African Economic Outlook: Promoting Youth Employment

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Part Two Special Theme: Promoting Youth Employment

www.africaneconomicoutlook.org/en/in-depth/Youth_Employment

Chapter 6

Promoting Youth Employment Why an African Economic Outlook on youth employment? As successive editions of the African Economic Outlook (AEO) have shown, Africa’s rate of growth has outperformed the global rate over the last decade. Yet high growth is not sufficient to guarantee productive employment for all. Large sections of the population, and particularly the young, can be left behind and become frustrated. In the absence of a political process allowing them to express their views and produce policy changes, instability can result, as it did last year in a number of North African countries. This is an opportune time to reset the policy agenda of African governments towards an inclusive, employment-creating and sustainable growth strategy, aimed particularly at addressing the special needs of the young. Africa has been experiencing fast economic growth. From 2001/10, six of the world’s ten fastest-growing economies were in sub-Saharan Africa. Africa weathered the 2008 financial crisis well, with many economies already growing at rates close to their pre-crisis averages. Assuming that the current market turmoil in developed countries passes without serious consequences for Africa, prospects for the coming decade seem equally good. With almost 200 million people aged between 15 and 24, Africa has the youngest population in the world. And it keeps growing rapidly. The number of young people in Africa will double by 2045. Between 2000 and 2008, Africa’s working age population (15-64 years) grew from 443 million to 550 million; an increase of 25%. In annual terms this is a growth of 13  million, or 2.7% per year (World Bank 2011a). If this trend continues, the continent’s labour force will be 1 billion strong by 2040, making it the largest in the world, surpassing both China and India (McKinsey, 2010). Africa’s youth population is not only growing rapidly, it is also getting better educated. Based on current trends, 59% of 20-24 year olds will have had secondary education in 2030, compared to 42% today. This will translate into 137 million 20-24 year olds with secondary education and 12 million with tertiary education in 2030 (Figure 6.1.). Although significant quality gaps remain, these trends offer an unrivalled opportunity for economic and social development if the talents of this swiftly increasing reservoir of human capital are harnessed and channelled towards the productive sectors of the economy. However, they could also present a significant risk and threat to social cohesion and political stability if Africa fails to create sufficient economic and employment opportunities to support decent living conditions for this group. Although many jobs have been created, there have not been enough to accommodate the number of young people in search of work. The International Labour Organization (ILO) estimates that between 2000 and 2008, Africa created 73 million jobs, but only 16 million for young people aged between 15 and 24. As a result, many young Africans find themselves unemployed or, more frequently, underemployed in informal jobs with low productivity

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Figure 6.1. Africa is experiencing a rapid growth of educated young people (20-24 year-old cohorts by education, 2000-2030) Tertiary education

Secondary education only

Primary education only

No education

Million 250

200

150

100

50

0 2000

2005

2010

2015

2020

2025

2030

Source: World Bank EdStats, authors' calculations. 12http://dx.doi.org/10.1787/888932600279

and pay. Of Africa’s unemployed 60% are young people and youth unemployment rates are double those of adult unemployment in most African countries. The problem is particularly acute in middle-income countries (MICs). In 2009 in North Africa youth unemployment was 23.4%, and the ratio of youth-to-adult unemployment rates was estimated at 3.8. In South Africa, youth unemployment was 48% and the ratio of youth-to-adult unemployment rates was estimated at 2.5. Among the employed young, the proportion of work in informality is significantly higher than that of adults. The costs of inadequate employment are high. Poverty is the most obvious consequence. On average 72% of the youth population in Africa live with less than USD  2 per day. The incidence of poverty among young people in Nigeria, Ethiopia, Uganda, Zambia and Burundi is over 80% (World Bank 2009). The highest rates of poverty can be observed among young women and young people living in rural areas. But the costs go much deeper. The first years in the labour market, the skills developed and the experience then accumulated considerably affect young people’s future professional development. Long spells of unemployment or underemployment in informal work can “permanently impair future productive potential and therefore employment opportunities” (Guarcello et al., 2007). For the few that manage to obtain a formal sector job, which offers increasing wages, initial unemployment can have significant negative effects on lifetime earnings (OECD, 2010). In fragile states, the lack of adequate employment is among the major risks to stability (Box 6.1.). Without urgent action to modernise their economies, African countries risk wasting the tremendous potential offered by their youth. In a paper titled “The Economics of the Arab Spring” Malik and Awadallah (2011) point to the “singular failure” of the Arab world to develop a private sector that is independent, competitive and integrated into global markets. Although such harsh words are not warranted for all of Africa, they do make a valid general point: given Africa’s strong population growth and the necessary downsizing of the public sector in many countries, a vigorous private sector is the most important source of jobs for the young. Yet this analysis of 53 countries in Africa reveals that a lack of sufficient job creation is by far the biggest hurdle young Africans face today. Maximising the impact of a stronger private sector and economic growth on youth

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Box 6.1. Youth employment and unemployment in fragile states Why is youth unemployment a critical issue in fragile states? Grievances among the young are most likely to be expressed violently, if non-violent political channels are not adequate or responsive (USAID, 2006), and these grievances revolve around unemployment, involving considerations of both income and social cohesion. One in two young people who join a rebel movement cites unemployment as the main reason for doing so (World Bank, 2011b). In Liberia, which has suffered two civil wars since 1989, driven by a combustible mix of ethnic divisions, predatory elites, corruption, and competition for the profits from natural resources, today it is unemployment that is seen as a major risk to stability (International Crisis Group, 2011). Conflict in one country shaves an estimated 0.5 percentage points off the annual rate of growth in a neighbouring country (Collier et al., 2003). It can create a refugee population, disrupt trade, provoke an arms race, provide a haven for rebels, and itself become theatre of a new war. Source: International Network on Conflict and Fragility (INCAF), OECD Development Co-operation Directorate.

employment requires intelligent policies based on a sound understanding of the issues that the young face in finding, and holding on to, decent employment opportunities. This chapter aims to make a contribution by painting a picture of youth in employment and unemployment, the needs they have and the obstacles they face.

How to read this report Africa’s youth employment challenges are as diverse as the continent itself. The poorest countries have very low unemployment rates alongside a large informal sector that employs up to 90% of the working age population. Most of Africa’s MICs, on the other hand, suffer from very high youth unemployment rates. Their formal sectors are bigger than those in the poorest countries and employ a large share of the population, but at the same time their informal sectors are relatively smaller and do not absorb young workers as they do in poor countries. To account for these differences this report will use the low-income (LIC), lower middle-income (LMIC) and upper middle-income (UMIC) categories as the main lens of analysis wherever possible. Where data are insufficient or differences small, lower and upper middle-income countries will be looked at as a single middle-income country (MIC) category. There are many concepts used to analyse youth employment and they can be confusing. Figure 6.2. is intended to serve as a “Rosetta stone”, or translation tool, for this report, by making the various definitions used in labour market analysis comparable with one another. Then the definitions are detailed for each labour market concept used in this report, which concludes with an explanation of the data used.

