Youth in today’s workforce face deficits in the education and training they need to be employable and progress in their careers, a delayed transition from school to work, and, once they have entered the workforce, difficulty in securing jobs that pay a living wage and offer social protections.
Employer surveys consistently reveal concerns about the lack of certain types of skills among potential employees, especially soft skills such as communication and teamwork, noting the constraints this imposes on business performance (1, 2, 3). Indeed, learning assessments show a substantive lack of functional literacy and numeracy skills at multiple developmental stages (4).
In the context of this skills deficit, young people are taking longer to complete the school-to-work transition. Once young people do enter the workforce, their quality of employment may be informal or characterized by a lack of protections (5). Regarding the success of self-employment, the World Bank’s (2010) youth employment policy primer identifies the following as factors impeding success, at least on the supply side: a lack of job-relevant and entrepreneurial skills, job search barriers (such as lack of access to information or weak soft skills), and start-up and social constraints (6).
Investments can help develop youth and young adults’ employable skills (technical and non-technical) by:
In low- and middle-income countries, nearly one in three young men and around half of young women aged between 25 and 29 are not working, whether they were formerly in school and have not entered the workforce or are neither in school nor employed (5). About 55% of workers aged 15–19 and about 40% of workers aged 20–29 are employed in the informal sector, where income inequality is higher than in the formal sector (5).
Moreover, a substantial minority of youth aged 15–19 are unpaid family workers, while a substantial minority of those aged 25–29 are own-account workers, meaning they are self-employed and have not continuously engaged employees to work for them (5). Despite reporting job-satisfaction scores and a sense of job security similar to regular employees’, own-account workers’ income ceases to increase and even falls slightly beyond age 22 (5). Finally, more than half of all working youth (aged 15–24, as defined by the International Labour Organization) are living in extreme or moderate poverty (8). Without action to give young people the education and skills they need to compete, more than a quarter of the population in low-income countries could still be living in extreme poverty in 2050 (1).
Youth benefit from this strategy by gaining new skills, knowledge, and access to resources, ideally improving their employment opportunities, reducing the length of their job searches, increasing their wages, and raising their performance on-the-job.
Employers gain access to a more skilled workforce, ideally facilitating a more efficient hiring process and improving business performance.
Skills Gap: Using young adults’ (aged 15–24) literacy as a proxy for foundational skills, low- and middle-income countries exhibit the greatest deficit (4). Sub-Saharan African countries have the highest percentage of low-proficiency readers (around 60%), followed by Latin America and the Caribbean (about 40%) and South Asia (about 30%; 4).
Quality of Employment: Data from the International Labour Office’s school-to-work transition survey (SWTS) reveal high percentages of youth and young adults employed in the informal sector in low- and middle-income countries: 90.7% in sub-Saharan Africa, 75.4% in the Middle East and North Africa, 72.9% in Latin America and the Caribbean, 54.3% in Eastern Europe and Central Asia, and 90.5% in Asia and the Pacific (8).
Self-employment: SWTS data also show high percentages of youth and young adults engaged in self-employment. While self-employment is the main form of employment in sub-Saharan Africa, it is less common in Eastern Europe and Central Asia and in the Middle East and North Africa (5). Asia and the Pacific, Latin America and the Caribbean, and some Central Asian countries have rates of self-employment somewhere in the middle (8). For example, in Asia and the Pacific, own-account and family workers constitute 40% and 12% of the total working population, respectively (8).
Unemployment: The Middle East and North Africa exhibits the highest youth unemployment rate in the world, expected by the International Labour Organization to exceed 30% by 2019 (8). The unemployment rate is especially high for women in this region: as of November 2018, 5.7% of female youth in Arab States were employed, compared with 38.5% of male youth (Employment-to-population ratio, ILO modelled estimates, Nov. 2018).
Strong evidence links employment to reduced risk of depression and overall improved mental and physical health (11, 12). However, most research has instead examined the negative consequences of unemployment, and most of the evidence is limited to high-income countries. Unemployment depreciates human capital and has a significant and negative influence on health, happiness, crime levels, and socio-political stability (13). An analysis of Northern Swedish workers connected youth unemployment with poorer mental health 21, 30, and 42 years later (14). Finally, another study found that unemployment creates a negative feedback loop: the long-term unemployed, unsurprisingly, have a harder time finding a job than the short-term unemployed (15).
This strategy can benefit the approximately 59.3 million youth (aged 15–24) who are unemployed worldwide and the 59.8 million youth in low- and middle-income countries who are working but still in poverty.
A systematic review showed that employment interventions have a greater effect in low- and middle-income countries than in high-income countries (9). Findings from another meta-analysis found that programs targeting disadvantaged youth seem to be more effective than programs targeting youth generally (10). The following are average effects of various interventions on employment, most relatively small and positive but significant: skills-training programs (0.06 standardized mean difference), entrepreneurship promotion (0.18 standardized mean difference), and subsidized employment (0.11 standardized mean difference). Skills-training programs also have a small and positive effect on income (0.12 standardized mean difference), as does entrepreneurship (0.14 standardized mean difference; 9).
