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FACTORS INFLUENCING YOUTH UNEMPLOYMENT IN TANZANIA
EDWIN PHILBERT
A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ECONOMICS OF THE OPEN UNIVERSITY OF TANZANIA
2017
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CERTIFICATION
The undersigned certifies that has read and hereby recommends for acceptance dissertation entitled: “Factors Influencing Youth Unemployment in Tanzania” in Partial Fulfillment of the Requirements for the Degree of Masters of Science in Economics (MSc. Economics) of the Open University of Tanzania
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Dr. Felician Mutasa
(Supervisor)
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Date
COPYRIGHT
No part of this dissertation may be reproduced, stored in any retrieval system, or transmitted in any form or by any means without prior written permission by the author or Open University of Tanzania.
DECLARATION
I, Edwin Philbert, do hereby declare that this dissertation is my own original work and that it has not been presented to any other University for a similar or any other degree award.
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Signature
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Date
DEDICATION
I dedicate this work to my Lovely Parents Mr. & Mrs. Philbert Katundu, my young sisters Hellen and Christine. Also to my fiancée Penila Muganda and lovely son Edson Edwin for their encouragement and support during my studies.
ACKNOWLEDGEMENT
This dissertation would not have been possible without the guidance and the help of several individuals who in one way or another contributed and extended their valuable assistance in the preparation and completion of this study.
First and foremost, I would like to express my utmost gratitude to Dr. Felician Mutasa my supervisor of this study. Whose sincerity and encouragement will never be forgotten Dr. Mutasa has been my inspiration as I hurdle all the obstacles in the completion of this research work. The same is extended to all my colleagues and staffs of Economics Department, for their kind concern and consideration regarding my academic requirements.
Indeed, my appreciations are also to staff of the university of Dar es salaam library for the permission given for solicit materials to undertake this study. I would also like to recognize with appreciation the support I received from Coordinator Timothy lyanga for their unselfish and unfailing support as my dissertation advisers.
I am also respectfully indebted to Dr. Aloyce Helpelwa of the University of Dar es salaam for editing the work done of this dissertation prior to printing of the required number of hard copies.
Last but not the least, much thanks to my Mother, Fiancée and son Edson for their patience and steadfast encouragement to complete this study; and the one above all of us, the almighty God for answering my prayers for giving me the strength to plod on despite my constitution wanting to give up and throw in the towel, thank you so much Dear God.
ABSTRACT
This study examines the factors influencing youth unemployment in Tanzania using integrated Labour force survey of Tanzania for 2014 conducted in Tanzania mainland. In analysis the issue of youth unemployment, the logit model has been used, with a series of independent variables. The model shows important role for youth’s level, education level, and age of a youth, youth’s gender, and youth’s place of resident, headship status. The findings show that being married, male head of the household, presence of paid and self-employed in the household, significant reduced the probability of a youth being unemployed. On the other hand youth‘s education level of and living in urban increases the probability of a youth being unemployed. Further, the result indicates that the likelihood of unemployment tends to decrease as age of a youth increases. The government may need to enhance gender equality in access to education, training and employment in order to reduce high unemployment among youth women. Moreover, there is a need for the government to focus attention on the rural- urban drift in order to deal with the problem of rural -urban migration and consequently reduce high youth unemployment in urban- rural areas. It is also important to restructure some human capital development and labour market issues that relate to employment in order to match skills with labour market demand.
TABLE OF CONTENTS
CERTIFICATION ii
DECLARATION iii
DEDICATION v
ACKNOWLEDGEMENT vi
ABSTRACT vi
TABLE OF CONTENTS viii
LIST OF TABLES xii
LIST OF FIGURES xiii
ACRONYMS xiv
CHAPTER ONE 1
1.0 INTRODUCTION 1
1.1 Background to the Study 1
1.2 Statement of the Problem 4
1.3 Objectives of the Study 4
1.4 Hypothesis of the Study 5
1.5 Significance of the Study 5
1.6 Scope of the Study 5
1.7 Organization of Study 6
CHAPTER TWO 7
2.0 AN OVERVIEW OF EMPLOYMENT AND UNEMPLOYMENT 7
2.1 Introduction 7
2.2 Overview of Unemployment in Tanzania 7
2.3 The Population of Tanzania 8
2.4 The Youth Population 9
2.5 Economically Active Population 10
