Determinants of students academic performance the case of mekong river data

UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM

ERASMUS UNVERSITY ROTTERDAM
INSTITUTE OF SOCIAL STUDIES
THE NETHERLANDS

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF STUDENT’S ACADEMIC
PERFORMANCE:
THE CASE OF MEKONG RIVER DELTA

BY
TRAN CHI NGUYEN

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, NOVEMBER 2016

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UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM
THE NETHERLANDS

INSTITUTE OF SOCIAL STUDIES

THE HAGUE

VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF STUDENT’S ACADEMIC PERFORMANCE:
THE CASE OF MEKONG RIVER DELTA

A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By
TRAN CHI NGUYEN

Academic Supervisor:
DR. PHAM KHANH NAM

HO CHI MINH CITY, NOVEMBER 2016
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DECLARATION
This is to guarantee that the complete contents of this thesis (Determinants of
student’s academic performance: The case of Mekong River Delta) which are drafted
by me and the thesis includes my knowledge and my literature reviews. This thesis has
not already been submitted for any degree and it only submitted for only for degree
of Master of Art in Development Economic to Vietnam - The Netherlands Program. I
take full responsibility for the whole contents that I wrote.

TRAN CHI NGUYEN

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ACKNOWLEDGEMENT
I would to thank the dedicated assistance and supports of my supervisor, Dr. PHẠM
KHÁNH NAM, during thesis time. The valuable comments and advices play a key role
in order to help to finish my thesis.
Besides, I sincerely thank all lecturers - officers in Vietnam – Netherlands Program,
especially Prof. NGUYỄN TRỌNG HOÀI and Dr. TRƯƠNG ĐĂNG THỤY, for their
dedicated instruction, for all the knowledge from lectures and the supporting for my
thesis during the course.
I also would like to thank my classmates, especially Mr. ĐẠT ANH, and my friend Ms.
THIÊN KIM, who has helped and supported me to complete my work.
Finally, I wish lecturer team all the best and hope they will achieve many success in
future path.

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ABBREVIATION
GSO: General statistics offices
UNESCO: The United Nations Educational, Scientific and Cultural Organization
OLS: Ordinary Least Square
VIF: Variance Inflation Factor
EPF: Education Production Function
VHLSS: Vietnamese Household Living Standard Survey
GPA: Grade Point Average
IV: Instrumental-Variable
BLUE: Best Linear Unbiased Estimator

IQ : intelligence quotient
EQ : emotional quotient

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ABSTRACT
This paper focus on examines factors that influence student academic performance in
Mekong River Delta, Vietnam. Basing on a survey that is conducted by the author in
2015, 297 students of Can Tho University have filtered to examine. The Education
production function of Bowles is applied and identified by a model includes eight
variables, which are related academic performance of student. The OLS estimation
results show that 5 out of 8 variables are chosen have significant influence on learning
outcomes of student and the rest variables have no significant effect on student
academic performance in this study. Hence, from the estimation results of this thesis,
the suitable policies will be suggested in order to improve learning outcomes of
student who experienced under performance group.

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TABLE CONTENTS
CHAPTER I: INTRODUCTION ............................................................................................. 1
1.1 Problem statements ..................................................................................................... 1
1.2 Research objectives ...................................................................................................... 3
1.3 Research questions ....................................................................................................... 3
1.5 Research scope ............................................................................................................. 3
1.6 Structure of the thesis .................................................................................................. 4
CHAPTER II: LITERATURE REVIEWS .................................................................................. 5
2.1 Review of key concepts ................................................................................................ 5

2.2Review of theory ............................................................................................................ 6
2.3Review of Empirical studies ........................................................................................... 8
2.3.1 Effect of family backgrounds on student academic performance. .................. 8
2.3.2 Effect of demographic factors on student academic performance...............11
2.3.3 Effect of geographic factors on student academic performance. .................13
2.3.4 Effect of self-motivation of student on their academic performance. ..........14
2.4Conceptual framework ................................................................................................15
CHAPTER III: DATA ANALYSIS AND RESEARCH METHODOLOGY ..................................... 16
3.1 Model specification ....................................................................................................16
3.1.1 Model specification ..........................................................................................16
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3.1.2 Measurement of variables ...............................................................................17
3.1.2.1 The dependent variable ............................................................................17
3.1.2.2 The independent variables .......................................................................18
3.1.3 Regression models............................................................................................22
3.2 Data .............................................................................................................................24
3.2.1 Data source .......................................................................................................24
3.2.2 Sampling strategy .............................................................................................24
CHAPTER IV: EMPIRICAL ANALYSIS AND DISCUSSION .................................................... 26
4.1 Overview of education system in Vietnam and Mekong river delta. .......................26
4.2 Data description. .........................................................................................................27
4.3 Regression results .......................................................................................................33
4.3.1 Results ...............................................................................................................33
4.3.2 Test ....................................................................................................................37
4.3.2.1 Testing for goodness of fit ........................................................................38
4.3.2.2 Testing for Heteroscedasticity ..................................................................38
4.3.2.3 Testing for multicollinearity .....................................................................39
4.3.2.4 Testing for normality.................................................................................40

