1. A Study Economic Factors effecting
Unemployment in Somalia
Project work submitted for the partial fulfilment of the
Requirements for the award of
Master of Arts Degree in Economics
Submitted by
Reg No. I1604002
D E P A R TME N T O F E c onomic s
A N N A MA LA I UN I VE R SI TY
A pril 2021
2. ANNAMALAI UNIVERSITY
D e p a r t m e n t o f E c o n o m i c s
Dr.M.RAJESWARI Date:
Assistant professor Annamalai Nagar
CERTIFICATE
This is to certify that the Dissertation
entitled “A Study on Economic factors
effecting Unemployment in Somalia " is a bona
fide record of Research work done by
REg.No.I1604002" and is submitted in partial
fulfilment of the requirement for the award of
M.A. degree in Economics of the Annamalai
University. It is also certified that the above
dissertation has not previously formed basis for
any fellowship or other similar titles and this
thesis is an independent and original research
work of the candidate.
(DR.M.RAJESWARI)
Supervisor
Forwarded
(Dr. T.R.JEYARAAJ)
Professor and Head
4. ACKNOWLEDGEMENTS
I express my deep sense of gratitude to Dr.M.RAJESWARI assistant
professor , Designation, Department of Economics , Annamalai University for
his/her valuable guidance and encouragements for doing this project work
successfully.
I am extremely thankful to Dr.T.R.JEYARAAJ, MA, M. Phil, Ph.D.,
Professor and Head, Department of Economics and all Professors,
Associate Professors and Assistant Professors of Economics for their sincere
interest of my work. I wish to express my thanks to all the supporting staff of
the Department of Economics Annamalai University for their support.
My special; thanks to one and all who have provided the data which
helped me to construct this project work effectively.
(Roll 1604210021)
Place: Annamalainagar
Date:-------------
5. CONTENTS
Acknowledgement
Chapters Page
I
Introduction and Statement of the
Problem
1-8
II Review of Literature and Methodology 9-19
III Profile of the Study Area 20-31
IV Analysis and Interpretation of Data 32-45
V Findings and Suggestions 46-51
Bibliography
6. List of tables
No. Title Page
4.1 Age wise distribution of the respondents 32
4.2 Gender wise of the respondents 33
4.3 Marital status of the respondents 34
4.4 Family type of the respondents 35
4.5 Educational status of the respondents 36
4.6 Employment status of the respondents 37
4.7 Causes of unemployment 38
4.8 Monthly income of the respondents 39
4.9 Opinion of the respondents regarding choice of their Work 40
4.10 Opinion of the respondents regarding unemployment effect of
Socio-economics status of the family
41
4.11 Opinion of the respondent regarding
Unemployment effects family relationship negatively
42
4.12 Opinion of the respondent regarding
Unemployment effects common people life
43
4.13 Opinion of the respondent regarding
Unemployment leads to corruption dishonestly crime and sins
44
4.14 Opinion of the respondent regarding
Unemployment people are usually drug user
45
7.
8.
9. 1
Chapter-I
1.INTRODUCTION
2.1 Background of the Study
The current global unemployment problems present a particularly
difficult labor market experience for young workers. The ILO estimates no
less than 40% of all unemployed population are youth. As available studies
show, youth are disadvantaged in finding employment, especially in rigid
labor markets. There are several factors, such as their relative lack of skills,
unstable labor market experience and discrimination, which contribute to the
difficulty usually faced by young people entering the labor market. Thus,
unemployment among youth become a major policy challenge for
governments and employers in the 21st century. The fact that during This
period countries must deal with slow growth and economic activities has
pressured public policy into creating opportunities for economic growth and
employment. There is no shortage of ideas and policy initiatives for
addressing the frightening challenge of youth employment, but the need for a
comprehensive policy approach which combines dedicated strategy for youth
employment must also include measures addressing systemic and
institutional impediments to the sustainability of policies for the employment
of young people. In addition to ensuring that young people stay in school
longer, public policies must also create the enabling environment and
avenues for skills acquisition and real work experience among young
10. 2
workers. Clearly, there is a strong case for governments and other
stakeholders to put in place policies that encourage or motivate employers,
particularly in the private sector, to recruit young workers, through various
forms of public and private initiatives that are dedicated to the promotion of
youth employment.
For national governments and international organizations worldwide,
youth unemployment and joblessness remain major issues. Undoubtedly, the
global economic crisis has further exposed the fragility of the youth in the
labor market. Between 2008 and 2009, the number of unemployed youth
increased by an unprecedented 4.5 million; at the end of 2010, there were an
estimated 75.1 million young people in the world struggling to find work –
4.6 million more than in 2007. Moreover, the number of youth who are not in
employment, education or training is on the rise in most countries. These
alarming trends, alongside recent youth-led political unrest, the persistent
lack of job opportunities and ineffective programs for school-to-work
transitions, call for action on the part of political and social institutions at
national and international levels. In an awareness of the seriousness of the
foregoing questions and consequences that ensue, the present volume aims to
provide some valuable insights into these issues, compiling contributions of
academics.
11. 3
1. Statement of the Problem
According to a UN report, unemployment rate for young people in
Somalia is one of the highest in the world at 67% among all 14 to 24-year-
olds. The Somalia Human Development Report 2012, issued by the UN
Development Program reflects 82% of Somalis to be deprived, with 73%
living on less than $2 a day. Unemployment among youths in Somalia has
also encouraged many to flee their country. Majority of the youth moved to
neighboring countries looking for better opportunities. Some youth crossed
the Mediterranean Sea into Europe in searching for better live dSedue to
worsening economic conditions of the country.
