Jobs for young Africans: New data tool reveals trends red, flags

Africa Youth Employment Clock provides real-time insights into the employment status of individuals aged 15-35 across the continent. [iStockphoto] An estimated 23.6 million young Africans (aged 15-35) are unemployed - that's one in 22 (4.5 per cent). With this number projected to grow to 27 million by 2030, the need for jobs is critical. But the key to good policies for job creation is good data. Against this backdrop, the World Data Lab (a data enterprise producing estimates for spending and demography) and the Mastercard Foundation have launched the Africa Youth Employment Clock - a tool to monitor youth job growth and forecast youth employment trends until 2030. Moina Spooner, from The Conversation Africa, asked data scientist Katharina Fenz, who developed the methodology and data modelling for the clock, about their key findings and what they hope to achieve. Why the clock on youth employment and how does it work? The Africa Youth Employment Clock provides real-time insights into the employment status of individuals aged 15-35 across the continent. This means employment numbers are always changing, showing new predictions every day. This includes youth employment status and whether they're in education or training. The clock operates by aggregating and analysing labour market and education data from various sources to present a comprehensive picture of youth employment dynamics. The sources include national data and data from the International Labour Organisation. How far the data goes back depends on the available country data. We found and used consistent data for 54 African countries. If there were missing national data, we filled in the gaps using estimated values of known data points or regional averages. We chose the method that seemed best for each country's data. We also provide forecasts of youth employment trends across the continent until 2030. We do this by combining national data on the share of the national labour force held by youth, youth employment shares by sector, and national-level absolute population numbers. We not only combined data from different sources but also created a model that considers both historical trends and expected future economic growth. This is country-level data for all African countries. For some select countries, like Kenya and Rwanda - which are the Mastercard Foundation's focus countries - sub-national data is provided. The data is broken down by gender, educational attainment and sector. This provides nuanced insights into the challenges and opportunities facing young people in the job market. It shows which groups of young people need the most support - for example, if there are more unemployed men or women or how educational attainment is related to unemployment. What are some of the key trends you've seen? The clock has data for the years 2015 to 2030. Based on the analysis we did at the World Data Lab, several key trends have emerged from the data provided by the clock. One notable trend is the decline in agricultural employment across all countries on the continent, indicating a shift in employment patterns towards industry and services. In particular, based on both past data and forecasts, projections suggest a significant increase in job opportunities in the construction sector, as was seen in Kenya. The data also highlights variations in educational attainment among young people in different countries. Data on education levels comes from the International Institute for Applied Systems Analysis and Wittgenstein Centre. Kenya outperformed the continental average on this score: 80 per cent of Kenyan youth have attained secondary education compared with 46 per cent across Africa. Insights like these are invaluable for policymakers, businesses, and educational institutions who want to align skill development initiatives with the evolving demands of the job market. What were some of the major red flags you picked up? Several warrant attention. One major concern is the persistently high number of young people who are not in employment, education or training across many African countries. In 2024, 111.6 million young Africans - corresponding to 21.2 per cent of all young Africans - were outside the labour force. Unemployed people and people out of the labour force are two different groups. The unemployed are those who currently don't have a job but are looking for one. People outside the labour force don't have a job either but are not looking for one. For example, they may be taking care of family members full-time. We expect the share of youth outside the labour force to remain almost constant until 2030, while we expect the absolute number to go up to 129.8 million people. When looking at country-specific data, the share of youth outside the labour force ranges from 3.8 per cent to 40.5 per cent. This indicates that countries are facing a significant challenge in getting young people into and keeping them in, productive activities. In addition, a considerable proportion of employed youth still live in poverty - 40 per cent of employed youth in Africa are living in extreme poverty. This highlights the prevalence of working poverty - the proportion of the employed population living in poverty despite being employed. This means their employment-related incomes are not sufficient to lift them and their families out of poverty and ensure decent living conditions. Youth living on less than $2.15 (280) per day are considered extremely poor, while those living on $2.15 to $3.65 (Sh471) per day are considered moderately poor. Youth living on more than $3.65 a day are considered not poor. This shows that urgent action is needed to address the structural barriers to youth employment and education. Policymakers must also ensure that economic growth translates into improved livelihoods for young people. Additionally, disparities in educational attainment across countries and genders signal the need for targeted interventions. What can be done? The data presented by the Africa Youth Employment Clock can be instrumental in informing evidence-based policy interventions. First, policymakers can use insights to prioritise initiatives that will increase educational attainment. For example, NGOs might be able to identify which countries need the most support. At the same time, insights could point to opportunities. Data on sectoral employment trends can also lead to the expansion of job opportunities in emerging sectors, such as construction. This might allow policymakers to ensure that there are enough young people with the skills needed in that sector. Investments in education and skills development programmes can help equip young people to secure decent employment opportunities. As economies move away from agriculture towards industry and services, companies need more skilled labour to meet international standards. In addition, technology is becoming more important in many jobs. Companies will look for people with skills in information technology and mathematics. These skills are often only achievable for people with at least some secondary education. Second, targeted efforts to reduce the number of youth not in employment, education or training can be informed by the geographic and demographic data available through the clock. Third, stakeholders can use the data on sectoral employment trends to promote economic growth which sees an increase in wealth and opportunity that benefits all members of society.

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