(Luận văn thạc sĩ) leaving unemployment of an individual the impact of unemployed benefits and familys income

UNIVERSITY OF ECONOMICS

INSTITUTE OF SOCIAL

HO CHI MINH CITY

STUDIES

VIETNAM

THE HAGUE
NETHERLANDS

VIETNAM – NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT
ECONOMICS

LEAVING UNEMPLOYMENT OF AN
INDIVIDUAL: THE IMPACT OF
UNEMPLOYED BENEFITS AND FAMILY’S
INCOME
By

LE THI CAM NHUNG
MASTER OF ARTS IN DEVELOPMENT ECONOMICS

Ho Chi Minh City, December 2015



ABSTRACT

This paper aims to analyze the determinants to affect the probability of having a job after a
period of being unemployed of Vietnamese labor by using Vietnam household living
standard survey. The study covers 1,156 observations by filtering all people in labor age
who were unemployed in 2010 to analyze their situation in 2012. Demographic
characteristics of each person are focused in order to discover the reasons to help people
find a job meanwhile the macroeconomics factors are considered to be unchanged.
Findings in this research emphasize that income of family, unemployed benefits, money
spending for inpatient fee contributed to demotivate people in seeking a job. On the
contrary, higher education could be helpful for an individual to leave unemployed
circumstance.
Keywords: unemployed people, determinants for having a job, income, education, fee

i


ACKNOWLEDGEMENT
Foremost, I would like to sincerely thank Dr. Pham Thi Bich Ngoc. I am grateful to her
enthusiastic instruction crucial advice and valuable guidance during the time I worked with
this thesis.
In addition to this, I would like to express my respect and thank Dr.Truong Dang Thuy
who gave me very useful advice and comments. More special thanks to all professors and
staff of Vietnam-Netherlands Program as well as classmate and Vietnam-Netherlands
Program alumni.
Finally, I would like to thank you, my family, who motivated me with the master program
and support me to finish this thesis.

ii


ABBREVIATIONS

GDP

Gross Domestic Product

VHLSS

Vietnam Household Living Standard Survey

Sd

Standard deviation

Coef.

Coefficient

NBS

National Bureau Statistics

iii


TABLE OF CONTENTS
ABSTRACT..........................................................................................................................i
ACKNOWLEDGEMENT .................................................................................................. ii
ABBREVIATIONS ........................................................................................................... iii
TABLE OF CONTENTS....................................................................................................iv
LIST OF TABLES ..............................................................................................................vi
LIST OF FIGURES .......................................................................................................... vii

CHAPTER 1: INTRODUCTION ........................................................................................1
1.1. Problem statement ......................................................................................................1
1.2. Research objectives ....................................................................................................2
1.4 Data and methodology ................................................................................................3
1.5. Thesis structure .............................................................................................................3
CHAPTER 2: LITERATURE REVIEW .............................................................................5
2.1. Some definitions and concepts ...................................................................................5
2.1.1. Unemployment definition ......................................................................................5
2.1.2. Type of unemployment ..........................................................................................5
2.1.3 Definition of leaving unemployment ......................................................................6
2.2. Literature review ..........................................................................................................6
2.2.1. The influence of demographic characteristics on leaving unemployment ............6
2.2.2. The impacts of unemployment benefits .................................................................9
2.2.3. Income and leaving unemployment .....................................................................10
2.2.4. Health status and being unemployed ...................................................................11
2.2.5. Summary of empirical researches about leaving unemployment ........................12
CHAPTER 3: DATA AND METHODOLOGY ...............................................................15
3.2. Data description........................................................................................................15
3.3. Analytical framework ...............................................................................................18
3.4. Econometric model ..................................................................................................19
3.4.1 Modeling for probability of leaving unemployment.............................................19
3.4.2. Econometric model in thesis ................................................................................21
3.5. Data consolidation and list of variables ...................................................................23
iv


CHAPTER 4: SUMMARY STATISTICS, EMPIRICAL RESULTS,
AND ANALYSIS ..............................................................................................................27
4.1. Overview of unemployment in Vietnam ..................................................................27
4.2. Statistics summary....................................................................................................28

