THE DETERMINANTS OF YOUTH UNEMPLOYMENT IN CASE OF BOLE SUBCITY WORDA 14

Unity University
School of Graduate Studies
Department of Management and Marketing
THE DETERMINANTS OF YOUTH UNEMPLOYMENT:
THE CASE OF WOREDA 14 OF BOLE SUB CITY.
A Thesis submitted to the School of Graduate Studies of Unity University in
partial fulfillment of the requirements for the Degree of Master of Science in Project
Management.
Prepared by: Zelalem Kiros Tesfaye
Advisor: Demmelash Habte (PhD)
September 2022
Addis Ababa

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UNITY UNIVERSITY
SCHOOL OF GRADUATE STUDIES
THE DETERMINANTS OF YOUTH UNEMPLOYMENT IN CASE OF BOLE SUBCITY
WOREDA 14.
BY
ZELALEM KIROS TESFAYE
Approval of Board of Examiners
External Examiner Internal Examiner
Name: ____________________ Name: ____________________
Signature: ________________ Signature: ________________
Date: ___________________ Date: _____________________
Advisor
Name: ______________________
Signature: ________________
Date: ___________________
Confirmation
Chairperson, Department Graduate Committee
Name_____________________
Signature__________________
Date______________________

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ACKNOWLEDGEMENT
I want to say thank you A special note of appreciation is due to my advisor Demelash Habte (PhD),
whose meticulous attention to detail has motivated me and maintained my work on schedule. I
want to express my gratitude to God and his mother for their guidance and support throughout my
life. In order to make this work a success, I would want to express my sincere gratitude to everyone
who put in time and effort. Mastewal, my wife, for her compassion; my other family members for
their encouragement and support; and my coworkers. Last but not least, I would like to extend my
sincere gratitude to The Bole Sub City Woreda 14 personnel and Administration manager, who
gave me the chance to distribute and gather all staff and outside questioners in order to gain all
available statistics on youth unemployment.

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Table of Contents
ACKNOWLEDGEMENT.......................................................................................................................................I
TABLE OF CONTENTS .......................................................................................................................................II
LIST OF TABLES........................................................................................................................................................IV
LIST OF FIGURES ....................................................................................................................................................... V
ACRONYMS.............................................................................................................................................................VI
ABSTRACT:.........................................................................................................................................................VII
CHAPTER ONE ....................................................................................................................................................... 1
1.1 BACKGROUND OF THE STUDY.......................................................................................................................... 1
1.2 STATEMENT OF PROBLEM..................................................................................................................................... 3
1.3 RESEARCH QUESTIONS ......................................................................................................................................... 6
1.4 Objectives................................................................................................................................................. 6
1.4.1 General Objective................................................................................................................................. 6
1.4.2 Specific Objective.............................................................................................................................. 7
1.5 SCOPE AND LIMITATION OF THE STUDY ........................................................................................................... 7
1.6 SIGNIFICANCE OF THE STUDY ..................................................................................................................... 7
1.7 ORGANIZATION OF THE RESEARCH............................................................................................................. 8
CHAPTER TWO.................................................................................................................................................... 9
LITRATURE REVIEW......................................................................................................................................... 9
2.1 THEORETICAL REVIEW...................................................................................................................................... 9
2.1.1 Definitions of Unemployment................................................................................................................. 9
2.1.2 Types of Unemployment ....................................................................................................................... 10
2.1.3 Natural Unemployment..................................................................................................................... 10
2.2 MEASUREMENTS OF UNEMPLOYMENT.................................................................................................................. 10
2.2.1 The Unemployment Rate................................................................................................................... 10
2.2.3 Minimum-wage effects on skilled and unskilled labor .................................................................. 11
2.2.3 Models of Unemployment.................................................................................................................. 13
2.3 EMPIRICAL LITERATURE..................................................................................................................................... 14
2.3.1 Effects of Unemployment................................................................................................................... 14
2.5 CONCEPTUAL FRAME WORK ............................................................................................................................... 17
CHAPTER THREE................................................................................................................................................. 19
RESEARCH DESIGN AND METHODOLOGY........................................................................................................ 19
3.1 RESEARCH DESIGN ............................................................................................................................................. 19
3.2 SAMPLING DESIGN.............................................................................................................................................. 19
3.3.1 Type of universe (Population).......................................................................................................... 20
3.3.2 Type of Unemployed youth................................................................................................................ 20
3.3.3 Study population and Sampling Technique .................................................................................... 20
3.3.4 Sample Size......................................................................................................................................... 20
3.3.5 Sample size and Sampling technique .............................................................................................. 21
3.4 DATA SOURCE AND ACQUIRING TECHNIQUES......................................................................................................... 21

3.5 DATA ANALYSIS................................................................................................................................................. 22
3.5.1 Descriptive statistics ......................................................................................................................... 22
3.5.2 Inferential statistics .......................................................................................................................... 22
3.6 RELIABILITY AND VALIDITY................................................................................................................................ 23
3.6.1 Reliability ........................................................................................................................................... 23
3.6.2 Validity................................................................................................................................................ 23
3.7 ETHICAL ISSUES ................................................................................................................................................. 24
CHAPTER FOUR................................................................................................................................................... 25
DATA ANALYSIS AND PRESENTATION............................................................................................................. 25
4.1 GENERAL INFORMATION ABOUT RESPONDENTS.................................................................................................... 25
4.2 RELIABILITY TEST ............................................................................................................................................. 26
4.2.1 Reliability ........................................................................................................................................... 26
4.3 DESCRIPTIVE ANALYSIS ...................................................................................................................................... 27
4.3.1 Analyses of Economic Factors........................................................................................................... 27
4.3.2 Analysis of Social Factors.................................................................................................................. 32
4.4 CORRELATION ANALYSES.................................................................................................................................... 36
4.4.1 Relationship between Socio economic factors & Unemployment status dimensions ................. 37
CHAPTER FIVE..................................................................................................................................................... 38
SUMMARY OF THE FINDINGS, CONCLUSION AND RECOMMENDATION....................................................... 38
5.1 SUMMARY OF FINDINGS ...................................................................................................................................... 38
5.2 CONCLUSIONS .................................................................................................................................................... 40
5.3 RECOMMENDATIONS .......................................................................................................................................... 43
REFERENCES........................................................................................................................................................ 44
APPENDICES ........................................................................................................................................................ 47

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LIST OF TABLES
Table 4.1 Educational status of respondents……………………………………………….….25
Table 4.2 Source of Income…………………………………………………….………….….26
Table 4.3 Reliability Analysis: Cronbach’s Alpha Value………………………………….….27
Table 4.4 Economic Factor-Income…………………………………………………………...28
Table 4.5 Economic Factor-Job Opportunity………………………………………………….31
Table 4.6 Economic Factor-Saving/Investment……………………………………………….32
Table 4.7 Social Factor-Health………………………………………………………………...33
Table 4.8 Social Factor-Education…………………………………………………………….34
Table 4.9 Social factors- Skill /Training………………………………………………………35
Table 4.10 Social factor- tradition…………………………………………………….……….36
Table 4.11 Correlation b/n Socio economic Factors &Unemployment status Dimensions……37

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LIST OF FIGURES
Figure 1.1 Minimum Wage segmented Labor Market………………………………….…......13
Figure 2.2 Conceptual framework of determinates of youth unemployment…………........….18
Figure 3.1 Unemployment trend from 2010 -2013E.C……………………………………...…21
Figure 4.1 Skill Mismatch and Information Asymmetry……………………….……………...29

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ACRONYMS
NGO Non-Governmental organization
GDP Gross domestic product
MSE Micro and Small Enterprises
TVET Technical and Vocational Education and Training
CSA Central Statistics Agency
GTP Growth and Transformation Plan
ILO International Labor Organization
CSO Civil Society Organizations
SAS Statistical analysis system

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Abstract:
The aim of the study was to examine the factors which determine youth unemployment in Addis
Ababa Bole Sub City Worda 14 and suggest way forward towards reduction of the problem. The
study uses Correlation measurement to analyze the determinants of unemployment in Bole SC
Woreda 14. The findings of the study show that gender, geographical location, education, skills
and marital status are all significant factors in explaining the difference in youth employment
status. From the findings the study several recommendations are made, first, the government and
policy makers should review job market laws and regulation in order to promote a smooth
transition of youth from education to job market. To make sure that all young people with
education or skills realize their investments in education and contribute to the development of the
country, the government should develop specific interventions, particularly in the creation of more
formal jobs and strengthening job market regulation relating to young people. In order to give
young people with the same level of education or training an equal chance, the study also suggests
that government or private educational institutions should offer soft skill training to graduates
who are unemployed in addition to strengthening the laws and regulations relating to gender
balance in the job market. Therefore, efforts should be made to reduce the number of young people
who are unemployed by increasing employment opportunities for those with education, facilitating
hiring without a need for work experience, lowering rural-urban migration, matching skills to
jobs, creating access to symmetrical job information, and providing relevant information for job
seekers.
Keywords: Determinants, Unemployment, Youth, Bole sub city woreda 14