4.4 Discussion ....................................................................................................................41
CHAPTER V: CONCLUSION AND POLICY IMPLICATIONS ................................................. 43
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5.1 Conclusion ...................................................................................................................43
5.2 Policy implications ......................................................................................................44
5.3 Research limitations and suggestion for further studies ..........................................45
References..................................................................................................................... 47
Appendix ....................................................................................................................... 54

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APPENDIX
Appendix 1: Matrix of correlation between variables ....................................................54
Appendix 2: Wald’s test of overall significant of the model ...........................................54
Appendix 3: Heteroscedasticity test ................................................................................55
Appendix 4: Multicollinearity test ....................................................................................55
Appendix 5: Skewness/Kurtosis test of residuals and National exam score ..................55
Appendix 6: PCA result .....................................................................................................56
Appendix 7: OLS estimation result ...................................................................................57
Appendix 8: Questionnaire ...............................................................................................58

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AP LIST OF TABLES
Table 3.1: List of variable and expected sign in relevance with student academic
performance .....................................................................................................................21

Table 4.1: The observation proportion by provinces ......................................................28
Table 4.2: Statistical description of factors on student academic performance ...........29
Table 4.3: Correlation of dependent variable and independent variables ....................33
Table 4.4: Regression result of OLS estimation ...............................................................35
Table 4.5: Result of Wald’s test ........................................................................................38
Table 4.6: Result of Breusch-Pagan / Cook-Weisberg test .............................................39
Table 4.7: Result of Multicollinearity test. .......................................................................40
Table 4.8: Result of Skewness/Kurtosis test for exam score. .........................................41
Table 4.9: Result of Skewness/Kurtosis test for residual ................................................41

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LIST OF FIGURES
Figure 2.1: Conceptual framework of the study. ............................................................15
Figure 4.1: Distribution of student’s score ......................................................................30
Figure 4.2: Relationship of gender and learning outcomes of student .........................30
Figure 4.3: Relationship between health and learning outcomes of student ...............31
Figure 4.4: Relationship between geography and learning outcomes of student ........32

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CHAPTER I:
INTRODUCTION
In this chapter, the current situation of Vietnam education system is introduced in
brief and based on information that the importance and the essential of this study will
be mentioned. Besides, there are some other crucial parts will be presented such as
problem statement, research objectives, research questions, research hypothesis,
research scope and organization of the research.

1.1 Problem statements
Nowadays, at macro level, education help a country to strengthen the human
resource of the economy and occupies a very important role in the development of a
country. Besides, at micro level, education has long been perceived as a main factor
help people to get the job, to get wealthy and promote earning of individual and
family. In the nineteenth century, it is generally believed that there is nothing can do
about what education cannot do. Recently, many researchers declared education
plays an important role in the economy of every nation around the world. Especially,
developing countries such as Vietnam schools regarded as main element in the
infrastructure. The problem here is the determinant of student performance. In
general, people think that student outcomes are affected by intelligent, environment,
effort, etc.
In development economics, beside the sustainable development goals, education and
health are two importance problems due to the influence of them in the long term.
The average education level of the society represents the level of development and
achievements as well as the future prospects. A community with high educational
level will be more favorable to improve living standard and based on that the national
economy is also benefited. Besides, enhancing intellectual level of the people, welltrained labor plus advanced technology will help any countries to improve their
productivity in both short term and long term.

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From the very beginning step, education is an essential part of human life; hence, the
exact measurement of children's learning ability is very important. The evaluation
demonstrates ability, cognitive level and reaction of children. Base on that, schools
and parents can make the right decision for each child in order to maximum the
limited human resource. Another aspect, children learning ability also illustrates the
advanced and efficient level of education system relied on those policy makers can
apply reasonable policies.

