasn’t
really critical info to provide)…ok, after looking at actual
abstract, I see that this is taken almost directly from the
abstract, as are other parts below… Comment by Susan: this is
also almost directly copied from the abstract1
The findings/interpretations of the researchers seem believable

based on the outcomes of their research. However, there might
be some other factors that have affected the educational
performance of the children while they are doing their research.
Factors such as the social environment in school, studying
techniques, resources that they may use for studying, etc. may
have affected their findings. Other data like how often do the
parents and the children see each other should have been
collected. I think that the researchers should do the same
research in other countries with different culture because they
might find other interesting findings as cultures in every
country operate differently. Another thing that they can do is
that they can perform research in different classes of people
based on their income as it may also contribute to the
educational performance of the child. Comment by Susan: T
Work cited
Zhou, M., Murphy, R., & Tao, R. (2014). Effects of parents'
migration on the education of
children left behind in rural China. Population and
Development Review, 40(2), 273-292.
P O P U L A T I O N A N D D E V E L O P M E N T R E V I
E W 4 0 ( 2 ) : 2 7 3 – 2 9 2 ( J U N E 2 0 1 4 ) 2 7 3
Effects of Parents’ Migration
on the Education of
Children Left Behind
in Rural China
Minhui Zhou
Rachel MuRphy

Ran Tao
In China in 2012 an estimated 163.4 million rural migrants were
living and
working outside their hometowns (China National Bureau of
Statistics 2012).
The majority of these migrants leave their children in the
countryside. Ac-
cording to figures from China’s 2010 census, more than 61
million children
aged between birth and age 17 years were “left behind.” Of
these children,
47 percent had two parents working away, 36 percent had a
migrant father,
and 17 percent had a migrant mother. Left-behind children
accounted for 38
percent of all rural children and 22 percent of all children in
China (All China
Women’s Federation Research Group 2013).
Chinese migrants leave their children behind in the countryside
because
key features of the country’s social welfare system discourage
them from
taking them to the cities. First, municipal governments use the
household
registration or hukou system, a legacy from China’s socialist
planning past, to
exclude rural migrants and their children from urban-based
schooling, health
care, housing, and social security (Li and Li 2010; Solinger
1999). Second,
the school curriculum varies across administrative districts, so
students must
take examinations for senior high school and university
entrance at their

registered province of residence, a requirement that
disadvantages those who
move across provincial boundaries (Xiang 2007; Ye, Murray,
and Wang 2005).
Finally, owing to long working hours, it is not feasible for most
migrants to
resettle with their families or to raise children in the cities (Ye,
Murray, and
Wang 2005).
While a large body of international and China-specific literature
has ex-
amined the effects of migration on the well-being of children
who accompany
their parents, the children who remain in the origin areas have
received much
2 7 4 E d u C a t i o n o f C h i l d r E n l E f t B E h i n d i
n r u r a l C h i n a
less attention even though their numbers are substantially
greater (Carling,
Menjívar, and Schmalz bauer 2012; Toyota, Yeoh, and Ngyugen
2007). Educa-
tional performance is an important aspect of these children’s
well-being because
it indicates how they are faring in the present and signals their
prospects for a
good life in the future (Schoon 2006: 6). The quest to earn
sufficient funds for
children’s schooling is often a principal objective motivating
parents’ migration
(Dreby 2010; Wan 2009; Yao and Shi 2009).

The positive effects of parental migration arise mostly from the
role of
remittances in alleviating household financial constraints,
thereby improving
children’s living conditions and nutrition as well as funding
their education
(Arguillas and Williams 2010; Bryant 2005; Hanson and
Woodruff 2003; Lu
and Treiman 2011). Remittances may also mitigate the
detrimental parenting
behaviors that can occur when parents face stresses associated
with poverty
(Duncan and Brooks-Gunn 1997; McLoyd 1998). Less has been
written about
the effect of parental absence itself on children’s education.
Therefore, when
addressing the negative effects of migration, scholars have
turned to a wider
literature on family structures that mostly focuses on spousal
separation in the
United States (Arguillas and Williams 2010; Booth 2003;
Kandal and Kao 2001;
Lu and Treiman 2011; Wen and Lin 2012). The family
structures literature
shows that the absence of a parent is associated with children’s
lower academic
achievement (Garfinkel and McLanahan 1986; Krein and Beller
1988; Seltzer
1994), while the presence of both parents is associated with
children’s higher
academic achievement (Coleman 1988; for a review see Cunha
et al. 2005;
Heckman, Stixrud, and Urzua 2006).
The present article draws on a survey of 1,010 children and
their guard-

ians—both parents and others—living in major labor-exporting
regions of
Anhui and Jiangxi provinces in China’s agricultural interior. It
uses the pro-
pensity score matching technique to deal with potential
endogeneity, that
is, the possibility that some of the observed difference in the
educational
performance of children with migrant parents and children with
at-home
parents may be caused by factors influencing the migration
decisions of the
parents rather than by the effects of the parents’ migration
status per se.
Whereas most research focuses on the effects of who migrates
on children’s
educational outcomes, we consider both the effects of who
migrates and the
effects of who acts as the guardians at home. We also explore
the role of chil-
dren’s sex in mediating the impact of parental migration and
guardianship
arrangements on their education, and so cast light on sex
differences in the
effects of disadvantage on children more generally.
Research questions
Culling from the migration studies literature and the family
structures lit-
erature, three main factors emerge as fundamental to how
parental absence
M i n h u i Z h o u / r a C h E l M u r p h y / r a n t a o 2 7