The country has the largest percentage of unemployment in the
populations, long period of Youth unemployment will lead to engaging
antisocial behavior including piracy, drug and alcohol abuse, unsafe sex and
other criminal activities like terrorism. Youth unemployment in Somalia is
compounded by significant level of unemployment and poor-quality jobs in
the formal and informal sector. There are rising concerns over poverty,
Prostitution, substance abuse and International Journal of Contemporary
Applied Researches Vol. 6, No. 3, March 2019 (ISSN: 2308-1365)
www.ijcar.net 175 drug and involvement of extremist activities, youth are
among youth groups in Somalia, youth are neglected and turned into political
ponds by politicians and interest groups. this situation presents youth as
disadvantaged, helpless, luck of representation and unprepared to make any
12. 4
contribution to national and regional development agenda. subsequently, they
are sidelined at the national state policies and have little legal position
Abbink et al, 2005).
The unemployment rate for youth (aged 14–29) is projected at 67 per
cent and is measured one of the highest in the world (UNDP, 2012: xix).
Youth unemployment is particularly concerning given Somalia‟s
demographic profile: 70 per cent of the population are below the age of 30.
Their low of education and skills, coupled with inadequate livelihood
opportunities, is seen as a driver of radicalization, migration and membership
of extremist and other armed groups (Federal Republic of Somalia, 2014).
The problem of youth unemployment is a global phenomenon.
According to a study from an International Labor Office in 2004, youth (15-
24) become nearly half (47%) of the world‟s unemployed in the population,
88 million out of 186 million, even though youth are become only 25% of the
world‟s working age group. Of the world‟s 550 million working poor who
cannot lift themselves above US $1 per day poverty measure, 150 million are
youth. The ILO projected in 2004 that halving global youth unemployment
would increase global GDP by US $2.2 trillion, 4% of global GDP. These
figures lend weight to the notion that youth unemployment is an alarming
problem worthy of world‟s attention. In addition, one may argue that tackling
unemployment in general would also lower poverty levels and add to GDP
(World Bank 2006).
13. 5
Unemployment is the most vital problem all over the world especially
in developing countries. In some ways unemployment became inconsistent
problem facing in many of the developed and developing countries. When
someone needs to work and have the knowledge and the skills to qualify and
don’t get a job is known as unemployment. Keynesian economics believe
that unemployment is there when markets and demand for goods and services
are in efficiency. According to IMF (2008) report stated that unemployment
is measured by the annually percentage of labor force which can’t find a job
but can work. According to the International Labor Organization rules that, a
person is jobless and unemployed if the person is not working, presently
accessible for work and looking for work. Generally, most of the people
understand only that unemployment is when the people do not have a job.
But, unemployment is more complex and broad that concept because
employment determines how every society looks like because the less
employment the less economic development and the less economic stability
in that society. So employment become always an important social factor
which indicates how society is developing. The ILO approach to defining
unemployment rests on what can be termed the ‘labor force framework’,
which at any point in time classifies the working age population into three
mutually exclusive and exhaustive categories according to a specific set of
rules: employed, unemployed, and out of the labor force - where the former
two categories constitute the labor force, i.e., essentially a measure of the
14. 6
supply of labor at any given time. In Somalia, Overall unemployment among
people aged 15 to 64 is estimated at 54 per cent in 2012. The unemployment
rate for youth aged 14 to 29 is 67 per cent, one of the highest rates in the
world. Females experience higher unemployment than males, 74 per cent and
61 per cent respectively. The majority of unpaid family workers are young
women who carry out household work due to entrenched traditional gender
roles. A high labor force participation rate for youth, estimated at 66 per cent,
further reflects lost opportunities for many who might otherwise attend
school and acquire skills that could raise their future productivity and
employment opportunities (OCHA, 2014). Somalia have gone through
various governmental structures from 1991 till now in 2017, as there had
been number of years where country lucked an active regime which can
control the extreme rate of unemployment Journal of Economics and
Sustainable Development www.iiste.org ISSN 2222-1700 (Paper) ISSN
2222-2855 (Online) Vol.8, No.22, 2017 201 which is making an increase
every year. But, as (Human Development Index, 2012) Indicates there is an
urgent necessity to develop, implement and monitor integrated national
policy frameworks, including national employment strategies with dedicated
action plans on youth employment, as well as coherent sectoral policies.
Unemployment in Somalia have enforced a lot of people to leave the country
and migrate in search of an improved life through dangerous journeys
through deserts and seas. More than 60% of youth have intents to leave the
15. 7
country for better living opportunities.
According to ILO (2010) defines Unemployment as without a job, want
a job, have actively sought work in the last 4 weeks and are available to start
work in the next two weeks or out of work, have found a job and are waiting
to start it in the next two weeks. Gross Capital Formation is defined as that
part of country’s current output and imports which is not consumed or
exported during the accounting period, but is set aside as an addition to its
stock of capital goods (Haryana, 2014).
1.1Objectives
1.1.1General Objective:
General objective of the research was to examine the factors influencing
youth employment in Somalia
– Bosaso district
1.1.2Specific objectives: The specific objectives:
1. to examine the influence of education on youth employment in Bosaso
2. to explain the influence of Job Opportunity on youth employment in Bosaso
3. to determine the influence of Culture on youth employment in Bosaso
4. to analyze the socioeconomic conditions of unemployed youth in bosaso
5. to examine the factor influencing youth unemployment among youth in
16. 8
bosaso
1.2 Research Questions The research answers the following questions 1.
What is the influence of education on youth employment in Bosaso? 2. What
is the influence of job Opportunity on youth employment in Bosaso? 3. What
is the influence of Culture on youth employment in Bosaso? 2.3 Justification
The research might be the first or one of rare studies that so far address the
problem of the research. The beneficiaries of the research will thus be the
decision-makers, particularly ministries of labor & youth, Ministry of
Planning and International Cooperation, Private Business sectors and
academic institutions and the researchers.
17. 9
Chapter -II
Literature Review
According to (Imran & Sial, 2013) studied the impact of gross fixed
capital formation, trade openness and wage proxy on employment in
Pakistan. With the use of time series data from 1997 to 2010. To determine
the long run relationship study applied cointegration test and to check the
properties of time series data the researchers used Unit root test. Results of
the study suggests that there are two cointegrating vectors under the study
period. Also the findings indicate that there is a positive relationship between
gross fixe capital formation and employment.
