Vocational education, training skills, and lifelong learning

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.

Multiple job-holding, or “moonlighting”, is an important form of atypical employment in most economies. New forms of work, driven by digitalization, may enable its future growth. However, many misconceptions exist, including the belief that multiple job-holders are only low-skilled individuals who moonlight primarily for financial reasons, or that the practice increases during economic downturns. Recent literature highlights the significant links between moonlighting and job mobility. Multiple job-holding allows for the development of workers’ skills and spurs entrepreneurship.

Evidence suggests that productivity would be much higher and unemployment much lower if the supply of and demand for skills were better matched. As a result, skills mismatch between workers (supply) and jobs (demand) commands the ongoing attention of policymakers in many countries. Policies intended to address the persistence of skills mismatch focus on the supply side of the issue by emphasizing worker education and training. However, the role of the demand side, that is, employers’ rigid skill requirements, garners comparatively little policy attention.

Measuring workers’ productivity is important for public policy and private-sector decision-making. Due to the lack of a general measure that captures workers’ productivity, firms often use one- or multi-dimensional performance measures, which can be used, for example, to analyze how different incentive systems affect workers’ behavior. The public sector itself also uses measures to monitor and evaluate personnel, such as teachers. Policymakers and managers need to understand the advantages and disadvantages of the available metrics to select the right performance measures for their purpose.

Apprenticeship training programs typically last several years and require substantial investments by training firms, largely due to the associated labor costs for participants and instructors. Nevertheless, apprentices also add significant value in the workplace. One tool to measure the costs and benefits of training for firms is employer surveys, which were first introduced in the 1970s in Germany. Such cost–benefit surveys (CBS) help to better understand a firm's demand for apprentices and to identify market failures. Therefore, CBS are an important tool for designing effective training policies.

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.

The labor market position of older workers is cause for concern in many industrialized countries. Rapid population aging is challenging pension systems. The recent economic crisis has forced many older adults out of the workforce, into either pre-retirement or non-employment. Encouraging people to work longer and fostering the employability of older workers have become priorities for policymakers. Training specifically designed for older workers might help attain these goals, since it may refresh human capital and reduce the pay–productivity gap. Training older workers might also benefit employers and society as a whole.

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.

Economists have long believed that firms will not pay to develop occupational skills that workers could use in other, often competing, firms. Researchers now recognize that firms that invest in apprenticeship training generally reap good returns. Evidence indicates that financial returns to firms vary. Some recoup their investment within the apprenticeship period, while others see their investment pay off only after accounting for reduced turnover, recruitment, and initial training costs. Generally, the first year of apprenticeships involves significant costs, but subsequently, the apprentice's contributions exceed his/her wages and supervisory costs. Most participating firms view apprenticeships as offering certainty that all workers have the same high level of expertise and ensuring an adequate supply of well-trained workers to cover sudden increases in demand and to fill leadership positions.

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.