Execution Risk: Some solutions could benefit an unintended demographic in a given country or context, perhaps benefiting upper-middle classes or private schools, for example, and deepening inequalities. To mitigate this risk, investors should collect data and indicators to verify the demographic served by the investee or fund.
Poor access to electricity and other resources in low-income countries can present challenges for some technological solutions. Investors should make sure such solutions fit the geography or demographic to be served.
Endurance Risk: Employability training must meet labor-market requirements to be effective, and such requirements vary widely by geography. Employability programs therefore risk providing participants with skills that might not be applicable to their immediate environments. To mitigate this risk, validation tests are required when entering a new region to ensure that services are relevant and in demand. Additionally, a strong sense of the local education system and its capacity is important to understanding the labor pipeline, including whether local entities are investing in corporate training, internships, or vocational training.
Evidence Risk: Efforts to assess impact may be hindered if a startup lacks the capacity to monitor and evaluate all of their outcome metrics. For example, a startup offering employability training to a local entity may be unable to collect information from that entity to accurately capture the impact of their solution. Inability to measure impact metrics or reliance on a third party to monitor progress introduces the risk for error. To mitigate that risk, investors should carefully consider the type of indicators investees provide and require metrics that better relate to the intended outcome of their solution.
External Risk: Factors beyond employability and vocational training can prevent youth from learning properly (e.g., cultural barriers to women working), thereby limiting the strategy’s expected impact on workforce entry. To mitigate this risk, investors should carefully understand the context in which a solution will be implemented, evaluating whether the offer fits the market and the intended impact.
Poorly designed or executed products and services, including those poorly tailored to the needs of the intended stakeholders, will not be used. Employers that are then discouraged from using the products and services or that find offered solutions ineffective may be less open to considering such solutions in the future—and may even be less likely to offer work-based learning opportunities or jobs at all.
Based in Brazil, Digital House provides coding school services intended to help students build careers in fields such as software development, data science, artificial intelligence, and analytics. The offered services include intensive, face-to-face, and practical courses that match students with the new generation of talent and professionals in the technological world, enabling them to learn new skills by practicing and experimenting. Digital House received investments from the Rise Fund and other investors. The organization has 10 units in three Latin American countries.
LabourNet is a social enterprise that supports informal workers through training, employment, and entrepreneurship in India, where 81% of those working are in the informal sector. LabourNet has one of the largest geographic footprints of workforce-development companies operating in India and has partnered with government, corporations, and schools. Acumen and the Michael and Susan Dell Foundation invested in LabourNet, which has training centers in more than 143 livelihood centers and 598 schools.
Laboratoria helps young women access better employment opportunities in Peru by teaching them coding and connecting them with businesses and organizations in need of their talent. This offers women from underprivileged backgrounds access to better jobs and living standards. The Inter-American Development Bank invested in Laboratoria. More than 1,000 women have graduated from the Laboratoria program, more than 80% of whom are working in technology.
Laqsh provides vocational training courses to students from lower socio-economic backgrounds in India. The company’s platform provides skill training in information technology (IT), IT-enabled services (ITES) and the retail sector, vocational education, and lectures on emerging technologies from industry experts and regular industry visits, which enable eligible students to nurture their soft skills and obtain good placements. The education impact investor Gray Matters Capital invested in the organization, among others. Laqsh serves students from 469 schools across 11 states in India.
Steer, Liesbet, Justin W. van Fleet, Gila Sacks, Nicholas Burnett, Paul Isenman, Elizabeth King, Annababette Wils et al. The Learning Generation: Investing in Education for a Changing World. New York: International Commission on Financing Global Education Opportunity, 2016.
dDi Gropello, Emanuela, Aurelien Kruse, and Prateek Tandon. Skills for the Llabor Mmarket in Indonesia: Ttrends in Ddemand, Ggaps, and Ssupply. Washington, DC: The World Bank, 2011.
dDi Gropello, Emanuela, Prateek Tandon, and Shahid Yusuf. Putting Hhigher Eeducation to Wwork: Skills and Rresearch for Ggrowth in East Asia. Washington, DC: World Bank Publications, 20121.
Filmer, Deon, Halsey Rogers, Samer Al-Samarrai, Magdalena Bendini, Tara Béteille, David Evans, Märt Kivine, Shwetlena Sabarwal, Alexandria Valerio et al. World Development Report 2018: Learning to Realize Education’s Promise. Washington, DC: World Bank, 2018.World Bank. World Development Report: Learning to Realize Education’s Promise. 2018. DC: World Bank.