4.2.1. Unemployed benefits ...........................................................................................28
4.2.2. Expenditure for healthcare ..................................................................................28
4.2.3. Family income .....................................................................................................29
4.2.4. Demographic characteristics ................................................................................30
4.3. Regression and analysis ...........................................................................................32
4.3.1. Empirical result .................................................................................................32
4.3.2. T-test for significant statistics variables .............................................................38
4.3.3. Descriptive statistics for type of jobs of employed people ..................................40
CHAPTER 5: CONCLUSION AND POLICY IMPLICATION ......................................46
5.1. Some findings ...........................................................................................................46
5.2. Policy implications .....................................................................................................48
5.3. Limitations ..................................................................................................................49
REFERENCES ..................................................................................................................50
APPENDICES ...................................................................................................................54

v


LIST OF TABLES
Table 3.1: List of variable in unemployed benefits group
Table 3.2: List of variables in health status group
Table 3.3: List of variables in family income group
Table 3.4: List of variable in demographic characteristics group
Table 4.1: Summary of unemployed benefit variable in 2012
Table 4.2: Summary of expenditure for healthcare in 2012
Table 4.3: Summary of family income variables in 2012
Table 4.4: Summary of age variable
Table 4.5: Determinates of unemployment leaving 2010 and 2012
Table 4.6: the role of partnership, gender, and unemployed benefits
Table 4.7: T-test for medical internal fee of 2012

Table 4.8: T-test for income of household in 2010
Table 4.9: T-test for unemployed benefits in 2012
Table 4.10: T-test for income by property in 2012
Table 4.11: Job types of employed individual in 2012
Table 4.12: the average working hour per days of employed people in 2012
Table 4.13: the average working days per months of employed people in 2012

vi


LIST OF FIGURES
Figure 3.1: The relationship between leaving unemployed and individual’s factors
Figure 4.1: Exit rate out of unemployment by gender
Figure 4.2: Marital status of unemployed group in 2010 and 2012
Figure 4.3: Marital status of employed group in 2010 and 2012
Figure 4.4: The status of signed labor contract of employed individuals in 2012
Figure 4.5: The status of obtaining unemployment insurance of employed individuals in
2012

vii


CHAPTER 1: INTRODUCTION
1.1.Problem statement
Unemployment has brought a lot of consequences to not only the economy but also
the society and individuals (Layard et al, 2005). First of all, a higher payment that this
phenomenon can cause to the society is insurance, pension, subsidiary as well as resulting
a waste of human resources. In addition, gross domestics product might drop because
individuals faced with the unemployed situation. Secondly, in the situation of jobless and
less income, it is easier for an individual to turn to crime to meet financial needs. This

action could result in an unstable situation and slow development for society (Jensen et al,
2003). Under the pressure of earning money for surviving, people are easier to get the
sickness and health problems. Furthermore, some people who could not suffer from
unstable circumstances and they did wrong behaviors such as suicide or disregarding
themselves and lives.
On the other hand, a good work could make an individual to develop their skills as
well as have some money to save for family and their activities, the better job people get,
the most satisfied people feel in their lives (Drobnič et all, 2010). Hence, the unemployed
situation of an individual could be explored deeply to find a solution to decrease such an
issue. In addition, time to find a job should be reduced to prevent demotivation for people
in the time of waiting.
According to data from General Statistics office, the unemployment rate of
Vietnam is quite low at 1.96 % in 2012, this number increased and reached 2.1% in 2014.
Nevertheless, this rise is not critical. Although the unemployment rate is low, the rate does
not really reflect the overall picture of labor employment because of some following
reasons. Underemployment is not reflected in the overall unemployment rate
(Fields,1975). Besides, that laborers who are on the way to quit the job and find a new one
are not mentioned.
From any point of view, unemployed situation do matter for government,
economist and each person. In the case of Vietnam, during the period from 2009 to 2010,
Vietnam had lost half million and one million jobs in 2009, 2010 respectively due to
economics slowdown (Cuong, 2010). This event could threaten the development of society
as well as living standard of citizens. Hence, it is necessary to find out the solutions to
reduce the unemployed situation to help employee and family release burden of physical
needs. Researchers studied on the impacts of economic recession to labor market and
1


employment in Vietnam. Kien et al (2009) found that trade liberalization in Vietnam can
help expand exports in Vietnam, which creates more opportunities and demand in the labor