5
through migration is likely to affect children’s educational
performance. These
are: the parents’ migration status, family structure/guardianship
arrangements,
and the children’s sex. The present state of knowledge on the
effects of these
three factors underpins our research questions and our analysis
of the empirical
data. The evidence in relation to these three factors is reviewed
in turn.
Our first main research question is: what is the impact of
parents’ mi-
gration status on children’s educational outcomes? The
migration studies
literature presents a mixed picture. Some studies find that
children whose
parents have migrated are advantaged in their education (e.g.,
Asis 2006),
while others find that they are disadvantaged (e.g., McKenzie
and Rapoport
2006). Some studies even produce different findings from the
same data set.
For instance, one study based on the 2006 China Health and
Nutrition sur-
vey finds that the likelihood of enrollment and of years of
schooling is not
significantly different for children with both parents at home
and for children
with one parent who has migrated (Lee 2011). However,
children with two
migrant parents are found to fare significantly worse than other
children.
The negative effects are attributed to the severe care deficit that

results from
the absence of both parents. Another study that uses the same
survey data
reports the unexpected finding that children left behind by both
parents are
not necessarily worse off than other children, while children
with one migrant
parent fare the worst. The former’s relatively good educational
attainment
is attributed to improvements in family wealth, the actions of
the migrant
parents in maintaining contact with their left-behind children,
and the ac-
tions of guardians in compensating for the absence of two
parents (Lu 2012).
Other studies aim to disentangle the different implications of
maternal
and paternal migration for the education of children left behind.
At least two
such studies pertain to China. One finds that the percentage of
children of
compulsory school age who drop out of school is highest among
left-behind
children who live alone (5.4 percent), followed by children
whose mothers
have migrated and who live with their fathers (4.2 percent),
children whose
fathers have migrated and who live with their mothers (2.3
percent), and chil-
dren with two migrant parents who live with their grandparents
(1.9 percent)
(Duan and Wu 2009). Another study reports that in families
where only the
mother has migrated, children’s self-reported school
performance is worse than

that of children in other migrant families and in non-migrant
families (Wen and
Lin 2012). Even though these two studies do not isolate the
effects of parental
migration from the effects of other family circumstances, they
suggest that
mother-only migrant families may have inherent vulnerabilities.
Other studies, notably several carried out in Southeast Asia,
find that
among children in migrant families, children in mother-only
migrant families
have the worst academic attainment, with the detrimental effects
increasing the
longer the duration of absence (Jampaklay 2006). This research
suggests that
maternal migration disrupts deeply entrenched gender and
generational roles,
including the mother’s caring role, causing family stress
(Jampaklay 2006; Par-
reñas 2005; Yeoh and Lam 2006). By contrast, father-only
migration is reported
to be the most advantageous to the children because of increases
in family
wealth, the continuity of the mother in her role as primary
child-carer, and the
support of the extended family (Jampaklay 2006; Parreñas
2005). However, a
study of overseas migration from the Philippines finds that
children in mother-

only migrant families complete more years of schooling than
children from
non-migrant families, while children in father-only migrant
families complete
the same amount of schooling (Arguillas and Williams 2010).
Our second research question pertains to the effect of both
paren-
tal absence and post-migration guardianship arrangements on
children’s
educational outcomes. Most of the family structures research
that has been
consulted by migration studies scholars has examined the
effects of single-
parent guardianship on children’s educational performance and
attainment.
These studies report that children who are raised by single
parents fare worse
than children who are raised by two parents (Astone and
McLanahan 1991;
Coleman 1988; Garfinkel and McLanahan 1986; Hetherington,
Cox, and Cox
1978 cited in Bronfenbrenner 1979: 72–80; Krien and Beller
1988; Seltzer
1994; McLoyd 1998). Explanations include disruptions to
parent–child at-
tachment, economic deprivation, and emotional and financial
stresses that
impair parenting quality.
Yet unlike in circumstances of divorce, parental absence in
circumstances
of migration does not usually signify an adult’s abandonment of
familial re-
lationships but rather a commitment to them (Nobles 2011).
Additionally,

parental migration does not usually indicate that the family is
economically
disadvantaged vis-à-vis the community average (Asis 2006;
Bryant 2005).
Therefore, even though the mix of parental care and income is
important for
the educational outcomes of children in circumstances of both
divorce and
parental migration, some findings in the family structures
literature may not
be directly relevant to one-parent migrant families.
Even though much of the migration studies literature has
examined
the effects of parents’ migration status on children’s education,
only a few
studies describe the effects of post-migration guardianship
arrangements
(e.g., Asis 2006; Duan and Wu 2009; Pottinger 2005). The
family structures
literature has also considered the effects of being raised by
grandparents or
other carers on children’s academic performance. The picture
that emerges
from this literature is that children who are raised by
grandparents or other
carers are disadvantaged vis-à-vis children who are raised by
their parents
(Sawyer and Dubowitz 1994; Sun 2003; Solomon and Marx
1995). In the US
setting, where much of this research has been conducted,
explanations in-
clude the pressures associated with the unavailability of the
biological parent
and the reasons for this unavailability (Edwards and Daire
2006). Additional