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CHAPTER ONE
1.1 Background of the study
As Per the World Bank (2015) definition Youth unemployment is a fundamental problem facing
and challenging the social, political and economic activities of all over the countries. Countries,
organizations, nation, NGOs and civic affiliations have different age categorization of youth based
on several factors for example in UKs introduced in 1998 young people age group with 18-24,
while in Italy youth people are aged between 14-29 within north and 14-32 inside the south
(O’Higgins, 2001:10). And in the United Nations (UN) 15-24, WHO 10-24, in Ethiopia, the age
of youth 15 -29 years, and other countries has divers’ age limitations (MYSC, 2004).
United Nations defines, those between the ages of 15-24, are more affected by unemployment.
Young people are more vulnerable and lack experience, social networks or other qualifications
that would make them difficult to find employment. In most regions youth were nearly three times
more likely to be unemployed than adults (ILO -Geneva: 2010 Global employment trends for
youth).
As ILO (2001) defined, unemployment is a condition of being without work but actively seeking
available job at the prevailing wage level in the given period of time; while graduate
unemployment is a type of unemployment among people holding academic degrees (Saptakee,
2001). Many Woreda officials’ researchers and government known those youth has potential
energy, motivations, innovation and talent to succeed economic and social development
throughout the country. But still there is a big gap between number of unemployed youths and new
job opportunities.

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In Africa, the numbers of youth is growing rapidly. In 2010, the 1.2 billion young people in the
world constituted 18 percent of the global population (UN, 2010). By 2015, 226 million youth
aged 15-24 are lived in Africa. As per World Bank report In Ethiopia youth unemployment rate
by 2019 was 3.17%. Thus numbers of youth are increasing rapidly from year to year around the
world. While there is lack of employment opportunities for youths. Youth unemployment is a
pressing issue in Ethiopia where almost two-thirds of the population is younger than 25 years.
Unemployed young people are more likely to abuse illicit substances than employed young people.
As indicated by UN (2003) report, unemployed youth are the fundamental drug users in Sub
Saharan Africa, which accounts 34 million youngsters speaking to 7.7 percent of the mainland's
youth population. Youth unemployment additionally contributes for the universality of wrong
doing and wildness in social orders where business opportunities are constrained. Okojie (2003)
and Haji (2007) found that numerous unemployed youth run criminal endeavors occupied with
brutality, furnished theft, auto grabbing, illicit fuel deals, and unlawful importation of arms. It total
youth unemployment is a negative life occasion that makes individuals despondent. Consistent to
this, Toit (2003) also found that experiencing depression is the consequence of unemployment.
Moreover, Berhanu et al (2005) stated unemployment results social exclusion and a sense of
hopelessness on youth.
In Ethiopia, Micro and Small Enterprise is one of the institutions given recognition in the country’s
industry development policy. It also serves as vehicles for employment opportunities at urban
centers fostering the economic development. MSE serves as sources for sustainable job
opportunities not only for developing countries like ours, but also for developed countries like
USA. Thus, they should be given prior attention as they are important and serve for sustainable
source of job opportunities and economic development in the country.
Addis Abebe, capital and largest city of Ethiopia. It is located on a well-watered plateau
surrounded by hills and mountains in the geographic center of the country. Several international
organizations have their headquarters in the city, notably the African Union and the United Nations

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Economic Commission for Africa, the latter of which is located in Africa Hall. Addis Ababa has
11 subcities, the Bole subcity is one of the largest subcity located in the eastern part of Addis
Ababa. The sub city has 14 Woreda (districts) and covers an area of 122.8 km². The focus of this
study determining the major factors of youth unemployment with in this sub city of Woreda 14.
As per Central Statistics Agency-CSA survey undertaken on the topic of "KEY FINDINGS ON
THE JANUARY 2020 URBAN EMPLOYMENT UNEMPLOYMENT SURVEY," the total
amount of unemployment in Addis Ababa are 398,346 out of which the total number of males are
161,818 which is 41% of it, and Female youth unemployed are 236,528 which is 59% of the total.
More specifically, according to Bole Sub City Woreda 14 data bases from 2011EC to 2013EC
data, there are 4899 registered young unemployed out of whom 2663 men, or 54% of the total, and
2236 women, or 46% of the total, are male. This indicates that a higher percentage of young men
than women are unemployed.
Many young people who are unemployed give up fighting long periods of unemployment that
don't affect their ability to find work. As a result, it is crucial to address various difficulties while
anticipating changes in the future. Finding the "Determinants of Youth Unemployment in Addis
Ababa, Bole Sub City Woreda 14" is the main goal of this thesis study. The study's findings are
significant for employers and other labor market participants because they help them understand
the issues that contribute to young unemployment, which represents a sizable portion of the labor
force in bole sub city woreda 14. On the other hand, the study gives information to the youth
themselves so they may comprehend the reasons behind unemployment and potential solutions.
The study also contributes to the body of literature by filling in information gaps regarding the
causes of youth unemployment and potential solutions for the issue in the nation.
1.2 Statement of Problem
Unemployment is a serious socioeconomic problem that affects all age groups in both developing
and developed countries, but it is most prevalent in developing countries with a high youth
population density. Adults have more opportunities than youths, implying that youth
unemployment is higher than adult unemployment. According to (ILO, 2004), youth in developing
countries are 4.1 times more likely than adults to be unemployed (Schiefebei and Farrel, 1982).
According to the International Labour Organization (ILO), Sub-Saharan Africa has a higher rate
of youth unemployment (18.4 percent) than the Middle East and North Africa (21.3 percent). The

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urban labor market situation in developing countries varies according to sector, worker
characteristics, and employer type. According to a study conducted by (Fayomid, 1992), urban
unemployment is more severe than rural unemployment.
Youth unemployment is one of the most serious socio-economic issues confronting most
developing and some developed countries, causing social unrest, political instability, and
economic recession. Thus, youth unemployment has been identified as one of the most difficult
economic issues confronting developing-country policymakers. If this trend continues, youth
unemployment will have a significant impact on human capital, as well as the region's economic
potential (Berhanu et.al, 2005). The ability of youth to engage in productive activities has both
social and economic consequences for an economy. However, the intensity of youth
unemployment is quite prevalent and widespread in developing countries. ILO (2010) indicates
that 13 youths out of 100 youth were unemployed globally. The situation is not different for youth
of Ethiopia who make up approximately 28.3% of the total population. As a result, the problem of
youth unemployment is a central issue of public discourse in Ethiopia. In another way, youth
unemployment may play a significant role in causing political instability as a result of economic
crises. The youth employment situation in Ethiopia is grave and shocking, not only for the country
but also for the youth (Guracello and Rosati, 2007). Females have a higher unemployment rate
than males.
Most studies conducted so far on youth unemployment were much more focused on macroanalyses
that generated incidences, durations, and trends of unemployment and tested other related variables
quantitatively. So far, there have been few studies that attempt to examine how young people
negotiate unemployment and what it means to be unemployed. Studies reveal that in developing
countries, due to limited opportunities, the youth life phase for some young people is prolonged
(Mains 2012).
Youth unemployment covers fundamental variations in a diverse group of young people, such as
youths living in town, young females, and young people with low educational completion. A high

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level of youth unemployment is one of the critical development problems facing Ethiopia. In line
with this, Berhanu et al. (2005) stated that the youth unemployment rate is consistently higher than
any other age group of the population in the country.
Logically, a high level of unemployment indicates the failure of a country's economy to use its
labor resources effectively. In general, there are various factors explaining unemployment, such
as a low level of general economic activity, recession, inflation, rapid changes in technology,
disability, willingness to work, and discrimination. In the case of Woreda 14, several factors
contribute to the causes of youth unemployment. According to Mryyan (2014), at least three
structural problems explain the persistence of high youth unemployment. First, the mismatch
between education outputs and the labor market's skills causes high unemployment among
university graduates. In contrast, labor market participation among high-skilled youth is
particularly low; young graduates are likely to face average labor market Determinants of Youth
Unemployment. Second, the inability of both the private and public sectors to absorb new market
labor entrants. Third, a lack of access to and quality national programs enables a smooth school-
to-work transition, including vocational training and career guidance.
This is mainly due to the unbalanced relationship between the rate of economic development and
the rapid population growth, and urbanization also plays a big role in aggravating the youth
unemployment problem. Beside that, in Ethiopia, relatively well educated and fresh job seekers
are largely affected by the prevalence of unemployment, with unemployment duration close to
four years and even more years for those seeking a white collar job (Mains 2007, Serneels 2007).
As it is known that Ethiopia is one of the least urbanized African countries, youth employment
opportunities in both the formal and informal sectors are concentrated in major urban areas. After
some level of schooling in Ethiopia, it is common for young people to move to urban areas to
search for jobs. This makes youth unemployment in Ethiopia an urban spectacle. Being the primate
city located in the heart of the country where major cultural, economic, and political institutions