Megbowon & Mushunje (2016) examined the relationship between
capital formation, foreign direct investment inflow and unemployment in
South Africa from the period of 1980 to 2014. Data in this study was time
series data which has obtained from the South Africa Reserve Bank Website
and the study used cointegration and causality tests. The findings of study
shows that there is a long-run relationship within the variables in the
employment model.
Sattar & Bhalli (2013) examined the causes of unemployment in
Pakistan with time series data from 1976-2012. Study examined also the
relationship amongst unemployment, inflations, external debt, FDI,
population growth and gross domestic product. To test the factors that can
18. 10
determine the unemployment in Pakistan, the paper applied Autoregressive
Distributed Lag (ARDL). Results of the study shows that population,
inflation, gross domestic product, and foreign direct investment were the
significant factors that causes unemployment in Pakistan in the long-run and
in short-run.
(Muhammad, 2013) investigated the relationship between real gross
domestic product and unemployment as the Okun’s law stated that there
inverse relationship among these variables. The paper employed time series
data from 1976 to 2010. To examine the relationship between gross domestic
product and unemployment the study employed Ordinary Least Squares
(OLS) method and unit root test. Results reveal that an increase of one
percentage of unemployment will lead a decrease of 0.36% of the real gross
domestic product growth.
(Abdul-khaliq, & Shihab, 2014) examined the relationship between
unemployment and economic growth rate in some of the Arab countries. The
general aim of the paper was to identify the relationship between
unemployment and economic growth rate in some Arab countries. Pooled
data of 1994-2010 was used. The study found the economic growth has
negative and significant impact on the unemployment rate. This indicates that
if economic growth increases 1% then the unemployment will decrease
0.16% under the study period.
19. 11
(Bakare, Akoko, & State, 2011) investigated the determinants of urban
unemployment in Nigeria. They used time series data from 1978 – 2008. To
test the stationarity of the variables Unit root test was used and OLS
regression was also employed. The findings indicated that the growth of the
population has an effect to the unemployment which means that population
causes high unemployment in Nigeria under the study period.
(Ogonna, Idenyi, Ifeyinwa, & Gabriel, 2016) studied the implications
of rising public debt on unemployment in Nigeria. Annual data series from
1980-2015 was used. Econometric analytic tools including auto regressive
model were used. The results showed that there is a long run relationship
between external debt and unemployment. Also the ARDL model indicated
that 1% increase in public debt on the average, will cause about 1.6% increase
in unemployment rate.
Literature explains unemployment from different theoretical
perspectives. Neoclassical economists view unemployment as voluntary
because the labour market is deemed to be always in equilibrium based on
the assumption of flexible wages and perfect market information (Baah
Boateng, 2016). An example of voluntary unemployment within the
neoclassical framework is structural unemployment created by a mismatch
between demand for labour and the skills of jobseekers, made obsolete by
slow response to technological advancements. Frictional unemployment is
seen as being caused by lack of labour market information, increasing the
20. 12
time that jobseekers take to locate and move into a new job and the time and
resources that employers take to identify and recruit suitable workers to fill
vacancies — failure to obtain the relevant information too is seen as having a
voluntary component (Phelps, 1970; Stigler, 1962 in Baah Boateng, 2016).
Clark & Summers (1982) stated that higher rates of youth
unemployment can be explained in two ways: one is limited availability of
jobs that makes job seekers remain unemployed for longer period of time and
the other is the employment instability that moves young in and out of the
labor market and treat them flow into unemployment. Most educated youth
have experienced the former problem that calls for job creation policy for
youth.
British economist, A.W. Phillips, in 1958 based on his good deal of
research using historical data from the U.K. for about 100 years in which he
arrived at the model that has become to be known as Philip’s Curve
(Pettinger, 2017).
The theory states that with economic growth comes inflation, which in
turn should lead to more jobs and less unemployment. The concept behind
the Phillips curve states the change in unemployment within an economy has
a predictable effect on price inflation. The inverse relationship between
unemployment and inflation is depicted as a downward sloping, concave
curve, with inflation on the Y~axis and unemployment on the X.axis
21. 13
(Pettinger, 2017). Increasing inflation decreases unemployment. 10 and vice
versa. Alternatively, a focus on decreasing unemployment also increases
inflation, and vice versa (Pettinger, 2017).
The relevance of Phillips Curve today in this present study, can be
analyzed through the current economic climate. Many countries are weighing
up how much importance they should give to reducing youth unemployment
and inflation. Some have considered using monetary policies to achieve
youth unemployment target and a willingness to accept higher inflation. They
feel to tolerate inflation would lead to youth employment, and vice versa.
This willingness to consider a higher inflation rate, suggest policy makers
feel that the tradeoff of higher inflation is worth the benefit of lower
unemployment (Pettinger, 2017). However, the theory does not make all
countries to allow inflation. If we allow inflation to increase, inflationary
pressures will become engrained, and monetary policy will lose credibility.
The governments would be unwilling to tolerate higher infiations — even as
a measure to reduce youth unemployment.
This study is based on the Labour-Market Theory formulated by Mark
Casson (1979). The theory of labor market posits the existence of a central
market for labor, consisting of buyers and sellers in open competition with
each other. The labor market is seen as functioning in the same way as other
markets. The function of the labour market is to match people to jobs. It
should be noted that, not all people are equally suitable for a given job, nor
22. 14
all jobs equally suitable for a given person (Casson , 1979). So far as the
suitability of a person for a job is concerned, there are certain individual
characteristics which must be taken as fixed notably age, sex and ability, and
some which can, at some cost, be changed- notably the individual’s skills and
place of residence. As such, in this model, the only difference• between
different workers wages and conditions arise from individual differences in
their human capital (skills, experience, or formal education) or tastes (Harald
, 2006). On the other hand, so far as the suitability of a job for an individual
is concerned, there are certain aspects of the job specification which are
difficult to change such as the type of work to be done and the industry in
which it is to be carried on (Casson, 1979).