Labour market definitions For the purposes of labour market analysis, young people aged between 15 and 24 are considered as Youth. Young people under 15 fall under the ILO’s child labour convention and should not be working. Aged above 24, young people are considered adults. In most systems young people can have concluded secondary and tertiary education of four years or less at this age and have entered the workforce. For most African countries measures of youth in employment are more relevant than

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Figure 6.2. The Rosetta Stone for labour markets 1. Labour Force Status

2. Time Use

3. Employment Status

4. Working?

5. Job Quality

In the labour force

Full-time worker

Wage employed

Employed

Wage employment

Self-employed Contributing family worker / unpaid worker

Part-time worker

Vulnerable employment 2

Voluntary part-time employed

6. Formality

Formal

Informal

Involuntary = Underemployed Out of the labour force

Job seeker

Unemployed

Inactivity or housework

Discouraged

Broad Unemployment

NEET*

Inactive In education

Student

Student

*NEET: Not in Employment, Education, or Training. Source: Authors' illustration. 12http://dx.doi.org/10.1787/888932600298

measures of youth not in employment. Among the poor, few can afford not to be employed. Instead, underemployment, vulnerable employment and working poverty are widespread. Focusing on the unemployment rate fails to take into account this reality. It implicitly assumes that those in work are materially better off than the unemployed. In most African countries, however, this assumption does not hold. In fact, the unemployed are less likely to suffer from poverty than many self-employed or underemployed. Another reason to be sceptical of the unemployment rate as the main measure of negative labour market outcomes is that it excludes many young people who are not in employment, even though they would be ready to work, but have given up looking for a job. These discouraged young people are often worse off than the unemployed and should be in the forefront of policy makers’ minds. As an alternative, the NEET rate of youth, which counts all youth who are not in employment, education, or training as a proportion of the total youth population, is suggested. Measures of young people who are not in employment. The youth unemployment rate is a measure of the unutilised labour supply and of the difficulty of finding work. It is calculated on the basis of the number of persons who, during the specified short reference period, were simultaneously: a) without work; b) currently available for work; and c) seeking work, as a percentage of the total labour force (ILO). It is a useful measure in high and middle-income countries, but less so in poor countries, where few of the young can afford to be unemployed. Even in better-off countries, the youth unemployment rate does not provide a full account of the situation of young people out of work since it does not take into consideration the discouraged, who have given up looking for employment. They are often worse off than the unemployed who are still looking. The discouraged worker rate of youth is similar to the youth unemployment rate, but

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focuses on those young people that have given up their job search. It measures the difficulty of finding work and the underutilisation of labour supply. It is calculated on the basis of the number of persons who, during the specified short reference period, were simultaneously: a) without work; b) currently available for work, but c) not actively seeking work, as a percentage of the youth labour force. In standard labour accounting the discouraged are not considered part of the labour force. This is unfortunate. Often discouraged youth are poor and disconnected from labour markets. Others are well educated but have given up the search for a job that rewards their qualifications. For South Africa it has been shown that the rate of discouragement is positively correlated to the rate of unemployment (Kingdon and Knight, 2004). Areas with the highest unemployment also have high rates of discouragement as the young see no hope of finding a job there. The relaxed, or broad, youth unemployment rate adds the discouraged worker rate of youth to the youth unemployment rate and expands the measure of the labour force by the number of discouraged youth. It is a broader measure of youth out of work and underutilisation of the labour supply than the traditional youth unemployment rate. The youth labour force participation rate measures the level of economic activity among the youth population. It is measured as the sum of all young persons who are employed or unemployed, i.e. looking for work, as a percentage of the youth population. Young people not in the labour force are either students or inactive, i.e. not looking for work. The youth labour force participation rate is lower in countries with higher income where many young people are in education. It also reflects cultural attitudes in countries where the labour force participation rate of young women is very low. It tends to be higher in poorer countries, where school enrolment is low and many of the young have to contribute to family income through economic activity. It suffers from the same shortcomings as the youth unemployment rate because the discouraged are not counted in the labour force. Youth out of the labour force is the sum of all young persons who are neither employed nor unemployed as a percentage of the youth population, except for students. This measure includes the discouraged young and those not able to take up employment for health, family reasons, or other reasons. The NEET rate of youth is an alternative indicator to the youth unemployment rate, measuring the sum of young people not in employment, education or training as a proportion of the entire age category. A young person is considered NEET if he or she has left the school system and is not employed or in continuing education. Thus the NEET include unemployed and discouraged young people as well as those who are considered to be out of the labour force or inactive (OECD, 2010). Measures of employed youth. The youth employment rate is a measure of the economically productive youth population and the ease of finding work. It is calculated as the sum of youth in all types of employment as a share of the labour force. The distribution of youth by employment status measures the composition of the types of employment among the employed youth population. The status groups are separated by the types of economic risk they represent and the amount of time spent working. Employment data based on the Gallup World Poll provide measures of the following employment statuses: • full-time wage employment • full-time self-employment • full-time unpaid employment (usually in family farming and business) • part-time employment (voluntary) • underemployment (involuntary part-time employment)

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The vulnerable employment rate of youth measures the share of young own-account workers and contributing family workers in total youth employment3. Vulnerable employment is a measure of people who are employed under relatively precarious circumstances as indicated by the status in employment. Because contributing family workers and ownaccount workers are less likely to have formal work arrangements, access to benefits or social protection programmes, and are more “at risk” to economic cycles, these are the statuses categorised as “vulnerable”. There is a strong connection between vulnerable employment and poverty: if the proportion of vulnerable workers is sizeable, it may be an indication of widespread poverty. The connection arises because workers in the vulnerable categories lack the social protection and safety nets to guard against times of low economic demand and are often incapable of generating sufficient savings for themselves and their families to carry them over these times. It should be remembered that the indicator has its limitations; some wage and salary workers might also carry high economic risk and some own-account workers might be quite well-off and not vulnerable at all. The rate of youth in underemployment is a measure of exclusion and the difficulty of finding a job. It is calculated as the share of young people who are involuntary part-time workers, i.e. have a part-time occupation, but want to work full time and cannot find fulltime work. In addition to measuring inefficiencies in the labour market it shines a light on exclusion and poverty because many of the underemployed are poor. Better-off youth would be likely to spend some time in unemployment, investing in finding a better fulltime job. Most youth in underemployment also have lower earnings than youth in full-time employment. The rate of youth in working poverty measures deprivation and work that is not decent. It is calculated as the rate of young people in employment living below a poverty line. The ILO uses the international poverty line of USD 1.25 per day per person. For the Gallup World Poll data a food insecurity line is constructed based on the question: “Over the past year, how often, if ever, have you or your family gone without enough food to eat?” Respondents who answer “several times” are considered moderately food insecure. Respondents answering “many times” or “always” are considered severely food insecure. Working poverty based on food insecurity is then measured as the share of the employed who report being moderately or severely food insecure.

Data Data on labour markets are notoriously difficult to obtain in Africa. Unemployment registers exist in some countries, but are often confined to urban areas and are not comprehensive. A country survey for this report has shown that in 23 out of 33 countries young people can register as unemployed, but only in ten countries is this service available to, or used by, more than 50% of unemployed youth. Only a few countries offer unemployment benefits with registration at such a service. Given this low coverage of unemployment registration, surveys are the only reliable and comprehensive source of labour market information in African countries. Labour force surveys (LFSs) are rare in Africa. Some countries, such as South Africa, Egypt, Tunisia and Morocco have regular LFSs that report with high detail and good coverage of the country on the situation of young people in the labour market. In other countries LFSs are more sporadic. A background paper for this report analyses 16 African LFS from 2002 to 2007. The most comprehensive depositories of labour market data are the ILO’s LABORSTA and Key Indicators of the Labour Market (KILM) databases that compile information from national sources for all available countries. KILM also provides estimates for a large range of indicators, for which national data are not available, based on the ILO’s TRENDS model4.