O’Higgins, Niall. 2017. Rising to the Youth Employment Challenge: New Evidence on Key Policy Issues. Geneva: International Labour Office, August 2017.
World Bank, 2010.
Psilos, Phil., and Tommy Galloway, What Works in Entrepreneurship Education and Training Programs for Youth? T. (2018). Entrepreneurship Programming for Youth: Evidence Report. Washington, DC: USAID’s and YouthPower: Implementation, YouthPower Action, 2018.
Kühn, Stefan, Santo Milasi, and Damian GrimshawInternational Labour Organization. 2019. World Employment Social Outlook: Trends 2019. Geneva: International Labour Office, 2019.
Kluve, Jochen, Susana Puerto S, David Robalino D, Jose Manuel Romero JM, Friederike Rother F, Jonathan Stöterau J, Felix Weidenkaff, F and Marc Witte. M, 2017. Interventions to Iimprove the Llabour Mmarket Ooutcomes of Yyouth: Aa Ssystematic Rreview of Ttraining, Eentrepreneurship Ppromotion, Eemployment Sservices and Ssubsidized Eemployment Iinterventions. International Initiative for Impact Evaluation (3ie) Systematic Review 37. LondonOslo: International Initiative for Impact Evaluation (3ie)The Campbell Collaboration, December 2017.
Betcherman, Gordon, Amit Dar, and Karina Olivas. “Impacts of Aactive Llabor Mmarket Pprograms: New Eevidence from Eevaluations with Pparticular Aattention to Ddeveloping and Ttransition Ccountries.” Social Protection and Labor Policy and Technical Notes 29142, Washington, DC, World Bank, 2004.
van der Noordt, Maaike, Helma IJzelenberg, Mariël Droomers, and Karin I. Proper. “Health Eeffects of Eemployment: Aa Ssystematic Rreview of Pprospective Sstudies.” Occupational and Environmental Medicine 71, no. 10 (2014): 730–-736.
Hergenrather, Kenneth C., Robert J. Zeglin, Maureen McGuire-Kuletz, and Scott D. Rhodes. “Employment as a Ssocial Ddeterminant of Hhealth: Aa Ssystematic Rreview of Llongitudinal Sstudies Eexploring the Rrelationship between Eemployment Sstatus and Pphysical Hhealth.” Rehabilitation Research, Policy, and Education 29, no. 1 (2015): 2–-26.
Bell, David N. F., and David G. Blanchflower. “Young Ppeople and the Great Recession.“ Oxford Review of Economic Policy 27, no. 2 (2011): 241-2–67.
Strandh, Mattias, Anthony Winefield, Karina Nilsson, and Anne Hammarström. “Unemployment and Mmental Hhealth Sscarring during the Llife Ccourse.“ The European Journal of Public Health 24, no. 3 (2014): 440–-445.
Abraham, Katharine G., John Haltiwanger, Kristin Sandusky, and James R. Spletzer. “The Consequences of Long-Term Unemployment: Evidence from Linked Survey and Administrative Data.“ ILR Review 72, no. 2 (2019): 266–-299.
Clemensson, Martin, and Jens Dyring Christensen, Jens Dyring. “How to Bbuild an Eenabling eEnvironment for Yyouth Eentrepreneurship and Ssustainable Eenterprises.” Small Enterprise Programme, International Labour Office. Strategies 17 (2010): 19Paper for the knowledge sharing event on Integrated Youth Employment Strategies, Moscow, February 17–19, 2010.
This mapped evidence shows what outcomes and impacts this strategy can have, based on academic and field research.
Kluve J, Puerto S, Robalino D, Romero JM, Rother F, Stöterau J, Weidenkaff F and Witte M, 2017. Interventions to improve the labour market outcomes of youth: a systematic review of training, entrepreneurship promotion, employment services and subsidized employment interventions. 3ie Systematic Review 37. London: International Initiative for Impact Evaluation (3ie).
Card, David, Pablo Ibarrarán, Ferdinando Regalia, David Rosas-Shady, and Yuri Soares. “The labor market impacts of youth training in the Dominican Republic.” Journal of Labor Economics 29, no. 2 (2011): 267-300.
Sianesi, Barbara. “Differential effects of active labour market programs for the unemployed.” Labour economics 15, no. 3 (2008): 370-399.
Blattman, Christopher, Nathan Fiala, and Sebastian Martinez. “Generating skilled self-employment in developing countries: Experimental evidence from Uganda.“ The Quarterly Journal of Economics 129, no. 2 (2013): 697-752.
Botha, Melodi, G. H. Nieman, and J. J. Van Vuuren. “Evaluating the women entrepreneurship training programme: a South African study.“ International Indigenous Journal of Entrepreneurship, Advancement, Strategy and Education 2, no. 1 (2006): 1.