2.6 Labour Force Participation 10
2.7 Employment and Unemployment Situation in Tanzania 11
2.7.1Employment Situation in General 11
2.8 Employment by Sectors 12
2.8.1 Agricultural Sector 12
2.8.2 The Trade Sector 13
2.8.3 The Construction Sector 13
2.9 Tanzania Youth Unemployment Situation 14
2.9.1 Global, Regional and National Youth Unemployment 14
2.9.1.1 Global Youth Unemployment Situation 14
2.9.2 Regional Youth Unemployment Situation 14
2.8.1 The Youth Unemployment Challenge in Tanzania 16
2.10 Government Employment-Related Policies and Programmes in Tanzania 17
2.10.1 National Employment Policy, 2008 17
2.10.2 National Youth Development Policy, 2007 18
2.10.3 Agricultural Sector Development Programme 18
2.10.4 Small and Medium Enterprise Development 19
2.10.5 Construction Industry Policy, 2003 20
2.11 Conclusion 20
2.10.1 Unemployment Rate by Sex and Area 21
2.10.2 Unemployment by Age Group and Sex 22
CHAPTER THREE 23
30. LITERATURE REVIEW 23
3.1 Introduction 23
3.2 Theoretical Literature 23
3.2.1Definition of Youth 23
3.2.2Who is Unemployed? 24
3.2.3Classical Unemployment Perceptive 24
3.2.4Keynesian Unemployment Perspectives 25
3.2.5Structural Unemployment Perspective 25
3.2.6Job Search Theory 25
3.2.7Human Capital Theory 26
3.3 Empirical Literature 26
3.4 Empirical Studies in Tanzania 30
3.5 Research Gap 31
CHAPTER FOUR 32
4.0 RESEARCH METHODOLOGY 32
4.1 Introduction 32
4.2 Conceptual Framework 32
4.3 Models 33
4.3.1The Log it Model 33
4.3.3The Empirical Specification of the Model 34
4.4 Definition of Variables 34
4.5 Estimation Techniques 36
CHAPTER FIVE 38
5.0 MODEL ESTIMATION AND INTERPRETATION OF RESULTS 38
5.1 Introduction 38
5.2 Descriptive Analysis 38
5.2.1 Youth Unemployment and Education Level 39
5.2.2Youth Unemployment and Age 40
5.2.3 Youth Unemployment and Gender 57% 40
5.2.4 Youth Unemployment and Marital Status 41
5.2.5 Youth Unemployment and Place of Residence 41
5.3 Analysis of the Estimated Logit Model Results 42
5.3.1 Youth Marital Status 44
5.3.2 Youth’s Age 45
5.3.3 Education level 45
5.3.4 Youth’s Gender 46
5.3.5 Place of Residence 47
5.3.6 The Presence of Employee in the Household 48
5.4 Summary 49
CHAPTER SIX 50
6.0 MAIN FINDINGS AND GENERAL POLICY RECOMMENDATIONS 50
6.1 Main Findings 50
6.2 Policy Recommendations 51
6.3 Limitations 53
6.4 Areas for further Research 53
REFFERENCES 54
APPENDICES 56
LIST OF TABLES
Table 2. 1: Population Structure by Age Group and Geographical Area: 2014 10
Table 2.2: Youth Employment by Age Group and Sex in Percentage, 2014. 12
Table 2.3: Employment by Sector 13
Table 2.4: Unemployment Rate by Sex and Area in Percentage, 2014 21
Table: 2.5 Unemployment Rate by Age Group Sex, 2014 22
Table 3.2.1: Summary Indicating Variable Name, Code and Expected Sign 36
Table 5.1: Characteristics of the variables in summary 38
Table 5.2: Youth Unemployment Rate and Education Level 39
Table 5.3: Youth Unemployment by Age 40
Table 5.4: Youth Unemployment and marital status 41
Table 5.5 Results of the estimated Logit Model 43
Table 5.5: Marginal effect after logit 44
LIST OF FIGURES
Figure 5.1: Youth Unemployment by Gender 41
Figure 5.2: Unemployment Rate by Place of Resident 42
LIST OF ABBREVIATION AND ACRONYMS
ASDP Agricultural Sector Development Programme
CAMARTEC Centre for Agricultural Mechanization Rural Technology
GDP Gross Domestic Product
ILFS Integrated Lobour Force Survey
ILO International Lobour Organization
NECP National Employment Creation Programme
NSGRP National Strategy for Growth and Reduction of Poverty
SIDO Small Industries Development Organization
TEMPO Tanzania Engineering and Manufacturing Design Organization
TIRDO Tanzania Industrial Research Development Organization
UN United Nations
YEN Youth Employment Network
EU European Union
Repoa Research for Poverty Alleviation
URT United Republic of Tanzania
ILFS Integrated Labour Force Survey
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CHAPTER ONE
1.0 INTRODUCTION
1.1 Background to the Study
High unemployment among the youth is one of the primary challenges facing the modern labour market. According to ILO, the number of unemployed youth aged 15-24 has been steadily growing in the recent decades, hundreds of millions of young people are working but still living in poverty. The ILO (2005). estimated the number of unemployed youth to be 88 million or 47% of the global unemployed. Youth consists of only 25% of the world’s working age population. In the absence of significant economic growth and development, high youth unemployment will persist as major challenges of most countries due to population growth and the influx of large numbers of young people into the labour market in developing countries. Some 238 million young people are living on less than US$1 a day and some 462 million young people are living on less than US$2 a day (ILO, 2005). The ILO estimated that decreasing global youth unemployment by half would lead to an increase in the global GDP by US$2.2 trillion an increase of 4%. Addressing youth unemployment in general would also lower poverty levels and add to GDP (World Bank, 2006).