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This model has been developed for the ILO’s annual employment outlook reports. For this report data are used from available LFSs and from the TRENDS model. In addition to these longstanding sources, analysis is based on a subsample of the Gallup World Poll. Since 2005, Gallup has been conducting its World Poll in over 150 countries around the world. Coverage of Africa has been fairly comprehensive since the beginning of the project. Between 2008 and 2010, 39 African countries and territories were covered. The wide, frequent and very recent coverage are the main advantages of labour market data collected in the framework of the poll. The drawback is the sample size of about 1 000 respondents per country or territory. All samples are probability-based and nationally representative of the resident population aged 15 and older, but do not deliver the same precision as LFSs that often have sample sizes of 20 000 or more. Nevertheless, the results for the subsamples of young people (aged 15-24) are indicative at country level and representative at the level of country groupings. In addition, Gallup World Poll data combine labour market data with a range of other questions on opinions and subjective well-being that make it possible to explore the relationship between employment status and well-being, as well as the perception of obstacles and opportunities to job search and business success. Gallup World Poll uses the same labour market module in all countries, which makes it possible to distinguish between those who are full-time wage-employed by an employer, full-time self-employed, unpaid work (which can largely be assumed to be as family workers), part-time workers who do not want to work more, underemployed (i.e. part-time workers who want to work more), as well as the unemployed, the discouraged and those out of the labour force. Additional dimensions available are occupation groups, educational status and the region (rural, small settlements, cities and suburban areas) where respondents live. The module is well developed to distinguish work for family and external employers and agricultural work from other household activities using a set of screening questions. Unlike LFSs, the Gallup World Poll does not collect standard informal sector information, such as information on the contractual status of employees, the size of the enterprise they are with, or, if self-employed, whether taxes are being paid on the business revenue. The “vulnerable employment” category (self-employed5, contributing family workers, part-time and underemployed) is therefore used to approximate informal employment.5 Although the relationship is not perfect, the principle underlying both concepts is similar: workers in unprotected forms of employment, with low productivity and high risk of poverty.

Youth in African labour markets Too many bad jobs in poor countries, too few jobs in middle income countries Africa faces a range of youth employment challenges. In poorer countries most young people work, in better-off countries more are out of work than in work. Figure 6.3. shows that in LICs 41% of young people are working. Only about one third of youth in LICs are fulltime students. In MICs about half of 15-24 year olds are students and fewer young people are working than in LICs. However, NEET rates are higher in better-off countries. In UMICs, 31% of the young are NEET, compared to only 22% who are working. In lower middle-income countries the shares of youth in NEET and working are almost the same with 27% and 26%. In LICs, about one quarter of the young (26%) are NEET, making it the smallest group in these countries.

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However, for those young people who do have a job, the quality of employment is much higher in MICs. In LICs only 17% of working youth (7% of all youth) are full-time employees, working for an employer. All the rest of the working young are in vulnerable employment, either self-employed, unpaid family workers, part-time employed or underemployed, meaning that they work less than full time but want to work full time. The proportion of young people in vulnerable employment is much smaller in MICs, while the proportion of youth who work for an employer is bigger. In LMICs 36% of working youth (9% of all youth) work full time for an employer. In UMICs this share is 52 % (12% of all youth).

Figure 6.3. Youth time use by country income group (2010) Student Inactive Discouraged Unemployed Underemployed Part-time employee Unpaid workers Full-time self-employed Full-time wage-employed

41% Working

31% NEET 22% Working 47% Student

20%

48% Student

40%

25% NEET

60%

34% Student

80%

27% NEET 26% Working

100%

0% LICs

LMICs

UMICs

Source: Authors’ calculations based on Gallup World Poll (2010). 12http://dx.doi.org/10.1787/888932600317

In all country groups more young people are discouraged than unemployed, suggesting that the youth employment challenge has been underestimated. In most labour market analyses the discouraged are not considered part of the labour force and are thus not counted among those in need of work. However, Figure 6.3. shows that focusing only on those counted as unemployed – because they are still looking for a job - underestimates the challenges faced by the young in labour markets. It excludes all those who have given up looking for a job, but are nevertheless inactive and not developing their skills or experience. The high rates of discouragement point to the severity of exclusion from labour markets that many young people face in Africa. As shown below, unemployed young people are on average betteroff, have more education and have a higher chance of finding employment than the discouraged. When young people are compared to adults, they emerge as overrepresented among the unemployed and the discouraged. Although they constitute around two fifths of the continent’s working age population, they make up three fifths of the total unemployed. This phenomenon is not specific to Africa. Youth-specific challenges such as school-towork transition are evident everywhere. However, in African MICs, the ratio of youth-toadult unemployment is often higher than in other parts of the world (Figure 6.4.). Among these, Southern African MICs have the highest unemployment rates for both the young and adults, whereas North African MICs have the highest youth-to-adult unemployment ratios.

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South Africa had a youth unemployment rate of 48% in 2009, compared to 19% for adults. Egypt, on the other hand, had a youth unemployment rate of 25% compared to only 4% for adults in 2007. Exceptions are poorer countries worldwide, which generally have much lower rates for both young people and adults. This is true in many poor countries of sub-Saharan Africa where adult unemployment is very low and not significantly different from youth unemployment.

Figure 6.4. Youth and adult unemployment6 % Youth unemployment (15-24) 60% South Africa

50%

Egypt

Ethiopia

OECD Tanzania

10%

EQUAL

Lesotho

Tunisia

30%

0%

Namibia

3 TIMES AS HIGH

40%

20%

2 TIMES AS HIGH

Ghana

East Asia

0%

10%

20%

30%

40%

50%

60%

% Adult unemployment (25-64) Source: ILO KILM, 7th Edition, 2011, authors' calculations. 12 http://dx.doi.org/10.1787/888932600336

Nevertheless, the employment challenge in MICs is not confined to youth; it reflects insufficient employment capacity in both the formal and the informal sectors. Figure 6.4. shows high youth unemployment, but also a strong correlation between youth and adult unemployment. Countries with higher youth unemployment also have higher adult unemployment. Figure 6.5. shows that employment rates of the working age population drop drastically as countries get richer, a pattern specific to Africa: other UMICs such as Brazil and China have much higher employment rates. Although the very high population growth in Africa certainly plays an important role in these results, the comparison reflects a specifically African “jobless” pattern of growth. Given that formal employment is higher in MICs than in LICs but overall employment much lower, Figure 6.5. points to the lack of informal employment opportunities in MICs as a bottleneck. Country level data suggest that youth employment is largely a problem of quality in LICs and one of quantity in MICs. Figure 6.6. shows five distinct types of labour markets for youth observable in Africa, based on GDP per capita, the level of wage employment (proxy for formal sector employment), vulnerable employment (proxy for informal sector employment) and NEET. The poorest countries have little wage employment, a large share of vulnerable employment and few youth in NEET. This group stretches from post-conflict states such as Liberia and Sierra Leone, where fewer than 5% of the out-of-school young were in full-time work for an employer in 2010, to countries such as Burkina Faso, Mauritania and Tanzania where this rate was just slightly higher and still below 10%. Working poverty among their youth in vulnerable employment is the biggest challenge in these countries. At the other end of the spectrum South Africa, Botswana and Algeria stand out for their low rates of vulnerable employment paired with very high NEET rates. Namibia is probably another member of this group, but not included in our sample. Morocco, Tunisia and Egypt follow the same general

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trend but have a better profile, with lower NEET and more wage employment than the group to the right, despite their lower GDP per capita. Senegal, Sudan and Djibouti represent the only stark deviation from the trend. Their NEET rates are high and vulnerable employment comparatively low at a level of GDP per capita that is correlated with much lower NEET and more vulnerable employment in other countries.