De Mel, Suresh, David McKenzie, and Christopher Woodruff. Business training and female enterprise start-up, growth, and dynamics: Experimental evidence from Sri Lanka. The World Bank, 2012.
Ibarrarán, Pablo, David Rosas Shady, and Yuri Soares. Impact Evaluation of a Youth Job Training Program in the Dominican Republic: Ex-Post Project Evaluation Report of the Labor Training and Modernization Project (DR0134). Inter-American Development Bank, 2006.
World Bank. 2015. Can skills training increase employment for young women? : the case of Liberia (English). Washington, DC : World Bank Group. http://documents.worldbank.org/curated/en/343811468266115466/Can-skills-training-increase-employment-for-young-women-the-case-of-Liberia
Each resource is assigned a rating of rigor according to the NESTA Standards of Evidence.
Number of people hired by the organization during the reporting period. This is the sum of all paid full-time and part-time employees hired.
Organizations should footnote all assumptions used, and should additionally measure how many students and skills training participants are hired.
This metric is intended to capture the number of unique individuals hired by the organization into full- or part-time roles during the course of the last reporting period. This metric excludes Temporary Employees (OI9028).
To understand if the strategy is successfully reaching the desired outcome of “increased number of youth employed.”
Number of females employed by the organization as of the end of the reporting period. This is the sum of all paid full-time and part-time female employees.
This metric is intended to capture the number of unique female individuals employed by the organization in full-time roles at the point in time defined by the reporting end date. This metric excludes Temporary Employees (OI9028).
To understand how many women and girls are benefiting from the solution. The gender lens is an important element in a workforce development strategy.
Number of students receiving vocational or technical training during the reporting period.
Organizations should footnote all assumptions used as well as details about the type of vocational/technical training received by the students.
The data would have to be gathered via school/training organization reportings.
To understand the scale of the solution. Completion of workforce development programs/trainings is linked to the employment and livelihoods of the individual who participate in and complete them, therefore are important for this strategy.
Number of unique client individuals who were served by the organization and provided access, during the reporting period, to products/services they were unable to access prior to the reporting period.
Organizations should reference New Access to Water, New Access to Energy, New Access to Education, New Access to Finance, or New Access to Healthcare in the glossary for more clarification.
Organizations should footnote all assumptions used. See usage guidance for further information.
This metric is not a measure of foot traffic. It is also not intended to capture the number of consumer transactions. For example, a customer who makes two purchases during a period should only be counted once. Organizations wishing to report on total client transactions should refer to Client Transactions (PI5184).
This metric is intended to capture the unique number of specific individuals serviced. Organizations should not use any household multipliers when reporting against this number. If organizations consider the entire household to be the customer/client, they can report against Client Households: Total (PI7954) and its associated sub metrics.
Organizations that rely on assumptions to report against this metric, including the process for determining the number of client individuals, should footnote all assumptions used in the calculation process.
For healthcare providers, client individuals refers to patients.
To understand the scale of new services offered to youth job seekers (i.e.: access to job search platforms, to coaching/mentoring, to labor market information, etc.).
Percentage of school students passing standardized tests set by a regional governance body during the reporting period.
"= (Number of enrolled students who passed standardized test) / (Number of enrolled students who took standardized test)"
Organizations should footnote the description of the standardized test, the threshold for passing, how many tests were taken, and other relevant details.
In many cases this data will need to be collected by schools/vocational training institutions or other third party. The investee company can work with those third parties to gather the information, as it can show effectiveness of the solution provided. If more than one test is taken, organizations should report on the average of the pass rates.
To understand if students participating to technical vocational trainings are passing standardized tests related to the technical skills they developed. The metric is a proxy for skills training effectiveness.
Skills here are meant to include soft skills (soft skills may be defined here as behaviors, attitudes, and personal qualities that enable people to effectively navigate their environment and complement technical, academic, and vocational skills, e.g. social skills, communications skills, self-control, etc.), vocational skills, technical skills, or other workforce-relevant skills defined by the program offered. Such assessments/tests may be administered by the workforce development/training service provider, an evaluator, a government agency, etc.
Number of youth with improved skills at post-test / Number of youth participating in skills programming
The data would have to be gathered via training organization reportings.
To understand effectiveness of the skills training solution. Improved skills are at the forefront of the theory of change for workforce development. Increasing skill levels enhances the ability to both get and keep a job. They also support productivity of firms and improved competitiveness. These are evidence of a healthy economy in terms of a population with economic opportunities and a robust business environment.
Value of wages (including bonuses, excluding benefits) paid to all full-time and part-time employees of the organization during the reporting period
This metric is intended to capture pre-tax wages/salaries paid to the organization’s employees and should not include benefits nor include payroll expenses. These wages should exclude Temporary Employee Wages (OI4202).
To understand whether the strategy is contributing to increase wages payed to youth workforce, once they acquire key skills through the skills development solutions.