Expert Group Meeting on Strategies for Creating Urban Youth Employment: Solutions for Urban Youth in Africa Measurement/indicators of youth employment Gora Mboup Global Urban Observatory (GUO) UN-HABITAT Nairobi, June 22-24, 24, 2004
TOPICS HABITAT Agenda and MDG Employment and Unemployment indicators Slum indicators Intra-city differentials: Gender, slum and education Family responsibilities and employment Youth homelessness: case of Addis Abba, UIS 2003 Youth indicators : comprehensive approach
The UN-HABITAT Agenda, paragraph 118 emphasizes the need to promote and strengthen productive enterprises, including micro-enterprises and other employment and training opportunities for youth at the international, regional and national levels and MDG8 Develop a global partnership for development Target 16: In co-operation with developing countries, develop and implement strategies for decent and productive work for Youth
Employment Indicators indicator 17: informal employment (HA) indicator 19: unemployment (HA) Indicator 45 Unemployment rate of 15-24 year-olds by gender (MDG)
Unemployed people Not employed during a specified reference Available for work Have taken concrete steps to seek employment. In situations where the conventional means of seeking work are of limited relevance, a relaxed definition of unemployment can be applied, based on only the first two criteria (without work and currently available for work, see ILO, 2004).
The youth unemployment rate and non-employment rate The youth unemployment rate gives the percentage of persons aged 15 to 24 years who are actively seeking, but unable to find employment. The youth non-employment rate is a measure of the youth who are neither in education nor in employment as a proportion of the total youth population. The non-employment rate takes into consideration those discouraged youth who have dropped out of the labour market and sometimes out of society in general (see ILO, 2004).
Youth age group Youth age group varies across country from 15 up 35 years old International youth age group: 15-24 years old
Youth indicators Youth employment indicators is part of a youth indicators project initiated in UN-HABITAT by the Partners and Youth section in collaboration with the Global Urban Observatory (GUO)
Youth indicators Youth indicators (education, employment, living conditions, health, etc.) aim at increasing knowledge on urban inequities and assisting the formation of youth pro-poor policies on the ground. While the global aggregates are needed to shape the global development priorities, youth indicators will provide instrumental guidance on improving the lives of the youth
Youth indicators Youth indicators EDUCATION EMPLOYMENT LIVING CONDITIONS HOUSEHOLD HEADED BY YOUTH HEALTH STATUS Literacy rates Level of education Non-employment rates Type of employment Access to water Access to sanitation Access to housing Access to information Access to energy Maternal and child health Antenatal and delivery cares Child immunization Child morbidity Maternal and child nutrition DECISION MAKING Use of resources Use of health services SOCIAL CAPITAL Networking Micro-finances INFORMATION/ COMMUNICATION Access media Access to key info HIV/AIDS knowledge prevalence orphanhood
Preliminary list of of Countries of of youth indicators project MIDDLE AND WESTERN AFRICA ANGOLA BENIN BURKINA FASO CAMEROON CAR CHAD COTE D IVOIRE GHANA GUINEA MALI NIGERIA SENEGAL TOGO EASTERN AND SOUTHERN AFRICA ETHIOPIA ERYTHEREA KENYA LESOTHO MADAGASCAR MALAWI MOZAMBIQUE NAMIBIA RDC RWANDA SOUTH AFRICA TANZANIA UGANDA ZAMBIA ZIMBABWE ASIA INDONESIA INDIA PHILIPPINES JORDAN PAKISTAN UZBEKISTAN KAZAKHSTAN LATIN AMERICA BRAZIL COLOMBIA PERU PARAGUAY NICARAGUA GUATEMALA MEXICO
Data collection and source Country data are available from Labour Force Surveys, Demographic and Health Surveys (DHS), Living Standard Measurement Surveys (LSMS), censuses, administrative records, and official national estimates.
Limitation of publication on youth employment Lack of intra-city differentials figures Figures of youth unemployment on urban slums encounters a critical problem. Existing data are rarely disaggregated according to intra-urban location Data sets such as Labour Force, LSMS, DHS disaggregate by urban and rural, but go no further. Few efforts have been made to reanalyze data sets where the geographic origins of the data can clearly be identified as slum and non-slum.