market. As the results, employment would be improved thanks to such an activity. Zhu
(2005) researched the change on human resources management in Vietnam during Asian
crisis and found that Vietnamese management system for human resources changed from
stable to be more competitive, flexible and market-oriented to adapt. In general, many
types of research in macroeconomics to look for the influence of changing in the economy
to labor demand and supply. However, it has less paper to find the determinants to support
individuals to find a job. This thesis will fill the gap and concentrate on how personal
factors could help an individual to have a job after unemployed time.
The distinct in personal circumstances could lead to the different in career path and
income. Hence, Vietnam needs a research to determine which demographic characteristics
influenced to the exit of the unemployed situation. Furthermore, the result could bring a
clear picture to policy makers in order to reduce the unemployment rate in Vietnam. There
were many economists studying the possibility to exit unemployed status. Among them,
Nickell (1979) used a logit model to estimate the probability of leaving unemployment
using the household Data of British in 1978. This research created a basement for the
following ones. Although the technique improved year by year, however, Nickell’s method
could be applied to study the probability of leaving unemployment in Vietnam.
1.2.Research objectives
There are three main research objectives needed to focus in this study. In general,
all studies aims to find out the probability of leaving unemployment in Vietnam thank the
data of Vietnam household survey in 2010 and 2012.
Firstly, this thesis will study the probability of leaving unemployment of people in
2012 who were unemployed in 2010. The determinants to affect probability were divided
into four groups: unemployed benefits, health status, family income and demographic
characteristics.
Secondly, we analyze the impact of unemployed benefits on exiting unemployment
with the role of gender and partnership of individuals.
Thirdly, given person who had jobs in 2012, we examine their types of job and how much
time they spent for such a job they got.

2


1.3. Research questions
In order to address all of research objectives, the following questions should be
answered:
-

What are the determinants of leaving unemployment in 2012 for those people who
were unemployed in 2010?

-

How do gender and partnership of individuals play a role in interfering unemployed
benefits on leaving unemployment?

-

Finally, once leaving unemployment, what do individuals work in term of types of
jobs and working time?

1.4 Data and methodology
Data of Vietnam Household Living standard Survey (VHLSS) in 2010 and 2012
are used in this thesis. The GSO conducted this survey every two years and more than
30,000 individuals of the household were interviewed. Information is given such as the
circumstances of income of the household, the situation of working of each individual as
well as the health status and educational background.
Basing on the dataset of 2010, a sample of unemployed people is extracted, then
employment situation of these individuals will be in 2012. Accordingly, the sample could
be divided into two groups: keeping unemployment and leaving unemployment. Finally,

data consist of 1,156 observations including 767 people remaining unemployed situation
and 389 persons exiting unemployment.
In this thesis, we study the probability of leaving unemployment or heaving a job
and the leaving unemployment might not focus of its economic definition, it is simple to
consider people who have a job is leaving unemployment and who don’t have are
unemployment. Data is covered within VHLSS only, thus, macroeconomics factors are
considered to be unchanged from 2010 to 2012 although it is not realistic. However, only
internal factors of the individual should be explored to answer research problem and the
question that which affected their probability of having a job.
Logistics regression is applied to research the probability of leaving
unemployment.
1.5. Thesis structure
The thesis is designed into four parts within four chapters. Firstly, chapter one is
the introduction to brief about the thesis including problem statement, the scope of study
and research objectives. The next one is chapter two to show literature review from
3


previous studies, this phase is indicating about theories, research problem, as well as
methods economists used to research on such a problem is mentioned in this part. The third
chapter is data and methodology consisting of econometrics model, a framework for
analysis, data and variables are introduced in this chapter. The fourth chapter expressed the
regression and results. Finally, chapter five summaries what message transferred as well as
some policy implication.