Figure 6.5. Employment rate to working age population (15-64) in Africa and comparators Africa

Benchmarks

80% 70% 60% 50% 40% 30% 20% 10% 0%

LICs

LMICs

UMICs

OECD

Brazil

China

Source: ILO KILM 7th Edition, 2011, authors' calculations. 12 http://dx.doi.org/10.1787/888932600355

Theory has it that where employment is quality constrained (work is available, but not of a high quality), unemployment would primarily be voluntary among those who can afford it. Where employment is quantity constrained (work of any sort is not available), however, the “bourgeois” hypothesis of unemployment no longer holds. Where work opportunities abound, unemployment would be freely chosen by those who can afford to forego an immediate work opportunity in a low-paying or low-quality environment and invest time in searching or queuing for a better job. With this type of unemployment in mind, Myrdal (1968) wrote: “unemployment is primarily a bourgeois problem and is most pronounced among those who have been accustomed to drawing support from their families – persons with some education and new entrants into the labour force.” Such a view of unemployment evidently rests on the assumption that demand for labour is not quantity constrained. Those who do not have the wherewithal to be unemployed would have no problem in finding a job in the large informal sector which “acts as some kind of a low earnings absorbent sponge” (Turnham and Eröcal, 1990) and has no entry requirements. Where labour demand is lower than labour supply, however, young people in search of employment would not be able to find any work because there is no work and thus remain unemployed. Such unemployment would be involuntary and undesirable, not at all “bourgeois”. Using data on the material well-being of individuals support can be found for both quality and quantity constraints. Gallup World Poll data on food insecurity can be used as a measure for material well-being. Those who report having gone several times without enough food during the past year are considered moderately food insecure. Respondents who have gone without enough food many times or always are considered severely food insecure. Figure 6.7. shows the level of moderate and severe food insecurity by employment status for young people in LICs and in MICs. In LICs wage employed, students and unemployed youth have the

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Figure 6.6. Five types of labour markets for youth in Africa NEET

Vulnerable Employment

% Youth (15-24) who are not in school 100%

Wage Employment

GDP per capita (right axis) GDP per capita (2005 PPP USD; 2008-2010 avg) 14,000

90%

12,000

80%

10,000

70% 60%

8,000

50% 6,000

40% 30%

4,000

20%

2,000

10%

0 S o A lg ut e r h ia A Bo fric tsw a an a

Ug an d Gh a an Ke a ny Ni a Ca geri m a er oo n Se ne ga Su l da Dj n ib ou ti M or oc co Eg yp Tu t ni sia

Li

be ri Ni a ge r Si er C ra AR Le on e M Co al Bu mo i rk ro in s aF as o Ch Ta ad n M zan au ia r it an ia

0%

Source: Authors' calculations based on Gallup World Poll (2010) and World Bank (2011a). 12 http://dx.doi.org/10.1787/888932600374

lowest food insecurity rates. Youth in vulnerable employment categories have the highest food insecurity. Discouraged and inactive youth have much higher food poverty rates than the unemployed but these are still lower than those of contributing family workers. In countries with higher per capita incomes the rankings among the better-off change dramatically. In MICs unemployed youth have the highest food insecurity rates, together with the underemployed. Unemployed youth in MICs are more likely to be food insecure than unemployed youth in LICs. Indeed, one reason for lower poverty among youth in NEET is that the poorest cannot afford not to work. Many of the poorest young must work to support themselves and their families and cannot go without income while searching for better job opportunities or being idle. Working poverty and unemployment rates are strongly negatively correlated in Africa, suggesting that many young people prefer unemployment over working poverty and will chose unemployment in the hope of finding a better job when they can afford it. Yet structural links are at work too. As countries grow richer low-skilled jobs disappear and the informal sector faces increasing demand constraints. As countries grow richer their economies often become more competitive and capital-intensive, shifting jobs away from the low-skilled to the semi and highly-skilled. At the same time the growing middle class increasingly demands higher quality goods, which puts pressure on many informal sector producers who often offer goods of lower quality. Surviving in the informal sector thus gets tougher (i.e. more people fall out of the informal sector into unemployment), but returns are higher for those who are successful. The following sections take a closer look at youth in employment and those out of employment.

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Who are the working youth in Africa? This section looks at the main characteristics of youth in employment and the characteristics that distinguish the young in wage employment from those in vulnerable employment.

Figure 6.7. Moderately and severely food insecure by employment status and country income level Moderately food insecure 60%