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are situated, Addis Ababa attracts more labor forces from every corner of the country, which raises
competition for the limited available jobs.
Thus, the purpose of this research is to identify determinants of youth unemployment, and to
change the level of factors that cause unemployment in Addis Ababa, Bole Sub City Woreda 14.
This research found that the problem of unemployment highly affects the population of Addis
Ababa, Ethiopia. Currently, 20.1 percent of the unemployment rate is estimated in Addis Ababa
city. As of the city subcity4 data a data, number of registered unemployed youth are 4899, out of
which 54% are male and the rest 46% are female youth unemployed. The declining of youth
unemployment was attributed to the adoption of youth policy in 2004 and the efforts made by the
government in making the young people actively participate in the development activities of the
country. The factual evidence indicated that youth unemployment in urban areas like Addis Ababa
is a serious problem. It reflects that efforts have been made to address the problem, in which a 10
percent decline was observed in the last eleven years. The results of the study are important to the
employers and other labor market players, for understanding the source of problems resulting in
unemployment of youth which account for a large share of the bole sub city woreda 14 labor force.
However, the issue requires further intervention from the concerned body in order to benefit from
the human resources, individually and nationally. Otherwise, the social and economic costs would
affect individuals and societies in particular, and the country in general the study also adds to the
literature by filling the knowledge gaps on the roots of youth unemployment and how the problem
can possibly be addressed in the country.
1.3 Research Questions
• What are the most influential factors for youth unemployment?
• How do you evaluate the measures to change level of factors that causes
unemployment in Addis Ababa, Bole sub–City Woreda 14?
• How to assess the extent of youth unemployment in this study area?
• What are the influential determinants to identify youth unemployment?
1.4 Objectives
1.4.1 General Objective

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The main objective of the study is to identify the determinants of youth unemployment in Bole sub
city Woreda 14.
1.4.2 Specific Objective
The specific objectives are:
• To assess the extent of youth unemployment in this study area.
• To identify the most influential determinants of youth unemployment.
• To evaluate the measure to change the level of factors that causes unemployment in Addis
Ababa, Bole sub–City Woreda 14.
• To assess the prospect of being unemployed among youth’s potential.
1.5 Scope and limitation of the Study
The study will be limited to, Bole sub city Woreda 14 because of the existence of alarming rates
of youth unemployment. There are only few projects that will create jobs for the increasing youth
population in the a Woreda.
This study is also specific to the determinants of youth unemployment in bole sub city Woreda 14.
This research study was also lack of time and had scarce of financial resources to carry out a more
thorough investigation. Because of geographical limitation, this study only considers bole sub city
Woreda 14 youth unemployment. Further, the job creation and policy contribution factors are
measured against number of actively employed youth only.
As the research is specific to youth unemployed of bole sub city Woreda 14 is geographically
confined to the capital city (Addis Ababa), it might affect the generalizability of the research
output. As the sampling technique of the study used to select sample Woreda’ and respondents is
limited to convenience, this could affect the reliability of the study. It would have been better and
more effective if samples were selected randomly which creates equal chance to be included in the
sample. In addition, shortage of related research works on the topic was another impediment of
this study.
1.6 Significance of the study
It is significant because it will add to already existing body of knowledge of youth unemployment.
It is significant because it will look into the cause and effect of youth unemployment in bole sub

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city Woreda 14 providing visible solutions to unemployment in that area. It will bring to light
various factors contributing to unemployment thus providing probable instrument to policy
makers. It will classify, locate and verity variables while are expected to form pre-conditions of
unemployment making problem solving possible.
Analyzing the impacts of youth unemployment is crucial for curbing it in Bole sub city Woreda
14 where there is a very small number of the population participating in the labor market and
particularly Bole sub city where there is a growing concern of increased number of young job
seekers. This research study will contribute to the understanding of unemployment from academic
perspective particularly the effects of youth unemployment it will helps the officials in the quest
for desirable youth targeting states as unemployment is concern. Last but not least, this study
might contribute to the future potential researchers who are interested to undertake their research
on the issue in the case of Addis Ababa city bole sub city.
1.7 Organization of the research
This study is organized under five chapters. Chapter one deals with Introduction which contains
background of the study, statement of the problem, objective of the study, delimitation and
limitation of the study. Chapter two reviews important concepts of the subject matter. Chapter
three discusses the methodology of the research which includes research and sampling design, data
source, data acquiring and analyses techniques etc. Chapter four deals with data analyses and
interpretation and chapter five contain conclusion and recommendation.

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CHAPTER TWO
LITRATURE REVIEW
2.1 Theoretical Review
2.1.1 Definitions of Unemployment
Unemployment occurs when people are without work and actively seeking work. The
'unemployed' are those actively looking for job, but cannot find the work according to international
labor organization (ILO). The 'inactive' are those without work and are not interesting in seeking
job. This inactive youth may include those who are in school.
In United States of America (USA), unemployment can be referred to as the unemployment rate
which is defined as the total number of the unemployed divided by the total labor force; this
consists of both the employed and unemployed persons. ''Youth'' are young people ages from 15
years to 24 years; (United Nations, UN), however, in practice there is no universal definition of
youth. It varies from one country to another based on cultural, social, institutional, and political
factors (United Nations, 1992).
In Africa there is no definite definition of youth, for instance, in Ethiopia a person age between 15
and 29 years is considered to be a youth, in Uganda a person age 12 to 30 years is said to be a
youth, in south Africa a person between the age of 14 to 28 years is considered to be youth,
(Ethiopia national youth policy, 2004). 9 the concept of youth is defined differently by different
institutions. Among these are; government, United Nations (UN), the Civil Society Organizations
(CSOs), (Boboya James Edmond, 2015).
According to the United Nations, youthful age range from 15 to 24 years, (UNPY, 2002). The
United Nations convention on the right of child considers any person below the age of 18 years as
a child. The definition of youth as any person age15 to 30 years. This definition will be employed
for the purpose of this study as the rate of unemployment affects such age category.

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2.1.2 Types of Unemployment
2.1.2.1 Cyclical Unemployment
This is refer to the difference between the rate of real unemployment and the natural
unemployment rate. According to john Keynes Maynard cyclical unemployment is a huge
aggregate excess supply of labor.
2.1.2.2 Frictional Unemployment
This is caused by natural frictions of labor market matching processes. Here the frictionally
unemployed search for job from whose suitable vacancies exist, but cannot find these firms. 10
2.1.2.3 Structural Unemployment
This occurs as a result unmatched skills possessed by the unemployed and other characteristics
that do not meet the requirements of the Technological changes in available job vacancies and
economy's structural changes usually as a result of changes in the skills composition as required
in the labor market. When the job seekers do not adjust to these changes, then the structural
unemployment will result, (Jeffrey parker, 2010).
2.1.3 Natural Unemployment
According to Milton Friedman in an address to the American economic association (Friedman,
1967) ''natural rate of unemployment'' refers to the rate resulting from the equilibrium operation of
micro economy when macro-economic conditions cause neither excess demand nor excess supply
of labor.
2.2 Measurements of Unemployment
2.2.1 The Unemployment Rate
Unemployment rate measures the percentage of work force that is considered to be out of work,
but searching for job (bankrate.com).
It indicates the state of the labor market and household's financial status. Rising unemployment
leads to reduced spending on consumption and bankruptcy, delinquency. It indicates a competitive
labor market, in which employers have hard time in finding workers to fill in the available job
vacancies. This will force the employers to pay high wages so as to attract more workers.
(bankrate.com). As it measured the percentage of work force, some individuals are not considered
as unemployed since they might be frustrated with looking for work and give up on trying to search
for job. These discourage workers will take jobs if it came along their way which mean that official

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unemployment underestimates the real unemployment. This leads to counterintuitive in which the
number of the employed and unemployed will move in the same direction instead of opposite
directions. it also underestimates the rate of unemployment because it does not consider the rate
of the underemployed workers, for instance part-time workers who may be willing to work full
time and those in employment below their qualification or low pay than those possessing the same
skills with them. It does not show the length of unemployment for individuals as duration of
unemployment is an important measure for unemployment rate. (Jodi, 2016).11
2.2.2 Labor Force Participation Rate
It is the percentage of the working age persons who are unemployed and actively looking for work
and also the employed in the economy. The working age is from 16-64 years those considered not
to be participating in the labor force are homemakers, non-civilians and the retirees and under 64
years on institutionalized people. (Mike, 2016). Since the output level per worker is the major
determinant of the standards of living in the economy. It is important to know how much of the
total population wants to work instead of only those who want to work are actually working. (Mike,
2016).
2.2.3 Minimum-wage effects on skilled and unskilled labor
As per Jeffrey Parker, Economics 314 Coursebook, 2014 explanation A two-sector labor market
is shown in Figure 1. The left panel shows the equilibrium of the market for skilled labor. In this
market, the equilibrium wage exceeds the minimum wage, so there is no direct effect of the
minimum-wage law on unskilled labor. The right panel shows the unskilled labor market in which
the equilibrium wage is lower than the legal minimum. The wage floor is effective in the unskilled
market, preventing demand from coming into equality with supply. As in our initial analysis of
Figure 1, employment is reduced and an unemployment gap exists.
This would be the end of the story if there were no connections between the markets for skilled
and unskilled labor. However, there may be spillovers on either the demand side or the supply side
(or both). On the supply side, there would be no immediate spillover of workers from one market
to the other. Unskilled workers cannot, presumably, become skilled immediately, while skilled
workers earn a higher wage in the skilled market and have no incentive to move.
In the longer run, supply flows in either direction are possible. Those who cannot find work in the
unskilled sector due to the excess supply situation may choose to acquire skills and eventually

