Educational and family background determinants to employments wage in vietnam , luận văn thạc sĩ

EDUCATIONAL and FAMILY BACKGROUND
DETERMINANTS TO EMPLOYMENT'S WAGE
IN VIETNAM

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Academic Supervisor: Dr. Nguyen Van Phuong
Student: Tang Thi Bich Hien

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ACKNOWLEDGEMENT
fl

First of all, I would like to thank Dr. Nguyen Van Phuong, my Academic
Supervisor, for his valuable comments and assistance. Without his support and
encourage, my thesis would not be finished.
I would like to special thank Prof. Nguyen Trong Hoai, our respectable Dean,
who has been interested in our studying during the Master course.
Supports from the Vietnam-the

Netherlands

Programme

Development Economics' staff and classmates are fully acknowledged .

•

•

Hochiminh city, Mar 2011
Tang Thi Bich Hien

•

for MA m


'
DECLARATION
I declare

that

"Educational

And

Family

Background

Determinants

to

Employment's Wage In Vietnam" is my own work, that is has not been submitted to any
degree or examinations at any other universities, and that all the sources used or quoted
are indicated and acknowledged by complete references .

•

•

I

11


ABSTRACT

'
Data from the Vietnamese Household Living Standards Surveys are used to estimate
the determinants impact on employee's wage. The analysis suggests that educational
attainment strongly affects the wage. The additional level of schooling years positive
changes the wage. It also found that wages have increased according to worker's age,
and a married person is paid higher than other person. The findings recommend that
parents got better education have positive interaction to their children' wages when they
enter labour market.

•

•

111

TABLE OF CONTENTS
I

i

ACKNOWLEDGEMENT...........................................................................................

DECLARATION.......

~................................................................................................

.ii

ABSTRACT ..............................................................................................................

iii

TABLE OF CONTENTS............................................................................................

iv

LIS LIST OF TABLES ...............................................................................................

vi

LIS LIST OF FIGURES .............................................................................................

vi

•

LIST OF ACRONYMS...............................................................................................

vii

•

CHAPTER 1: INTRODUCTION ................................................................................

1

1.1 Research goals and objectives ............................................................................
1.2 Research questions............................................................................

2
.3

o •••••• o . ooooooo .0

CHAPTER 2: LITERATURE REVIEW....................................................................
o ...................

2.1 Theoretical fratneworks .....................

4
o ..................

o .........

o

...... o . oooo ••

2.2 Previous empirical studies .................................................................

0 ••••••••••••••••

CHAPTER 3: OVERVIEW OF VIETNAM LABOUR MARKET .......................
0. 0 ............

3.1 Employment by age and gender ............

•

3.2 Employment divided by regions

0 .....................

0 .......

o .......

0

°

00...

o .. oooooooo ..

. o ........

oooooooooooooo•o

3.3 Employment with education and training ...................

IV

0 ..........

0 ...........

4
6

13
...0..0

o ... o ... o ...............

0

0 ..............

14
17

18

3 .4 Employment by status ......................................................................................
3.5 Unemployment ...............................................................................................

21
23

CHAPTER 4: THE MODEL .....................................................................................

26

CHAPTER 5: DATA...................................................................................................

31

5.1 Statistics descriptive analysis ofVHLSSs ........................................................

32

CHAPTER 6: ESTIMATING RESULTS.................................................................

35

6.1 Results analysis .................................................................................................

35

6.2 Test of education attainment dependence .........................................................

39

6.3 Test of family background dependence ............................................................

40

6.4 Measurement of goodness-of-fit ........................................................................

40

CHAPTER 7: CONCLUSION ..................................................................................

41

7.1 Conclusion .........................................................................................................

41

7.2 Policy implications ............................................................................................

41

7.3 Limitations .......... :..............................................................................................

43

REFERENCES ............................................................................................................

44

APPENDIX ................................................................................................................

