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Creating jobs…. or shifting existing jobs?

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Many countries in Africa are challenged with very large populations of young people without work or in vulnerable employment; creating more and better jobs is a critical policy challenge. Back in October, David and Eliana Carranza posted two blogs (here and here) featuring the findings of their Journal of Economic Perspectives paper on evidence related to job training and job search assistance programs in developing countries. In their paper, the first of three main reasons they outline as to why jobseekers might struggle to find employment is “the lack of overall labor demand in the economy”. They go on to state that “Our sense is that in many cases the largest issue is a lack of labor demand for jobs, especially ‘good’ jobs, and that policies to help firms to grow and demand more labor need to be a primary part of any jobs policy solution.” David and Eliana’s paper came to mind in the course of reading the employment effects from an impact evaluation of two training programs in Nigeria. Specifically, it begs the question how should we think about the treatment effects of supply-side interventions on employment outcomes when there is a strong suspicion of very weak labor demand?

Crawford et al (2021) study an intervention consisting of two training programs in northern Nigeria designed to reduce “the gap between the number of young people looking for work and the limited employment opportunities that are available to them.”

·       The Apprenticeship program upgraded and formalized the traditional apprenticeship system, offered 6 months of foundational and soft-skills business training, support with opening bank accounts and linking participants to loan providers, a stipend (for food and transport), and a link to master craft persons for a one-year apprenticeship.

·       The Skills Training program, focused on building trade-specific skills with classroom instruction and fully equipped workshops and production facilities. It also included foundational skills training and business-related soft skills development.

The setting is one of low levels of employment and high rates of poverty. Levels of education are very low, especially for women. They measure the employment effects as well as other outcomes (employment, assets, consumption, job search, savings, loans, religious norms, and anti-social behavior) for youth 15-24 years old, 6-9 months after completion of the interventions. Given the express purpose of the interventions, a key question is: Did either of these two programs “create” jobs?

There are two broad categories of employment outcomes measured: employment in self or family-owned businesses (SE) or in wage employment (WE). For SE employment, both programs increased employment and SE profits relative to their respective control groups: The Apprenticeship program by 17% (8 percentage points) for employment, and profits by 17% as well. The Skills Training program increased SE employment by 35% (14 percentage points) and profits by 38%. There is no information on what portion of the SE business are new or existing ones, but given the increase in employment, it is likely that many were new activities. So for this subset of participants, it appears that at least some new jobs were created and the objective was met.

Wage work is another story. The Apprenticeship program has modest impacts on employment rates (a 10%/2 percentage points increase), while the Skills Training program participants were 39% (4 percentage points) more likely to be in wage employment than young people who were not enrolled.

But is this job creation? We don’t know, but we doubt it. Most likely these newly trained young people, armed with (hopefully) better skills, have taken jobs that the control sample could have landed if they did not have to compete against program participants. To know for sure, either (a) the geographic intensity of the programs would have had to be varied, as it was in Crepon et al. (2023) , who found the active labor market policies in France indeed achieved their results by displacing the untreated, or (b) the firms receiving the participants would have to be randomized as happened in Alfonsi et al. (2020 gated and ungated), who found that increasing the supply of skilled applicants did not increase the number of people hired in Uganda. (Possibly there could be insights on displacement from the control sample if there is sufficient scale and spatial overlap with the treatment group).

The study estimates the cost-benefit ratio for this program, and finds the costs to be quite high relative to the private returns the participants reaped. But the calculation does not take into account the lost in income for those whose wage job was likely displaced. This group would have the gap between their aspirations and the opportunities available widen. Similarly, for the SE, there could be costs to crowding in the microenterprise space in terms of  profits bring displaced from control SE to those treated (as shown by Hardy and Kagy 2020 for female tailors in Ghana, where there are “not enough customers”). On the other hand, there may be benefits elsewhere that could be factored into a cost-benefit calculation. Even if wage jobs were not created (rather, if they shifted), there may be a productivity boost for firms if they now have higher skilled workers or filled vacant slots faster than without the program. Factoring in such benefits would necessitate surveying the firms that employ these young people. 

Kathleen Beegle

Research Manager and Lead Economist, Human Development, Development Economics

Louise Fox

Visiting Professor of Development Policy, University of California, Berkeley

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