Vietnam and the people of Vietnam was recognized the essential role of education to
the country. Hence, the government has made a very strong push for the
improvement of this field. According to Le (2003), from 1991 to 2003, he mentioned
that more than 120 tertiary institutions was built and this education field encountered
highest growth rate in the last 10 year. In the same period, Pham (2002) discovered
that the number of student who studied postsecondary raised approximately six
times. In addition, the amount of student who studying upper secondary in Mekong
river delta is about 377.099 students.
There are some researchers focus on the determinant of education achievement in
Vietnam. In particular, Le (2000) has determined the factors of Vietnam's secondary
education and he found that there is a difference in the enrollment rate between
males and female students at upper secondary level. Moreover, Le (2003) using the
data of batch 26 students of HCMC University of Economics, he examined the factors
between urban and rural students who studying in HCM University of Economics, the
result shows that there is a gap between provincial and city students.
Mekong River Delta has long been perceived as a remote region, the geographic
location of Mekong Delta has many rivers and canals and the infrastructure, road
system is underdeveloped which creates an obstacle for student to access to school.
Moreover, the youth literacy rate of Mekong River Delta is the third lowest in
comparison with other regions in Vietnam and this rate is 0.80 percentage points
lower than National youth literacy rate. The adult literacy rate in Mekong Delta is

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83.10 percent and it is about 6 percentage points lower than the National rate.
Therefore, more attentions should be paid for the low education level region such as
Mekong River Delta.
In fact, there are a few researches examine about the case of Mekong River Delta.
This thesis is the first research which examines the influence of the determinants on

the individual student’s academic performance with the dependent variable is the
individual score of students from National High School Graduation Examination in
2015 for the Mekong River Delta.
In brief, the intellectual level of people in Mekong River Delta is quite low in
comparison with the whole country. A large part of population still living in the
countryside, and the accessibility to education is very limited. Therefore, the
researches is about solving the education problems in Mekong River Delta is very
necessary. Hence, a method in order to identify determinants of student academic
performance and the magnitude of the influence of those factors will be necessary.
This study will propose determinant factors which influence the student academic
performance and base on that, the policy recommendations will be suggested to
policy makers in order to have suitable policies. Especially for developing country like
Vietnam where the middle-income trap is becoming national problem
1.2 Research Objectives
There are two key research objectives of this paper:
(1) To examine the determinants of student’s performance.
(2) To give policy implications to enhance student academic performance.
1.3 Research Questions
In order to match the objectives in the section above, this study must concentrate on
these questions:
(1) What are the determinants of student’s academic performance?
(2) Do these determinants affect academic performance of student?
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1.4 Research scope
The scope of this research is Mekong River Delta of Vietnam, including 12 provinces.
An Giang, Bac Lieu, Ben Tre, Ca Mau, Can Tho, Dong Thap, Hau Giang, Kien Giang, Soc
Trang, Tien Giang, Tra Vinh, Vinh Long. All statistic and data in this study are collected
from a survey of the author at Can Tho University in 2015.

1.5 Structure of the thesis
This study contains five chapters:
Chapter 1 is the introduction part of this study, which mentions about background
and foundation of this study. Chapter 2 provides fundamental definition about
learning outcomes, theoretical reviews and some empirical studies relevant to
determinants of student academic performance. Moreover, there is also a recap table
of literature reviews and analytical framework the end of chapter two. Chapter 3 will
present the methodology, data and regression model for this study.
Chapter 4 contains the data descriptive statistics and regression result of this study.
Conclusion of chapter 4. Chapter 5 base on the regression result in chapter 4 and
gives a recap of estimation result. Make recommendation to policy maker on main
findings of the thesis then points out thesis limitations and suggestion for further
research.