46

Regression results ................................................................................... ·· · ..... · · · .. ·· · ·.46
Definitions ...............................................................................................................

v

49


LIST OF TABLE
Table 3.1: Labour force participation............................................................................................. 14
Table 3.2: Labour force divided by sex, regions (%).................................................................17
Table 3.3: Labour force classified by education(%).................................................................. 19
Table 3.4: Distributions of status in employment by sex......................................................... 22

•

Table 3.5: Unemployed workers (person).................................................................................... 23
Table 4.1: Variable description........................................................................................................ 29
Table 5.1 :Mean of wage, age, parents' education and employees' siblings ......................33
Table 5.2: Group of determinants by binary characteristics in year 2008 by
percentage............................................................................................................................................... 34
Table 6.1: Models of Log Hourly Wages...................................................................................... 35
Table A 1: Construction of Duncan index variable....................................................................51
Table A2: Youth labour force participation rates(%)................................................................ 52
Table A3 :Labour force classified by sexes and regions.......................................................... 53
Table A4: Unemployed workers by age-bands (person).......................................................... 54

Table AS: Distributions of status in employment by sex......................................................... 55
LIST OF FIGURE
Figure 3.1: GDP growth rate (%).................................................................................................... 13
Figure 3.2: Workforce classified by age-bands (person)

16

Figure 3.3: Employed worker's skills(%)..................................................................................... 20
Figure 3.4: Workforce vs. employed workers (thousand of person)................................... 24

vi


LIST OF ACRONYMS

GDP

Gross Domestic Product

GSO

General Statistics Office

ILO

International Labour Organization

MOLISA

Ministry ofLabour, Invalids and Social Affairs

UNDP

United Nations Development Programme

VCCI

Vietnam Chamber of Commerce and Industry

VHLSS

Vietnamese Household Living Standards Survey

WTO

World Trade Organization

Vll


CHAPTER 1
INTRODUCTION
The Doi Moi reforms are widely credited with improving incentives for
production and growth. Economic integration and the transition to a socialist-oriented
market economy provide both challenges and opportunities for the people in Vietnam.
Under Doi Moi Renovations, the opening up of Viet Nam to a competitive global
marketplace, with rapid changes in information technologies, capital flows, mass media
and culture. The transition to a market economy in Viet Nam involved a drastic
modification of young men and women's transition from school-to-work. Today, many
youth enter the labour market resulting in labour is a critical aspect of Vietnam's

development strategy in overcoming persistent poverty and enhancing further
economic growth as set out in a number of documents, such as the country's ten year
national strategy for socio-economic development (200 1-2010) with its second five
year socioeconomic development plan (2006-2010). One of main objectives for
Vietnam is to further strengthen its economy and prepare the country for further
integration into the world community that need numerous skilled employments.
Meanwhile, education has played an important role in preparing knowledge for an
employment prior to joining labour market. The linkages between the education and
training system and the labour market have to be strengthened to close the gap between
the skills in demand and the skills offered on the labour market. It is said that a person's
successes in seeking a job after quitting school is remarkable affected by the period he
have stayed at school. As a result, individuals with high levels of education are able to
find work more easily, to command higher wages within a given occupation, and also
to improve their chances of upward occupational mobility.

1


Harmon and Walker (1995) suggest that educational attainment is the main
observed determinant of occupational status, which directly influences earnings.
Vietnam has been viewed as labour endowment but low productivity because of
unskilled

or

semi-skilled

employment.

Consequently,

being

employment

or

unemployment is not hirge distance. For example, if an employment gets higher
education, he enables to adapt easily with changes of technology in a firm, so that he
has more opportunities to be hired again. Additionally, Hamilton et al. (2000) proves
that workers who receiving more training will receive higher income because their
training costs are lower than others without or less training. Adversely, he will become
unemployment if his company makes changes in technology. By finding contribution of
education on employment's wage, we can stress the impact of schooling to individual at
initial stages.
On other hand, children are affected by their family background. Father, mother
and siblings create an environment that help a member better, otherwise adversely
effect by their interactions. Meghir (2005) finds that one of factors is parents' education.
Practically, parent with good education and pay more time for children can be instructor
that encourage them to better study and confident in choosing a work. If we combine
two ideas above, we can find an interesting relationship between wage and family
background of a person after quitting school. Within this framework, the purpose is to
determine the extent to which parents' schooling outcomes feed through into children's
schooling. The determinants effect on wage of an employee is obtained by running
ordinary least squared model. I have utilized data of VHLSS 2006 and 2008 for my
thesis. The next section will introduce previous relevant empirical studies. Section III
will present about Vietnam labour market. Section IV explores the model and
introduces the data in Sections V. The empirical findings are reported in Section VI
with several sensitivity tests are undertaken, and Section VII provides concluding
comments.