UN-HABITAT Efforts to disaggregate city data 2002: EGM on slum definition 2003: Review slum definition and country slum estimates 2003: Publication of Slums of the World: The face of urban poverty in the new millennium
Slum Household Indicators lack one or more of the below conditions: Access to improved water Access to improved sanitation Access to secure tenure Durability of housing Sufficient living area
Youth employment: Country estimates
Youth non-employment Mozambique 39 Tanzania 38 Kenya 37 Zambia 36 Zimbabwe 31 Nigeria 31 Mali 30 Uganda 28 Chad 27 Ghana 26 Cote d'ivoire 23 Benin 22 CAR 21 Guinea 20 Burkina Faso Cameroon Togo 13 20 20 * Percentage of youth neither in school nor in employment
Young women non-employement Tanzania Mozambique Malawi Zambia Uganda Chad Mali Zimbabwe Namibia Kenya Nigeria CAR Ghana Cote d'ivoire Burkina Faso Rwanda Cameroon Guinea Madagascar Benin Togo 15 32 30 29 29 28 28 27 26 24 36 41 40 40 40 45 44 50 48 56 64 * Percentage of young women neither in school nor in employment
Young men non-employement Kenya Nigeria Zambia Ghana Mozambique Zimbabwe Benin Mali Cote d'ivoire Tanzania Guinea Togo Burkina Faso Cameroon Uganda 13 13 12 11 11 10 17 19 20 22 21 22 23 26 * Percentage of young men neither in school nor in employment 34
Gender differentials Young women non-employment rates (neither in school nor in employment) are higher than young men non-employment rates. However, employment data do not adequately reflect the situation of women in the labour market, especially in African countries where women are engaged in subsistence work and, more often than men, work in the informal sector (ILO,2001).
Young women neither in school nor in employment Mozambique Zimbabwe Malawi Uganda Kenya Mali Nigeria Cote d'ivoire Cameroon CAR Rwanda 18 20 27 39 30 33 36 27 28 26 34 24 33 33 31 42 38 47 44 54 61 61 Non-slum Slum * Percentage of young women neither in school nor in employment
Young men neither in school nor in employment by type of residence Mozambique 16 23 Zimbabwe 11 22 Uganda 9 16 Kenya 27 43 Non-slum Nigeria 23 30 Slum Cote d'ivoire 14 18 Cameroon CAR 10 12 13 9 * Percentage of young women neither in school nor in employment
Gender differentials While the proportion of women who are not working is higher in the slum than in the non-slum, the proportion of their counterparts men who are not working is lower in the slum
Possible explanations Men living in the slum need to be involved in early economic activity, they are less educated than their counterparts men living in non-slum who also have less urgent need to be involved in economic activity. This can explain the high fertility in poor communities as it has been stated in several studies. In these communities the value of children in term of labour rationalizes high fertility rates.