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CHAPTER II:
LITERATURE REVIEWS
This chapter contains the literatures about theoretical, analytical and relevant
empirical researches on learning outcomes of students. This chapter first begins with
some basic definitions about learning outcomes of student. Then, the second part
introduces the main theory on education achievement, which applied for this study.
The last part presents the review of empirical studies about determinant of learning
outcomes and it shows the analytical framework for this study.
2.1 Review of key concepts
Before investigate relevant theories, it is essential to look at some definitions and key
words have connection with the issues, foundation of deeper analysis is to understand
about fundamental notions clearly.
Learning Outcomes

There are several definitions about learning outcomes in the world. These definitions
are different because of standpoints and aspects. However, the similarity is learning
outcomes are records that represent important and necessary knowledge that
learners have achieved, and accurately display at the end of a process. In other words,
learning outcomes label what knowledge the student will get and can do at the end of
a program or course.
Suskie (2009) asserts that learning outcomes are objectives that demonstrate how
learner will be different because of a schooling or leaning experience. More precisely,
learning outcomes are the ability, skills, information, mindset and attitudes that
learner will carry with them from schooling or learning experience.
University of Warwick (2011) concludes the definition of learning outcomes as “The
ability, knowledge learners will acquire upon successful completion a process of
learning or a course.”

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University of Manchester Institute of Science and Technology defines “learning
outcomes are the acquisition of person's understanding, ability, knowledge or mindset
that is the desired outcome of a learning process and will be demonstrate at the end
of that process or program” (UMIST, 2001).
In a compilation from other resources, Vlãsceanu et al. (2004) states that student
learning outcomes are the statements of what student is anticipated to figure out,
recognize, and/or can explain after completed a learning process as well as peculiar
practical or intellectual ability earned and showed by the successful fulfillment of a
program or a course. Learning outcomes, along with evaluation criteria, decide
definitely the minimum requirement for the reward of credit, while the evaluating is
based on achievement above or below the minimum requirements for the reward of
credit. Moreover, the learning outcomes are different from the goals of schooling in
that they are involved with the attainments of student rather than with the general

purposes of teachers.
Learning outcomes score
Learning outcomes score is a worldwide-accepted score or a standardized-test score
with highly reputation and are most precise criteria for ranking student.
There are many grading systems around the world; each country uses their own
grading system to measure varying levels of achievement in a course. Grades can be
assigned as a range (for example 1 to 10), as letters (typically A, B, C, D, F), or as a
percentage of a total number of correct answers and so forth. In Vietnam, the main
grading systems is from 1 to 10 and 10 is the highest score. ("10" - Excellent, "9" - Very
good, "8" - Good, "7" - Acceptable, "6-5" - Satisfactory, "4-3-2" - Insufficient, "1" Fail).
Typically, the lowest passing grade is 5 and it depends on each school.
2.2 Review of theory
Educational production function theory

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Historically, the production function was applied as an economic concept to the field
of education and it is called educational production function (EPF). The original idea of
educational production function came from Coleman (1996), which had been carried
forward by Bowles (1970) and Hanushek (1986). This EPF has received a lot of
attention because education clearly captures an important place in every major
economy of the world.
In general, this function reflects the relationship between factors affecting student
learning and learning outcomes of student. These factors include schools, families,
peers, neighborhoods, etc. Bowles (1970) notes that this method makes the
educational production process is probably become a specific value both in normative
investigations and in descriptive studies of human capital formation to identify
optimum educational resources distribution. In addition, if there are some evidence
show that schooling greatly affects labor productivity or earnings, it is necessary to

know how schooling affects the development of human cognitive skills and attitudes
in school by tracking those evidences. Moreover, a production function associating
inputs of school to the advancement of productive capacity can provide a better
explanation of why the more educated the better certified for productive aspects.
According to Hanushek (1986), the most common measure of schooling in previous
studies are years of schooling completed. However, a big problem with this popular
measure of outcomes is that it assumes the same amount of student's achievement,
or skills are produced in a year of schooling. This is simply counts the time people
learn in schools without mentioning what actually happens in schools - therefore, it
does provide an incomplete or inaccurate picture of outcomes.
Hanushek (2007) showed the academic achievements of individual students is
correlated to inputs that both controlled by policy makers (such as the characteristic
of schools, curricula, teachers and so forth) and not under-controlled as friends and
families and innate intellectual abilities and learning capacities of learners.
Furthermore, educational process is cumulative, current levels of attainment affected

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by inputs applied in the past. To be more specific, he pointed out those sociodemographic characteristics such as parental income, education and size of family
usually used to identify family background of student. Peer inputs typically are
attainments for a school (or classroom) or aggregates socio-demographic
characteristics of students. School inputs commonly include teacher background,
school organization (such as class sizes, administrative expenditure, facilities and so
forth), and location or community factors (e.g., average expenditure levels). Most of
empirical researches (except Coleman Report) based on data for other functions
hence statistical analysis (commonly some form of regression analysis) is applied to
conclude what particularly affects achievement.
According to Bowles (1970), an educational production function is defined as:
A = f(X1, . . .,Xm, Xn, . . . ,Xv,Xw, . . .,Xz)

Where:
A = measure of school output – for example, score on a standardized
test;
X1,…,Xm =

variables determining the school environments (such as teaching
quality, school facilities, and length of time student is exposed to
these inputs).