4


CHAPTER 2: LITERATURE REVIEW
2.1. Some definitions and concepts

2.1.1. Unemployment definition
Unemployment is one of the most striking feature attracting quite of few of experts
and economists to discuss and find out solutions to improve such a situation to bring a
better life for individual in particular and society in general. Hence, there are many
definitions about unemployment.
According to International Labour Organization (1954), a person who considered
unemployment if he or she satisfied three conditions: firstly, this individual does not
possess any job; the second requirement is that he or she is ready to work and finally this
person is seeking jobs.
Whereas, US Bureau of labor statistics defined unemployment as a person who is
jobless and finding a job last four week, besides that they are also ready to work. Besides
that, people who are temporarily laid off and waiting to recall for a job is also including the
unemployed group.
Besides that China has classified the perception for people is unemployed in the
urban area. National Bureau Statistics of China said that “the registered unemployed
person in urban areas refer to the person who are registered as permanent residences in the
urban area, engaged in non-agriculture activities, age within the range of working age (1650 for male and 16-45 for female, capable to work, unemployed but desirous to be
employed and (who) have been registered of local employment services agency to apply”
(NBS, 2002 CD-ROOM).
In Vietnam, Ministry of Labour gives a definition of unemployment as groups are
people who in the range of labor are capable of working. They aim to work and are
available to work but could not find a job.
In general, there are many definitions of unemployed and ways to divide this
indicator, however, all perceptions focused on three requirements: people in the labor
force, be able to work, and finding a job.
2.1.2. Type of unemployment
Unemployment is classified in many categories depending on appearance, causes
of unemployment and unemployed characteristics. Thus, there are many types of

5

unemployment. However, there are three main types: cyclical, frictional, and structural
unemployment.
Cyclical unemployment is rated to the cycle of an economy. Every economy has to
witness up and down. When the economy is good, cyclical unemployment is not
meaningful, however after recessions, many people lose their jobs because there are not
vacancies for them, which is considered to cyclical unemployment.
Among individuals who have jobs, there are quite a few of people intend to take new jobs,
when turnover happens among the organizations, which create frictional unemployment.
Structural unemployment is created by the mismatch between demand and supply.
By this I mean, the workers provide skills and experiences do not meet the employer’s
requirements.
It could not be denied that we always have a number of unemployed people in an
economy. The unemployment rate is never 0. However, the responsibility of economists
and governors is to try to help people to find a job to get income for their lives.
2.1.3 Definition of leaving unemployment
Mortensen (1976) with his own research showed that leaving unemployment is the
receiving an offer and accepting it. To start with the new job, Every person intensively
maximize their expected utility. Employee considered the income and leisure they received
during out of work time and the expected income for a new job to decide whether they
took over them
Nickell (1979) developed this theory by adding one factor to influence individual’s
decision. This is “environment” surround, In addition to income and expenditure, people
should care about morale, self-esteem, customs and culture when they accepted an offer.
The two mentioned theory stated that leaving unemployment means that individual start a
job, in this circumstance, having a job is a mandatory field to remark that people leave
unemployment.
On the other hand, when building competing risk model, Olga Kupets (2006)
assumed that leaving unemployment was exiting to employment or falling to an inactive

situation, which meant that people could be retired, quit a job to study or do volunteer jobs.
2.2. Literature review
2.2.1. The influence of demographic characteristics on leaving unemployment
One of the important factors affected the possibility of leaving unemployment is
age. According to Nickell (1979), age played an important role in the duration of
6


unemployed periods of old workers. It is easy to understand because people were hurrying
to have a job when they considered that they were older and older with less competition.
When researching unemployment in Ukraine, Olga Kupets (2006) recognized the negative
relationship between age and having a job. In the changing of the economy of Ukraine,
older candidates are a disadvantage in competition to leave unemployed. Van den Berg and
Van der Klaauw (2001) stated that people who were in 25 years old has a double
probability to leave unemployed situation comparing to the individuals who were at 50
years old. Hunt (1999) studied in the determinants of unemployment and non-employed in
Germany. He found that age is one of the most significant factors affecting during of
unemployment. Moreover, in his research, he emphasized that individuals were over fifty
had a much longer duration of non-employment than younger people. From a different
view, Brooks and Volker (1986) made a research on the probability of leaving
unemployment in Australia basing on Australian Bureau Statistics. They presented an
interesting indication that among the same age groups, the older women had the highest
probability to shift from unemployed to employed whereas men witnessed the lowest
possibility when they got older and older. When investigating effects of length of
unemployment and age on jobless in Israel, Kulik (2001) found that middle age candidates
saved more time to searching jobs and obtained some advantages when attending
unemployment group than the younger generation. Hahn (2009) built a model to match
searching of unemployed people and labor market using data of US employment and EU15. He pointed out a summary that when people became old, the matching model was less
meaningful, which means that it is more difficult for older people to find a suitable job
than the young generations.