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move to the skilled sector. This would increase the supply of skilled workers and drive their wage
down. However, the gap between skilled and unskilled wages has been reduced (for those unskilled
who have work), so there may be less incentive for workers to acquire skills if they believe that
they will be successful in getting an unskilled job at the higher minimum wage.
This spillover would tend to offset the previous one, leaving the net effect on supply uncertain. On
the demand side, firms’ demand for skilled workers may be affected by the increase in the wage
for unskilled labor. If skilled and unskilled workers are substitutes, the firm will increase its
demand for skilled workers, which will tend to push skilled wages upward. If they are
complements, this will reduce skilled-labor demand and lower skilled wages. Although the
substitute-complement relationship between skilled and unskilled labor is likely to vary across
industries, the most common assumption is that they tend to be substitutes. If that assumption is
true, then an increase in the minimum wage will raise the wages of skilled workers. This hypothesis
is supported strongly by the intense political support for minimum-wage legislation by labor
unions. Most members of labor unions already earn more than the minimum wage, so they have
no direct interest in a higher minimum wage.
To summarize, effective minimum-wage laws appear to benefit the fraction of unskilled workers
that are able to find jobs. They reduce the welfare of those unskilled workers who cannot find
employment. Skilled labor seems to gain from higher minimum wages as substitution by firms
pushes the entire wage structure upward.

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Fig 2.1 Minimum Wage in Segemented Labor Market
Source: Own Construct based on the data Bole sub city Woreda 14 MIS record
2.2.3 Models of Unemployment
2.2.3.1 The Minimum Wage Models
The model is used in the analysis of price floor. Labor is said to be homogenous. Individual
workers participate in particular labor market and are paid equal wage. Assume a Walrasian
market, thus the wage will be w*. If the minimum wage is imposed above the equilibrium wage at
w1, then the market will be at disequilibrium. Only L workers will be employed at w1 and L''-L '
workers will be unemployed. Deere, Murphy, and Welch (1995). Gilroy Brown and Kohnen
(1982) and Brown (1988), Neumark and watcher (1995) Card and Krueger (1995). 12
2.2.3.2 The Lake Model of Unemployment and Employment
This model is the basic analytical tool for analyzing the flows between unemployment and
employment and how it influences the steady state unemployment and employment rates. The
model make it easy to interpret monthly labor reports, net jobs created and jobs destroyed. The ''
lakes'' in the model are the pools of the unemployed and the employed persons. The '' flows'' in the
model are caused by hiring and firing, entry and exit from the labor market.

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2.2.3.3 The Job Search Model
This determines the average time unemployed job-seeker takes to get new job. If the job seeker
finds and accept new job quickly, then the unemployment rate is lower. Search for Job is modeled
by analyzing both the marginal benefits and the marginal costs. If the marginal benefits of search
are higher than the marginal costs, then the search will be foregone. The wage income that an
individual has foregone for not accepting the offer is said to be the cost of search. The lengthy the
search period, the better offers one accumulates, so the marginal cost of continue searches is likely
higher.
The benefits of continued search are that a better employment would be got. The marginal benefit
declines as search is continued, since the incremental increase in job quality becomes smaller as
more jobs have been checked. The decline in the marginal benefit's curve below shows the
decrease in the marginal benefit of the search and the increasing marginal cost shows the increasing
cost of the job search. The length of the job search is measured on the duration D*. Change in
marginal benefit or marginal cost affects the equilibrium unemployment.
2.3 Empirical Literature
2.3.1 Effects of Unemployment
Lorenzini and Giugui (2010) pointed out that youth unemployment leads to social isolation and
decreased social contacts and collective participation of individuals as they became psychological
depressed and feels lonely. It usually affects both the mental and psychological health of
individuals and the person becomes pessimistic that either the person can attempt suicide or
involve themselves in activities that negatively affect their lives. Because of these, individual's
self-esteem is affected negatively and feeling that they became burden to their family and society.
Social isolation make young people consider themselves as useless, termed as unable to do
anything useful to the family and the society. Gul et al., (2012) argued that the social and private
costs of unemployment are ''rigorous financial distress, homelessness and debt, poverty, family
tensions, and breaks down of family relationship, housing stress, stigma and alienation shame.
Increased crime, erosion of self- esteem, social isolation and confidence.
Another argument is that these effects increase with expanded period of unemployment. Morin
and Kochhar, (2010), pointed out that unemployment often breaks family ties and friends
especially at time the unemployed person wants some support from family and friends. According

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to Morin and Kochhar those who stay for long without job are significantly more cynical about
their chances of getting a job as good as they lost than the short-term unemployed people. Nadia
Llyas, (2015), argued that unemployment affects not only an individual's life. It has serious
negative consequence on the entire economy as a whole.
Society can become a prey to unemployment as it posed numerous challenges to the people of
specific society. By becoming unemployed in the future, the impact is it lowered a young person's
wellbeing, injured self-esteem and foster feelings of helplessness among young people. Reynolds,
(2012), noted that unemployment leads to scarring effects, the combination of poverty and
unemployment can permanently increase psychological distress, similarly at global levels, and
unemployment is a manifestation of structural challenges.
As noted from numerous studies conducted by Andrew S. (2000) in the United States of America
(USA) and Kevin O'. (2003) for the world bank as it is cited by the youth unemployment 17
challenge and solution (2011) it is said that youth who find it difficult to integrate into the labor
market at earlier entrant face scarring effects that diminished their ability and resiliency to thrive
in a demanding and dynamic labor market. Sarah Ayres (2013), in the research paper titled ''the
high costs of youth unemployment'' indicated that youth unemployment have huge negative costs
and long term effects for both individual youth and the whole country's economy.
According to her, being unemployed for long at youthful age leads to lack of skills and experience
acquisition during this time which leads to reduced future earnings for an individual over the entire
career. Because of this reduced future earnings an individual suffers from low purchasing power
during their entire lives. This also has a serious negative consequence on the country's economy
and aggravates youth unemployment and often adds on to the reduced economic growth of a
country (Ayres, 2013). East African Community u.d, (EAC) in its report titled 'youth
unemployment head on'' stressed that unemployment brings violence and crime among the youth,
commercial sex work and as a result leads to spreads of HIV/AIDS, civil disorder and drug abuse
are direct consequence of youth unemployment in sub-Saharan Africa. These illicit activities and
failure of employment bring huge economic and social costs such as increased level of insecurity
and increased costs for security, loss foreign direct investments (FDIs), waste of productive human
resource and increased costs of health services.

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Mitchell (2012) argued that youth unemployment enforces substantial, social, individual and
economic effects such as '' social exclusion, loss of skills, loss of current output, psychological
problems which resulted into increased rates of suicide, reduction in life expectancy, loss
motivation, undermining family life and relationship, gender and racial inequality and loss of
responsibility', social values and ill health. Jacob, (2011) sustained that unemployment for
children, young, unmarried mothers are Crucial, as they might grow up in an environment within
poverty cycle, especially when this young mother have no marketable skills or have no financial
help from the child's father. Another consequence of youth unemployment is on political stability.
As argued by Azeng and Yogo in their quantitative research, they concluded that high rate of
young people unemployment has significant negative impact on the political stability of the
country especially in low developing countries (LDCs). (Azeng and Yogo, 2013, P.19) Vena
Nedeljkovic (2014) argued that the social and economic costs of unemployment among the youth
in Europe must be understood carefully as it has numerous negative impacts not on future prospect
for employability of youth only, but also on individual youth self-esteem, their role in society and
represent a serious economic burden on state finances. Being young and unemployed can leads to
increased risk of social exclusion, deskilling and poverty, loss of motivation and ill health.
Unemployed youth are extremely prone to worst future career opportunities.
Poverty risk and lower wages Unemployment among the youth leads to reduction in their levels
of happiness and mental depression. Being employed is crucial for young people as they feel much
accepted in the community. Therefore, be unemployed can cause socio-economic, political and
cultural isolation. Stress and unemployment worries cause individual ill health such as mental
depression, increased consumption of drugs and alcoholic addiction as well as increased levels of
crime among the youth (Nedejkovic, 2014).
High unemployment rate among the youth has negative consequence on productivity and
economic growth. Skilled human resource and talent risk being wasted since a huge number of
young graduates were unable to find jobs in order to put their capabilities and knowledge into
production, innovation and contributing to economic growth, moreover, having a large share of
young people out of work not only leads to reduction in productivity and gross domestic product
(GDP). But it also leads to increased economic costs of the country's economy. Since much money
is paid as social benefits and less money is raised from the taxes (Nedejkovic, 2014).