Xn,…,Xv =

variables representing environmental influences on learning outside
the school ( e.g., the parent’s income, education and so forth).

Xw,…,Xz = variables representing the student’s abilities and the initial level of
learning attained by the student prior to entry into schooling
question.
2.3 Review of Empirical studies
2.3.1 Effect of family backgrounds on student academic performance.
There are many literatures have aimed on influence of parental backgrounds on their
children's outcome, including education. Among varies characteristics of parents,
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parental education and income are two determinant affect significant to children's
education.
Glick and Sahn (2000) examined the influence of parental education and income on
learning of boys and girls in West Africa, depending on utility theory, applying binary
and ordered probit models. Accordingly, they separate life of family into two stages.
The first stage is to work and raise their children. The second stage is the retirement

of parents. In the first stage, current income of the parents take responsibility for all
the household spending. There are two kinds of spending at that moment, including
spending for education expenditure or education of their children and other
consumption for living. The education expenditure, in turn, determines the income
levels of household in forthcoming time, the second stage when parents retired. Thus,
parents have to look at the tradeoff between the two expenditures. The result
depicted that rising in household earnings lead to the increasing on education
achievement of girls but none influence on the boy children. Furthermore, they also
asserted that the positive significance is not only the achievement but also displays
grade achievement. Besides, the research declared that parents' education has
positively association with children learning. In specific, the higher parents’ education
level is, the higher achievement rate of children earns. Moreover, mother occupies a
crucial role in the schooling determination of their children. Undoubtedly, mother
who is lacking education or is traditional women likely to forbid their girls taking part
in secondary school.
Halle et al. (1997) concluded that mother with high level of education tend to have
higher expectation on their children academic achievement and these expectations
were correlated with better performance of children in Math and Reading, using a
dataset of an outnumbered group of families with low-income. Similarly, Corwyn and
Bradley (2002) declared that maternal education had a direct effect on their children
cognitive and learning outcomes.

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Similarity, Tansel and Bircal (2006) also pointed out that family with high levels of
income invest more money for education of their children rather than low-income
household.
Another research created by Blanden and Gregg in 2004 verified that the relationship
between family income and education achievement was very close in the United

Kingdom and it has been enhancing over time. They also declared that earnings do
have a causal effect on educational outcomes. Besides, raises 1000$ in annual family
income from 2 to 5 years leads to the growth of student achievement by 6% standard
deviation (Duncan, Morris and Rodrigues, 2011).
Moreover, Hashimoto (1995) asserted that the average income elasticity is 1.72;
applying OLS model to predict the elasticity of income of education in Japan. That is,
when income increase one percent, the spending of education will raise one point
seventy-two percent. This elasticity is much higher than that of the other
consumption spending. Similarity, Huston (1995) indicate the same outcome, which
means that when family earnings increases, education spending ratio, which is
determined by education spending over total family spending, is raised.
In Vietnam, there is a tight relationship between household earnings and children's
education. Behrman and Knowles (1999) created the study, which aimed at
demonstrating the relationship between educational cost, the spending of parents
directly paid to school, and income of household. Actually, it linked three implications
to assess the relationship. The implications were the education cost directly paid to
school, school’s quality and quantity of school. The outcome indicated that there are
higher parents’ earnings there is more money for spends on education. Indeed, the
elasticity is approximately 0.65. To be more specific, when households’ earnings raise
one percent, the spending on education also increase 0.65 percent. Besides, it also
asserts that income of household positively influenced enrollment rate.

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In brief, there are many researches focusing on the influence of parental background
on their children's education. Undoubtedly, education and earnings of parents
positively affected learning of their children.
2.3.2 Effects of demographic factors on student academic performance.
Demographic factor is explained as family size, gender factor and health condition.