1.1 Research goals and objectives

2


The goal of this research is to examine how much of the correlation in wage

~-

can be explained by education and family background by:
i.Employment characteristics: age, martial status, ethnicity as demography and
level of education attainment of observed person, experience, urban, region.
ii.Family background characteristics: father's education, mother's education,
number of siblings.
The thesis aims to establish a model for examining the relationships of wage
on the basis of employment and family background characteristics. Results from
this study can be evidences that education directly affect wage and strengthen the
impact of family to outcomes of a person. From the results, policy
recommendations are suggested.
1.2 Research questions
In order to reach the goals and objectives, this research
following questions:
i. How do employment characteristics affect wage?
ii.How do family background characteristics affect wage?
Specially, the thesis aims to answer questions below:
i. Is the educational attainment level a key factor of wage?
ii.Does family background affect an employee's wage?

3

IS

to answer the


CHAPTER2
:

· LITERATURE REVIEW

2.1 Theoretical frameworks
The Mincer model ( 197 4) has received a lot of attention because of focus on
human capital earnings. That function also reflects the advances in and the spirit of
human capital theory that had been carried forward by Mincer and others in the
intervening years. In his discussion of investment in human capital, Mincer notes that
full-time investment, which is primarily acquired in schools, precedes part-time
investment which is generally conducted on the job. Moreover, for several reasons
investments in on-the-job training would decline relative to earning potential and in
absolute value as experience increases. These factors include the finiteness of the
working life, that profitable investments (i.e., investments where the internal rate of
return exceeds the discount rate) are more profitable if made sooner rather than later,
and the rising opportunity cost of investment as more skill is acquired.
On the other hand, to the extent that the stock of human capital due to prior
investments in training increases the productivity of new investments in on-the-job
training, additional investments are encouraged. If the interest cost of funds schedule
has a non-negative slope, optimal investment occurs in the downward sloping portion
of the marginal rate of return schedule.
Mincer shows that the concave experience earnings profile that we observe in the
data is implied by declining investment ratios (i.e., investment relative to potential
earnings). According to Mincer, there is an important distinction between age-earnings

profiles and experience-earning profiles, where experience means years since leaving
school (Mincer and Polachek, 1974). If individuals differ in their level of schooling,
they differ in the age at which post-school (on-the-job training) investments begin, and
hence the two profiles differ. Mincer demonstrates that there would tend to be a positive
correlation between schooling and on-the-job

4


.:

training investments, not because they are necessarily complements, but because "it
reflects the dominance of individual differences in factors determining the scale of
total human capital accumulation. Individuals who invest more in human capital,
invest more in both forms of it" (Mincer 1974, p.31 ). That is, those with greater
ability and a lower interest cost of funds would tend to have these characteristics for
both schooling and on-the-job training. Research suggests that there is a positive
correlation in dollar investments among all forms of human capital, even though at
the margin various types of human capital can be substituted for each other to attain
the same earnings.
He recognizes that age is relevant if only because of the depreciation of human
capital with age, but in the absence of a mechanism

for measuring experience

independent of age, experience is to be preferred. On the other hand, to the extent
that schooling raises weeks worked by lowering job turnover, unemployment and
absenteeism, controlling for weeks worked biases downward the partial effect of
schooling.
To construct the human capital earnmgs function, Mincer needed to make

assumptions that the investment in on-the-job training in each year declines as years
of experience increase.

Concerned with "mathematical simplicity and statistical

tractability" he shows the development of four functional forms, one for each of the
four cells defined by dollar investments (Ct) vs.