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This can leads to increased family tension and mental and financial crisis within the family.
Unemployment can cause young girls and women to drop out of school at earlier age in order to
serve their families in a bid to earn some income. Unemployment may leads to high crime rates,
depression and substances abuse by youth.
2.5 Conceptual Frame Work
The following conceptual frame work is extracted from the above reviewed literature. From the
above concept, the dependent variable (youth unemployment) is an output of demographic &
socio economic factors, and implementation of appropriate policy intervention.

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Fig.2.2 Conceptual framework of determinates of youth unemployment
Source: Own construction based on the model developed by Nganwa, et al, (2013)

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CHAPTER THREE
RESEARCH DESIGN AND METHODOLOGY
3.1 Research Design
Research design is described as a plan for a study that provides the overarching framework for
data collection by Leedy (1997:195). According to MacMillan and Schumacher (2001:166), it is a
strategy for choosing participants, research locations, and data collection techniques to address the
research topic (s). They also suggest that the objective of a decent study design is to provide results
that are regarded as credible. The research design that should be used relies on the study's purpose,
claims Kothari (2004). The author has divided the research design approaches into three major
groups. The first is called exploratory and is utilized in cases where exploratory research
investigations are being conducted, the main goal of which is to formulate a problem for a more
focused inquiry. The second type of study design is experimental, and it is employed in studies
that test the hypotheses positing a causal relationship between variables. The third one, known as
a descriptive one, is used to describe the features of a specific person or group of people in
descriptive research studies. Accordingly, the study's research design is descriptive because it
focuses on narrating facts and characteristics pertaining to the group of youth unemployment.
3.2 Sampling Design
A clear strategy for selecting a sample from a certain population is known as sample design. The
method or process the researcher would use to choose the items for the sample, as well as the
number of items to be included in the sample, are referred to by this phrase. The sample design
takes into account the kind of universe or quantity of populations, the sampling unit, sampling
frame, and sample size.

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3.3.1 Type of universe (Population)
3.3.3.1 Employee and Unemployed
A population that included both employee and unemployed young people could have improved
representation. The study, however, solely focuses on Unemployed individuals due to limited
resources, geographical location and ease of management and administration.
3.3.2 Type of Unemployed youth
The majority of young people without jobs need to find employment, and there are a few job
listings and opportunities in a few nearby cities for people with various educational backgrounds.
So, it makes sense to concentrate on job seekers. As a result, there are 4899 registered job seekers,
both educated and untrained, in the Bole sub city woreda 14 where the survey was conducted
(extracted from MIS process records of the Bole sub city woreda 14, on September, 2022). The
majority of those who have registered as job seekers are educated but lack sufficient work
experience.
3.3.3 Study population and Sampling Technique
Youth residing in Bole sub city woreda 14 who are unemployed and educated or not make up the
study's population. When people lack a job and actively seek one, they are said to be unemployed
(or jobless) (ILO,1982). Therefore, the sample and the units of analysis are chosen depending on
the nation youth age group used in this article. This indicates that respondents are those individuals
living in the research area, between the ages of 15 and 29, who are unemployed and eligible for
employment.
3.3.4 Sample Size
The study used a straightforward random sampling method. To select a sample in simple random
sampling, random integers must be used. More particular, it needs a database or list of every person
in the population as its sample frame at first. Using Excel or another SW, produce a number at
random for each element, and then collect the first n samples that were needed. 4 unemployed
young people of both sexes were thus chosen and interviewed with the aid of key informants. As
of August 30,2013, E.C, the total number of registered youth unemployed of the Bole sub city
woreda 14 was 4988.

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3.3.5 Sample size and Sampling technique
The sample size is determined based on a format extracted from bole sub city woreda 14 data base
(August 30, 2013 E.C). The recommended sample size for a population size above 1125 at 95%
confidence level and a margin of error (degree of accuracy) of 5% is 287. Since the total number
of registered youth unemployment is more than 1125, the sample size is 287.
Fig 3.1 Unemployment trend from 2010 -2013E.C
Male Female Total
Qty 2,663 2,236 4,899
Percent 54% 46% 100%
Source: Bole sub
city Woreda 14 MIS record
3.4 Data source and acquiring techniques
The study used primary, secondary, and tertiary data sources. Secondary data were gathered from
books, journals, and research papers. The Woreda youth unemployment registration data base's
reports and pertinent documents were used to gather secondary data. On the other hand, physical
interviews and questionnaires were used to gather the primary data. The questionnaire's constructs
were tested in a pilot study by being given to 15 unemployed youth and Bole sub city woreda 14
employees, ensuring that they could all grasp them. The constructions were modified in response
to the feedback. Finally, throughout the time of data collection, the questionnaires were widely
dispersed.
2,663
2,236
4,899
54% 46% 100%
-
1,000
2,000
3,000
4,000
5,000
6,000
Male Female Total
Table 3. Unemployment trend from
2010-2013 E.C

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There are three sections to the survey questionnaire. The respondents' gender, age, education level,
source of income, marital status, location, and occupation are all included in the first section's
description of their demographic profile. Constructs relating to causes that contribute to
unemployment are found in the second section, while constructs relating to the social and
demographic effects of unemployment are found in the third section. A five-point Likert scale with
a strongly disagree to strongly agree range was used to construct it. Five points were given for
strongly agreeing, four for agreeing, three for neutrality, two for disagreeing, and one for strongly
disagreeing.
The unemployment factors are own constructs that contain five questions and also the
Unemployment's social and demographic impact related questions are adopted from Tashi
Yangchen, with little modification in order to best suit the specific service of the study. Further,
some of them are developed by the researcher. based on the definition of Amanuel Disassa
Abshoko. (2016)
3.5 Data Analysis
The researcher used Statistical Package for Social Science (SPSS) Version 2022 to analyze the
data. This software has been widely used by researchers as a data analysis technique. Both
descriptive as well as inferential statistics are used to analyze the data.
3.5.1 Descriptive statistics
Descriptive statistics were used to analyze the respondents' demographic profiles, the effectiveness
of the factors that contribute to unemployment (such as a lack of job information and skill
mismatch), the social and demographic factors that contribute to unemployment (such as economic
migration, hopelessness, and a lack of job opportunities), and the respondents' level of
worklessness, information asymmetry, unemployed depression, and mental health issues. The
corresponding frequency and mean value are tabulated and summarized. Following a brief analysis
and interpretation of the tables, a discussion follows.
3.5.2 Inferential statistics
In this study, Pearson correlation coefficient is used to measure the strength of the association
between the Unemployment factors and the Unemployment social & demographic impact which
is correlation coefficient used to measure the linear association between two scale variables.

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3.6 Reliability and Validity
3.6.1 Reliability
Reliability, according to Bhattacherjee (2012), is the degree to which a construct's measure is
dependent or consistent. Reliability is concerned with the consistency or stability of the score
received from a measure or assessment technique through time and under various conditions
(Anastssi & Urbina, 1997; white & saltz, 1957). The reliability of each concept in this study was
assessed using the Cronbach's alpha scale.
3.6.2 Validity
Validity has been defined and explained by many academics in a variety of ways. According to
Bhattacherjee (2012), the validity of a measure is the degree to which it accurately represents the
underlying construct that it is intended to measure. Both theoretical and empirical methods can be
used to evaluate validity. Theoretical evaluation of validity is concerned with how well a
theoretical construct's concept is translated into or reflected in an operational measure. An
empirical validity assessment looks at how well a specific measure correlates with one or more
external criteria using empirical observations.
According to the most popular definition, reliability measures the extent to which an experiment
or any other process that involves measuring procedures will yield the same results if repeated
trials are carried out (Ferrell, n.d., para. 2). In other words, a reliable test or experiment is the one
that provides consistent results every time that it is conducted, with only minor deviations
acceptable. The validity of a test is an entirely different concept that concerns not only the results
of the study but the overall design and performance.
The three most popular ways to prove validity are called content related, criteria related, and
construct related validity (Campbell, 1960). When a measurement approach or instrument is
relevant to the construct being measured, it is said to have content-related validity (Fitzpatrick,
1983). The process for figuring out content validity begins with the operationalization of the target
notion. Other measurement techniques that are used into research design and methodology can
also be related to content validity. The use of already-existing, readily-available tools is prevalent
in much research.

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3.7 Ethical Issues
The bole sub city woreda 14 has been informed of the study's goals and objectives through
introductory letters, and the researcher has made sure that permission was obtained. On the
questionnaire, the respondents were given a detailed explanation of the study's goals and
objectives. Informing respondents not to write their names on the questionnaire served as another
confirmation of information confidentiality.