Young women not working but in school Nigeria Namibia Cameroon Malawi Togo Burkina Faso Ghana Madagascar CAR Guinea Mali Mozambique Zambia Chad Kenya Zimbabwe Rwanda Uganda Tanzania Cote d'ivoire Benin 34 36 32 39 26 37 26 25 25 38 24 22 22 32 20 19 30 17 37 17 15 30 15 35 14 20 13 19 13 41 13 28 13 19 11 26 11 16 10 49 49 53 Non-slum Slum * Percentage of young women not working but in school
Young men not working but in school by type of residence Mozambique Nigeria Burkina Faso Cameroon Chad Guinea Zambia Cote d'ivoire Ghana Benin Tanzania Kenya Uganda 13 14 25 24 26 36 35 32 37 36 32 32 33 51 54 44 53 41 50 45 48 44 43 58 57 68 Non-slum Slum * Percentage of young men not working but in school
Young women working in the informal sector Benin Cote d'ivoire Rwanda Togo CAR Madagascar Chad Burkina Faso Guinea Mali Ghana Cameroon Zambia Kenya Uganda Ethiopia* Senegal* Tanzania Mozambique Nigeria Zimbabwe Namibia Malawi 8 13 14 16 17 17 21 25 25 24 16 21 19 18 16 26 16 28 28 35 31 34 34 34 32 32 31 30 30 33 33 36 38 40 42 41 41 39 52 50 52 48 47 46 50 58 Non-slum Slum * Percentage of young women working in the informal sector
Young men working working in the informal sector Zimbabwe Benin CAR Tanzania Chad Zambia Cameroon Burkina Faso Kenya Mali Ghana Uganda Mozambique Cote d'ivoire Togo Guinea Senegal* Nigeria 8 7 8 10 17 17 14 16 15 21 21 27 25 27 25 25 27 24 24 27 26 28 27 31 30 38 35 34 33 33 32 32 42 44 60 61 Non-slum Slum * Percentage of young men working in the informal sector
Percentage of youth working in the informal sector living in slum area CAR Burkina Faso Chad Tanzania Mali Ethiopia Mozambique Madagascar Uganda Rwanda Nigeria Malawi Senegal Benin Togo Zambia Guinea Kenya Cameroon Ghana Cote d'ivoire 54 53 49 48 46 77 76 71 71 66 63 98 97 95 95 95 93 90 88 86 84 * Percentage of youth working in the informal sector living in slum area
Informal sector as expression of slum conditions Youth employment in informal sector is the expression of slums conditions in African cities. In most African countries, the majority of young people working in the informal sector are slum in-habitants. Per example in Benin they are 75 % and more than 90 % in Burkina Faso, Ethiopia, CAR, Chad, etc.
Youth in non-slum are attending school while youth in slum are strugling in informal sectors While youth living in non-slum areas are still attending school, youth in non-slum are either working in informal sector or looking for job
Employment and education In most countries youth who are working in the informal sectors are low educated or with no education at all. In fact educated people with complete secondary education or higher prefer formal job or are still attending school
Reasons for stopping to attend school Zimbabwe Zambia" Uganda Togo Tanzania Nigeria Mozambique Mali Madagascar Kenya Guinea Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 2 2 2 3 3 2 2 4 4 6 4 5 3 4 4 5 6 8 4 7 7 8 9 10 10 11 10 12 11 12 16 17 18 28 Got married Got pregnant * Percentage of young women working in the informal sector
Reasons for stopping to attend school Zimbabwe Zambia" Uganda Togo Tanzania Nigeria Mozambique Mali Madagascar Kenya Guinea Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 4 4 5 5 6 6 8 10 11 Family need help Take care of childrn * Percentage of young women working in the informal sector
Reasons for stopping to attend school Zimbabwe Zambia" Uganda Togo Tanzania Nigeria Mozambique Mali Madagascar Kenya Guinea Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 4 8 11 11 15 21 30 26 26 28 25 27 26 38 43 46 51 74 Need to earn money Could not pay school * Percentage of young women working in the informal sector
Reasons for stopping to attend school Zimbabwe Zambia" Uganda Togo Tanzania Nigeria Mozambique Mali Madagascar Kenya Guinea Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 2 1 3 2 2 4 10 12 13 15 18 22 23 24 26 28 33 35 Did not like school Did not pass exams * Percentage of young women working in the informal sector
Reasons for stopping to attend school 8 Zimbabwe 9 Zambia" 11 Uganda 3 Togo 1 Tanzania 23 Nigeria 19 Mozambique 2 Mali 2 Madagascar 2 Kenya 34 Guinea 4 Cote d'ivoire Chad 2 1 Graduated, enough CAR 1 Cameroon Burkina Faso Benin 1 3 5 * Percentage of young women working in the informal sector
Promote school retention An important element of governments promotional efforts may be to convince more young people to complete school. Despite the efforts of countries to improve the employability of youth through the education system, many still leave school with very limited skills (ILO, 2001). DHS data show that exclusion from education, training and employment is often systemic: early school leavers and other at-risk young people are often drawn disproportionately from slum communities.
Remedial education is particularly important for illeterate young people Remedial education is also important, particularly for illiterate young unemployed people and those with poor competencies in the prevailing national or regional language. Attracting premature school leavers back into education and training is a vital element of remedial education (ILO, 2001).