Among personal factors, it could not be denied that gender played an important role
in human life because it affected energy and ability to work of a human. Røed and
Nordberg (2003) did a research about the probability of leaving unemployment in Norway
and pointed out that women have less probability to find out a job after being unemployed
than men although they tried to test in single risk or competing risk model. However,
Ciuca et al (2010, Oct) studied the factors helped people to overcome the unemployed
situation and they found that the differences between male and female are not significant in
the probability of leaving unemployment. On the other hand, the female youth had a higher
opportunities to leave unemployment for schooling or working, which is the conclusion of
Jensen et al (2003). Furthermore, Dolado and Jimeno (1997) explored the causes of
unemployment in Spanish and emphasized that most of long-term unemployed people are
women in the youngster in the 90s. Hunt (1999) also gave an opinion about the interaction
7


of gender on unemployment duration. Women who were over fifty or having a child would
spend more time in the non-job situation.
Education is one a striking feature when analyzing unemployment at the individual
level. Nickell (1979) did a research named “education and lifetime pattern of
unemployment” to discover the effects of education on being unemployed. He recognized
that when people pursue higher education but not far away from university level, the
unemployment should be improved. On the other hand, Franz and König (1986) researched
the causes and duration of unemployment in Germany in 1970s, after working, they found
that the demand for higher education could lead to reducing unemployment because these
individuals left the labor force. According to the statistics, people who took vocationally or
apprenticeship training has a shorter duration of unemployment than persons possessed a
university degree or not attending any training. Jensen et al (2003) were concentrating on
finding out the interact of youth when encountering to be unemployed in Denmark. They
listed out the reasons made unemployment rate in the young drop and noted that the transit
from unemployment to schooling for higher education could lead to such a decrease.

Hence, the probability of leaving unemployment increased but the result was not expected
because young people did not shift from unemployed to employed. Those people left the
labor force to follow higher education. Tansel and Tasci (2004) studied the elements
contributing to boosting people leave unemployment in Turkey and found that the higher
education could result in higher probability of existing unemployment, he also mentioned
that this conclusion is suitable for most Organization for Economic Co-operation and
Development countries. Mincer (1991) researched on male labor face of United State of
Americ, he found that the higher education people achieved, the lower risk at unemployed
they faced. Besides that the turnover among educated people is also lower than noneducated workers.
In our society, the relationship of human is complicated, however, marital status is
a factor should be a concern when we analyzed individual behavior. Edin (1989) pointed
that the probability of to be re-employed is higher for married persons when he
investigated the factors affected leaving unemployment in Sweden. However, the data set
is limited in the pulp factory. There was a pulp factory was closed in 1977, all workers
were informed since 1976. Edin investigated the situation of workers who lost job since
1976 to 1981 and found the conclusion as mentioned above. However, Arulampalam and
Stewart(1995) discovered the factors to affect leaving unemployment in the 1980s when
the unemployment rate was quite high in 1995. They did a research on leaving
unemployment in 1978 and 1987, the two years witnessed significant unemployment ratio
8


in England. In 1978, marital status played an important role for people to leave
unemployed status. However, having a partner in 1987 did not have much influence to
motivate people to get a job. Kupets (2006) also found that married men after facing
unemployment were hurried up for seeking a job, which is easy to understand because men
in the perception of family leader, they were responsible for a budget of the whole family,
so they needed a job. While married women had lower leaving unemployment probability.
2.2.2. The impacts of unemployment benefits
Bover and Bentolila (2002) chose unemployed men from 1987 to 1994 in Spain to