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CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION
4.1 General Information about Respondents
From the 384 questionnaires distributed to the youth employed & unemployed, 248 were returned.
This resulted in 65% response rate. Out of the total questionnaires returned, 22 were incomplete
so they were eliminated from the data. Hence, the completed and usable questionnaires were 287
or 75% of the questionnaires distributed. This suggests that the response rate was high. The basic
information provided by the respondents—including gender, age, education level, occupation,
income and number of years without a job—was the subject of the study that followed. Statistical
information is included in the appendix column (Appendix 2.1).
Source: IBM SPSS V22 Output 2022
According to the collected information, men made up 69.4% of the respondents. 48.8%, 32.7%,
and 18.5% of the sample respondents fall into the 15–29, 30–60, and above 60 age groups,
respectively, according to the age category. This suggests that the majority of those seeking job
and those in the woreda 14 are young and middle-aged, which presents woreda 14 with a strong
opportunity given that these age groups are thought to be the most productive. 16.9%, 19.8%,
50.8%, 6%, and 1.6% of respondents said that they had a certificate, diploma, degree, master's

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degree, or Ph.D., respectively, based on their educational level. Less than high school is only
attended by 4.8% of respondents. As a result, it may be inferred that the majority of respondents
have solid educational backgrounds and have likely had exposure to a range of employment
opportunities.
Source IBM SPSS V22 Output 2022
Another significant element that affects how much respondents make is occupation. As per the
above data analysis, the percentages of employees working for the government, private companies,
self-employed and the jobless are respectively 29.8%, 19.0%, 7.7%, and 43.5%. This suggests that
while the majority of respondents (56.5%) have their own money, which is positive, many
respondents are still young people who are unemployed (43.5%), thus it will take a lot of work to
provide job opportunities for the youth in the woreda.
4.2 Reliability Test
According to Hatcher (1994) cited by Ma and Liu, Cronbach’s alpha is an index of reliability
associated with the variation accounted for by the true score of the underlying constructs which is
the hypothetical variable that is being measured. Thus, Cronbach’s alpha is calculated to examine
the consistency of the constructs and the statistics results are presented in Table 4.1
4.2.1 Reliability
The study's constructs' internal consistency is gauged by their reliability. If a construct has an alpha
value better than 0.70, it is considered dependable (Hair et al., 2013). Cronbach's Alpha was used
to evaluate the construct's reliability. The four-item scale measuring economic elements

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(Alpha=.835) and the four-item scale measuring social aspects (Alpha=.806) were found to be
reliable, according to the results. Similarly, the youth unemployment rate was determined to be
trustworthy (Alpha=.802). The table below shows that the Cronbach's alpha for each construct
under investigation is higher than the minimum acceptable level of 0.70. This demonstrates the
accuracy of the measurements that were taken. Table 4.3 provides a summary of the reliability
findings.
Table 4.3 Reliability Analysis: Cronbach’s Alpha Value
Constructs No. of Items Cronbach’s Alpha
Economic Factors 4 .835
Social Factors 4 .806
Unemployment youth status 2 .802
Total 10
4.3 Descriptive Analysis
The levels of young unemployment for the two economic and social components are described by
the mean value in this section of the analysis. It is evaluated using a five point Likert scale, with 1
representing strong disagreement and 5 representing strong agreement. The neutral value is
assigned the value of 3.
4.3.1 Analyses of Economic Factors
4.3.1.1 Income
In this study, the Income is measured in terms of how the level of income are categories in low
income, Health problem, Negative family effect and effect of unemployment in economy. The
statistical values of respondents are presented in table 4.4

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Table 4.4 Economic Factor-Income
N Mean Std. Deviation
Income/Low Income 248 3.70 .774
Income/Health problem 248 3.29 1.043
Income/Negative family effect 248 3.53 .819
Income/effect of unemployment on
the economy
248 3.40 .930
Valid N (listwise) 248
Grand Mean 3.41
According to table 4.4, the mean response on low income, health problems having a negative
impact on families, and the impact of unemployment on the economy is 3.70, 3.29, 3.53, and 3.4,
respectively. This suggests that the majority of respondents concur that the low income causes
youth unemployment income to diminish or become unavailable, which translates to a high rate of
unemployment. Regarding health problem, the typical response value is 3.29. This shows that the
majority of respondents are divided on the issue of unemployment caused by a health problem.
The grand mean value of source of income is typically 3.41. This suggests that the majority of
those surveyed concur that the effects of teenage unemployment on different reasons explained.

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Fig 4.1 Skill Mismatch
Source Own construct based on Bole sub city Worda 14 MIS data
One of the key causes of educated youth unemployment is the skill mismatch between the
educational system and the labor market, as is seen above. Of those surveyed, 42.74% strongly
agree. They link the mismatch between the labor market and the field of study to the current
unemployment. A mere increase in a higher institution's capacity without modifying the market
that graduates enter might have devastating effects. Given that Ethiopian government and public
institutions graduate students at a rate that exceeds 70% annually (Ministry of Education (MoE,
2015), the proportion of graduates who are unemployed is rising in relation to overall
unemployment. The number of college graduates was significantly higher than the work market
could handle. As if it were convenient for this paper, the majority of respondents expressed their
emotions. First, they listed their department, university, and year of graduation before saying, "I

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have spent so many years looking for job openings every day since graduating, but I have received
the response that there are no jobs for the department I graduated." This report claims that there
are numerous issues facing educated young and that there is no institutional connection between
higher education institutions and the labor market. Because of a mismatch between labor supply
and demand, or labor underutilization, there was an imbalanced demand for jobs.
4.3.1.2 Job Opportunity
Since it can have a bad influence on young people's well-being as well as a negative impact on the
nation's economic performance and social stability, youth unemployment is a significant concern
for Bole sub city woreda 14. The development of woreda is consequently most urgently hampered
by the need for employment generation. To enable professional staffing of the occupations and so
positively contribute to economic growth, another task is to provide vocational and technical
training for the workers. There are numerous fresh job seekers who have registered in the Bole sub
city woreda 14 databases. Following is an evaluation of the identified socioeconomic and
employment policy barriers for young people looking for work:
• lack of or insufficient information on employment opportunities and self-employment,
• inadequate and inefficient public employment services,
• limited access to finance to become self-employed,
• inadequate and inappropriate vocational training options (e.g. apprenticeships, technical
courses).

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Table 4.5 Economic Factor-Job Opportunity
Job Opportunity/lack of information on employment
opportunities and self-employment
248 3.84 1.115
Job Opportunity/inadequate public employment
services,
248 3.78 1.345
Job Opportunity/limited access to finance to become
self-employed,
248 4.00 1.136
Job Opportunity/inadequate and inappropriate vocational
training options
248 4.01 1.247
Grand Mean 3.90
Table 4.5 shows that, with the exception of two constructs—lack of knowledge on employment
and inadequate public employment—all other mean values are greater than the grand mean of 3.9.
The job opportunity of receiving insufficient and inappropriate vocational training in their line of
work receives the highest mean score, 4.01, followed by limited access to financing to start their
own business, with a mean score of 4.00. This shows that the majority of respondents concur that
there are many career opportunities, but that the available training options and vocational trainings
are inadequate. However, as the mean value is 3.78, they are neither in agreement nor disagreement
on the job potential of having little access to financing to start their own business.
4.3.1.3 Economic Factor-Saving/Investment
Bole Sub City Woreda 14 needs to take urgent action to address the significant issue of youth
unemployment. Political instability, high population density, a lack of vocational training options
for recent graduates, and ethnic tensions nationwide all contribute to the worsening of
unemployment in the Bole sub-city. Therefore, policymakers must focus and ensure increased
economic growth and investment in order to meet the growing need for jobs, particularly among

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young people. Additionally, the administration must address the ongoing political and ethnic
unrest before it negatively affects the economy.
Table 4.6 Economic Factor-Saving/Investment
N
Mea
n Std. Deviation
Saving/assure an increase in economic
growth
248 3.24 1.055
Saving/investment in order to create
more jobs
248 3.41 1.061
Saving/increasing demand for jobs 248 3.53 .819
Grand Mean 3.39
Table 4.6 demonstrates that the mean economic component of increased employment demand,
investment, and saving power is 3.53, 3.41, and 3.24, respectively. As a result, the majority of
respondents think the economic factor contributing to the rise in demand for jobs in the woreda 14
is conceivable. However, neither agree nor disagree that it has power.
4.3.2 Analysis of Social Factors
Finding the right social element to influence unemployment and developing it is not the only goal.
The ultimate purpose of the whole youth job accessibility on health manner is to transform young
people's desired behavioral patterns. The primary predictors of youth unemployment, along with
socioeconomic variables, include health problems. Income & social protection, unemployment &
job insecurity, working circumstances, & food insecurity, basic utilities & the environment are the
categories of health factors.

