MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS, HO CHI MINH CITY
NGO HOANG THAO TRANG

DETERMINANTS OF SECONDARY SCHOOL
DROPOUT IN VIET NAM

MASTER OF PUBLIC POLICY THESIS

HO CHI MINH CITY - 2010


HO CHI MINH CITY - 2010 CERTIFICATION
I certify that the substance of the thesis has not already been submitted for any
degree and is not being currently submitted for any other degrees.
I certify that to the best of my knowledge any help received in preparing the
thesis and all sources used have been acknowledged in the thesis.
The study does not necessarily reflect the views of the Ho Chi Minh City
Economics University or Fulbright Economics Teaching Program.

Author Ngo Hoang Thao Trang ACKNOWLEDGEMENTS
I would like to express my deep gratitude to my parents who always encourages
me in my life and my studying.
I would like to express my sincere appreciation to my supervisor, Dr. Jonathan R.
Pincus, who has help me in performing the thesis. With rich knowledge, experience
and enthusiasm, he has effectively contributed to my thesis.
ABBREVIATIONS
GSO: General Statistic Office
MOLISA: Ministry Of Labor –Invalids and Social Affairs
VHLSS: Vietnam Household Living Standard Survey
CONTENTS
CHAPTER 1: INTRODUCTION……………………………………….….…… 01
1.1 Problem statement…………………………………………………….….…… 01
1.2 The scope and the purpose of the study….…………………………… ……….02
1.3 Research questions of the study ……………………………………… ………03
1.4 The structure of the study………….………………………………….……… 03
CHAPTER 2: LITERATURE REVIEW…………………………… ………… 04
2.1 Concepts …………………………………………………………… …………04
2.2 Theoretical background ……………………………………………… ……… 05
2.2.1 Demand for education…………………………………………… ……… 05
2.2.2 Education production function………………………………… …………08
2.3 The framework of determinants of the dropout … …… ……………… ……08
2.4 Empirical studies of school leaving in Viet Nam……… …………… ……… 16
2.5 Conclusion …………………………………………………………….……… 19
CHAPTER 3: OVERVIEW OF SECONDARY SCHOOL IN VIET NAM ….20


LIST OF TABLES
Table 5.1: Logistic regression of school dropout as a function of selected individual,
household, school and demographic characteristics, and the children sample aged
11-18, VHLSS 2006……………………………………………………………… 43
Table 5.2: Marginal effects of the probability of dropping out…… ……………44
Table 5.3: Predicted dropout probabilty of children by education level of
parents…………………………………………………………………… ……….52
Table 5.4: Predicted probability of dropping out by hours working per
year…………………………………………………………………………………54
Table 5.5: Predicted probability of dropping out by region……………………… 55

LIST OF FIGURES
Figure 3.1: Number of pupils in secondary school in Vietnam from 1999-
2006… 21
Figure 3.2: Secondary education dropout and repeat rate, 1999 – 2004 …… ……22
Figure 3.3 Secondary education dropout and repeat quantities, 1994-2004….… 22
Figure 5.1: Dropout rate in Vietnam in 2006, by gender and by age…………… 38
Figure 5.2: Dropout rate in Vietnam in 2006, by hours working per year…………39
Figure 5.3: Dropout rate in Vietnam in 2006, by household expenditure…………39
Figure 5.4: Dropout rate in Vietnam in 2006, by parent educational level ………40
Figure 5.5: Dropout rate of Vietnam in 2006, by urban and regions………………42
Figure 5.6: Conditional effect plot of dropout probability according to educational
level of parents…………………………………………………………………… 53
Figure 5.7: Conditional effect plot of dropout probability according to hours
working per year………………………………………………………………… 54
Figure 5.8: Conditional effect plot of dropout probability by regions …… ……55