find out the relationship between benefits and leaving unemployment probability. They
found that the more benefits during unemployment time increased, the lower leaving
unemployment probability was. Jenkins and García (2004) tried to discover the impact of
unemployed benefits on the decision to come to be employed of workers in Spain. They
researched on the influence of unemployment benefits, especially unemployment insurance
(UI) people received during the non-job time. The conclusion is the impact of unemployed
insurance is quite small on discourage people to come back with a job. However, if we
investigated at an average level, the effects were larger for 4 to 18 months unemployed
men.
In long-term, the influence of UI seemed to be neglected. Alba-Ramírez et al.
(2007) gave a new concept of leaving unemployment. When existing unemployed
situation, people could recall to the previous job in case that they were laid-off or quit and
searched for a new job. They chose data set of all unemployed people in Spain from June
1999 to June 2002 and concluded that people who claimed for unemployment benefits
consisting of unemployment insurance, assistance were slower in leaving unemployment
than the non-claimers. Meyer (1988) researched the effects of unemployed insurance on
the spell of male unemployed in twelve states in the US from 1978 to 1983. He found the
conclusion that higher benefits could lead to the lower probability of leaving
unemployment. However, the probability would increase dramatically if the insurance
benefits stop.
In addition, if people continued to receive benefits after stopping a while, the
probability of leaving unemployment in the first week was still high. Poterba and Summers
(1995) studied to re-confirm the impact of unemployed insurance on the duration of
unemployment as well as the probability of exiting unemployment. They used the data
from Current Population Survey of US in May 1976 and 4668 men who were unemployed
fulfilled the survey form for the estimation. The result of this study emphasized that
9


benefits received during the unemployed period in general and money from insurance, in

particular, contributed remarkably to lengthen the duration of unemployment. D'Addio and
Rosholm (2005) studied the exit from a temporary job in European Community from 1994
to 1998. The panel data was used to estimate such an issue. People who took temporary
jobs were less educated, low wages, less social skills, etc. as the resulting money they
received from jobs was less as well as a low unemployed benefit when they quitted jobs.
The lower benefit in the spells of unemployment could lead people to make a decision of
taking temporary jobs again as they considered to maximum their utilities. In this case, the
probability of leaving unemployment was high but it could not reflect the quality of the
job, as well as the future of individual as most of the temporary jobs, was dead end ones.
2.2.3. Income and leaving unemployment
Income is considered to be the most influence for individual to exist unemployment
situation. Many types of research and paper to emphasized the interaction of income. Perry
et al. (1972) studied the inflow of US unemployment and found the turnover among
teenagers were high. Perry in his point of view explained this phenomenon as the result of
an increase in family income and more opportunities out of labor force. Actually, he
emphasized that if income in family increased, young people were more freedom to choose
another job or even pursue another activity such as higher education, voluntary action, etc.
Lynch (1983) reviewed job search among youth unemployment. This research was based
on previous empirical of Nickell, Lancaster, and Chesher. However, the conclusion of
Lynch is a contrast with the previous study. Income was not an important factor to the
affected decision of leaving unemployment to be reemployed in young people in Great
Britain in 1980s.
Narendranathan and Stewart (1993) investigated the influence of income during the
duration of unemployment. They point out that the interaction of income decreased in align
with time and was not significant in the long term. By this way, there was no effect of
income on the probability of leaving unemployment after five months being in this
situation. Within 5 months after registering as unemployment, the influence of income
drop steadily. Stancanelli (1999) promoted the analysis about unemployment duration in
Britain and argued that there was a negative impact on income on the probability of
leaving unemployment.

Kupets (2006) in his study about determinants of leaving unemployment in Ukraine
emphasized the negative effects of household income on existing unemployment situation.
In details, household income contributed to making the probability of leaving
10


unemployment low. Nickell (1979) focused on the replacement ratio defined as household
income during the unemployed period divided by expected income when an individual got
a job. He found the result emphasizing that within 20 first weeks of unemployment,
replacement ratio had a negative impact in leaving unemployment. However, after this
mentioned period, this interaction was not considered.
Arulampalam and Stewart (1995) explored the years witnessed high unemployment
in Great Britain, which were the 70s and 80s of the twentieth century. They concentrated
on investigating the income of other members in the family, especially focused on partners
(wife or husband) and gave an interesting conclusion that a male with working wife had
much higher probability of exiting unemployment than a single man as he faced with selfesteem and had to find a job to continue as family leader.
2.2.4. Health status and being unemployed
Health is one of the mandatory fields for people to check whether an individual
could be suitable for a work. Bernklev et al. (2006) studied effects of inflammatory bowel
disease on unemployment and sick leave. They investigated 495 patients in Norway and
followed during five years from interviewed time. The authors found that unemployment
and sick leave rate of disease people are higher than normal individuals in the population.
Akhavan et al. (2004) researched the influence of health in unemployment of
immigrated people in Sweden classified by gender. These researchers chose 30 men and
women and half of the observations were under poor health or had a problem with health.
They found that the process of migration made people sick and led to unemployment or
sick leave in work. Janlert (1997) discovered the link between health problem and
unemployment; he did research in Sweden and found that people who suffered health
problem had more problems in finding a job than normal persons in the population.
On the other hand, unemployed status could lead to the extent of using alcohol and