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4.3.2.1 Social Factors– Income and social protection
The effectiveness of the social determinants affecting health as a result of income and social
protection is discussed in this section of the analysis. The non-medical elements that affect health
outcomes are known as social determinants of health. In addition to the larger group of factors and
systems influencing the conditions of daily life. These factors and systems include political
systems, societal norms, social policies, economic policies and systems, and development
objectives.
Table 4.7 Social Factor-Health
N
Me
an
Std.
Deviation
Health/Income & social
protection
248 3.21 1.008
Health/unemployment & job
insecurity
248 3.48 .753
Health/working circumstances,
& food insecurity
248 3.29 .971
Health/basic utilities & the
environment
248 3.51 .858
Grand Mean 3.37
Table 4.7 shows that the grand mean value of 3.37 is not reached by the mean values of the job
insecurity construct. This shows that the majority of the respondents concur that youth
unemployment and job insecurity capture their attention and that they can readily distinguish this
from other socioeconomic issues affecting health.
4.3.2.2 Social Factors -Education
It is a known fact that less well-educated people have higher unemployment rates than better
educated people. A possible explanation of this finding is job competition: employers prefer higher
over lower educated workers for jobs that were previously occupied by lower-educated employees.
Inadequate education and lack of productivity is costing jobs. Unemployment increases
progressively with decreased educational levels; and the education system is not producing the
skills for the labour market. Labour supply is affected by the increase in the number of job seekers
over the years.

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Table 4.8 Social Factor-Education
N Mean
Std.
Deviation
Education/Inadequate education 248 3.71 .651
Education/lack of productivity 248 3.12 1.140
Education/Labour supply is
affected by the increase in the
number of job seekers
248 3.06 1.151
Valid N (listwise)
G. Mean
248
3.30
As shown in table 4.8, There are numerous reasons for youth unemployment. The most frequently
advanced theory, however, is that young people's unemployment is caused by their lack of
education, training, and skills. Inadequate education, low production, and a rise in the number of
job seekers are represented by 3.71, 3.12, and 3.06 correspondingly. Which suggests that the
majority of respondents concur that receiving a good education has improved their understanding
of how social variables affect people. Knowledge has an overall mean value of 3.30. This shows
that the majority of respondents have an excellent knowledge of the value of a good education.
4.3.2.3 Social Factors –Skill/Training
The Georgina Diallo December 2011 UNICEF explanation claims that young people between the
ages of 15 and 24 are unable to pinpoint the skills they will require for upcoming economic
prospects. A common method for businesses to confirm the talents new hires claim to have is
lacking, and young people are also unable to receive training in pertinent skills. According to
Georgina Diallo, there is a gap between the criteria and the education and training systems, which
prevents young people without internet connection from taking advantage of online training
options. Young people need a mechanism to track their talents correctly, safely, and verifiably so
that they can share them with potential employers.

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Table 4.9 Social factors- Skill /Training
N Mean
Std.
Deviation
Skill/unable to identify which skills they need
for future employment opportunities
248 3.46 .752
Skill/unable to access relevant skills training 248 3.25 .963
Skill/employers lack a standard way to verify
the skills new employees claim
248 3.49 .868
Grand Mean 3.4
As per Table 4.9 demonstration, on job market, young people are particularly vulnerable. Many of
them do not have the necessary skills, training, work experience, job-searching skills, or financial
resources to secure employment. According to the majority of respondents, one of the biggest
issues with youth unemployment is that there is no common method for businesses to confirm the
abilities that new hires claim they have. It is 3.49, which is greater than the overall average of 3.4.
The remaining, with a mean of 3.46 and 3.45, were respectively unable to determine which skills
they lacked and to access them respectively. Many people who do have jobs put in a lot of
overtime, have short-term or informal contracts, are paid little, and have little to no social
protection.
4.3.2.4 Social Factors –Tradition
The concept of unemployment related to the realm of socio-economy and politics while
unemployment experience takes the form of individual subjective involvements (Celik 2006:6). It
is now necessary to evaluate individual experiences in order to explore how individuals are
impacted by the connections between the political environment, the general economy, and

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unemployment. Lack of entrepreneurship skills, extensive rural-to-urban migration, skill mismatch
with the labor market, and faster population growth are among important socioeconomic issues
that influence tradition.
Table 4.10 Social factor- tradition
Tradition/lack of entrepreneurship
skill
248 3.67 .664
Tradition/huge rural urban migration
248 3.12 1.140
Tradition/skill mismatch with the
labour market
248 3.21 1.008
Tradition/higher population growth 248 3.46 .752
Grand Mean 3.36
According to table 4.10, the mean response rate for the social aspects of tradition, larger population
growth, skill mismatch, and significant rural migration is 3.67, 3.46, 3.21, and 3.12, respectively.
This shows that the majority of respondents believe that a major issue is a lack of entrepreneurship
skills. The grand mean score of 3.36 indicates that the majority of respondents do not believe that
tradition may foster favorable attitudes regarding the elimination of adolescent unemployment.
4.4 Correlation Analyses
The degree of correlation is measured using a variety of correlation coefficients. The Pearson
correlation coefficient, which solely considers a linear relationship between two variables, is the
most popular of these. A statistical measure that assesses the linear relationship between two
variables is the Pearson's correlation coefficient, commonly abbreviated as r. Its value falls
between +1 and -1, signifying a perfect positive and negative linear relationship between the two

37 | P a g e
variables, respectively. In order to offer the most reliable numbers for reporting in scientific
investigations, statistical tools like SPSS and SAS typically calculate the correlation coefficient.
A correlation value of zero, according to Cohen (1988), signifies that there is no linear relationship
between the two variables. A correlation value that is near to 1 indicates that the data are more
positively correlated than average. A correlation value that approaches -1 denotes a linearly
negative relationship between the two variables. The Pearson's correlation coefficient can be
interpreted using some well accepted rules. Cohen (1988) states that a Pearson correlation
coefficient value between 0.1 and 0.29 indicates a weak or tiny association between the two
variables, while a value between 0.3 and 0.49 indicates a moderate or medium relationship. There
is a strong or significant association between the variables being examined if the Pearson
correlation coefficient is between 0.5 and 1. The two fundamental presumptions that must be taken
into account while constructing the Pearson correlation function are that the variables have a linear
relationship and that both variables are normally distributed.
4.4.1 Relationship between Socio economic factors & Unemployment status
dimensions
Pearson correlation coefficient was used to measure the strength of the association between the
Unemployment status factors and the Socio-economic dimensions. Preliminary analyses have been
done to assure no violation of the above assumptions is committed. To this end, normality and
linearity of the scale distribution has been analyzed and the assumption of correlation is not
violated.
Table 4.11 Correlation between Socio economic Factors &Unemployment status Dimensions
Socio
Economic
factors
Unemployme
nt Youth
status
Socio Economic factors Pearson Correlation 1 .768**
Sig. (1-tailed) .000
N 248 248
Unemployment Youth
status
Pearson Correlation .768**
1
Sig. (1-tailed) .000
N 248 248
**. Correlation is significant at the 0.01 level (1-tailed).
Source IBM SPSS V22 output 2022

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As shown in table 4.11, there is a positive relationship between the socio-economic factors and the
youth unemployment status. Pearson The two variables' correlation coefficient is 0.768, which is
higher than 0.5. This suggests that socioeconomic conditions and youth unemployment have a
significant relationship.
CHAPTER FIVE
SUMMARY OF THE FINDINGS, CONCLUSION AND
RECOMMENDATION
5.1 Summary of Findings
In this study, several factors that affect youth unemployment have been analyzed. The youth
unemployment status was used as the dependent variable. And also the independent variable is
grouped in to two, that are Economic factors that include Income, savings, job opportunity and
economic policy and also second independent variable is Social factors that include Education,
Health, Skills/training, and tradition. Data extracted from bole sub city woreda 14 data base
(August 30, 2013 E.C). from the period of 2010 E.C.-2013 E.C were analyzed. There is a positive
relationship between the socio-economic factors and the youth unemployment status. Pearson The
two variables' correlation coefficient is 0.768, which is higher than 0.5.
According to the findings, there is a strong correlation between socioeconomic characteristics and
youth unemployment. To facilitate assessment and targeting with research on youth employment,
the determining elements of young unemployment in Bole sub-city Woreda 14 were examined
using correlation and regression analysis. First, we analyze the significance of the link between
the independent factors in our model and the dependent variable. This was important to assess the
model's capability to correctly forecast the dependent variable. Two important factors that affect
how much respondents make are gender and age. Men made up 69.4% of respondents, while
women made up 30.6%, according to the data collected and analyzed on table 4.1.48.8%, 32.7%,
and 18.5% of the sample's respondents, respectively, fall into the age brackets of 15 to 29, 30 to
60, and older than 60. Given that young and middle-aged people are thought to be the most
productive age groups, this suggests that the majority of job searchers are in these age categories,
which presents woreda 14 with a huge opportunity.

