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«Comparative Study and ‘Outcome and Impact’ Analysis of Six Vocational Training Projects in West Africa Synthesis report based on six case ...»

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Some evaluations looked at effectiveness and impact (OICG) but most did not. MTS for instance was evaluated twice since 2006. The evaluators said MTS has had a significant impact on the needs of “school drop outs and illiterates” (remark: both groups are not the prime target group of MTS) without showing how the impact was measured.

None of the partners ask students/ trainees to evaluate the training. Participatory monitoring methods are not sufficiently or not at all applied.

3.5 Effectiveness

The main criteria for assessing effectiveness were:

• Perception whether choice of the field of training was right

• Utilisation of skills learned for income generation and

• Employment of graduates in field of training and quality of employment

• Income earned, coverage of basic needs by income earned and increase of income compared with the situation before training

Berufsbildung | Evaluierung

• Effectiveness of the different measures provided (skills training, counselling, etc.) • Achievement of project objectives Direct and indirect effects on communities are dealt with under chapter impact

Information and data on effectiveness comes from the following resources:

• Results of the comprehensive tracer study • Focus group discussions • Case studies For comments on the validity of the quantitative data see section methodologies.

3.5.1 Quantitative analysis Overall employment and skill utilisation rate The vast majority of graduates interviewed in the tracer study think that the choice of training was right.

–  –  –

According to the tracer study 70% of all graduates traced are employed and earn an income.

This percentage includes graduates working in their field of training and in any other field not related to training.

–  –  –

The highest employment rate (91%) has been recorded for the YOWDAST apprenticeship scheme, the lowest for MTS as a formal vocational school (56%). Both institutions/ projects are situated in the rural North East of Nigeria, the same consultant collected the data. The highest rate of unemployment has been recorded for MTS (32%) and SLOIC (26%), the lowest for YOWDAST (4%) and LOIC (10%).

Approximately 31% of the employed graduates are wage employed and approximately 69% are self-employed. The highest rate for wage employment has been recorded by VTF supported VTI. The highest rates for self-employment were documented for YOWDAST (91%) and LOIC (83%).

The employment records have to be seen in the context of each country and each location.

The following (external) factors are thought to influence the unemployment and employment

rates:

• The situation of the local labour market and market fluctuations

• The personal motivation of a graduate

• The educational background and prior skills of the trainees

• The economic and social background of the graduate and his/ her family

- Economic factor: People in absolute poverty can not be unemployed. They have to generate income for survival!

- Age factor: the older graduates are the higher the economic pressures for “self reliance” will be. According to case studies and interviews, many of the younger graduates below the age of 25 still live with their families and are supported by their families.

- Gender factor: marriage and pregnancies/ child care need to be taken in consideration when assessing the employment rate of women

• Livelihood patterns: in rural communities, the vast majority of the population is engaged in agriculture. Young people, particularly young men, do this rather by necessity than by choice, as rural livelihood does often not match with their aspirations Berufsbildung | Evaluierung The table below lists external supportive and hindering factors observed in urban and rural

locations:

–  –  –

More than half of the training locations are rural or semi-rural in character, where the majority of the population earns a livelihood through agriculture.

–  –  –

* in the case of LOIC this question was answered by graduates of all categories ** validity of number in question as many responses were invalid As said repeatedly, the quantitative analysis has some limitations. For instance it does not differentiate between full time employment and doing a job once in a while. Self-employment may mean that a tailor is running his/ her own business in the market place or working from home and doing sewing mainly for family members. Factors that may have influenced the

employment rate in some cases:

• Provision of tools and equipment for free (LOIC) or to a subsidised rate (YOWDAST) • Practice of combining training in agriculture and trade skills (LOIC) as a high percentage of graduates earns an income in agriculture and thus is utilising the skill • Selecting persons with a background of prior learning (amongst others) such as graduates of technical colleges (YOWDAST). Expectedly, such persons have a better chance to succeed in the market Number of persons that answered the question “Is your work related to your field of training?” The question Q10 “work related to training” was answered by persons employed (w/s) and in apprenticeship. It is assumed that all other categories do not work in the field of training. There might be a small percentage of persons in further education who work in their field of training besides going to school/college. This group is not considered in the analysis Includes both categories: “working” and “working just a bit” Berufsbildung | Evaluierung Quantitative analysis per gender





The employment rates per gender are the following:

–  –  –

The average employment rate of males is about 1.07 times higher than for females. The average unemployment rate for females is about 1.4 times higher than for males. This includes females who became pregnant after training and who take care of small children.

–  –  –

Differences also occur when comparing the employment status of male and female employed graduates. The overall percentage of wage employed males is 1.3 times higher than for females.

In the case of apprenticeship schemes, the differences are significant. This is an indication for substantially better wage employment opportunities for males, especially in the urban informal sector. This finding from the tracer study was confirmed in focus group discussions

Berufsbildung | Evaluierung

and through market observations. Women for instance have fewer opportunities extending their apprenticeships and working for someone else (see case studies OICG and YOWDAST).

An estimated 65% of all male graduates traced are thought to work in the field of training (see table 10). The estimated percentage of females is 56%. On average, the employment rate in the field of training is approximately 1.2 times higher for males. In one case (OICG), the difference between men and women is significant. In this case only 40% of the women are thought to work in the field of training while the rate of men lies at 83%.