smokers was easier to become unemployed than non-smokers. Schuring et al. (2007)
explored the possibility of people who faced health problem to find or maintain a paid job.
It was owing to the fact that male or female had a problem with health had lower
probability of leaving unemployment than normal men with good health. This conclusion
contributed to confirm that health played an important role when people find new jobs or
even maintaining currently paid jobs. Ill health could lead to the low probability of leaving
unemployment as well as the exiting of the labor force. van den Berg et al. (2010) explored
the interaction of health problem on paid employment. The result argued that health

11


problem had significantly affected on leaving paid unemployment to retire in European
workers among 50 to 63 years old.
2.2.5. Summary of empirical researches about leaving unemployment
Authors
Jeskins

Methodology

and Hazard model

Independent variables
Unemployed benefits

Results
Negative

impact

on

García (2004)

leaving unemployment

Bover

Negative

and Discrete hazard Unemployed benefits

Bentolila

models

impact

on

leaving unemployment

(2002)
Poterba

and Multinomial

Summers

Unemployed benefits

logit model

impact

on

leaving unemployment

(1995)
Perry

Negative

of individual
et

al. Logit model

Family income

(1972)

Negative

impact

on

leaving unemployment

of individual

Kupets (2006)

Janlert (1997)

Cox

Family income

Negative

impact

on

proportional

leaving unemployment

hazards model

of individual

Descriptive

Health status

statistics

Health problem could
reduce the opportunity
of leave unemployment

Schuring et al. Logistic
(2007)

Health status

regression

Ill health could prevent
people in finding a job

analysis
Van

der Maximum

Klaauw

likelihood

(2001)

two datasets

Age

The younger individual

for

is,

the

higher

probability of leaving
unemployment he got

Nickell (1979) Logit model

Age

Old people are more
difficult in getting a job
than the young

Røed
Nordberg

and Competing risk Gender
model

Males have more pros
in finding a job than

(2003)

female
12


Authors
Ciuca

et

al Cox

(2010, Oct)

Tansel

Methodology

Independent variables
Gender

Results
Gender did not play an

proportional

important

hazard model

leaving unemployment

and Hazard model

Education

Tasci (2004)

role

in

The higher level of
education could lead to
higher probability of
exiting unemployment

Edin (1989)

Competing risk Marital status

Married

people

are

model

more hurry in finding a

job than the single ones

Source: author’s summary
2.3 Hypothesis testing
According to previous studies done by Bover and Bentolila (2002), Jenkins and
García (2004) and Meyer (1988), the more unemployed benefits people received, the lower
probability of leaving unemployed they got. We have the first hypothesis as below:
H1: unemployed benefits have negative impact to probability of leaving unemployment
Perry et al. (1972), Kupets (2006) concluded that income of family contributed to
demotivate peole in finding a job. The second hypothesis could be described as followings:
H1: family income influences negatively to leave unemployed situation of an
individual
Bernklev et al. (2006) and Akhavan et al. (2004) considered that the healthy people
have more advantages than the sick ones when finding a job. Below is hypothesis:
H1: illness contributed to make probability of leaving unemployment low.
Nickell (1979) and Van der Klaauw (2001) studied the influence of age in seeking
a job and gave a conclusion that the young individuals were easier to find a job than the
older. Hence, we have the following hypothesis
H1: the old people is more difficult to find a job than the young ones.
Nordberg (2003) and Dolado and Jimeno (1997) discussed the influence of gender
to unemployment and found that males had more advantages in seeking a job than females.
Thus, the below hypothesis could be applied:
H1: men are more easier to leave unemployment than women.
Tansel and Tasci (2004), Mincer (1991) emphasized the important role of
education to help people find a job. We can test the hepothesis:
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H1: the higher year of education individual attend, the lower probability of leaving
unemployment he receive.

