Vocational education, training skills, and lifelong learning

Reducing youth unemployment and generating more and better youth employment opportunities are key policy challenges worldwide. Active labor market programs for disadvantaged youth may be an effective tool in such cases, but the results have often been disappointing in Organisation for Economic Co-operation and Development (OECD) countries. The key to a successful youth intervention program is comprehensiveness, comprising multiple targeted components, including job-search assistance, counseling, training, and placement services. Such programs can be expensive, however, which underscores the need to focus on education policy and earlier interventions in the education system.

Workers participating in firm-sponsored training receive higher wages as a result. But given that firms pay the majority of costs for training, shouldn’t they also benefit? Empirical evidence shows that this is in fact the case. Firm-sponsored training leads to higher productivity levels and increased innovation, both of which benefit the firm. Training can also be complementary to, and enhance, other types of firm investment, particularly in physical capital, such as information and communication technology (ICT), and in organizational capital, such as the implementation of high-performance workplace practices.

The objective of providing vocational training for the unemployed is to increase their chances of re-employment and human capital accumulation. In comparison to mandatory course assignment by case workers, the awarding of vouchers increases recipients’ freedom to choose between different courses and makes non-redemption a possibility. In addition, vouchers may introduce market mechanisms between training providers. However, empirical evidence suggests that voucher allocation mechanisms prolong the unemployment duration of training participants. But, after an initial period of deterioration, better long-term employment opportunities are possible.

The level of financial literacy in developed countries is low and contributes to growing wealth inequality. Benefits from increasing the level of financial literacy include more effective saving for retirement and better debt management. However, there are significant costs in terms of time and money of acquiring financial literacy, which imply that the net value of acquiring financial literacy is heterogeneous in the population. This potentially makes designing effective interventions difficult.

Common proxies, such as years of education, have been shown to be ineffective at capturing cross-country differences in skills acquisition, as well as the role they play in the labor market. A large body of research shows that direct measures of skills, in particular cognitive and socio-emotional ones, provide more adequate estimations of individuals’ differences in potential productive capacity than the quantity of education they receive. Evidence shows that cognitive skills in particular are quite relevant to explain wages, while socio-emotional skills are more associated with labor force and education participation decisions.

Although early human capital theory recognized the relevance of workers’ experience, its focus was on education and formal training. More recent studies show that much of the performance of newly hired workers is driven by learning by doing or learning from peers or supervisors in the workplace. Descriptive data show that workers learn a lot from the various tasks they perform on the job. Informal learning at work seems to be relevant for all age groups, although it is more meaningful for younger workers’ performance. Informal learning is far more important for workers’ human capital development than formal training courses.

Time plays an important role in both the design and interpretation of evaluation studies of training programs. While the start and duration of a training program are closely linked to the evolution of job opportunities, the impact of training programs in the short and longer term changes over time. Neglecting these “dynamics” could lead to an unduly negative assessment of the effects of certain training schemes. Therefore, a better understanding of the dynamic relationship between different types of training and their respective labor market outcomes is essential for a better design and interpretation of evaluation studies.