Severely food insecure

A. LICs

40%

20%

60%

al To t

t en ud

rf ou ab

St

ce or

ge ra ou sc Ou

to

Un

fl

Di

Un

de

d

ed em

pl re

m

Pa

pl

oy

oy

ed

e t im r t-

s er rk wo

Un

Se

pa

l f-

id

em

Em

pl

pl

oy

oy

ed

ee

0%

B. MICs

40%

20%

al To t

t en ud St

ce ab fl

to Ou

Di

sc

ou

ou

rf

ra

or

ge

d

ed em Un

pl m re Un

de

pl

oy

oy

ed

e t im r tPa

s er rk wo

Un

pa

id

pl em Se

l f-

Em

pl

oy

oy

ed

ee

0%

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600393

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“Good” jobs vs. “bad” jobs Good jobs must serve to translate economic growth into material well-being. Yet for most of the working young in Africa this link is broken. The concern with employment stems primarily from a concern for the material well-being of young people. The assumption behind calling for jobs for Africa’s youth is that jobs are good and allow young people to make a living, provide for their family and build a stable foundation for professional growth. Yet a closer look at most types of youth employment, and employment in Africa in general, reveals that only a very few jobs meet these assumptions. Working poverty, vulnerable employment and underemployment abound among Africa’s youth and across all occupations. The ILO estimates that across a sample of 24 African countries 49% of working young people live on less than USD 1.25 a day and 73% live on less than USD 2 per day. Using food insecurity as a measure of material well-being, Figure 6.7. showed similar results. Across 22 countries, 41% of young people in work are food insecure. The figure for young people in vulnerable employment in LICs who are food insecure is 50%: 15% are even severely food insecure, meaning that they have gone without food many times during the past year. Figure 6.7. also showed that many among the young people in work are worse off than those still in school or in NEET. Job quality is closely linked to employment status. High job quality is associated with fulltime wage employment, low job quality with vulnerable employment and underemployment. In terms of material well-being, working conditions and security, the best employment status to have is full-time wage employment for an employer. These young people have the lowest food insecurity rates and the highest rates of life satisfaction. Other types of employment, such as self-employment and contributing family work, are much more precarious, linked to higher poverty and poorer working conditions, and are therefore summarised as vulnerable employment. The young in vulnerable employment lack the social protection and safety nets to guard against times of low economic demand and are often incapable of generating sufficient savings for themselves and their families to offset these times. The third type of employment status is underemployment. The underemployed face exclusion from labour markets, and are unable to use their full labour capacity productively. They have a part-time occupation, but want to work full time and cannot find full-time work. Better-off young might well spend some time in unemployment, investing that time in finding a better full-time job. Most young people in underemployment also have lower earnings than those in full-time employment. In most African countries vulnerable employment and informality are closely linked. Informal employment comes in two forms: informal employment in the informal sector (i.e. in micro-enterprises and other non-registered businesses7) and informal employment in a formal firm (i.e. employment without a contract and social protection in enterprises with five employees or more). Informal sector employment is the dominant form in most of sub-Saharan Africa. Heintz and Valodia (2008) find that self-employment of various kinds is the predominant form of informal employment, accounting for four-fifths of informal employment in Kenya, Ghana, Mali and Madagascar. Vulnerable employment and informal employment are thus closely linked. Despite the close link between vulnerable employment and informal employment, informality needs to be considered separately from employment status. This is in part because some informal own-account workers might be quite well-off and not vulnerable at all. A small proportion of informal firms are quite successful, enjoying high productivity and growth rates. Such entrepreneurs actively choose informality to avoid paying taxes and complying with regulations, and also to opt out of social insurance schemes and other public services that they consider to be of low quality (Jütting and Huitfeldt, 2009, Perry et

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al.,2007; Maloney, 2004; Jütting et al., 2008). Although formality and participation in social protection should generally be encouraged, successful informal entrepreneurs, especially among the young, can provide many lessons for creating jobs for the young. On the other hand, where informal employment in the formal sector is a widespread practice, wage and salary workers might carry high economic risk and wage employment is thus no longer identical with good jobs. This is the case in some middle income countries: Charmes (2009) finds paid employment accounts for 65% of informal employment in Egypt and 79% in South Africa during the 2000s, up from 50% and 75% respectively during the 1990s. De Vreyer and Roubaud (2012) come to similar findings for urban West Africa in the early 2000s, where informal employment accounted for 40% of wage employment. In MICs and some urban areas, vulnerable employment is thus still a good measure of bad jobs, but tends to underestimate the full extent of bad jobs in the economy. Vulnerable employment is the most prevalent form of youth employment in most African countries. Only upper middle income countries have more wage employment. According to Gallup World Poll data, in 2010, 75% of the working young were in vulnerable employment in low income countries, and 57% in lower middle income countries. In upper middle income countries, 26% of working youth are in vulnerable employment. Among the countries in the LFS analysis, Mali has the highest share of vulnerable youth employment with 95%, South Africa the lowest with 12% (Table 6.1.).

Table 6.1. Wage employment and vulnerable employment among Africa’s working young Country

Wage employment

Self-employment

Contributing family work

Other

Total

Vulnerable employment 8 Full-time or voluntary part-time

Gallup World Poll (2009/10) LICs LMICs UMICs

24.7 43.0 73.6

43.2 43.2 23.3

32.1 13.8 3.1

0 0 0

62.8 20.1 10.1 64.9 17.9 13.3 14.9 5.4 72.6 27.7 12.3 84.8 8.0 14.0

7.2 55.3 49.1 4.1 24.1 26.2 18.9 41.6 17 16.8 41.7 7.09 9.0 20.9

29.9 17.8 36.3 31.0 58.0 50.4 56.0 53.0 8.5 55.5 46.0 5.9 20.2 63.6

0.1 7.5 4.2 0 0 10.2 10.3 0 1.9 0 0 2.1 62.8 1.6

100 100 100

49.9 25.4 35.1 21.9 10.3 16.1

LFS (2002-2007) Botswana Congo DR Congo Egypt Ethiopia Ghana Malawi Mali Nigeria Rwanda Senegal South Africa Tanzania Uganda

100 100 100 100 100 100 100 100 100 100 100 100 100 100

35.7 72.5 85.4 35.1 82.1 75.6 74.9 94.6 25.5 72.3 88 11.8 28.5 84.4

Shows the distribution of wage and vulnerable employment among young people who are working or NEET, excluding students, by education, gender, rural and urban living and country income level. On the right side the graph also shows the distribution of employment by age cohort.

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Underemployment

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Figure 6.8. Employment and its drivers Vulnerable Employment 70%

Wage Employment

Youth

All Ages

60% 50% 40% 30% 20% 10%

e( 15 -2 e ( 4) 25 A g -2 e ( 9) 30 Ag -3 4 ) e( 35 Ag -39 ) e( 40 Ag - 4 4 e( ) 45 Ag - 49 ) e( 50 -6 4)

Ag

Ag

IC UM

C

IC

LM

LI

n

l ra

ba

Ur

Ru

e

e

al m

al

Fe

y

M

y

ar

1+

te

r ti

ar

ar

nd co

9

to

fu

ll

se

r im

uc

ar

ed

ye

al

8

rm

to

fo

1

No

sp

at

io

y

n

0%

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600412

Living in a rural area and having little education are good predictors for being in vulnerable employment. The average young worker in Africa lives in a rural area and works in family-based farming. Of youth in rural areas 79% are in vulnerable employment compared to 61% in urban areas: 72% have no, or only some, primary education. Among working young people who have no education 90% are in vulnerable employment. For those with secondary education the proportion is 70% and falls to 55% for those with at least one year of tertiary education.9

Box 6.2. Child labour and working poverty Child labour is still a pervasive phenomenon which conditions the life of future generations. It is estimated that 60% of child labour in the world is in agriculture, and especially in its most hazardous forms (ILO, 2011a). Child labourers of today are likely to become the unskilled youth of tomorrow. They find it harder to get jobs, start their own businesses or run productive farms. They are less able to provide for their families, they put their own children to work to meet basic household needs, and the cycle of poverty continues. The elimination of child labour is fundamental to promoting better employment prospects for youth. Children need time and energy to participate fully in relevant and good quality education to become skilled youth able to meet the demands of the labour market or become successful entrepreneurs. They will be more likely to have higher incomes as youth and adults through increased productivity as producers or employees. This is in part because as educated producers, they will be more likely and able to innovate, adopt new technologies and allocate resources efficiently.

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The strongest predictors for job quality and wage level are education and the country’s income level Multivariate analysis of both Gallup World Poll (Annex 2) and LFS data (AfDB, 2012) reveals that the strength of a country’s economy and the level of education are strong predictors for being in wage employment rather than vulnerable employment and for having a higher wage. The share of wage employment increases with education and is much higher among university educated youth and adults than among those with no or little education. The most powerful predictor for being in vulnerable employment is working in farming. Everything else being equal, not working in farming has a stronger influence on the likelihood of being wage employed than having tertiary education. This result underlines the very small role that commercial farming plays in employment in most of Africa compared to traditional farming. Women are less likely to work than men, but among working women vulnerable employment is more frequent than among working men. Education has a stronger positive impact on women than on men.