Edin (1989) and Kepets 2006 said that people being married were more hurry in
finding a job than people who did not have a spouse. Hypothesis for this point is given as
below:
H1: partnership has positive impact to support people leave unemployment.

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CHAPTER 3: DATA AND METHODOLOGY
3.1. Data source
Data is extracted from Vietnam Household Living Standard Survey (VHLSS) in
2010 and 2012. VHLSS has been doing by Vietnam General Statistics of Vietnam since
2002. The data is collected every two years. The main purposes of this survey are to
provide information about living standard of citizens for a policy maker to develop a good
strategy to improve the quality of lives. Objects of the survey are households in 64
provinces of Vietnam. The sample is designed to thank the existing one in Vietnam
Population and housing census in 1999 and 2009.
The investigation is starting from enumeration area in town or ward and coming to
a household with all members.
The results of this survey provided information about families and general status of
town and ward. Demographics characteristics of each person in the family including age,
gender, health, educational background are mentioned in the result of the investigation. In
addition to this, the infrastructure, economic situation, the environment of town and ward
are also reverted in the survey.
VHLSS is official dataset which covered many sides of household and residences
situation in Vietnam. Hence, this survey is used to research on many topics such as
poverty, employment, migration in Vietnam.
3.2. Data description
The target population is laborers who were unemployed in 2010 survey. We
observe the dependent variable by looking at the employment status of these people in

2012 survey. The dependent variable is a dummy one indicating unemployment exit,
which take the value of 1 if the laborer turns out to be no longer unemployed in 2012,
otherwise 0.
All variables are chosen based on theory to study their effects on the main factor:
leaving unemployment.
According to the literature review, the main factors to affect the probability of
leaving unemployment are age, gender, educational background, income, benefits during
unemployed, health. However, in the restrictions of VHLSS, we could only filter some
indicators to describe such a research problem. Age is fallen into the labor age according to
current law of Vietnam. Hence, only people are from 15 years old to 58 years old in 2010

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for male and 15 to 53 years old for female are chosen. Marital status contributed to the
decision of each individual to accept an offer to get rid of being unemployed.
In VHLSS, we have 5 marital situations of an individual including single, married,
divorced, widow and legally separate. Nevertheless, among five categories, we have two
main groups which are people who stayed with a partner (means that wife or husband) or
lived alone. Besides that, obviously, 2 genders are mentioned, these are men and women.
Educational background is chosen from the highest degree people get according to
their statement on the survey. there is a tool to evaluate the education in this situation
basing on the current education system of Vietnam, which is the number of years
individual attended school. For instance, we have 0 years for no educated in school
persons, 5 years for a primary diploma, 9 years for secondary, 12 years if individual
finished high school with a certificate, 15 years for college, 16 years for university and 18
years for a master degree.
To analyze the interaction of income in getting a job, income has divided into four
sections including income of household earning by working, in VHLSS, interviewees
supplied income they earned for the main work and the second one; income getting from

lending money, house and real estate, investing in fund and insurance; income given by
another individual and organization in domestic or foreign by offering in special occasion
such as wedding, funeral, birthday or another parties in countryside of Vietnam; income
which is not mentioned above and not belonged to the three classified group. Because
income is one of the key factors in this thesis, we investigate the impact of every type of
income. When people facing the unemployed situation, they had occasion to receive
subsidiary or assistance from government or organizations thank unemployed insurance or
the policy of the company to support when employee quitted the job.
In this research, unemployed benefits are counted by summing up all money person
receive when they leave a company or organization because of any reasons including that
company needs to cut cost or ask to retire earlier although they were in labor age.
Moreover, a household in Vietnam also received some avocations from the government
such as subsidiary or support for family contributing in battles of Vietnam or subsidiary for
natural disasters. Hence, in this research, there are two supports should be considered, one
is for individual and other is for the household.
Health is an important factor contributing to the development of individuals and
society. Thus, the indicators showed health situation are selected to analyze. However, the
variable related to health should be emphasized. During the data of VHLSS survey, it is
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