Percentage of women living in slum area who have family responsibilities Zambia Uganda Togo Tanzania Senegal Rwanda Nigeria Namibia Mozambique Mali Malawi Madagascar Kenya Guinea Ghana Ethiopia Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 30 33 33 29 28 39 40 60 59 53 52 60 58 65 46 55 58 58 61 64 51 50 Have child or married Head of household * Percentage women living in slum area who have family responsibilities
Percentage of women living in non-slum area who have family responsibilities Zambia Uganda Togo Tanzania Senegal Rwanda Nigeria Namibia Mozambique Mali Malawi Madagascar Kenya Guinea Ghana Ethiopia Cote d'ivoire Chad CAR Cameroon Burkina Faso Benin 7 10 42 31 21 30 27 21 44 28 31 28 25 28 42 28 19 33 37 40 26 62 Have child or married Head of household * Percentage of women living in non-slum area who have family responsibilities
Percentage of men living in slum area who have family responsibilities Zambia 15 Uganda 34 Togo Tanzania 16 14 Senegal Nigeria 8 4 Mozambique 3 Mali Kenya 6 27 Have child or married Guinea Ghana 5 21 Head of household Ethiopia 15 Cote d'ivoire 16 Chad 16 CAR 14 Cameroon Burkina Faso Benin 9 9 21 * Percentage men living in slum area who have family responsibilities
Percentage of men living in non-slum area who have family responsibilities Zambia 4 Uganda 5 Togo 6 Tanzania 5 Senegal Nigeria 4 2 Mozambique 3 Mali Kenya Guinea 8 5 14 Have child or married Head of household Ghana 17 Cote d'ivoire 2 Chad 9 CAR 11 Cameroon Burkina Faso Benin 7 13 11 * Percentage men living in slum area who have family responsibilities
Youth family responsibilities Youth residing in slum areas are more likely to have a child, or be married or to head an household than their counterparts living in non-slum areas. As family responsibilities increase, needs of job evolve. However due to the lack of performance of African economies and their low level of education these young people could find only jobs in the informal sector. With a low salary and insecure job, these young people will remain raising their family in slum communities. This is the poverty trap
Percentage of women who are working by family responsibilities Benin Togo Ghana Madagascar Rwanda Guinea Burkina Faso Ethiopia CAR Cote d'ivoire Kenya Cameroon Mali Uganda Zimbabwe Chad Zambia" Senegal Namibia Nigeria Tanzania Mozambique Malawi 59 58 57 56 56 55 51 47 45 43 42 40 38 36 36 35 30 28 24 79 75 71 66 No Family responsibilities Family responsibilities * Percentage of youth working in the informal sector living in slum area
Percentage of men who are working by family responsibilities Tanzania Zimbabwe Benin Uganda Cote d'ivoire Burkina Faso Zambia" Senegal Kenya Ghana CAR Chad Ethiopia Mozambique Mali Togo Guinea Nigeria Cameroon 57 55 55 62 60 72 68 68 67 80 79 79 74 85 82 82 81 91 90 No family responsibilities Family responsibilies * Percentage of youth working in the informal sector living in slum area
Family responsibilities create the needs of job among youth Youth who have family responsibilities are more likely to hold a job than their counterparts. However there is considerable number of youth with family responsibilities who are still looking for a job or are unskilled workers.
Consequences of Youth non-employment: Homelessness: Addis Abba Urban Inequities Survey 2003 Key findings
Homeless people by age group, Addis Ababa Urban Inequities Survey,, 2003 25 27 47 Pourcentage Male 30 30 30 Female 13 2 13-19 20-29 30+ Don't Know Âge
None Primary Secondary or higher Homeless people level of education, Addis Ababa Urban Inequities Survey,, 2003 57 47 Pourcentage 33 Male Female 28 25 10
Homeless people by migration reasons Addis Ababa Urban Inequities Survey,, 2003 64 41 33 Pourcentage Male Female 19 20 8 9 6 Work-Cash income Family Abused at home other