explanations pertain to the difficulties that grandparents can
face in their
7
role as surrogate parents, including decreased energy levels,
illness, pov-
erty, low education levels, and a lack of desire for a parenting
role (Minkler
1999, cited in Edwards and Daire 2006). Notably, this latter set
of difficulties
among grandparent guardians in rural China has been much
discussed in the
Chinese-language literature on left-behind children (Ding and
Sun 2009; Li
and Song 2009; Wang and Dai 2009).
Our third research question pertains to the ways in which the
effects of
parental migration and the effects of post-migration
guardianship may vary
by the children’s sex. The migration studies literature offers
some insights into
sex differences in the effect of parental migration on children’s
educational
outcomes. Studies in Mexico and Thailand report that girls from
poor families
experience the greatest gains in their years of schooling when
remittances are
received, because in circumstances of family poverty they are
more likely than
boys to be deprived of educational investment (Hanson and
Woodruff 2003;

Jampaklay 2006). By contrast, research from the Philippines
observes that
boys benefit more from parental remittances, which alleviate the
household
credit constraints that prevent investment in boys’ education.
An explana-
tion is that since girls generally contribute more support to their
parents
later in life, in circumstances of limited resources girls are more
likely than
boys to receive educational investment (Arguillas and Williams
2010). Other
research from Mexico finds that among older boys the potential
benefits of
remittances are eroded by a “competing alternatives” effect in
which they use
their migrant parents’ knowledge of labor markets and migrate
rather than
continue studying (Hanson and Woodruff 2003). Finally, Lee
and Park report
that in Gansu province in China, the correlation between higher
test scores
and father-only migration (the only type of migration they
consider) is strong
and significant only among girls. The authors suggest that the
advantage of
girls in these families may be explained both by the increase in
family income
and by the mother’s enhanced ability to create a nurturing
environment in
which girls can flourish (Lee and Park 2010).
Methodology
Data

Anhui and Jiangxi were selected for this study because both
provinces have
a high proportion of children classified as left behind. A
definition of a left-
behind child commonly used by Chinese scholars and
policymakers is a child
with one or two parents who work outside the county and who
therefore do
not ordinarily live with the child (All China Women’s
Federation Research
Group 2013). According to figures from the 2010 census, over
half of rural
children in Anhui and Jiangxi were left behind, a proportion
that is consider-
ably higher than the national average for rural areas (ibid.).1
Appendix 1 describes our sampling strategy. After excluding
cases for
which we did not have complete information about test scores,
the final sam-
ple covered 1,010 children: 538 (53 percent) in Anhui province
and 472 (47
percent) in Jiangxi province. In the case of 304 children, both
parents were
at home; the other 706 children had at least one parent who had
migrated.
There were 997 primary school students, that is, in grades 4 and
6 (69 per-
cent) and 313 junior high school students (31 percent). Boys
numbered 553
and comprised 55 percent of the sample, which reflects their

higher propor-
tion in the general school-age population, while girls numbered
457. Children
in the sample were aged between 8 and 17, with an average age
of 12 years.
Independent variables
Our main independent variable is parents’ migration status. We
designated
three main types of migration status: both parents are at home,
one parent is
a migrant, and both parents are migrants. We also subdivided
the migration
status of “one parent has migrated” into only the father has
migrated and only
the mother has migrated. Other independent control variables
are child’s age
and sex, parents’ age and education level, family characteristics
of siblings
and income, and a county dummy.
Dependent variables
The principal dependent variable is children’s educational
performance, as
measured by the average of children’s test scores for 2009 and
2010 in Chi-
nese and mathematics. These test scores were transcribed by
each student’s
homeroom teacher from school records and then standardized by
school and
class year. Standardization was necessary because, owing to
variations across
schools in marking scales, the raw data were not amenable to
comparison

outside of a school’s single grade.
Statistical methods and model specification
When analyzing the impact of parents’ migration on children’s
educational
performance, it is necessary to address the problem of
endogenity because
the parents’ decision to migrate may not be random. The
decision may be in-
fluenced by the families’ attributes, the parents’ attributes, and
the children’s
attributes. Therefore, the differences between children who are
left behind
and children who are not left behind may reflect not the impact
of being
left behind but rather the covariates that determine who is left
behind. For
example, parental poverty might influence being left behind and
simultane-
ously influence children’s test scores through avenues that have
nothing to
do with whether they are left behind. For this reason, regression
analysis that
simply compares the scores of left-behind children and not-left-
behind chil-
9
dren, such as the OLS method, can lead to bias, with the impact
of parental
migration on children’s educational performance being either
underestimated

or overestimated.
In the present study, we would ideally like to observe the
differences in
test scores for individuals when they have been left behind and
again for the
same individuals when they have not been left behind. But
either each child
has been left behind or he has not; there is only one state of the
world. It has
therefore been necessary to find other ways of dealing with the
endogeneity
problem. Social scientists commonly select one of the following
approaches:
instrumental variables, social experiments, or propensity score
matching
(PSM). There are difficulties in using the instrumental variables
approach.
This is because the selected instrumental variable must have a
consistent re-
lationship to the main independent variable but must not explain
any of the
variation in the model other than through its impact on the
instrumented
variable. Therefore, when studying the effects of migration, it is
necessary to
find a variable that potentially affects parents’ propensity to
migrate yet is
external to the families. This is difficult if not impossible. The
social experi-
ment approach, which would randomly assign children to left-
behind and
non-left-behind groups, is clearly infeasible.
PSM, first proposed by Rosenbaum and Rubin (1983) and
Heckman,