"time equivalent'' investments

(kt=CtfEt_J), and linear vs. exponential forms of declines in investments (Mincer
1974, pp.84-89). Largely due to data availability (that is, the data on schooling and
potential experience are available in years), time equivalent investment ratios are
preferred, and for simplicity the assumption of a linear decline is preferred to the
exponential decline in investment, even though the latter would have greater
consistency with economic theory.
The investment ratio/linear decline specification is that kt=ko-(Ko/T*)Tt. where
kt is the investment ratio in the Tt year of on-the-job training, k 0 is the ratio in the
initial year and T* is the number of years of positive net investment in training

5


:

beyond which kt = 0. Next, if LnEit is the log of earnings of person i in year t and
rk
is the same for all levels of schooling. And then the logarithm of gross earnings
5

5

(i.e., earnings in year t if there is no further investment in on-the-job training EiO)
can be expressed as a quadratic function of years of labor market experience).

lnE. = ln E.
11

+r
z0

s

ks

S.+(r.k
z

1

0

)

T.-(
z

rjk o

2y

2

* )T.

z

where rj is the rate of return from investments in on-the-job training. This function has
become the basis for economic studies of education in developing countries and has
been estimated using data from a variety of countries and time periods

2.2 Previous empirical studies
Worker's skills directly affects employment's wage and there are many empirical
studies examination its correlation. Buchinsky and Leslie (2009) introduced a dynamic
model of individuals' educational investments that allows them to explore alternative
modeling strategies for forecasting future wage distributions. Authors use data only on
male between the ages of 14 and 65 who were either working or in school from the
March Current Population Surveys in the U.S for the years 1964 through 2004. With the
goal is to incorporate a realistic forecasting model into an analysis of individual's
schooling decisions, the research focuses on incorporating uncertainty about aggregate
parameters which are future wage distributions, while presuming certainty over
individual parameters such as parameters of the agent's utility function. The study
contributes an important innovation which is incorporate the role of parameter
uncertainty into the decision making process.
In words, the risk-averse individual in our framework not only takes into the
account the uncertainty of future wage draws (conditional on education and
experience), but also the uncertainty in the distributions themselves such as the
uncertainty in the parameters of the estimated conditional wage distributions. That

6

explains the reason the VAR-Gibbs model is chosen for running regression. There

.·

are two important issues that this research is particularly well-suited to analyzing .
Firstly, they consider how individuals with differing degrees of risk aversion make
educational choices. The result is increasing the degree of risk aversion leads to lower
educational investment because education is a more risky investment than experience,
at least during the period we study. Secondly, the study analyzes the importance of
financial resources for individuals considering higher education by examining the
potential impact of changes in initial wealth on educational choices.
We find distinctive differences across forecasting methods in the fraction of individuals
that attend school in any given year, the average level of accumulated education, and
the time elapsed until a college degree is completed. The study concludes higher initial
wealth also increases the speed at which education is accumulated.
Hamilton et al. (2000) examined how such heterogeneity influences the
distribution of output between workers and employers. These authors analyzed
relationship between profits and wages of a firm to suggest some important findings.
The study is distinct of the study of Sattinger ( 1993) in considering a labor market in
which workers and firms are vertically differentiated. In words, they consider a model
in which common level of general Human capital is identical while worker's skills vary
across workers. The innovation allows them to account for some inherent and
idiosyncratic characteristics of workers that make the population of equally educated
individuals un-equally suitable from the firms' perspective. The study also follows a
different path by assuming a population of workers who are heterogeneous in the type
of work they are best suited for, while firms are also heterogeneous in their job
requirements. And then they develop a nonhierarchical assignment model that can be
viewed as complementary to hierarchical assignment models.