Youth employment by sectors Understanding the types of work that young people undertake is important in identifying their role in the economy and how best to support them. Many barriers and obstacles that youth face are specific to the type of work they do. Young people in agriculture, for example, could be much more productive if they knew about better production methods or had access to important inputs such as tools and fertilisers. Equally important is better access to markets to sell their products, which often represents a big hurdle for agricultural producers in rural areas. Many young people in urban areas, on the other hand, work as street vendors or hawkers (see also Box 6.3.). They face very specific challenges such as credit constraints, of which their suppliers will take advantage in order to pocket most of the profits, or harassment by public officials who also want a share of their profits. Knowing where young people work can thus help policy makers to support them most effectively.

Figure 6.9. Where young Africans work Professional Worker, Manager, Teacher

Business Owner

Services

Construction & Manufacturing

Agriculture

Other

Sales

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% LICs

LMICs

UMICs

Africa Total

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600431

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While the average young worker in Africa is in family-based agriculture, other important occupations are services and sales and 13% are business owners. Manufacturing plays only a small role in LICs but is important in UMICs. According to Gallup World Poll data, the average young worker in Africa lives in a rural area and works in farming attached to the family: 38% of working youth in Africa are in agriculture. Yet this average changes dramatically with a country’s income level. In upper middle income countries only 4% of working youth are in farming – not far from the OECD average of 2%. Of African young people 20% work in services, including clerical work, transportation, repair and installation work, and 13% in sales, while 13% identify themselves as business owners. The proportion of business owners among the young increases significantly with a country’s level of economic development, in all probability reflecting better conditions for entrepreneurs. In upper middle income countries 20% of working youth are business owners, compared to 11% in low income countries (Figure 6.9.). Construction and manufacturing jobs account for only 8% of the working young across Africa and only 5% in low income countries. In upper middle income countries 14% of working young people are employed in construction and manufacturing.

Box 6.3. Street trading in Africa, a typical urban sales job Informal street trading accounts for a large proportion of new urban jobs in sub-Saharan Africa, the result of a combination of factors such as urbanisation, migration and economic development (Skinner, 2008). The main concerns of street traders relate to the right to a place to work and harassment by police, city officials and retail traders. Other worries have to do with the strong position of wholesale traders and access to capital. Often traders have to borrow from the wholesale traders at very high interest rates. The strengthening of organisations of street traders and their participation in urban planning are central to addressing these concerns. “Best practice” is found in Dar es Salaam (Tanzania) and Durban (South Africa), where street traders have been issued licences to operate. Associations of street traders have established good relationships with city authorities and specific infrastructure was set up in central locations. However, many street traders are not members of any organisation. Source: Jütting and Huitfeldt (2009).

Adults are more likely to be professional workers or business owners, reflecting higher entry requirements and scarcity of opportunity for youth (Figure 6.10.). The occupation category with the best income, status and education profile is that of professional worker. This includes all white collar professions, such as doctors, lawyers, teachers, accountants etc., as well as employees with executive functions in the private and public sectors. In Africa 12% of working adults fall into this category, compared to only 6% of youth. This gap partly reflects the higher entry requirements into this occupational category, often requiring tertiary education or several years of working experience. However, it also reflects a scarcity of these good jobs for young people compared to adults, as a result of reductions in the public sector workforce through lower recruitment. Business owners are also more likely to be found among adults than the young (17% versus 13%). Although the business owner category is largely made up of informal self-employment at low rates of productivity, the higher proportion of adults reflects entry barriers into self-employment in the form of capital requirements and the need for business expertise, skills and a network of contacts that are usually accumulated through working experience.

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Figure 6.10. Youth and adults by occupation Adults

Youth

40%

30%

20%

10%

0% Professional Worker or Manager

Business Owner

Services

Sales

Construction & Manufacturing

Agriculture

Other

Source: Gallup World Poll (2010), authors' calculations. 12 http://dx.doi.org/10.1787/888932600450

Who are the Unemployed, Discouraged and Inactive Youth in Africa? The NEET category is made up three distinct states of employment: unemployment; discouragement; and inactivity, or having left the labour force. Traditional labour market analysis counts the unemployed among the labour force, whereas the discouraged and inactive are considered to be outside it. • The unemployed are without work, actively looking for a job and able and willing to start work. • The discouraged are equally without work and able and willing to start work, but are not looking for a job. Most of them have given up or never even attempted to search for a job because they consider it futile. When asked the main reason why they are not working, almost a third of the discouraged young answer that they are unemployed (Figure 6.14.), clearly unaware of the labour analysts’ definition of unemployment. • Finally, the inactive are either not doing anything at all or pursuing activities that do not contribute directly to any economic activity, as work in a family enterprise or on a family farm would. Figure 6.11. shows the distribution of youth in unemployment, discouragement and inactivity among those that are working or NEET, excluding students, by education, gender, rural and urban living and country income level. On the right side the graph also shows the distribution of employment by age cohort10. Three important observations stand out: • First, unemployment increases with education, but discouragement and inactivity decrease. • Second, women have much higher rates of inactivity (i.e. not actively participating in economic activities, including agricultural work or work for a household enterprise), but similar rates of discouragement and unemployment. • Third, unemployment and discouragement are higher among younger cohorts than older ones, but the proportion of the inactive increases with age. The following three subsections take a closer look at each of these NEET categories and these observations.

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Figure 6.11. Who are the unemployed, discouraged and inactive youth in Africa? Inactive 70%

Discouraged

Unemployed

Youth

All Ages

60% 50% 40% 30% 20% 10%

s

e( 15 -2 e ( 4) 25 A g -2 e ( 9) 30 Ag -3 4 ) e( 35 3 Ag e ( 9) 40 Ag - 4 4 e( ) 45 Ag - 49 ) e( 50 -6 4) Ag

Ag

s

IC

UM

Cs

IC

LI

LM

l

n ba

ra

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Ru

e

e

al m

al

y ar

M

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1+

9

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co

nd

ar r im

sp

ar ye

8 to

1

No

fo

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al

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uc

at

io

y

n

0%

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600469

The unemployed This section takes a closer look at the unemployed by a number of characteristics, such as whether they live in rural or urban areas, their education and gender. Knowing more about the characteristics of the unemployed is important if their needs for support are to be understood. Unemployment is higher among urban youth. Most Africans live in rural areas and so do most of Africa’s young and most of the unemployed. However, among those who live in urban areas unemployment rates are higher than among the rural young. In some countries, the urban youth unemployment rate was estimated to be more than six times higher than the rate in rural areas (AfDB 2012, Figure 6). In multivariate analysis of the determinants of unemployment, the urban coefficient nearly always comes out as positive and significant (Annex 2 and AfDB, 2012). This higher rate of urban youth unemployment seems to be the result of migration by the young from the countryside to towns in the hope of better opportunities, increasing the young urban population as well as competition in the urban labour market. The proportion of young people as a proportion of the urban population tends to be slightly higher than their share of the rural population In Rwanda, 26% of the urban population are young, compared to 23% of the rural population. In Mali the equivalent statistics are 19% and 13% respectively (AfDB, 2012). A similar pattern holds for education: most unemployed young people have little education but the young who do have some education are more likely to be unemployed. Certainly most young unemployed have little education, because Africa’s overall education profile is very poor. However, unemployment rates tend to be higher among the educated than the uneducated. Young people with no education are more likely to be discouraged or working. While this pattern holds for almost all African countries, unemployment rates among the educated tend to be much higher in MICs than in LICs (Table 6.2.). The highest

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rates of unemployment among university graduates are found in North African countries and South Africa. In Tunisia the unemployment rate among university graduates in 2008 was 33% among men and 46% among women (Stampini and Verdier-Chouchane, 2011). In Egypt unemployment among university graduates was 34.2% in 2006. In South Africa it was 34.9% in 2007 (Table 6.2.). These high rates point at serious mismatch and school-to-work transition problems that will be discussed in more detail in the section on education later in this report.