Ichimura, and Todd (1998), is arguably the best available
method for dealing
with the endogeneity problem. In this method, the probability of
each indi-
vidual receiving a treatment (being left behind) is estimated by
using probit
or logit regression on researcher-selected individual and family
characteristics.
The resulting estimates are known as propensity scores. Each
individual in
the treated group is subsequently matched to a “nearest
neighbor” from the
control group on the basis of the independent control variables
described
above. In this study, the nearest neighbor is the not-left-behind
child whose
propensity score is most similar to that of the selected left-
behind child.
The reasoning is that if members of the treated and control
groups are
identical to each other in all other respects, the differences
between the
groups can be attributed to the effects of parental migration (Lu
and Treiman
2011: 1131). Results from randomized experiments suggest that
the PSM
technique can reduce bias by 58 to 96 percent (Shadish, Clark,
and Steiner
2008 cited in Lu and Treiman 2011: 1131). The concrete steps
for using PSM
are explained in Appendix 2.
Analysis
Parental migration and child guardianship

arrangements
Of the children in the sample, 43 percent lived in families
where both parents
were migrants, and nearly a quarter in families with only a
migrant father
(Table 1). Even though the proportion of children with migrant
parents is
higher in our sample than in samples reported for other China-
based surveys,
the breakdown of the parents’ migration status resembles that
described in
other rural Chinese settings (Chen et al., 2009; Duan and Wu
2009; Lee 2011;
Lu 2012; Lee and Park 2010; Wen and Lin 2012). Specifically,
two-parent and
father-only migrants are the dominant arrangements, while
mother-only
migrants are in the minority.
The parents’ duration of absence varies depending on which
parent is
the migrant. The average duration of absence is the longest,
around five years,
when both parents are migrants. When both parents are
migrants, the parents
have on average been away from their children for nearly 90
percent of the
time since they started school.

When both parents are migrants, care by grandparents is the
dominant
arrangement. Specifically, 54 percent of children living in two-
parent migrant
families were cared for by grandparents during the week, while
82 percent of
them were cared for by grandparents on the weekend. In
families with only
one migrant parent, the vast majority of children were cared for
by the at-
home parent. Additionally, a significant proportion of children
in our survey
reported looking after themselves during the week. This reflects
the avail-
ability of facilities for boarding at school from Monday to
Friday.
Table 2 shows the variables that need to be controlled in the
analysis
because they could influence both the parents’ migration
behaviors and
children’s test scores. Although not shown in the table, it is of
interest that
parents from migrant families are on average slightly younger
than parents
from non-migrant families, while their average level of
education is slightly
higher: this reflects the generally better urban employment
prospects of
younger and better-educated migrants. Also included as a
control variable is
per capita income.
Tables 3–5 present the results of both OLS and PSM analysis on
the
children’s standardized test scores. We present both OLS and

PSM results in
order to demonstrate the impact of controlling for endogeneity
on the analy-
sis. In the columns labeled OLS, the figures give the effect on
test scores of
TABLE 1 Distribution of children in the survey sample by
parents’
migration status
Total sample Anhui Province Jiangxi Province
No. of No. of No. of
Parents’ status children Percent children Percent children
Percent
Both parents have migrated 437 43.3 180 33.5 257 54.4
Both parents at home 304 30.1 166 30.9 138 29.2
Only the mother has migrated 25 2.5 5 0.9 20 4.2
Only the father has migrated 244 24.2 187 34.8 57 12.1
Total 1,010 538 472
1
being left at home as estimated by OLS regression of test scores
on left-behind
status and the independent control variables described above.
For example,
in Table 3, the 2010 Chinese test scores of children who have at
least one
migrant parent (the treatment group) are estimated to be higher
than the

scores of children whose parents are at home, the difference
between them
being 0.07. The column labeled PSM gives the difference
between the means
of the PSM-matched control and treatment groups (the average
effect of the
treatment on the treated, or ATT, as described in Appendix 2).
In this case,
the 2010 Chinese test scores of the children with at least one
migrant parent
were, on average, 0.01 higher than those of their nearest
neighbors in the
control group. Also available from the authors are results
obtained from an
alternative to the nearest neighbor (NN) matching approach
known as the
kernel algorithm. It is customary for researchers to use at least
two different
algorithms as a robustness check on their results (Chen et al.
2009).
Table 3 examines the standardized test scores of children in
families
where at least one parent is a migrant. The results indicate no
statistically
significant difference in the scores of children with at least one
migrant par-
TABLE 2 Descriptive statistics for the main control variables
Total Anhui Jiangxi
Control variable sample Province Province Boys Girls
Children’s age (years) 12.2 11.7 12.8 12.1 12.3
Children’s sex (percent male) 55 57 53 — —
Parents’ average age (years) 39.0 38.8 39.3 39.2 38.8