Firstly, if firms are not able to identify the skill type of any individual worker,
workers who receive less training also receive higher net wages. Because firms do

7


not discriminate between workers on the basis of their type, those with a better match
end up with a higher net wage, even though workers have the same level of general
human capital and the same ex post productivity, they incur different training costs
because of different matches. Additionally, as the number of firms increases,
equilibrium wages rise because adjacent firms compete for workers who are better
matches. If the number of firms becomes arbitrarily large, the wage tends to the
competitive level of common level of general Human capital, while profits tend to zero.
The competitive model of the labor market is thus the limit of the spatial model of job
assignment. Finally, when common level of general Human capital increases, gross
productivity rises while the training cost of each worker decreases. As a result, the net
wage increases with the level of general human capital, as supported by many empirical
studies, while profits decrease be-cause firms lose some of their monopsony power, an
effect that overcomes the gain in productivity.
Secondly, if firms are fully informed about the quality of individual job matches
before hiring. Since each firm knows the skill type of each worker, firms can make
different offers to workers of different skill types. The employer just focuses on the sum
of wage costs and its share of training costs, while the employee pays attention on the
wage net of any training costs she or he must bear. Therefore, it is inessential who pays
the training costs in that it is implicitly determined as part of the bargaining process.
When firms can make personalized offers based on skill types, workers who receive
more training now receive higher net wages. However, this is not because they are more
productive than others, as in standard human capital models, but because their training
costs at alternative firms are lower than others. Here workers who are poorly matched
with a firm have a better outside alternative than others who are well matched with the

same firm, thus increasing these workers' bargaining power.

Wage and schooling are also interesting issues for economists besides the U.S.
Meghir (2005) evaluated the effect of the reform on final educational attainment

8


and earnmgs. He used data of Swedish Level of Living Survey and national education
register and the tax record from 1985 to 1996. To apply different in different
methodology, sample was divided two cohorts of pupils. The first is 10,309
observations who were born in 1948 including 5,235 men and 5,074 women. The latter
is 9,007 observations that were born in 1953 including 4,525 men and 4,482 women.
For each group, earnings were collected for the entire 1985- 1996 period. A logit model
is fitting to consider years of education, level of education as measured by two binary
outcomes (whether the final completed level of education was the new compulsory level
or any other, and whether the completed level of education was more than the new
compulsory level or any other). All changes in educational attainment taken together
translate into an increase in years of education by 0.298 of a year. These effects are
highly significant. Within that group, those with low ability increased their attainment
by moving up to the new compulsory level with an almost equal drop in the proportion
attending the former compulsory level. For those of higher·ability, however, the
increase in attainment is reinforced by a large increase beyond the new compulsory
level. The overall effect of the reform on earnings at 1.42 percent was small and only
significant at the 10 percent level. However, this conceals substantial heterogeneity in
the effects for different groups of individuals. For those with unskilled fathers the
reform increased earnings by 3 .4 percent, which is highly significant.

Some older studies have attempted to investigate impact of schooling on wage.
Harmon and Walker (1995) examined the rate of return to schooling on wages and

incomes. The data set used in this analysis is the U.K. Family Expenditure Survey
(FES). The sample consists of 34,336 employed males aged 18-64 in the year of
interview, obtained from pooling the nine consecutive annual FES cross sections from
1978 to 1986. They follow the Instrument variable dealing with the endogenous issue.
However, the study relied on the exogenous changes in the educational distribution of
individuals caused by the raising ofthe minimum school-leaving age in the United
Kingdom (which has occurred twice over the age-spread

9


-- --------

-

of the working-age individuals in our data) to provide instruments for schooling. By
choosing this way, this research has a little bit different to previous studies such as An
grist and Krueger (1991) through exploiting natural variation in data caused by
exogenous influences on schooling decision. Results of this study strongly support the
findings of Ashenfelter and Krueger ( 1994) and suggested that an additional year of
schooling will affect more than 15% increasing of wage. Another finding is residents
living in big cities get higher wages than other regions.
Social scientists from several academic disciplines have long been interested in
the association between family background and economic and social status during
adulthood. There are several studies examined wages under effect of family factors such
as parental income, parental education, and number of siblings. Levin et al., (2007)
exploited a very different way that has not been previously used to measure the brother
correlation in earnings in two different time periods. Specifically, they use two different
cohorts of men from the National Longitudinal Surveys (NLS). The NLS data sets
contain enough siblings from nationally representative samples to enable us to detect

meaningful changes in the sibling correlation across our two cohorts. Using this
approach, we find that the correlation between brothers' annual earnings, family
income, and hourly wages has increased sharply in the United States for cohorts of
young men born between 1957 and 1965 compared with those born between 1944 and
1952. For example, for annual earnings, the correlation has risen from 0.26 to 0.45, and
the change is statistically significant. The results are robust to a variety of sample
selection rules. These results are impression, practically, for the more recent cohorts,
close to half of the variance in earnings and wages can be explained by family and
community influences. Although the sibling correlation captures more than just the
effects of parent income, we argue that the results also suggest that there has been a
decline in intergenerational mobility for more recent cohorts of young men. Findings
show no change in the correlation in years of schooling between these cohorts,
suggesting that a greater association between family influences and educational
attainment does not explain this