A broad set of institutional factors preventing young people from
entering the labour market or increasing their risk of becoming unemployed
have been discussed by Dietrich (2001).
These include lack of seniority, firm-specific human capital or labour
market experience (Martin, 2009), as well as greater likelihood of working
under short-term contracts and other forms of precarious employment
(Marchand. 1999). In such circumstances, school-to-work or training-towork
transitions tend to take the form of a chain of temporary episodes of training,
education, compulsory or voluntary military or civilian service, labour
market schemes or other temporary activities, frequently within an
institutional framework characterized by fixed entry dates, outside the market
23. 15
and oblivious to its requirements (Dietrich, 2003). Young people undergoing
such a trajectory accumulate little experience of job search and do not
develop a clear picture of what kind of job and/or what income they should
be aiming for. Furthermore, young people tend to have fewer resources than
older workers and in some countries a strong financial attachment to the
family, which means that they are less mobile (Martin, 2009).
Unemployment and the unemployment rate are strongly connected to
labour market participation. This applies in particular to young people below
25 years of age, a significant proportion of who have not yet entered the
labour market. The entry patterns characterizing school-to-work transitions
and the average age at which specific types of school-to-work transition are
observed depend on qualifications and national systems of general and/or
vocational education and training (OECD, 2010). The expansion of education
in a given country increases the average age of new labour market entrants
over time (Dietrich, 2005).
Rural Urban Migration: according to Adebayo (1999) rural urban
migration is usually explained in terms of push-pull factors. The push factor
includes the pressure resulting from man-land ratio in the rural areas and the
existence of serious underemployment arising from the seasonal cycle of the
lack of infrastructural facilities, which makes the rural life unattractive.
Youths move to urban areas with the probability of securing lucrative
employment in the industries. In addition, Alanana (2003) notes that, there is
24. 16
the concentration of social amenities in the urban centers which meant that
the rural areas are neglected in the allocation of social and economic
opportunities.
Lack of Steady and Sustainable Power Supply: Onifade, (2011),
Identified that sustainable power supply/energy crises leads to firms
depending on generators for their operation whose cost of buying, fueling
and maintenance are high, thereby increasing the cost of operation, high and
multiple levies and taxations paid by these companies, energy crises have
combined to make the cost of doing business very exorbitant. When the
industries and factories close shops or relocate to a friendlier economic
environment, workers are laid off and prospect of recruiting new ones are
dashed. All these exacerbate the crisis of youth unemployment in the labor
market (Adeloye, 2010).
Corruption is another factor responsible for youth unemployment.
According to Okafor (2010), Corruption robs the country of developing a
vibrant economic base. Funds meant for development projects are
misappropriated, diverted, or embezzled and stashed away in foreign banks,
while some incompetent and corrupt bureaucrats and administrators in the
public enterprise and parastatal liquidate these organizations. Ayinde (2008)
noted that “The ruling (political) class failed because they replaced the
vision, policy and strategy, which should be the thrust of every leadership
with transactions (contract award and other mundane money-related
25. 17
activities), as each successive government took turns to prey on the nation’s
wealth, by using public power, resources, good will, utilities, instrument of
abuse, and personal gains”.
Low Standard of Education: Henrik (2006) has argued that most
graduates in Africa do not possess the skills needed by the employers of
labour for a formal employment. After ~l1 employers do not need people to
pay or spend their money on but people that will help their organization grow
and make more profit as the primary goal of every enterprise is to make
profit. Often, this is attributed to the education system, with its liberal bias.
Low opportunities for young graduates create problem of violence due to
lack ofjob and idleness, because without job they will not be able to play a
useful role in the society (Onno, 2011).
The Rapid Expansion of the Educational System: Utomi (2011)
identified that the rapid expansion of the educational system which directly
leads to increase in the supply of educated manpower above the
corresponding demand for them, contributes to the problem of the youth
unemployment.
Unemployment is rampant among youths because the government has
not done enough to create jobs for youths. Most of the youths have never
attended school and therefore cannot find jobs, others who are educated lack
enough experience to compete for the few jobs available. The greatest
26. 18
challenge in Somalia is political instability that makes the nation not to be a
safe place to stay in.
According to Karl Pribam (1946), “unemployment” is when the supply
of labor power is more than the number of available openings. In this regard,
unemployment is realized when the market has excess supply of the required
labor power. Karl says that to create market equilibrium, labor supply should
match with the labor demand. If either of them is more, the market loses its
equilibrium. Madan’s (1965) defined “unemployment is the absence of
opportunities of jobs for people willing to and actively looking for a job. The
definition is based on the supply-demand phenomenon. He argues that this
grossly ignores the aspect of value in employment. In as much as market
equilibrium is emphasized, the labour value should be emphasized on.
Fairchild (1978) in his research, acknowledges the importance of the value in
employment. He says unemployment is enforced and involuntary.
There are varying ideas about the effects and causes of unemployment
in the world. It is a well known fact that one of the burning issues of modern
time is unemployment, yet there are claims that having a certain percent of
unemployment can be “healthy”, according to studies carried out by the
International Labour Organization in 1996.
According to Ajufo (2013), desperation as a result of unemployment
can drive many people into li~ ing outside the law in order to sur~ ive and as
27. 19
a means of expressing dissatisfaction for the apparent neglect of their very
existence. She noted further that the negative consequences include poverty,
psychological problems, and all manner of criminal behaviors causing
general insecurity of life and businesses across the nation.
Bell (2009) notes that, volatility of local economies in an era of
recurrent global economic crises, the vulnerable position of youth within
labor markets may become more solidified as they are often not the priority
in the agendas of policy makers. Recent studies of the effects of the 2008
crisis and studies of prior crises have shown that youth have been adversely
affected and much more so than adults; the effects have been very severe and
long lasting (Verick, 2009).
29. 21
Map of Bosaso district
Source
History
Previously Bosaso was known as Bandar Qasim, a name derived from
an Ahmed Harti first trader of the same name who is said to have settled in
the area during the 14th century.