Parents’ average education
level (years) 6.1 5.9 6.2 6.0 6.2
Child has a sibling (percent) 62 55 70 51 76
Per capita family income (log value) 8.7 8.8 8.7 8.8 8.6
TABLE 3 The influence of having at least one migrant
parent on children’s test scores, OLS regression and
nearest neighbor (NN) PSM results, Anhui and Jiangxi
provinces, both sexes
NN
OLS PSM
2010 Chinese scores 0.07 0.01
(0.08) (0.13)
2010 math scores 0.11 0.07
(0.09) (0.13)
Average of Chinese scores for 2009 and 2010 0.08 –0.08
(0.08) (0.12)
Average of math scores for 2009 and 2010 0.11 0.03
(0.08) (0.11)
NOTE: Treatment group = children with at least one migrant
parent.
ent and the scores of other children. Table 4 adds guardianship
arrangements
to the analysis. The table considers the test scores of children

who live in at
least one-parent migrant families and who usually live with a
guardian other
than a parent. The results show that these children fare worse in
their Chinese
scores. Moreover, when the results are disaggregated by
children’s sex, being
cared for by an adult other than a parent corresponds with
significantly lower
math scores among boys but not among girls.
TABLE 5 The influence of having two migrant parents on
children’s
test scores, OLS regression and nearest neighbor (NN) PSM
results,
Anhui and Jiangxi provinces, both sexes
Both sexes Boys Girls
NN NN NN
OLS PSM OLS PSM OLS PSM
2010 Chinese scores –0.10 –0.18** –0.08 –0.32** –0.07 –0.07
(0.08) (0.09) (0.12) (0.13) (0.10) (0.10)
2010 math scores –0.07 –0.16* –0.13 –0.36*** –0.01 0.00
(0.08) (0.09) (0.12) (0.14) (0.12) (0.13)
Average of Chinese scores –0.09 –0.22*** –0.09 –0.29* –0.05
–0.07
for 2009 and 2010 (0.09) (0.09) (0.11) (0.15) (0.10) (0.10)
Average of math scores –0.05 –0.20** –0.11 –0.29* 0.01 0.03

for 2009 and 2010 (0.05) (0.09) (0.12) (0.14) (0.11) (0.13)
*Significant at p < 0.10; **p < 0.05; ***p < 0.01.
NOTE: Treatment group = children with two migrant parents.
TABLE 4 The influence of having at least one migrant parent
and
living with a non-parent guardian on children’s test scores, OLS
regression and nearest neighbor (NN) PSM results, Anhui and
Jiangxi
provinces, both sexes
Both sexes Boys Girls
NN NN NN
OLS PSM OLS PSM OLS PSM
2010 Chinese scores 0.01 –0.20** 0.06 –0.16 –0.02 –0.09
(0.07) (0.09) (0.11) (0.15) (0.09) (0.11)
2010 math scores 0.04 –0.14 0.04 –0.28** 0.04 –0.01
(0.08) (0.10) (0.12) (0.13) (0.11) (0.13)
Average of Chinese scores 0.00 –0.23** 0.04 –0.24 –0.01 –0.09
for 2009 and 2010 (0.07) (0.10) (0.11) (0.16) (0.09) (0.10)
Average of math scores 0.07 –0.08 0.07 –0.22* 0.06 0.00
for 2009 and 2010 (0.08) (0.09) (0.11) (0.13) (0.11) (0.12)
*Significant at p < 0.10; **p < 0.05.
NOTE: Treatment group = children with at least one migrant
parent and care usually provided by a non-parent
guardian.

3
Table 5 analyzes the test scores of children in families where
both parents
have migrated. Children from two-parent migrant families have
lower test
scores than other children. Disaggregating the results by
children’s sex shows
that having two migrant parents has a significantly negative
impact on boys’
Chinese and math scores but not girls’.
Comparing the scores of children from families where two
parents have
migrated to those of children from families where only one
parent has mi-
grated, we again find a significant disadvantage among boys
with two migrant
parents (see online Table A).2
Our results indicate that regardless of whether left-behind
children
live in mother-only or father-only migrant families, there is no
significant
difference in test scores when compared with children whose
parents are
at home (see online Table B). However, when the test scores of
children in
one-parent migrant families are compared with those of children
in two-
parent migrant families, the higher scores of the former are
statistically
significant only for children from father-only migrant families.
Moreover,
children in father-only migrant families have significantly

higher scores
than children in mother-only migrant families (see online Table
B). This
may be attributed at least partially to the fact that when only the
father
migrates, parental care by the mother remains the dominant
guardianship
arrangement. The higher scores also lend weight to other
findings about the
importance of maternal care and the difficulties that extended
families face
in substituting for this care (Jampaklay 2006; Wen and Lin
2012).
The effects of parental absence longer than three years
The preceding discussion demonstrated that children with two
migrant parents
have lower test scores than other children. To better understand
how parental
migration may affect children’s educational performance, we
consider the effect
of the duration of parents’ absence on children’s test scores.
Table 6 analyzes
data only for children from two-parent migrant families. The
treatment group
is children whose mother and father have both been absent for
three or more
years since they began school. Three years was selected as the
cutoff because
children in the sample are from grades 4, 6, and 8, so their
parents could not
have been away for more than four years since they started
school. Addition-
ally, as noted earlier, the average duration of parents’ absence
from families