10


increase. In addition, while the returns to education have risen markedly between these
two cohorts, this can only explain a very small portion of the overall increase in the
brother correlation in earnings.
Using the same data source from NLS, but Betts (200 1) specifically examines the
impact of school resources on labour market outcomes of women by measuring the
impact of high school resources on women's educational attainment and earnings in the
U.S. The research extracts data from survey of National Longitudinal Young women
who from aged 37 to 50 for the period from 1991 to 2000. There are totally 2,551 the
whites and 801 the blacks participating this study. First stage, Betts fitted an ordered
probit model to investigate education attainment. That model allows interpreting the
coefficients as the marginal impacts on years of schooling. The predicted impacts of
additional school inputs on years of education for black women are in some cases

meaningful. Most impressively, a 10% increase in the starting salary of teachers with a
bachelor's degree, or $605, is predicted to increase black women's education by about
0.1 year. A 10% reduction in class size is predicted to increase black women's
educational attainment by 0.07 year. Similar proportional changes in the other two
school inputs do not lead to changes in education that are as large. The corresponding
changes predicted for white women are much smaller: only for teachers' salary and
books per student is there a positive measured link between education and inputs, and
the coefficients in both cases are much smaller than they are for black women. The
results showed that no significant connection between school resources and wages is
found for while women but school inputs are in several cases significantly and
positively related to black women's wages maybe. because of smaller sample size.
Second stage, a probit model is fitted to examine determinants of women's earnings
with reference to years of schooling is an endogenous function of personal background
proven in the first stage regression. Wage elasticities with respect to school inputs are
uniformly larger for black women. Finally, the impact of school resources on earnings
remains constant or in some cases weakens as workers grow older.

11


In Vietnam, it is popular to recognize the role of parent to children's

.-

education. Broadly, family affects strongly children's development both physical
and metal elements. To study impact of parental and siblings factors on wage of
Vietnam's young labour, the research of Dang, Le and Nguyen (2005) is significant in
recent time. They strongly suggested that the family serves as an important factor in
determining the employment experience of Vietnamese youth. In fact, the family in
which a young person lives is the strongest predictor of his or her future in the job

market. The significant effects of family economic status, parental occupation, and
parental divorce are notable in the analytical results. The sample included 6,604 young
people aged 15-24 from data of Survey Assessment for the Vietnamese Youth in 2003
(SAVY). This research utilized time series data for analyzing instead of cross-sectional
to look at trends in youth employment. Despite data constraints, the research derives
from the multivariate analysis of youth employment that allows us to simultaneously
control for the many factors that may affect labour market outcomes. They found that
educational attainment is also one of the significant factors influencing youth
employment outcomes. The higher the level of education, the less likely they are to be
working at the time of the survey and the more likely they are to look for suit.able
employment as high education is found to be an important factor in increasing the
probability of unemployment, the results indicate the mismatch between supply and
demand for labour services of young people. The probability that a young person is
employed, unemployed or underemployed is reduced when young people live in betteroff families. Additionally, he reaches a better position to enter into the labour market.
Their likelihood to receive job training is enhanced when the father is in a professional
or technical job, belonging to Kinh group and residing in urban centers. All these
combine to make the placement and promotion of their employment easier in the labour
market.

12


CHAPTER3
OVERVIEW OF VIETNAM LABOUR MARKET
Vietnam's macroeconomic performance has been remarkable between 1997 and
2008 (illustrated in figure 3.1). In 2008 due to the impact of global crisis, GDP growth
rate dropped steeply over 2% comparison to the previous year. An average annual
growth rate during this period is 7 .16%. In line with high economic is employment
growth average 2.6 % per year and labour productivity in the country increased steadily,
at an average annual growth rate of 5.3 % from 1997 to 2007 (MOLISA and GSO).