"About 3 1 ⁄2 hours’ walk from Bet Nur, we came to Bander Kasnin
(also called by the Arabs: the native name is Bosaso), which was built about
sixty years ago, the Kaptallah (a seafaring tribe, now almost extinct) being
the first to build few huts there. They were joined by, not long after, by the
Deshishe".Historically, Bosaso has been a Dishiishe Darod stronghold.
30. 22
Near Bosaso, at the end of the Baalade valley, lies a 2-to-3-kilometre-
long (1.2-to-1.9-mile) earthwork. Local tradition recounts that the massive
embankment marks the grave of a community matriarch. It is the largest such
structure in the wider Horn region.
Since centuries the city was among the areas ruled by the Dishiishe
clan. Later forming a part of Italian Somaliland, Bosaso was represented in
the parliament of the succeeding Trust Territory of Somalia by the MPs Ugas
Yasin Ugas Abdurahman and Haji Bashir Ismail Yusuf. The town would
eventually be administered through the official Bari region in the post-
independence period. Barkhad Ali Salah served as first mayor of the town.
With the start of the Somali Civil War and the subsequent formation of
Puntland in the 1990s, Bosaso has become the business capital of the
northeastern regions of Somalia. In recent years, it has served as a refueling
station for maritime transport between the Red Sea and the Persian Gulf
ports, and has also become an important commercial point of entry.
Geography
Location and habitat
Bosaso is situated in northeastern Somalia, on the Gulf of Aden coast.
Nearby settlements include to the east Rehiss (3.5 km or 2.5 miles), to the
northeast Marero (14 km or 8.5 miles), to the west Baalade (3.5 km or 2
miles), to the southwest Laas Geel (16.5 km or 10 miles), to the south
31. 23
Lasgoriga (20.5 km or 13 miles), and to the southeast El Dhurre (36 km or
22.5 miles). The largest cities in the country most proximate to Bosaso are
Erigavo (212 km or 132 miles), Burao (442 km or 275 miles), and Berbera
(465 km or 289 miles). Shimbiris, the highest peak in Somalia, is located
some 220 km (140 miles) to the southwest in the Cal Madow mountain
range.
In June 2014, the Puntland government launched a new tree-planting
campaign in the state, with the regional Ministry of Environment, Wildlife
and Tourism slated to plant 25,000 trees by the end of the year. Bosaso is
among the seven cities and towns earmarked for the reforestation initiative,
which also include Garowe, Qardho, Dhahar, Buuhoodle, Baran and
Galkayo. The campaign is part of a broader partnership between the Puntland
authorities and EU to set up various environmental protection measures in
the region, with the aim of promoting reforestation and afforestation.
Climate
Bosaso has a hot desert climate (Köppen climate classification BWh).
It has a mean annual relative humidity of around 60%. The average daily
mean temperature year-round is 30 °C (86 °F), with an average annual high
of 35 °C (95 °F) and an average annual low of 25 °C (77 °F). Average low
temperatures are coolest during the winter months of December to February,
when thermometer readings typically level out at 20 °C (68 °F). The weather
32. 24
slowly heats up in the spring, as the April rainy season begins. Average high
temperatures later peak during the summer months of June to August, when
they consistently exceed 40 °C (104 °F). Come September, cooler weather
starts to set in again. Rainfall reaches a high over this period, with an average
precipitation of 7 mm (0.28 inches) in November. Total rainfall year-round is
around 19 mm (0.75 inches) promoting reforestation and afforestation.
Demographics
Bosaso's total population is estimated at around 164,906 residents
(2005 est.). An additional 50,000 registered internally displaced people
primarily from conflict-stricken parts of southern Somalia have also sought
refuge in camps on the outskirts of the city.
Furthermore, Bosaso is a major port for boats carrying emigrants from
within the country as well as adjacent territories across the Gulf of Aden to
settle (sometimes illegally) in the Persian Gulf states
While Bosaso today is a melting pot, with residents hailing from many
different parts of Somalia, most of the city's population is from the Harti
confederation of Darod sub-clans.
Municipality
Bosaso city affairs are managed by the Bosaso Municipality, its
leadership is appointed by members of the area's 29 District Councilors. The
33. 25
municipal authority is currently led by Mayor Abdisalam Bashiir Abdisalam
who succeeded Yasin Mire Mohamud who himself succeeded Hassan
Abdallah Hassan in office.
Each of the city's various districts also has its own municipal
subauthorities, complete with a mayor and civil servants.
Economy
Bosaso is a city that is experiencing a period of rapid growth. Prior to
the Somali civil war, it had a population of under 50,000 inhabitants. Since
the conflict, Somalis belonging to the Harti Darod sub-clans began migrating
back to their ancestral areas of Puntland. As a consequence of these
migrations, Bosaso's population and the local housing industry have grown
tremendously.
In December 2011, a new commercial market opened in Bosaso's
northern Dayaha ("Star") neighborhood, near the port. Approximately one-
half kilometre (550 yd) in size, it was designed to ensure easy vehicle access.
The market is the result of careful planning between Puntland
government officials and civil society representatives. In September 2013,
Puntland Minister of Fisheries Mohamed Farah Adan also announced that the
Ministry in conjunction with the FAO would open a new fish market in the
city, complete with modern refrigerators. Bosaso is home to Golis Telecom
Somalia, the largest telecommunications operator in northeastern Somalia.
34. 26
Founded in 2002 with the objective of supplying the country with GSM
mobile services, fixed line and internet services, it has an extensive network
that covers all of the nation's major cities and more than 40 districts in both
Puntland and Somaliland. According to The Economist, Golis offers one of
the cheapest international calling rates on the planet, at US$0.2 less than
anywhere else in the world. In addition, Netco has its headquarters in the city.
Other telecommunication firms serving the region include Telcom and
NationLink.