Table 6.2. Youth unemployment by level of education (%) Data Source

Country

No education Basic education

Secondary education Vocational University/Tertiary

Gallup World Poll (2009/10)

Low Income Middle Income

7.9 22.7

12.1 17.5

15.9 29.5

.. ..

18.8 34.6

Botswana Congo DR Congo Egypt Ethiopia Ghana Malawi Mali Niger Nigeria Rwanda South Africa Senegal Tanzania Uganda

24.4 0.0 0.0 4.9 1.9 3.2 1.3 10.2 7.9 11.7 4.6 31.4 14.1 2.3 0.9

33.7 37.8 29.7 39.7 43.4 0.0 0.0 0.1 9.7 51.2 6.9 37.0 21.6 6.2 14.6 17.2 0.6 4.5 11.7 18.5 54.1 65.1 16.9 16.1 15.6 19.7 14.7 5.1 20.2 10.7 54.9 54.3 49.7 25.2 30.2 14.3 8.1 32.8 23.4 2.1 6.3 6.6

33.0 47.8 4.8 34.2 13.5 46.1 23.2 85.3

National surveys (2002-2007)

21.1 34.9 6.8 23.2 19.0

Source: Gallup World Poll (2009/10) and national household surveys, authors’ calculations.

In spite of their higher rates of unemployment, those with higher levels of education are more likely eventually to escape unemployment than those with lower levels of qualifications. As was seen in the preceding section, young people with a university education not only have the highest unemployment rates, they also have the highest rates of wage employment. In addition, analysis of earnings provides evidence that those with higher level qualifications earn more when they are in employment (see annex 6.2.). Previous research (World Bank, 2008) has shown that, over time, as young people gain initial experience, higher education increases the employment incidence and enhances occupational mobility. Figure 6.12. and Figure 6.13. show that unemployment and discouragement rates among those with secondary and tertiary education are much lower for those over 30 than for younger cohorts, suggesting that most unemployment, and even discouragement, among educated youth is largely a transitory phenomenon.

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Figure 6.12. Employment status by education and age cohort in LICs Unemployed

Underemployed

Part-time

4 -6 50

9

4 -6 50

9 -4 45

-6 50

-4 45

-4 40

-3 35

-3 30

4

0% -4

0%

40

10%

9

10%

-3

20%

35

20%

4

30%

4

40%

30%

9

40%

4

50%

9

50%

4

70% 60%

9

70% 60%

-3

80%

30

80%

9

90%

-2

90%

25

100%

-2

-4

15 -

1+ tertiary

100%

25

Full-time

45

4 -6 50

-4 45

-4 40

-3 35

-3 30

-2 25

9 to full secondary

4

0% -4

10%

0%

40

10%

24

20%

9

20%

4

30%

9

30%

4

40%

9

50% 40%

24

50%

9

60%

-3

60%

4

70%

35

80%

70%

-3

80%

30

90%

9

90%

-2

100%

25

100%

15 -

Self-employed

1 to 8 years primary

No formal education

15 -2 4

Unpaid workers

15 -2 4

Discouraged

Source: Authors'calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600488

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Figure 6.13. Employment status by education and age cohort in MICs Unemployed

Underemployed

Part-time

4 -6 50

9 9

4 -6 50

-6 50

-4 45

-4 40

-3 35

-3 30

-4

0% 45

0%

4

10%

-4

20%

10%

40

20%

9

30%

-3

30%

35

40%

4

40%

-3

50%

30

60%

50%

-2 9

60%

25

70%

4

70%

9

80%

4

90%

80%

9

90%

4

100%

-2 9

-4

15 -

1+ tertiary

100%

25

Full-time

45

4 -6 50

-4 45

-4 40

-3 35

-3 30

-2 25

9 to full secondary

4

0% -4

0%

9

10%

40

10%

-3

20%

35

30%

20%

4

30%

24

40%

9

40%

4

50%

9

50%

4

60%

9

70% 60%

24

70%

-3

80%

30

80%

9

90%

-2

100%

90%

25

100%

15 -

Self-employed

1 to 8 years primary

No formal education

15 -2 4

Unpaid workers

15 -2 4

Discouraged

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600507

A closer look at the educated unemployed reveals that the unemployment rate varies by type of educational degree. Among university educated youth in Tunisia the unemployment rate is lowest for engineers (24.5%), and highest for graduates in economics, management and law (47.1%) and in social sciences (43.2%) (Stampini and Verdier-Chouchane, 2011). Assuming similar patterns across other countries the high numbers of students choosing to enter these fields with high unemployment rates are surprising. Unemployment among educated youth thus fits Myrdal’s bill of “bourgeois” unemployment, but is also the result of important mismatches between the education on

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offer and what is in demand from employers. The better educated often come from betteroff families and can afford to stay unemployed while waiting (“queuing”) for a good job, often in the public sector, behaviour frequently observed in North African countries, but also in Ethiopia (Serneels, 2004) and Senegal. The strong link between field of study and unemployment rate, however, suggests a major mismatch. Unemployment is slightly higher among women than men. There are considerable variations among countries. Across the Gallup World Poll sample the unemployment rate among young women is 18% compared to 15% for men. This masks strong variations among countries and regions. Across sub-Saharan Africa the unemployment rate for women is 16% compared to 14% for men. In North Africa, however, 31% of women are unemployed compared to 19% of men. In some countries unemployment rates among women are much lower than among men. According to LFS data, the unemployment rate among women in Rwanda is only 60% that of men and in Niger this ratio is 50%. As appears from the following sections, however, women are more likely to be discouraged or out of the labour force than men.