with two migrant parents is longer than for other migrant
families. The total
number of children in the sample with two migrant parents is
437 and, of these,
410 reported an absence of at least three years. The results in
Table 6 indicate
that children whose parents have been away for more than three
years have
lower test scores than other children. Moreover, the sex of the
child is again
important in that the correlation between longer periods of
parental absence
and poorer educational performance is strong and significant
only among boys.
The effects of parental care versus family income
Thus far our analysis of the correlation between parents’
migration status and
children’s educational performance has controlled for the
effects of annual
per capita family income. This has allowed us to concentrate
solely on the
effects of parental availability on children’s education. Yet, as
noted earlier,
parental income may also affect children’s test scores.
Therefore, it is useful to
compare the effects of parental availability with the effects of
parental income.
Our survey data suggest that families with migrants have higher
income than

other families. For instance, in 2009 the average per capita
income of dif-
ferently structured families (including grandparents, parents,
and children)
was as follows: families with two migrant parents—7,824 yuan;
families with
one migrant parent—7,600 yuan; and non-migrant families—
5,015 yuan.
For reference, the annual per capita income of all families in
our survey was
6,815 yuan. Our data also show that in 2009 migrant fathers
earned more
than migrant mothers. In families with two migrant parents,
fathers earned,
on average, 24,995 yuan per year and mothers 18,873 yuan,
while in families
with one migrant parent, fathers earned 24,423 yuan and
mothers earned
15,231 yuan.
Given the higher income of migrant families, we determined the
rela-
tive effect of parental income versus parental care on children’s
academic
performance. (OLS estimates are provided in online Table C.)
Although this
approach may present endogenity problems, the estimates
indicate that re-
gardless of whether the control group is children under the care
of at least
one parent or only one parent, having two migrant parents has
negative care
effects and positive income effects. Moreover, the income
effects are much
smaller in scale than the care effects even if we take into
account the impact

TABLE 6 Effects of both parents being absent at least three
years
on children’s educational performance: OLS regression and
nearest
neighbor (NN) PSM results
Both sexes Boys
NN NN
OLS PSM OLS PSM
2010 Chinese scores –0.10 –0.20** –0.11 –0.28*
(0.08) (0.09) (0.12) (0.14)
2010 math scores –0.07 –0.26*** –0.16 –0.34**
(0.08) (0.09) (0.12) (0.14)
Average of Chinese scores –0.09 –0.25*** –0.11 –0.37**
for 2009 and 2010 (0.07) (0.09) (0.12) (0.15)
Average of math scores –0.05 –0.16* –0.13 –0.33**
for 2009 and 2010 (0.08) (0.09) (0.12) (0.13)
*Significant at p < 0.10; **p < 0.05.
NOTE: Treatment group = both parents have been migrants for
at least three years.
5
of the different units of measurement for the two variables.
Specifically,
when the control group is (A), children with at least one parent

at home, the
average effect of care is 5.6 times that of income. When the
control group is
(B), children with one migrant parent, the average effect of care
is 26.7 times
that of income. Hence, comparison of B with A suggests that the
impact of
income on children’s test scores is less than the impact of
parental availabil-
ity. Therefore, if migrant parents want to offset the negative
effect of their
absence on their children, they need to earn at least an
additional 5,600 yuan
per capita per year. In fact, however, families with two migrant
parents earn
an additional average of only 2,200 yuan more per year than
families with
one migrant parent.
OLS estimates further show that boys are more adversely
affected than
girls by the deficit in parental care. (OLS estimates for boys are
provided in
online Table D.) In the regression on boys in the sample, if the
control group
is (A), children with at least one parent at home, the average
effect of parental
absence is 12.8 times that of income, while if the control group
is (B), children
with one migrant parent, the average effect of parental absence
is 128.1 times
that of income. Clearly, the income of families with two
migrant parents is
not high enough to offset the negative effect of parental absence
on boys’
educational performance. Yet our finding is not just one of

boys’ disadvantage
but also one of girls’ advantage because girls whose parents
have migrated
benefit more than boys from improvements in family income
while suffering
less from the absence of parental care. (OLS estimates for girls
are provided
in online Table E.) To reiterate, the combination of changes in
both parental
availability and family income associated with the migration of
two parents
has markedly different effects on boys and girls.
Conclusion
This article has analyzed data from a randomized survey
conducted in four
counties in the major labor-exporting provinces of Anhui and
Jiangxi to ex-
amine the effect of parental migration on the educational
performance of the
children left behind. We used propensity score matching, a
technique that
mitigates endogenity, to conduct a cross-sectional comparison
of children’s
educational performance by their parents’ migration status. The
analysis has
shown that the children’s Chinese and mathematics test scores
are signifi-
cantly lower only when both parents have migrated, while the
migration of
one parent has little effect. However, when we also consider the
daily guard-
ianship arrangements, the adverse effects associated with
parental absence
become more pronounced. Moreover, among children with two