In September 2013, Puntland Deputy Minister of Environment Burhan
Elmi Hirsi also announced a plan by the Puntland government to establish a
gas manufacturing plant in Bosaso. The new project is part of a broader
campaign by the Puntland environmental authorities to avert deforestation
and promote alternative sources of fuel.
The Hafun Fishing Company was established in 1992 in Bosaso. It was
named after the northeastern port town of Hafun, where HFC also has an
office. The firm exports a wide range of fish products, which it mainly sends
to partners in the Middle East.
The company is exploring additional global markets for its fish goods.
It also maintains commercial interests in Puntland's housing market, which
are represented by the firm's growing local real estate sales and development
division.
35. 27
Additionally, the Bosaso Tannery is based in the city. A ten-year-old
manufacturing, distributing, wholesale and import/export company, it
processes wet salted, dry salted, wet blue, limed, pickled, and air/frame dried
sheep and goat hides and skin. Principle wet blue exports are to Turkey,
Pakistan, India and China. Raw camel hides and sheep and goat skin are also
exported to the United Arab Emirates.
Commercial banks serving Bosaso include Amal Bank and Salaam
Bank. Salaam Bank provides personal banking and corporate banking
services. Its Islamic banking services and facilities include Mudarabah,
Murabaha, Musharakah and Istisnaa. Additionally, the bank offers electronic
banking, SMS banking, mobile banking and internet debit. In August 2011,
the bank also launched an independent (Kaaftoon) service partnering with
Golis Telecom Somalia.
Transportation
Bosaso is traversed by a 750-kilometre (470 mi) north–south highway.
It connects major cities in the northern part of the country, such as Galkayo
and Garowe, with towns in the south. In June 2012, the Puntland Highway
Authority (PHA) launched an upgrade and repair project on the large
thoroughfare between Bosaso and Garowe. The transportation body also
began rehabilitation work in October 2012 on the central artery linking the
36. 28
city with Qardho.
Additionally, plans are in the works to construct new roads connecting
littoral towns in the region to the main highway. In June 2014, Puntland
President Abdiweli Mohamed Ali along with Bosaso Mayor Hassan
Abdallah Hassan and other state officials also inaugurated a new 5.9-
kilometre (3.7 mi) paved road in the city. The construction project leads to
the Bosaso seaport, and was completed in conjunction with UNHABITAT.
According to Ali, his administration plans to invest at least 23 million
Euros in contributions from international partners in similar road
infrastructure development initiatives.
The city has a major seaport, the Port of Bosaso. It was constructed
during the mid-1980s by the Siad Barre administration for annual livestock
shipments to the Middle East. In January 2012, a renovation project was
launched, with KMC contracted to upgrade the Bosaso Port's harbor. The
initiative's first phase saw the clean-up of unwanted materials from the
dockyard and was completed within the month.
The second phase involves the reconstruction of the port's adjoining
seabed, with the objective of accommodating larger ships.
Besides its busy seaport, Bosaso has a major airport, the Bender
Qassim International Airport. In 2008, the Puntland government signed a
multimillion-dollar deal with Dubai's Lootah Group, a regional industrial
37. 29
group operating in the Middle East and Africa. According to the agreement,
the first phase of the investment is worth Dhs170m ($46.28m) and will see a
set of new companies established to operate, manage and build Bosaso's free
trade zone and sea and airport facilities. The Bosaso Airport Company is
slated to develop the airport complex to meet international standards,
including a new 3.4-kilometre (2.1 mi) runway, main and auxiliary buildings,
taxi and apron areas, and security perimeters.
. In December 2014, the foundation stone for a new runway was also
laid at the airport. The China Civil Engineering Construction Corporation is
now slated to upgrade the airport's existing gravel runway, pave it with
asphalt, and convert it from 1.8 to 2.65 km (1.12 to 1.65 miles) in accordance
with the code 4C operations clause
Education
Bosaso has a number of academic institutions. According to the
Puntland Ministry of Education, there are 74 primary schools in the Bosaso
District. Among these are the Iftin School, Alfurqan, Umul-Qura and Garisa.
Secondary schools in the area include Hamdan, Shafi'i, Ugaas Yasin, Najah
and Bosaso.
Tertiary education is provided by Bosaso College (BC), As well as the
Puntland Nursing Institute (PNI). East Africa University (EAU) also has a
Bosaso branch, one of its seven campuses in Puntland. Additionally, the Sam
38. 30
Greathouse School of Modern Technology (SG-SMT) has been working with
the local government to construct a large scale dial-up network linking Bosaso
to other northern Somali cities, including Berbera and Las Anod.
Media
Bosaso is home to a number of private media outlets. Radio Daljir,
Puntland's largest radio station, has its main headquarters in the city. The
broadcaster's network of 7 FM transmitters reaches most of Puntland as well
as part of the neighboring Galmudug region to the south.
Also centered in Bosaso with its studios in Garowe is the Somali
Broadcasting.
Corporation (SBC), Puntland's oldest and second largest private radio
station. Additionally, Horseed Radio, Al Xigma, and One Nation Radio have
headquarters in the city.
In May 2013, Radio Garowe likewise launched a new FM station in
Bosaso. The city also has its own private television channels and studios, the
Eastern Television Network (ETN TV) and SBC TV.
bosaso port
The modern Port of Bosaso was constructed during the mid-1980s by
the Siad Barre administration for annual livestock shipments to the Middle
East. In January 2012, a renovation project was launched at the Bosaso Port,
39. 31
with KMC contracted to upgrade the harbor. The initiative's first phase saw
the clean-up of unwanted materials from the dockyard and was completed
within the month. The second phase involves the reconstruction of the port's
adjoining seabed, with the objective of accommodating larger ships.
On 6 April 2017, Dubai-based P&O Ports won a 30-year concession
for Port for the management and development of a multi-purpose port project.
The approximate investment for the modern multi-purpose facility was USD
$336 million. President of Puntland, Abdiweli Mohamed Ali signed the
agreement in Dubai on 6 April 2017
The Work on the project will involve building a 450m quay and a 5
hectare back up area, dredging to a depth of 12m with reclamation work using
dredge spoil. There will also be major investment in an IT and Terminal
Operating System (TOS), mobile harbor cranes and container handling
equipment.