The discouraged Discouraged young people are more disadvantaged than the unemployed, have less education, higher food insecurity and are more likely to be women. Across the Gallup World Poll sample, 71% of the discouraged young have never been to school or have had only primary education. The impact of education on discouragement is opposite to that on unemployment. For many African countries the more education young people have, the better their chances of not being discouraged (Figure 6.12. and Figure 6.13.). The effect is even slightly stronger for women. In LICs food insecurity among discouraged youth is 52% compared to 34% among those who are unemployed (Figure 6.7.). Like unemployment, discouragement is more frequent among women, and young women are more likely to be among the discouraged than young men. Across the Gallup World Poll sample women are on average 20% more likely to be discouraged than men. Discouragement generally results from labour market exclusion. The discouraged are more likely than the unemployed to say that they do not know where, or how, to find work, or that they lack employers’ requirements (Figure 6.14.), indicating that they have given up their job search as a reaction to rejection, or have never actively searched because they see little chance of success. Kingdon and Knight (2000) find that in South Africa discouragement is negatively correlated with the likelihood of finding employment, given characteristics such as education and location. The lower the chance of finding a job, the higher the rate of discouragement. The same holds for the Gallup World Poll sample. Multivariate analysis of the determinants of being discouraged, rather than unemployed, produces negative coefficients for education as well as the share of wage employed given education and location. In other words, the more education young people have, and the higher the likelihood of finding wage employment, the less likely it is that they will be discouraged. Discouragement is higher among urban youth. Like all young Africans, discouraged young people are more likely to live in a rural area. However, when the impact of education is taken into account urban youth are more likely to be discouraged than rural youth. There seem to be two explanations: more competitive urban labour markets, and higher average income in urban areas. First, many young people come to urban areas in the hope of finding work, making urban labour markets more competitive and the finding of employment more difficult. The result is greater discouragement among young people who have not succeeded in finding employment in spite of their search. Second, average income in urban areas is significantly higher than in rural areas. Based on the correlation between higher incomes and higher inactivity rates described in previous sections, urban areas exhibit higher rates of unemployment and inactivity because more of the young can afford it than in rural areas.

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Figure 6.14. Unemployed versus NEET: self-reported reasons for not working Unemployed

Discouraged

45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Believe no suitable Cannot find work available suitable work (in an area relevant to one's skills/capacities)

Dont know how I am unemployed Lack employer's or where to seek work requirements (qualifications, training, experience, age, etc.)

Other

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600526

Although young people with higher education are less likely to be discouraged, a significant problem exists. Across most countries only 3% of the discouraged have tertiary education. Nevertheless the discouraged account for over 10% of the university educated in the labour market. Young people with higher education are even more likely to point to lacking the skills required by employers as the reason for being out of work than discouraged youth with less education (Figure 6.15.). Clearly, the young with university education have higher expectations about a job than those who have never been to school. But ineffective education that does not provide the young with the skills sought by employers seems to be a significant problem at all levels of education. Discouraged youth with higher educational qualifications need specific support, helping them to acquire job-relevant skills and to apply the educational training they have obtained in a way that can be useful to them in the labour market or as entrepreneurs. Although they often have the lowest proportions of entrepreneurial aspirations, many highly educated young could become robust entrepreneurs if given the motivation and financial possibilities. Subsequent sections will look into the issue of entrepreneurship in more detail.

The inactive Among the NEET inactive youth are the worst off. Their average education is the lowest of all NEET. Indeed, 38% have no education at all and another 40% have some or full primary education only. Of inactive youth 47% have gone without food several times or more during the last year. Inactive youth are 40% more likely than the average young African to live in a rural area. Only those who work for a family business without pay (contributing family workers) have a worse record across these characteristics.

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www.africaneconomicoutlook.org/en/in-depth/Youth_Employment

Figure 6.15. Self-reported reasons for not working among discouraged youth by educational achievement No formal education

1 to 8 years primary

9 to full secondary

1+ tertiary

40%

30%

20%

10%

0% Believe no suitable Cannot find work available suitable work (in an area relevant to one's skills/capacities)

Dont know how I am unemployed Lack employer's or where to seek work requirements (qualifications, training, experience, age, etc.)

Other

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600545

Inactive youth are disproportionately women. On average there are three inactive women for each inactive man. Figure 6.16. shows the distribution of NEET categories by age and gender. The share of women who leave the labour force seems to be driving the differences observed across the other employment categories. Inactive youth are unlikely to make their way back into the labour market. Inactivity often starts immediately after the end of schooling and increases with age. It is the only NEET category for which the adult rate exceeds the youth rate.

Figure 6.16. Transition pathways by male and female youth (15-30) In Education

Not in Labor Force (NEET)

Unemployed (NEET)

Discouraged (NEET)

Vulnerable employed

Wage employed

A. Men

B. Women

100%

100%

90%

90%

80%

80%

70%

70%

60%

60%

50%

50%

40%

40%

30%

30%

20%

20%

10%

10%

0% Age

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

0% Age

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Source: Authors' calculations based on Gallup World Poll (2010). 12 http://dx.doi.org/10.1787/888932600564

© AfDB, OECD, UNDP, UNECA 2012

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6. Promoting Youth Employment

Box 6.4.Women’s struggle to join the labour market Despite a “feminisation of the labour force” that has taken place in the last decades, women still face enormous obstacles in entering the labour market. Generally, in less developed countries, young women experience higher NEET rates than young men. In African countries 20% of young men aged 15-24 are NEETs while the rate for young women in the same age group is 35%. Although the female African NEET rate is lower than that observed in other countries such as India and Turkey, where it reaches 60% and 50% respectively, it still exceeds the rates observed in other countries, such as Brazil and Mexico, and is much higher than that seen in European countries. In many African countries, the lack of qualifications still represents a critical barrier for women’s employment, especially in good quality jobs. In spite of significant improvements across the world, Western, Eastern and Central African countries present the lowest participation rates in primary and secondary education, as well as the largest gender gaps in education (OECD, 2012b). The figure in this box shows that women with higher levels of education are less likely to be NEETs than women with less education both in North and Sub-Saharan African regions. Female

Male

A. North Africa

B. Sub-Saharan Africa NEETs Age Adolescent Young women Education No Education Primary Secondary Marital status Never married Married/Divorced/Widow

100%

80%

60%

40%

20%

0%

0%

20%

40%

60%

80%

100%

12 http://dx.doi.org/10.1787/888932605846

Discriminatory social institutions play an important role in shaping women’s employment outcomes. Early marriage, which disproportionately affects young girls in some countries in the region, decreases the chances that girls continue studying or engage in economic activities, as they usually became responsible for home tasks and the care of children (UNICEF, 2005). The figure in this box shows that both in North and Sub-Saharan African regions married women are more likely to be NEETs than unmarried women. Young girls are much more likely than young men to be married early and therefore look for more flexible jobs that they usually find in the informal sector. The rates of women in informal employment are higher than those for men across several world regions including Africa, being especially high in informal employment categories with lower earnings. The segmentation of women in the lowest categories of informal employment increases their risk of poverty and, because of the lack of social protection, increases their vulnerability (OECD, 2012b). Gender inequalities in education and employment can also have a negative intergenerational impact, as it has been well demonstrated that children are less likely to be educated or immunised if their mother has not been educated or is not in work (UNICEF, 2006). The figure in this box shows that the likelihood that girls will continue studying or engage in an economic activity decreases as they enter their early 20s. Adolescence is a decisive time for boys and girls everywhere. But in most African countries while adolescent boys enter the labour market, adolescent girls usually leave school, missing their chance to enter the labour force. For instance, a study done in Kenya on the transition from school to work in the 15-24 age group shows that the NEET rates for women increased as their age increases much more than for men (OECD, 2012b). In African countries there is a need for policies that tackle the specific barriers women face in the labour market and a need to address discriminatory social institutions which hold them back from realising their full potential. The failure to overcome the constraints which prevent women from entering the labour market can have lasting effects on poverty and social exclusion over the course of their lives.

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© AfDB, OECD, UNDP, UNECA 2012

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African Economic Outlook: Promoting Youth Employment

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