These trends have been positive, since they suggest that many new labour market
entrants or people who changed jobs were taking on more productive work, which can
be considered relatively decent as well, including sufficient remuneration, a key
component for successful poverty reduction.
Figure 3.1: GDP growth rate(%)
--------------- ----·-------- -- --------·

--------

GOP( all sectors)

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Year
~-~~-------~--~- --·~--~~--

Source: GSO, Statistical Handbook, 2009
Until April 1, 2009, Vietnam's workforce got 49.2 million people over 15 year-old
and accounted for 57.3% total population. It included 47.70 employed

13


workers and 1.5 million unemployed workers. The population of Vietnam has been
growing at a fast rate with natural increasing ratio yearly is around 11% from 1997 to
2008. It results in a labour endowment country and young employment holding a

majority proportion in ·labour force. Addition, workforce concentrates in rural.
However, unskilled or less skilled workers become a critical issue of the economy. In
this section, I will view generally Vietnam labour market including information about
employment and jobs, skills, how many people is looking for a job. The analyzing
based on data ofVHLSS 2006 and 2008.

3.1 Employment by age and gender
Table 3.1: Labour force participation

2006
(People)

Both sexes (over 15)

I

(Percent)

24,510

Male

12,115

Female

2008
(People) !
(Percent)

62.73
I

24,321

69.18

49.43

12,081

49.67

12,395

50.57

12,240

50.33

Both sexes (15-24)

6,861

27.99

6,434

26.45

Male
Female

3,595

3,266

52.40

3,451

53.60

2,983

46.40

I

47.6o

I

l

Source: VHLSS 2006-2008
Employment-to-population ratio represents the proportion of the relevant
population groups that are employed. They are, therefore, very important indicators of
economic activity in Vietnam. As suggested in the previous section, this ratio has been
decreasing with a steady upward trend over years, from 62.73 % in 2006 to 69.18 % in
2008. The employment-to-population ratio increased. In terms of population structure, the

youth population is roughly equally divided by sex. From

14

i
I


table 5.1, male experienced increasing ratios but decreasing quantity. With respect to
labour force participation rates, the women' rate 50.33 % comparison to men' 49.67%
in 2008 was slightly higher. Decreases in ratios occurred for women, and women held a
larger proportion than men did in labour force. These are adverse tendency comparison
to results of the Population and Housing surveys from 1997 to 2007 (Appendix, table
A3 ).
Those surveys recorded that all age and sex group experience declining ratios and
women held smaller percentage than men did in labour force. In the survey last year,
employment-to-pop~lation was 53.3% and the ratios of men and women were 52% and

48% respectively. It can be explained there were 39,071 observations in VHLSS 2006,
but there were 35,154 observations in 2008 while labource increased slightly results in
the ratio workforce over total samples increased. In addition, VHLSS focuses on rural
residences where female employment often accounts bigger share. Furthermore, women
participate in agricultural activities and become the bread-earner of a family. They are
unpaid family workers or self-employed. A large number of these individuals have
affected sample size.
Meanwhile, the Population and Housing survey includes all member of a country
that shows the result of a population unsteadied of a sample. The biggest share of this
overall labour force growth occurred among persons in the youth. Young people
between 15 and 24 years of age comprised 27.99% and 26.45% of the total workforce
in 2006 and 2008 respectively. One of sources are young people have tendency to
prolong study process leading to falling in quantity of participation in works. Male's
contributions are more than female suggest that men begin working earlier than women
do. The youth ( 15 to 24 years old) labour force fell over 400 between 2006 and 2008,

or 1.54%. However, below men's labour force participation, the differential between the
two participation rates is much smaller than is the case for many other countries
throughout the world. For both, labour force participation rates declined between 1997
and 2007. Women's declining participation was most pronounced among youth (15 to
24 years old).