migrant
parents, the longer the duration of absence, the lower the test
scores, a find-
ing that is of particular concern given that migrants’ duration of
absence has
been increasing (Rozelle et al. 1999).
We also found that the migration of two parents is only
significantly
correlated with poorer academic performance among boys.
When the child
is male, migrant parents’ strategy of arranging for grandparents
to care for
their children does not adequately compensate for the decline in
parental
availability. We observed further that when the child is male,
parental earn-
ings also do not adequately offset the negative effect of the
parenting deficit.
Although we recognize that migration itself is often aimed at
providing for
the future of the child (Dreby 2010; Boehm et al. 2011), it is
not feasible
for most parents to earn the additional income that would be
required to
mitigate the detrimental impact of their absence on their sons’
educational
performance.
Our finding that two-parent migration disproportionately
adversely

affects the educational performance of boys corresponds to
findings from re-
search conducted in the vastly different socio-cultural and
economic settings
of the United States and Europe. Specifically, a large literature
on family struc-
tures and education suggests that boys are ”more vulnerable to
early stressors”
than girls and that they are more adversely affected by non-
maternal care
arrangements (Brooks-Gunn, Han, and Waldfogel 2002). This
literature also
suggests that girls are better endowed than boys with the
protective psycho-
social qualities that enhance their resilience in the face of
reduced parental
input (Bertrand and Pan 2013).
Culturally specific dynamics may also be at work. For instance,
research
has revealed that parenting customs in Chinese societies can
differ by the
child’s sex. Some scholars have suggested that boys are raised
with an em-
phasis on being independent and economically successful in life
so that they
can later support their families, while girls are raised with an
emphasis on
being dependent and fulfilling their relational obligations (Bond
1991 cited
in Chen and Liu 2012: 487). Parents’ different approaches to
raising their
sons and daughters may thus contribute to the greater
vulnerability of the
former and the greater resilience of the latter when a child is
confronted with

family separation.
To conclude, even though the implications of parental migration
for
children’s education vary by family structure, guardianship
arrangements,
and sex, it is clear that the well-being of large numbers of
children is sig-
nificantly adversely affected.3 We believe that the dominant
policy response
to the difficulties faced by left-behind children should involve
adopting the
fundamental and multi-faceted reforms in education, housing,
and labor
protection that would enable rural families to benefit more fully
from urban
employment and to settle with their sons and daughters in the
cities. In the
absence of such reforms, the considerable sacrifice that many
rural people
make on behalf of their children will impose a further,
unintended, sacrifice
on the next generation.
7
Appendix 1: Sampling strategy
Our survey sample was drawn using a multi-stage stratified
design and involved a
random sampling procedure at each of five stages. In the first
stage, we selected Anhui
and Jiangxi, two provinces with a high proportion of children

with migrant parents.
In the second stage, we randomly chose 2 out of 16 prefectures
in Anhui and 2 of 11
prefectures in Jiangxi. Within each prefecture, we randomly
chose one county. In the
third stage, we used a list of all townships ranked by per capita
income to randomly
select a richer township and a poorer township from within each
county. This pro-
duced a total of eight townships.
In the fourth stage we selected the schools and grades 4, 6, and
8. Children in
grades 4 and 6 are usually in primary school while children in
grade 8 are in junior
high school. However, in one township in Jiangxi province the
grade 6 students were
in junior high school. In Jiangxi province, owing to school
mergers, each township
had only one complete primary school, that is, a school that
offered the full range
of grades, so these schools were included in the survey. Every
township in Anhui
province had several complete primary schools. Given the
possibility of differences
in the backgrounds of children in the central primary school
located in the township
and the schools located in the villages, we randomly selected
one or more village
schools as well as the main township school in order to form the
dataset. The final
sample comes from 24 schools: 8 middle schools, 8 central
primary schools, and 8
village primary schools.
In the final stage of sampling, 120 students were randomly

selected in each of 7
out of 8 townships, namely, 40 students each from grades 4, 6,
and 8. Sampling was
facilitated by a government policy to “Care for Left Behind
Children,” which required
schools to keep a record of which children’s parents had
migrated. This requirement
enabled the survey team to calculate the numbers of students
from migrant families
and non-migrant families for each grade for inclusion in the
sample. The survey team
then randomly selected students from the respective name lists
of the left-behind
children and the other children. In one township, however, 180
students rather than
120 students were randomly selected. This is because we
initially carried out our
survey in Jiangxi province and subsequently assumed that the
conditions in Anhui
province would be the same. Hence, in the first township that
we visited in Anhui,
we drew a proportionate sample of left-behind children and
other children from the
central school. However, after talking with teachers we learned
that the distribution
of schools in Anhui was different from that in Jiangxi. With the
help of the county
education bureau we determined the ratio of left-behind
children to other children
for the whole township rather than just for the central school
and then used this
as the basis for sampling. Next we added cases from village
schools to the sample
already drawn from the central school, which resulted in the
inclusion of 60 addi-
tional questionnaires for that township. We then determined our

sampling strategy
for the three remaining townships located in Anhui.
Specifically, a sampling quota
of 40 children for each grade was distributed among the central
and village schools
based on the ratio of the number of students in the central
school to the number of
children in schools in each township, and then the students were
randomly selected
from the respective name lists.
Appendix 2: Propensity score matching
The concrete steps for using propensity score matching are as
follows. First, a probit
or logit model (in our study we use a probit model) is used to
estimate the propensity
score p(X) of every child where X is a set of researcher-selected
variables. In our study,
the propensity score is the probability of becoming a left-behind
child. In determining
the propensity score, the researcher controls for the variables
that could indepen-
dently influence both (1) whether or not an individual receives
the treatment and
(2) the outcome variable, such that the treatment variable—in
this case the child’s
left-behind status—functions as an exogenous independent
variable (D, equal to 1 if
the child is left behind and 0 if not). In our study, X includes
four kinds of variables:

(1) children’s age and sex (Chen et al, 2009); (2) parents’ age
and education level; (3)
the family characteristics of siblings (Steelman and Mercy
1980) and income (Blau
1999); (4) a county dummy to control for county characteristics
such as local migra-
tion networks, educational quality, and so on.
Next, the researcher chooses a matching algorithm to compute
the PSM estimator.
We have used two PSM approaches, the nearest neighbor
approach and, as a check
on robustness, the kernel approach (results for the latter
available from the authors).
To implement the nearest neighbor approach, each untreated
(non-left-behind, D=0)
child is matched to a treated (left-behind, D=1) child whose
propensity score comes
nearest. The process is repeated until all left-behind children
have been matched.
Each child is, in effect, assigned a doppelgänger, as close as
possible in all respects
except for having received or not received the treatment. The
difference between
the test score of the treated individual (Score 1) and the test
score of an untreated
individual (Score 0) is computed. The mean of the differences
between the matched
nearest neighbors is calculated and serves as an estimate of the
expected value of the
effect of parental migration on the children’s test scores. This
mean, conventionally
denoted τ, is referred to as the average effect of the treatment
on the treated, or ATT.
Using standard terminology,

τ
ATT
PSM = E
p(X) | D=1
[E(Score
1
| D=1, p(X)) – E(Score
0
| D=0, p(X))]
Notes
This project was funded by a British Academy
Career Development Grant, and we gratefully
acknowledge this support that made our sur-
vey and collaboration possible. We are also
grateful for supplementary funding from an
Oxford University John Fell Fund Grant.
1 It is not always easy to classify an indi-
vidual as either a migrant or a non-migrant.
For instance, when we asked children and
guardians “who in your family works out-
side?,” some respondents replied according
to who was working outside at the time of
the survey, while others replied according to
what was the usual situation. In 170 cases in
our sample, children and their guardians gave
different replies about who was absent. To
determine a classification in these cases, we
considered children’s answers to a question
about who usually looks after them, in order

to ascertain which parent or parents are usu-
ally absent. We also used information from
the guardians’ questionnaires to calculate how
long the parent had been away from home
since the child started school, and used “more
than 50 percent of the time” as the benchmark
to be classified as a migrant. Hence some
9
children were counted as a having a migrant
parent even though the parent may have been
at home at the time of the survey.
2 Online tables are available at http://www.
ccsp.ox.ac.uk/sites/sias/files/ documents/Zhou_
Murphy_Tao_PDR_2014_OnlineTables.pdf.
3 We believe that the long-term policy
approach for addressing the difficulties faced
by spatially separated families does not lie,
as some Chinese scholars and policymakers
propose, in expanding rural boarding facili-
ties (Chen et al. 2009; Wan 2009; Xie 2009;
Yan and Zhu 2006; Yao and Shi 2009; Zhou
2007) because such an approach could argu-
ably encourage two-parent migration. This
conjecture is informed by two observations
from our fieldwork. First, two-parent migra-
tion was more common in our survey counties
in Jiangxi where boarding, particularly at the
primary school level, was widespread. Second,

some parents told us that the presence of
boarding facilities enables them to feel more
at ease with the idea of leaving their children
behind, because teachers would watch over
them during the week and the burden on
grandparents would be reduced.
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Guidelines
· Teacher & teaching assistants in Youth Centers – What are
some of their duties/responsibilities during their hours with the
children? How would you characterize their interactions with
the children? How might their actions and words be affecting
the children’s development?
Relate your answers to broad theories of development (e.g.,
Bandura, Bronfenbrenner) and/or material specific to early

childhood development. In your conclusion, include
questions/comments about development or developmental
research prompted by this topic.
Be sure to reference all information sources, which may include
your course text, notes, or other readings; there is no need to
consult outside sources. Include a reference list at the end of
your paper AND in-text citations (author, date) for any material
that you looked up. For lecture notes, include the instructor’s
last name (Klauda) and the lecture date (Fall 2017) for the in-
text citation; include the lecture topic in the reference list.
Try to avoid quoting material directly from your text (rather,
describe theories and concepts in your own words) –- but if you
do quote, give the page number with your in-text citation.
( Format: Your paper should be typed in 12 point Times New
Roman font, with 1 inch margins all around and double-spacing.
Your reference list and in-text citations should be formatted
according to the APA style manual or a style manual that is
widely used in your field. Reports must be submitted in
MICROSOFT WORD format with a .doc or.docx file extension.
If you submit it as a pdf or in any other file format, it will be
subject to the late assignment penalty until you correct
it.Grading
Content & organization (80 pts): follows guidelines above;
demonstrates strong understanding of developmental theories
and concepts AND makes explicit connections to course
material; conclusion is substantive –- it is a short paragraph that
does more than simply summarize paper; altogether paper is
well-organized, with a clear, logical overall structure and a
main idea for each paragraph
Writing quality & mechanics (20 pts): free from spelling,
grammar, punctuation, word choice, and formatting errors or
typos; references properly cited; overall, written in a very fluid,
clear, and engaging style

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