3.5.2 Qualitative analysis of employment and income

The quality of employment has been assessed through FGD, case studies and the tracer study.

Main indicators used are:

• the place of business (working from home or owning a business) • the increase of income, coverage of basic needs, in some cases actual income earned • whether graduates are supported by parents or provide support Place of business

–  –  –

According to the data above a slight majority of the self-employed graduates works from home (58%). In the case of LOIC, the tracer study data on place of business may not be sufficiently valid (see different figures in case study report LOIC). Without consideration of LOIC data, 67% of the self-employed work from home. This is a clear majority and an indication that many of the self-employed rather work on “survival mode”. Case studies also

Berufsbildung | Evaluierung

show that the boundaries between self-employment and wage employment are fluid. A mason working as a daily labourer (contracted and paid on a daily basis) may say he is self-employed but in reality he is working for the same contractor. The percentage of self-employed women running a business on their own is relatively low. This result is supported by FGD where usually less than 20% of the participating women have established a business outside their home. This rate is even lower in urban contexts as business start-up costs (e.g. renting a shop) and the risks of business failures are substantially higher.

Income, coverage of basic needs

The effectiveness of project interventions on changes in the income situation and coverage of basic needs has been assessed quantitatively through the tracer study and qualitatively through

FGD. Indicators used were:

• the increase of income in % since graduation

• the coverage of basic needs in % through income generated in trade

• whether graduates are supported by parents or provide support Responses of graduates on increase of income and income coverage are by nature very subjective and strongly depend on the expectations of an individual. Some contradictions appeared in the analysis. In the case of OICG, the income coverage was rated very high (51% said their income covers 100% of basic needs), but FGD revealed a far less positive situation.

In Ganye (YOWDAST), the FGD gathered some young, quite successful entrepreneurs, all trained in the apprenticeship scheme of YOWDAST. None of them had rated the income coverage more than 75% as they expected their businesses to grow and to become more profitable.

The raw data of MTS and YOWDAST was checked during the main study, results were found largely logical. The income coverage of persons running a business outside the home and employing others was usually above 50% while home businesses ranked below 50%.

–  –  –

Please note: determination of basic needs is based on graduates’ subjective opinion.

Berufsbildung | Evaluierung A key finding of this study is that a majority of graduates interviewed and found working can not make a living from the trade alone. According to the tracer study 64% of the graduates (without OICG 73%) earn an income that covers their basic needs by 50% and below. Only 35% (without OICG 27%) cover their basic needs by 75% and above. One explanation is that a substantial number of graduates may still be in a learning situation (e.g. working as low paid apprentice or semi-skilled labour).

Another indicator used is the perceived change of income since graduation. 36% said their increase of income is 25% and below, 32% said their income increased by 50% and 30% said 75% and above. Differences are visible between men and women. While only 27% (without OICG 20%) of women asses their increase 75% and above the rate of men is 36% (without OICG 28%).

A high percentage of graduates either gets support from the family or needs to have another source of income. Considering that 67% of all graduates interviewed are between 20 and 29, this is not a totally surprising result. In industrialised countries, youth unemployment is almost twice the rate of people above 2919. Young people face more insecure employment situations and earn less.

FGD showed that women are more often affected by underemployment than men. If income levels are too low some women opted to learn another trade, often in apprenticeship (see text box below). Many underemployed women living in urban contexts compensate their low income with petty trade. Men do this for instance with unskilled contract work, e.g. on construction sites. Trading in the informal sector is sometimes a lucrative alternative to working in a trade with low income (cases with income-coverage of 75%). Graduates holding a senior secondary school (SSS) certificate often have aspirations that are difficult to meet with work in the informal sector. Some girls rather opt staying at home and trying to study something else (e.g. teaching). In general SSS graduates, typically enrolled in formal VTI, do have more career options than a school drop out. Some men gave up working in their trade as the payment was too low and tried to get into the military service or enrolled at another technical college in order to advance their certificates and enter the formal labour market (case MTS).

The tracer study and FGD showed that the vast majority of graduates living in rural areas compensate their income with agriculture. For many, this is a normal practice in rural livelihoods. FGD in Nigeria showed that almost 80% of the participants still earn their livelihood in agriculture, some by choice others by necessity. However, there are reported cases (e.g. Mattru Jong) where scarcity of land is forcing young males to seek alternative sources of livelihood. If they can not earn a living with their trade, they are forced to migrate.

As said above, too little is known about the living situation of those who migrated. Sometimes migration can trigger a success story. A woman from Ghana who graduated in catering migrated to Accra and worked for someone there. She returned with some saved money and now successfully runs her own business (VFT supported VTI).

Source OECD, unemployment statistics EU 19; 2009: Age group 20-29: 11.15% Age group 25-64: 6%.

–  –  –

Case 1: Graduates of computer class MTS, Garkida, Nigeria Elisabeth worked in a business centre in her home town after graduation in 2008. The income she received was very small and she felt cheated by the employer so she gave up the job. She has opted to work in tailoring from her home. The income is still small and irregular but she can earn something with her own hands. Elisabeth is living with her parents and helps her parents on the farm.



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