15


-

-

- -

Similar to the labour force participation rate, the employment-to-population ratio in
Vietnam is high if considered from a regional perspective, though it is not as high as the
ratio in East Asia. Until 2009, women have still held smaller proportion than men have
in workforce. Women labour accounted for 48% comparison to 52% of men as a trend
during 30 previous years (Population and Housing survey 2009).
Comparison to East Asia as well as South East Asia and Pacific labour force,
Vietnam labour force has gradually dropped during this period. However. Vietnam
changes rapidly than both of them. If male participating workforce fell largest in East
Asia, Vietnam is conversely. The same trend is found for the South East Asia and
Pacific which female's percentages participate in labour force reducing highest (ILO,
May 2009). If the percentage of men in work force accounts similarly to countries in
region, Vietnam's women account a larger proportion. For example, women took part in
work force accounting 79.5% while the Philippines, Indonesia, and Korea that
percentage-was approximately 50% (ILO, 1997-1998). Figure 3.2: Workforce classified
by age-bands (person)

i 2,500

I 2,000

1,500

-+-Male
--Female

1,000

500

0~--------------------------------~--------~

15-19

20-24

25-29

Age-bands

30-34

35-39

40-44

45-49

50-54

55-59

Source: VHLSS 2008
Figure 3.2 states that women and men participating in labour force fluctuate and
gradually fall from aged 15-19, and then they gradually decline. The differences

16


of participation works between male and female begin at aged 15-1 9. The differences
fall gradually from aged 20-24 and reach peak at aged 20-24. From aged 40-44 both
male and female labour is downward declining and this age-band is the smallest
difference. After 55 year-old, women have still taken part in works, even though; they
contribute more than men do. Because VHLSS has been designed for investigating
living standards of rural residences, thus rural areas hold bigger percentage in total
sample. Meanwhile, women are main bread-earners in agricultural activates and unpaid
family workers. They work at all age-bands and do not retire from agricultural tasks as
wages and salaries workers.
3.2 Employment divided by regions
Table 3.2: Labour force divided by sex, regions(%)
r··········································································2aa6··························

····························2ao8·····························1

:

l

'

i

Regions

'

:

1

RedriVerdelta·

-N~rth E-asi________________________--

-N~-rth-west·---------------------

'
~'

·"ATC~exe~---- ··Male____ ---Fe~a1e___ ·A:ifsexes____ -M~1e________ ·:pe~a!e·---

------19.:33-49.-00 ST.OO
----------T5:s·4-- ···49:·5s-- --------·5a-.-42------------··-s-:7"3--

-N~-rth-·ce~1~a:rc0a-5T____

:

~9~16
-----------is·.-~fa··

49-:32

------·-sajj-

5D.681
--------49j~

1·1

---49:"35-- -------··s(Y_-6·5- -------------6.-"1"6-- --------49-:8T ---------s·a:T9--

To:2r 49:·55 ·5o-.-4·5- -------------9.-6"6"

--solith·--------------------------------- ------------··s:7·4-- -··s·a:·i·s·· ---------49-.-82- -----------··s-.-82--

49-."73-o;~-

-··s·a:·s6·o;~-

-----·-·-s·a:-27

--

-------49:·44--

Central Coast

··cefii~a:rt~rgili~n:a~---------

--------------------

South East

--Mekong-~i"~e~-cieita:··-----

------------·6:73-- ---4-9:-78-- ---------5a·:22· -------------6-:94-- ··-·-s-T.-s?·o;~- -------48:-43----------------------··· ---------······· -------------·····-·· ------------------······ --------------------

12.74

49.45

··2o-§s·---------- --49:2"3"--

·u;ban_________________________________ ---23".-74__________ --4&-:6·5·--

--Rli~ar··

50.55

13.07

48.62%

··s-o:??"_______ ··ia-."74·----------- --49-.-:290/~---

··sT3·s··------

·23j~6------------

~--------------------

51.38%

·s·a:-7To/~---

4

j

-48-:6T______ ·s-1:"39________ .

---7"6:26·-----------49.-?·a··- ··s-o:3·a··------ --76-:14·-----------··sa·:aK______ ·49-:94·------- j
i

Source: VHLSS 2006-2008
:,: .....
.

17