thousand at the primary level, forty thousand at the lower secondary level and thirty
eight thousand at the upper secondary level. The Mekong Delta had the highest
number of dropouts at twenty five thousand. The Central Highlands had eleven
thousand dropouts and the North-West 4,600 dropouts. The consequence of pupils
dropping out include private and public costs. For individuals, they cannot get
skilled employment so they earn little money and face many risks and
discrimination in society. For the country, dropouts reduce the rate of growth of the
skilled labor force. Moreover, dropouts make the gap between the poor and the rich
larger.
Motivated by this situation, this study analyzes the determinants of the dropout
rate from secondary school in Vietnam. The contribution of the study is to find out
which factors influence the dropout rate and to suggest policies to reduce it.
1.2 The scope and the purpose of the study
The study focuses on analyzing empirically factors that affect dropout behavior
of children at the individual, household and school level. The analysis is carried out
on the case of dropouts from the secondary level in Vietnam in 2006. The study
aims at identifying the degree of impact of factors affecting the dropout rate from
secondary school. The study provides input for policy makers formulating policies
to reduce the dropout rate at the secondary level in Vietnam. 3
1.3 Research questions of the study
The study attempts to answer the central question: What are the most prominent

order to show the effects of such factors on dropouts.
2.1 Concepts
As a first step, it is useful to provide the concept of school dropouts used in the
study. According to MOET, a child is viewed as a dropout if he or she did not
continue his or her schooling. Vo Tri Thanh and Trinh Quang Long (2005) criticize
this definition since it does not count those who do not continue to enroll in school
after having finished a given grade. This may lead to an underestimation of school
dropouts. In the study, a child is a dropout if he or she has not completely enrolled
in school in the twelve months prior to the survey, given that he or she used to
enroll in school sometime before.
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2.2 Theoretical background
This sub section is devoted to a review of the main literature relating to
investment in education on the demand and supply sides. Then it discusses factors
affecting dropouts in recent empirical studies. The subsection is not intended as a
complete and extensive review, it merely sets the stage by presenting relevant
considerations.
2.2.1 Demand for education
An elegant theoretical framework regarding determinants of the optimal length
of education has evolved from the human capital theory of Becker (1967) and Ben-
Porath (1967) [cited in Ranasinghe (1999)] . Human capital theory argues that
additional schooling generates benefits in terms of enhanced future earnings and
entails direct costs such as expenditures on school tuition and opportunity costs
associated with delayed entry into the labor market. The individuals will compare

household decision making regarding investments in education of boys and girls
(Glick and David, 1998), parents are considered to live over two periods. In the
first period, they earn money spending; feeding their children and spending money
for their children to go to school. Consumption in the first period includes personal
spending and spending on the education of children. In the second period, the
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consumption of parents will depend on remittances from their children.
Nevertheless, remittances from their children depends on the returns on educational
investments of their children as well as their specific characteristics. Parents will
choose the duration of their children’s education to maximize their utility subject to
income, time constraints for the household members and the earnings of the
production function for each child. The limitation of household models is that
preferences of parents for their children are identical. To overcome the limitation of
the model, bargaining models assume that parents have different preferences for
their education of sons and for that of boys leads to gender specific demand
functions for schooling. Differential preferences may be a response to the actual or
perceived differences in the labor market returns to female and male schooling
(Patton, 1993) [cited in Chu Bao Hiep (2008)].
In the study, human capital models are embedded into a model of household
demand where both parents and the individual child are decision makers. This
framework captures the close economic interdependence between the child and the
family. The basic implication of such a framework is that the decision to attend
school depends not only on market forces and public programs that determine the
costs and benefits of education, but also on the preferences of the family, resource
constraints and alternative uses of the time of children in non-school activities, such
as work or leisure.