Smits and Hosgor (2006) examining the influence of demographic factors on
education attendance in Turkey, declared that gender factor, number of children,
profession of parents and parents' educational level are fundamental factors
determining the school achievement rate in Turkey. Particularly, it verified that there
is the difference in the attendance rate of the girls and boys. Actually, the attendance
of the boys much higher than the girls.
According to Mandilaras (2002), women tend to have better achievement than men
do in economics course. Besides, the Department for education and skills in Great
Britain also publishes a statistic summary and it shows that girls tend to do better in
majority of subjects than boys. However, there are some other researches show that
males seem to have higher learning outcomes in economics (Choudhury 2001, Kane
and Spizman, 1999). In addition, Ellis, Durden and Gaynor (1998) proved that there is
no relationship between gender of student and academic performance.
Jæge (2006) discovered that the influence of family size, parent resource distribution
to the outcome of children, applying data form Wisconsin Longitudinal study, with
instrumental variable (IV) approach and OLS. Accordingly, this research predicted the
influence of parental resources and other inputs including social, time, economic, and
relational with their children. The outcomes of this study implied that when number
of children in the family who at schooling age increases the total volume of parental
resources and other inputs accessible for children increase but decline to each child.
Ray (2000) joining the employment information, demographic aspect, applying data of
Employment survey in Rural and Urban in India implemented in 1993, examined the
effect of the size of the family on benefit of children in India. To evaluate, the research
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connected the relationship between family size and gender of breadwinner to the
economic status of the family. Accordingly, the study indicated that the root of
poverty is relevant to family size in India. As a result, this brought to the negative
effect on benefit of children, education achievement. As a matter of fact, it illustrated

that children from bigger size families are tending to receive less schooling chance
than those from smaller families.
Huston (1995) conducting the study on influence family size, which is denoted as
number of children who at schooling age, to educational spending ratio. The outcome
of the research indicates that when family size rise, educational spending ratio (which
is determined as ratio between educational spending over total household spending)
increase as well. In other words, when number of children who at schooling age
increases, the proportion of educational spending on total spending of family be apt
to rise. Absolutely, the relationship between size of family and children's academic
achievement is negative.
Poterba (1997) pointed out that increases in number of children who at schooling age
in the family leads to the decline of educational spending for each child, the study
applied panel date of the State of United State from 1960 to 1990 proposes the same
outcome that demographic structure influences the schooling expenditure. Similarity,
Tilak (2002) also confirmed that the amount of education expenditure for children
raises when the number of schooling children increase but it declines for each child of
family in India. Additionally, Downey (1995) demonstrated that if the children from
large and small family have the same level of parental resources, the children from
large family gain less benefit compared to the children from small family from the
parental resources.
There are several studies apply socioeconomic surveys of behavioral data and found
that there is a strong positive relationship between health of children and educational
attainment (Florencio, 1988; Moock and Leslie, 1986; Gomes-Neto et al, 1992). These
studies also point out that learning outcomes of a child is negatively correlated with

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the chronic malnutrition status. Moreover, Leslie and Jamison (1990) the lack of
nutrition and poor health have a negatively influenced on school outcomes and school

attendance.
Briefly, there are many researches on influence of gender factor, size of family and
health condition on education of children. The typical outcome is that gender of
children and health condition also occupy an important role in the learning decision.
Furthermore, when number of children who at schooling age rises, the education
expenditure for each child is decreased but it brings a rising in total amount of
education expenditure for children.
2.3.3 Effects of geographic factors on student academic performance
Ersado (2005), pointed out that there is a difference between city and countryside
regions connected to children's education achievement, applying the multinomial
logit framework, combining with data from Zimbabwe, Nepal and Peru, insufficient
determinants effect on decision for schooling in countryside and city. Indeed, the
education achievement rate in countryside is lower than that of city regions. In the
countryside zone, if the family earnings are not enough, children will join the labor
market instead of taking school. The schooling decision also relies on the possibility to
approach to commercial bank. Actually, there is a positive influence on schooling by
approaching the bank. Moreover, the education achievement will rise when the
country infrastructure is enhanced, and the number of schools is raised.
Similarity, Park (2008) indicated that there are several differences in education
between countryside and city in China. The first characteristic is the school admission
rate, the ratio in countryside, from 84 percent to 90 percent is lower than that in city,
from 93 percent to 95 percent. The second characteristic is the school's quality in
these regions. Indeed, countryside household cannot support for their child in order
to finish 9 years necessary in accordance with education law.
Another study created by Jeynes (2007) discovered that the effect of parents on their
children education in the city regions of the United State. Accordingly, the outcomes
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