40. 32
Chapter – IV
Data Analysis and Interpretation
Table No. 4.1
Age of the respondent
Age wise distribution of the respondents And Locality
Age Group of the
respondents
Urban Rural Percentage
15-19 Years old 13 0 13.4
20-29 Years old 38 5 56.7
30-39 Years old 5 3 17.9
40-49 Years old 0 3 12.0
Total 56 11 100
Source: computed from primary data
From the table No-4.1 explains the different age group of the
Respondents. of the 67 respondents, 56.7% percentage of the respondents are
from Urban people they are both male and female, 17.9% percentage of the
respondents are rural people they are both male and female, while the 12%
percentage of the respondents are rural also and the age between 15-19 years
all of them are Urban.
It is inferred from the above analysis that the majority of the respondents
in urban and rural area are between 20-29 years old
41. 33
Table No-4.2
Gender wise distribution of the respondents
Gender Urban Rural Percentage
Male 42 6 62.7
Female 14 5 37.3
Total 56 11 100
Source: computed from primary data
From the Table No-4.2 shows that, from 56 respondents, the majority
62.7% of the respondents are male , and the 37.3% of the respondents are
female so the majority of the respondents are Male.
It is observed from the analysis Most of the respondents are Male from
Urban area and its 62.7% percentage of the respondents.
.
42. 34
Table No-4.3
Marital status of the respondents
Marital status Urban Rural percentage
Single 54 8 80.6
Married 2 3 19.4
Total 56 11 100
Source: computed from primary data
It is observed Table No-4.3 shows that out of 56 respondents 80.6%
percentage of the respondents are belong to single and the rest of the 19.4% of
the respondents to married.
It is observed from the analysis more number of single are the
respondents. It is found that all the married respondents are less its only 19.4%
percentage of the respondents
43. 35
Table No.-4.4
Family Types of the respondents
Type of the
family
Urban Rural Percentage
Nuclear 28 0 41.8
Joint 28 11 58.2
Total 56 11 100
Source: computed from primary data
From the No-.4.4 portray the family type of the respondents. It is
observed from the table out of 56 respondents, 28 respondents are nuclear
family. Another 28 respondents are joint family
It is clearly there is a same result in the nuclear and joint family of the
respondents in bosaso city
44. 36
Table No. 4.5
Educational status of the respondents
Educational Urban Rural Percentage
Illiterate 2 0 3.0
Primary 4 0 6.0
Secondary 3 0 4.5
College 47 1 71.6
Intermediate 0 10 14.9
Total 56 11 100
Source: computed from primary data
From the table No.4.5, show that 71.6% of the respondents are
collegiate, 14.9% Percentage of the respondents are intermediate, 6%
percentage of the respondents are primary school , 4.5% percentage of the
respondents are secondary level and the 3% of the respondents are belongs to
illiterate.
It is clearly found that more number of respondents are having college
level education status and they are belongs to the Urban areas.
45. 37
Table No. 4.6
Employment status of the respondents
Current status Urban Rural Percentage
Employed 22 0 32.8
Unemployed 34 11 67.2
Total 56 11 100
Source: computed from primary data
From the table No.4.6, show that, out of 67 respondents, the majority 67.2% of
the respondents are Unemployed and the rest of the 32.8% of the respondents
are employed.
It is noticed from the table that most of the respondents are unemployed
and all of them in rural areas are unemployed.
46. 38
Table No. 4.7
Causes of Unemployment
Causes Urban Rural Percentage
Economic
recession
30 0 44.8
Increased birth
rate
16 0 23.9
Increasing
technology
10 2 17.9
Illiteracy 0 9 13.4
Total 56 11 100
Source: computed from primary data
From the table No. 4.7, shows that 44.8% percentage of the respondents
says that economic recession is the causes of unemployment, 23.9% percentage
of the respondents they said increasing birth rate are causes unemployment
while the 17.9% percentage of the respondents are increasing technology and
the 13.4% of the respondents are says illiteracy are the main causes of
unemployment.
The above analysis clearly shows that in urban areas most of the
respondents are says that economic recession is the Causes for unemployment.
And In majority of the rural respondents are believes that Illiteracy.
47. 39
Table No. 4.8
Monthly Family Income of the respondents
Monthly income Urban Rural Percentage
200 to 350 $ 44 0 65.7
400 to 550 $ 8 0 11.9
600 to 750 $ 4 2 9.0
800 to 1000 $ 0 9 13.4
Total 56 11 100
Source: computed from primary data
From table No.8 shows that, 65.7% of the respondents are having 200-
350$ monthly income 13.4% percentage of the respondents are having 800 to
1000$, 11.9% percentage of the respondents are having 400 to 550$, and the
9.0% percentage of the respondents have their income per months as 600 to
750$.
From the above analysis, Clearly found that the majority of the
respondents belongs to urban category are having only family monthly income
of 200 to 350$. But in rural areas, Maximum number of respondents having
family monthly of 800 to 1000$.
48. 40
Table No. 4.9
Opinion of the respondent regarding to if you are not employed what you
want to do
Opinion Urban Rural Percentage
Own business 50 0 74.6
Job 6 11 25.4
Total 56 11 100
Source: computed from primary data
From Table No.9 shows that, 74.6% percentage of the respondents they
want to do own business and the rest of the respondents they like to do own
job, if they are not employed.
From the above analysis clearly shows that the majority of the
respondents in urban area are willing to do their own jobs and all the
respondents from rural area want to go job.
49. 41
Table No. 4.10
Opinion of the respondent regarding
Unemployment affects the socio economics status of the family
Opinion Urban Rural Percentage
Agree 38 0 56.7
Disagree 18 0 26.9
Strongly agree 0 8 11.9
Strongly
disagree
0 3 4.5
Total 56 11 100
Source: computed from primary data
From Table No.10 shows that, 56.7% percentage of the respondents are
agree with the statement that Unemployment affects the socio economic status
of the family, 26.9% percentage ,11.9% percentage and 4.5% percentage of
the respondents are disagree, strongly agree and strongly disagree with the
statement respectively.