is individually considered through the presentation of the most relevant results in
theories and in empirical studies.
Group 1: Individual characteristics
Gender
This subsection deals with the relationship between gender and school dropouts.
On this point, there is a consensus that gender inequality affects the dropout rate of
boys and girls. One line of reasoning is that parents predict that the returns to the
education of boys is higher than girls (Schultz, 1993). In the labor market, girls may
be discriminated against in terms of earning, so the future earnings of girls are
lower than that of boys. This means that monetary benefits to invest in education for
girls may be lower than for boys. Moreover, even if educated girls receive earnings
on a par with men, income remittances to parents from married women may be
lower than married men. Another line of reasoning is that the opportunity cost of
educating girls is higher than for boys. Girls in developing countries and in rural
areas have to perform more domestic responsibilities than boys, reflecting cultural
or social attitudes toward the proper economic role of women and girls. This means
that the marginal cost of time of girls may be higher than that of boys and
consequently the demand for their schooling will be lower (Glick and David 1998).
Furthermore, girls have a higher probability of dropout if budgets of parents are
constrained (Deaton, 1989).
On the other hand, gender disparities in education are different between
countries. According to Filmer (2006) girls are at a great educational disadvantage
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in particular regions such as South Asia and North, Western, and Central Africa,
especially in poorer households. At the other extreme there are countries, mostly in
Latin America, where there is no female disadvantage, and often a small female

supported the negative relationship between the educational level of parents and the
dropout probability. They argue that educated parents are more likely to recognize
the benefits of schooling than less educated parents. Moreover, educated parents are
more able to assist in the learning of their children than less educated parents.
On the other hand, there is evidence that the effects of parents’ educational
attainment is different between boys and girls. According to Tansel (1997) an
increase in the schooling years of parents decreases the probability of a child
dropping out. Moreover, he found that there are differential effects for boys and
girls. The effects of the educational level of both mother and father on the
probability of a daughter dropping out was larger than on sons except for the
education of the mother at the primary level. This may be due to several reasons. It
is possible that relatively uneducated parents tend to be in locations where there are
some barriers to the school attendance of girls. It is also possible that the education
of parents has a big effect on their attitudes towards girls’ schooling.

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Household income
Like education of parents, the negative relationship between income and the
probability of dropping out is strongly supported by theoretical as well as empirical
studies. According to Glick and Sahn (1998), wealthier household are likely to be
able to pay for schooling out of current income or savings and have easier access to
credit. Children from such households are expected to be more likely to enroll and
to stay in school longer. Otherwise, poor households may be unable to afford the
direct or indirect costs of schooling and are constrained in their ability to borrow to
cover the costs. Moreover, richer household can invest in the education of children
by tutoring at home or improving the health of children, thus increasing demand for
schooling (Le Van Chon, 2000).

dropout. Many theoretical and empirical studies form a consensus on this issue.
Becker (1975) [cited in Ranasinghe (1999)] argues that whether a child goes to
school depends on a comparison between future benefits of the human capital of the
child and the direct and opportunity costs of schooling. So higher costs of schooling
increase the probability of dropout. Most empirical research concludes that school
characteristics related to costs and benefits influence enrollment and attainment of
children (Al-Samarrai & Peasgood, 1998; Chernichovsky, 1985; Dostie &
Jayaraman, 2006; Wolfe & Behrman, 1984; Zimmerman, 2001). Furthermore,
Glewwe and Patrinos (1999) state that if school fees are excluded from models of
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determinants of school dropouts, it would limit our understanding of family
decision making on investing in education. He concluded that high costs keep some
children out of school and this is particularly important for countries where free
education is limited by resource constraints.
School quality
This subsection focuses on dealing with the connection between school quality
(infrastructure and teacher qualifications) and dropouts. There have been
inconclusive results in the empirical literature. No consensus has been reached on
the direction of the connection as many theoretical and empirical studies provide
contradictory arguments and evidence. Coleman (1966) [cited in Kain and Singleton
(1996)] report that school inputs such as class size, teacher quality and
infrastructure have a marginal influence on the achievement of pupils. A study in
China concluded that community resources and school provisions reinforced
transmission of background effects from parents to children, due to effects of school
availability and quality (Hanum, 2003). Other studies in developing countries have
also reported that common causes of inequality in educational opportunities were
regional differences and school availability, expenses, and quality, as measured by

demographic differences. They are suggested as factors affecting dropout of