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The respondents' occupation plays a substantial role in determining youth unemployed income.
According to the analysis shown in table 4.2, the percentages of workers employed by the
government, private businesses, self-employed individuals, and unemployed people are,
respectively, 29.8%, 19.0%, 7.7%, and 43.5%. This indicates that although while the majority of
respondents (56.5%) have their own money, which is encouraging, many of the respondents
(43.5%) are still young people who are unemployed, thus it will need a lot of work to provide job
possibilities for the youth in the woreda 14.
This study measures youth unemployment in terms of how it interacts with income, job
opportunities, savings, economic policy, health, education, skills, and tradition. Looking at the
individual variables, however, the perceptions of respondents on low income, health issues having
a negative impact on families, and the impact of unemployment on the economy which are very
important characteristics of youth unemployment are not as such effective as the mean values are
3.70, 3.29, 3.53, and 3.4 respectively. The mean value of health problem is 3.29. This implies that
the majority of respondents do not concur that the young in the woreda region are jobless as a
result of health issues.
The time frame for the data used in this analysis was 2010–2013 EC. Additionally, the
investigation only included data from the Bole sub-city Woreda 14. As a result, both the time
period and the number of woredas included in the data set may be increased. Before drawing any
conclusions, it is important to recognize these restrictions. According to the research literature,
numerous empirical investigations use different econometric models to ascertain the effects of
variables. A dynamic model can be created to track changes in youth unemployment over time
because the time impacts of some variables can be seen in the term after. The explanatory power
of research will be improved much further in this approach.
In terms of the social aspects of health, education, skill, and tradition, the young unemployment
rate in the Woreda 14 is assessed. The highest mean value for youth unemployment is 3.4 for
skill/training, followed by 3.37, 3.36, and 3.30 for health, tradition, and education, respectively.
This shows that the majority of respondents concur that young unemployment is low because they
are educated, healthy, and traditional.
The socioeconomic characteristics and the youth unemployment rate are positively correlated, as
shown in Table 4.11, and this association is significant. Pearson The correlation coefficient

40 | P a g e
between the two variables is 0.768, which is greater than 0.5. This implies a considerable
connection between socioeconomic factors and youth unemployment. Last but not least, the
research's conclusions about the connections between economic factors and aspects of youth
unemployment show that they are high (.835), social factors and youth unemployment are
Moderate (.806), and therefore there is a substantial relationship between the two factors.
5.2 Conclusions
The purpose of this study is to investigate the factors that contribute to youth unemployment in
Bole Sub City Woreda 14 and offer solutions for reducing youth unemployment. In this study, the
factors influencing unemployment in Woreda 14 are examined using a linear regression model.
Youth unemployment status, the dependent variable, which was divided into employed and jobless
categories, served as the study's dependent variable. The study's conclusions in this dependent
variable are that educational status, age, location, skill mismatch, gender, income, hopelessness,
information asymmetry, and lack of skill/training are all significant factors in explaining the
difference in youth unemployment status.
The study's findings indicate that gender is a significant independent variable and that it affects
unemployment in a considerable way. Compared to female youth, male youth are more likely to
be employed than jobless. Men's literacy rates are particularly low compared to women's. Men and
women had higher and lower participation rates, respectively. For rural women, staying at home
to care for their families is a valid excuse, but for urban men it is typically being a student. Women
marry younger than men, which is a result of the disparity in opportunity structures between men
and women. Women are more likely than males to be unemployed while they are young in
metropolitan areas, particularly in Bole Sub City Woreda 14, and men do not marry as young,
which enables woreda 14 youth to acquire better education opportunity than women.
Job Position available Significant, youth unemployment among the Woreda 14 is discovered.
Youth are at a disadvantage on the job market due to a variety of variables, including the
information asymmetry of work. The focus of the current policy is to address the employment
challenge by promoting the private sector, increasing investment to increase productivity,
organizing youth, and providing loans with the integration of banks and microfinance institute to
provide a loan for the youth business proposal, that helps them to crop cash. In order to encourage

41 | P a g e
them, the woreda 14 have made it possible for various work loans for groups of loans to be used
to invest in their business proposals.
The chances for young people will be limited as long as the Woreda 14 small and medium projects
continue to experience slow growth, which also affects the number of jobs created annually. The
accessibility, and availability of jobs all contribute significantly to the labor market's effectiveness.
Information on the labor market is limited, and not all job seekers have access to it. The absence
of these services disadvantages those just entering the workforce.
The Woreda 14 youth unemployment data source reveals that the majority of the unemployed are
uneducated or have only a limited amount of education, despite the fact that there is a growing
population of high school graduates in the labor sector. The impact of skills on youth employment
status results, which showed that unskilled youth were more likely to be unemployed than
employed, confirmed the results on schooling. In addition, the Woreda 14 Education Department
is offering soft skills training to young people who are unemployed in order to help them become
better communicators, problem solvers, time managers, technology users, curriculum creators, and
self-explainers so they can find better employment opportunities. This kind of action has had a
positive impact on the youth unemployment rate. and would be inspired to carry on; also, it serves
as an excellent model for other woreda adolescent unemployment.
As one of the dependent variables of social factors, education is one that we attempt to discuss in
this study. Youths and their parents desire an education to better their social and economic
circumstances; however, young people frequently experience post-secondary unemployment and
long periods of unemployment. Education is crucial in the Bole sub city of Woreda 14 since
employment creation is difficult due to the enormous growth in student enrollment at all levels.
This widens the gap between what students actually receive in school and what they expect.To
highlight a few of the gaps, the government's poor economic performance and its failure to offer
enough opportunities are recognized and investigated as contributing factors to graduate young
unemployment. The labor market and skill mismatch are also cited as contributing factors to
unemployment since they push recent graduates to rely more on the government than on building
their own businesses.
Furthermore, migration from rural to urban areas is one of the factors contributing to the imbalance
between job demand and supply, and it has a direct and indirect effect on the rise in youth

42 | P a g e
unemployment in woreda 14. Youth groups migrate from rural to urban areas, particularly Bole
sub city woreda 14, in search of employment opportunities, which reduces the availability of
employment opportunities in rural areas. The unemployment rate will rise as the population
increases more quickly. Additionally, the study made an effort to examine and evaluate the
solutions offered to the unemployment problem. A few of the suggested tactics include luring
foreign investment, skill-matching schooling with the job market, and concentrating on enhancing
students' entrepreneurial skills. As a further measure to address the issue of educated youth
unemployment, sufficient job opportunities should be created in both formal and informal settings
in rural and urban locations.
Last but not least, this study came to the conclusion that the study in Bole sub city woreda 14 gave
a thorough account of the key elements of the young labor market. The labor market in the
aforementioned sector has significantly improved, however youth unemployment in bole sub city
woreda 14 is still pervasive. The research reveals that in addition to implementing tactics that will
help the growing number of educated youth entering the job market, policies should be made to
address the poor labor market circumstances for women in both rural and urban locations. Along
with boosting job information, the study's conclusion included concrete employment policies and
initiatives that target youth and seem to have promise. Other goals included reducing skill
mismatches and information asymmetry. Additionally, by working with the private sector and
entrepreneurs, good career possibilities can be created for young people who enroll in
comprehensive soft skill training.

43 | P a g e
5.3 Recommendations
Based on the findings of the research the following recommendations are made.
● Policymakers and higher education institutions must work together to reduce the number
of unemployed young people and attract more potential foreign investment to the country's
economy.
● Rural-urban migration is one of the main causes of youth unemployment, and it needs to
be addressed by offering young people who move from the countryside to cities
employment options.
● In order to reduce the skill mismatch between the profession of the graduates and the labor
market, education is one of the dependent variables of social factors, and it is necessary to
increase the attentiveness of educational institutions to the demands of the labor market.
● A significant contributor to youth unemployment is the asymmetry of job information. The
Woreda 14 administration must endeavor to obtain employment data for each unemployed
young person in order to solve this issue.
● One of the significant problems with increasing youth unemployment is limited job
availability, so the private sector's and entrepreneurs' participation has a big effect on
reducing the number of unemployed youth.
● Hopelessness and unwillingness among young people to turn to alcohol, chat, cigarettes,
and other addictions, rather than focus on searching for jobs are major factors in the
tremendous increase in the unemployment rate. Therefore, the Woreda 14 administration
has to build youth trust and confidence within themselves and with other stakeholders.
● The government should take steps to foster the entrepreneurial abilities of the unemployed
youth and encourage them to design their own company proposals and use microfinance
loans to complete their own projects in order to inspire youths to expect jobs from other
sources besides the government.
● Insufficient work possibilities in the public, private, and investment sectors are one of the
factors causing unemployment. In order to address unemployment, the government must

44 | P a g e
establish the institutions and processes needed, such as a job portal system that accepts
applications in a transparent manner and hires candidates based on their qualifications and
recommendations.
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APPENDICES-1
A study on the Determinants of youth unemployment in case of Bole sub city woreda 14. The purpose of study is to identify and describe
the determinants of youth unemployment. Your helpful collaboration will enable the researcher to locate trustworthy data, which will
be utilized solely for educational purposes. Please make an effort to respond to each query.
The researcher can be conducted via Tel. XXXXXXXX
Part I. Background Information
DIRECTION: Please choose your response by check the appropriate response category for each question.
Part II. Unemployment Situation
1. Gender Men Women
2. Age 15-29 30-60 > 60
3. Marital Status Married Single Divorced Widowed
4. Education Certificate Diploma Degree Masters
5.Location Sub city Woreda Kebele

THE DETERMINANTS OF YOUTH UNEMPLOYMENT IN CASE OF BOLE SUBCITY WORDA 14

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