Although the recent report on Global Employment Trend for Youth by ILO revealed some encouraging trend with declining youth unemployment rates between 1997 and 2007 in some regions of the world including Sub-Saharan Africa, youth unemployment is still a major challenge. The report revealed that despite recent economic growth, rapid population growth which is most youthful represents a significant challenge to the region. Sub – Saharan Africa also faces decent work deficits which create limits in the development of skills among the young population, as families have difficulties affording education and training, even if adequate facilities are available. Maison modern,(2016).observes “In recent years, there is growing awareness of the importance” of tapping human resources potential around the world, the international community and international agencies. Initiatives to promote decent employment opportunities for youth and to assist them in their transition from school to work have been established in most countries of the world (ILO, 2005). Unemployment rates are much higher for women especially younger women than men in most regions of the world, but the youth (Mainly school leavers) are the most affected. Most of the women compared to men occupy low-paid, low productivity and vulnerable jobs. They also work more in the agriculture and informal sector. According to a recent ILO report, the status of women at the labour markets throughout the world has not substantially narrowed gender gaps in the work place (ILO, 2008)
The vast majority of the world’s youth work in the informal economy. In Africa, 93% of all new jobs and in Latin America almost all newly created jobs (for young labour market entrants) are in the informal economy. Young informal workers frequently work long hours with low wages, under poor and precarious working conditions, without access to social protection, freedom of association and collective bargaining. A number of causes on youth unemployment have been put forward and these are analyzed from microeconomic or macroeconomic perspectives. The macroeconomic determinants of unemployment are aggregate demand, youth wages, and the size of the youth labour force and the lack of skills among youth. Indeed, changes in aggregate demand affects young people more than the adult due to the fact that young people are more likely than older workers to leave their jobs voluntary particularly during recession. During recession, it is expected that the first reaction of firms is to stop recruitment, and this affects young people more strongly. Moreover, when firms start redundancy procedures, it is cheaper for them to fire young workers rather than older workers.
The microeconomic determinants which deal with individual characteristics includes level of education, work experience, gender, imperfect information on the labour market, marital status, age and location. This study chooses to examine the determinants of youth unemployment looking on the individual characteristics because they have a greater influence on youth unemployment. Youth unemployment imposes heavy cost to the individual and the economy as a whole. Unemployment in early life may permanently impair employability, earnings and access to quality jobs. Youth unemployment means that investment in education and training by the government are wasted. On the other hand youth unemployment means that young people have less to spend on products and services, and that personal savings are reduced for investment in business, resulting in loss of production. In addition high and rising unemployment levels among youth may cause hopelessness and other social evils such as crime, violence, break up of families, alcoholism and prostitution. In general, youth unemployment and poor jobs contribute to high levels of poverty.
Therefore, investment in youth is very important to economic growth and development of the country. Decent work for young people has multiplier effects throughout the economy, boosting consumer demand and adding to tax revenue. The demand for social services decreases significantly when youth have decent work, because their time is spent in productive, self-esteem building and healthy ways. Successful early career development is correlated with long-term career prospects. It shifts young people from social dependence to self – sufficiency and helps them escape poverty and actively contribute to society. This study seeks to examine the determinants of youth unemployment at a national level in Tanzania. Analyzing the determinants of youth unemployment is useful in understating on factors which contribute to youth being unemployed and provides important policy recommendations.
1.2 Statement of the Problem
Employment generation is very important in curbing poverty and attaining long term economic growth. In her effort to reduce youth unemployment, like strengthening and Expanding services for commercial training, sensitizing youth to start joint youth economic groups and starting special fund for the purpose of covering training costs and providing loan for self-employment activities. Tanzania formulated the Youth Employment Development policy (2000).which aims” to promote sustainable economic and employment growth in order to reduce youth unemployment and under-employment in the rural and urban areas; ultimately attaining full productive and decent youth employment and thus eradicating poverty”. Moreover, reducing unemployment has been recognized as one of the operational targets in National Five Year Development Plan II (FYD II) with a target to reduce unemployment from 2011/12 rate of 28.2% to 16.7% by 2021.The 2014, ILFS indicate that unemployment rate (national definition) of youth aged 15 – 24years has declined from 16.5% in 2006 to 14.9% in 2014.This rate is still high when compared to the rate for other adults and the 11.7% total unemployment. Unemployment levels among the youthincrease mainly due to the increase in urban employment as result of rural –urban migration. Most of the young people are migrating to big urban centers like Dares Salaam to seek jobs. Hence, youth Unemployment is still a problem worth of attention. Thus, it is important to analyse the factors influence youth unemployment a step towards addressing the problem.