From the above analysis found that the majority of the urban
respondents are agree with the statement unemployment affects the socio
economic status of the family, and the same way majority of the respondents
are strongly agree with that statement.
50. 42
Table No. 4.11
Opinion of the respondent regarding
Unemployment effects family relationship negatively
Opinion Urban Rural Percentage
Agree 32 0 47.8
Disagree 14 0 20.9
Strongly agree 10 4 20.9
Strongly
disagree
0 7 10.4
Total 56 11 100
Source: computed from primary data
From the Table No.11 shows that, 47.8% percentage of the respondents
are agree with the statement that Unemployment effects family relationship
negatively while the 20.9% percentage of the respondents are disagree, 20.9%
percentage of the respondents are strongly agree and 10.4% percentage of the
respondents are strongly disagree with the statement respectively.
The above analysis shows that majority of the urban respondents are
agreed that unemployment effects family relationship negatively but in rural
area, the majority of them are strongly disagreed.
51. 43
Table No. 4.12
Opinion of the respondent regarding
Unemployment effects common people life
Opinion Urban Rural Percentage
Agree 42 0 62.7
Disagree 7 0 10.4
Strongly agree 7 7 20.9
Strongly
disagree
0 4 6.0
Total 56 11 100
Source: computed from primary data
From the Table No.12 shows that, 62.7% percentage of the respondents
are agree with the statement that Unemployment effects common people life
10.4% percentage of the respondents are disagree, 20.9% percentage of the
respondents are strongly agree and 6.0% percentage of the respondents are
strongly disagree with the statement respectively.
The above analysis shows that the majority of the respondents are
agreed that unemployment effects common people life in both urban and rural
area.
52. 44
Table No. 4.13
Opinion of the respondent regarding
Unemployment leads to corruption dishonestly crime and sins
Opinion Urban Rural Percentage
Agree 35 0 52.2
Disagree 11 0 16.4
Strongly agree 10 3 19.4
Strongly
disagree
0 8 11.9
total 56 11 100
From the Table No.13 shows that 52.2% percentage of the respondents
are agree with the statement Unemployment leads corruption dishonestly
crime and sins, 16.4% percentage of respondents are disagree, 19.4%
percentage of the respondents are strongly agree and the 11.9% percentage of
respondents are strongly disagree with the statement respectively.
From the above analysis found that the majority of the urban
respondents are agree with the statement Unemployment leads to corruption
dishonestly crime and sins, but the majority of the respondents in rural area
are strongly disagreed with that statement.
53. 45
Table No. 4.14
Opinion of the respondent regarding
Unemployment people are usually drug user
Opinion Urban Rural Percentage
Agree 20 0 29.9
Disagree 25 0 37.3
Strongly agree 5 0 7.5
Strongly
disagree
6 11 25.4
Total 56 11 100
Source: computed from primary data
From the Table No. 14 shows that 29.9% percentage of the respondents
are agree with the statement Unemployment people are usually drug user,
37.3% percentage of the respondents are disagree, 7.5% percentage of the
respondents are strongly agree and the 25.4% percentage of the respondents
are strongly disagree with the statement respectively.
From the analysis, it shows that the Most of the Urban area respondents
are disagreed that the unemployment people are usually drug user. But all the
respondents in rural area are strongly disagreed with that.
54. 46
Chapter – V
FINDINGS AND SUGGESTIONS
The present study entitled “Factors affecting unemployment in
Somalia” was carried out with the following objectives,
1. to examine the influence of education on youth employment in Bosaso
2. to explain the influence of Job Opportunity on youth employment in Bosaso
3. to determine the influence of Culture on youth employment in Bosaso
4. to analyze the socioeconomic conditions of unemployed youth in bosaso
5. to examine the factor influencing youth unemployment among youth in
bosaso.
Findings
The majority of the respondents in urban and rural area are between 20-
29 years old.
The majority of the respondents in urban and rural area are unmarried.
All the respondents in Rural are in Joint family and the respondents in
Urban area are equally shared in joint and Nuclear Family.
The majority of the respondent in urban are having college level
education status and most of them in rural are intermediate.
The majority of the respondents are unemployed in both area.
55. 47
The majority of the respondents in urban areas most of the respondents
are says that economic recession is the Causes for unemployment. And
in majority of the rural respondents are believes that Illiteracy
The majority of the respondents in urban are having only 200 to 350 $ as
a family monthly income. But in rural area most of them having 800 to
1000$, which is much higher than an urban area.
The majority of the respondents in urban area are willing to do their
own jobs and all the respondents from rural area want to go job, if they
are not employed.
The majority of the respondents are agreed that unemployment affects
the socio economics status of the family.
In urban area majority of the respondents agreed that Unemployment
effects family relationship negatively, but in rural area majority of them
are strongly disagreed.
The majority of the respondents are agreed and strongly agreed that
Unemployment effects common people life in urban and rural area
respectively.
In urban area majority of the respondents agreed that Unemployment
leads to corruption dishonestly crime and sins, but in rural area majority
of them are strongly disagreed.
56. 48
The majority of the respondents are disagreed and strongly disagreed
that Unemployment people are usually drug user in urban and rural area
respectively.
Suggestions
Based on the above findings,
Both urban and rural area respondents are in different mindset and they
are facing different problems and unemployment affects them in
different things.
In urban area, unemployment affects family life, family relationship and
leads to corruption and crime. So, consider this as a important issue and
make some decision to reduce the unemployment.
Unemployment affects the people life in the rural area as same as the
urban area. But in rural place unemployed does not affects family
relationship and leads to crimes. So, consider urban place as a priority.
Most of the respondents did not agreed with the Unemployment people
are usually drug user, but the second most majority respondents are
agreed that in both area. So, have to consider this as agreed one.
57. 49
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