Machine learning methods to uncover mechanisms underlying the impacts of two long-term evaluations of youth skills training programmes in Uganda (7-year follow-up)

Enhancing evidence transferability

Paul Gertler

Educate!/UC Berkeley

Innovations for Poverty Action Kenya
University of California, Berkeley
World Bank
University of California, Los Angeles
Educate! Uganda

February 2020 to January 2023 (TBC)

Uganda

This study aims to shed light on the underlying mechanisms and components through which two innovative youth skills development and entrepreneurship interventions in Uganda operate. This will be done through collecting data in a 7-year follow-up to assess and compare the long-term impacts of three youth skills curricula that feature different combinations of soft and hard skills; namely, SEED-hard (25% focus on soft skills), SEED-soft (75% focus on soft skills) and Educate! (approximately 90% soft skills).

Follow-up instruments will be designed to shed light on the underlying mechanisms and components through which these interventions operate and yield impacts. Machine learning methods (i.e. regression trees) and causal mediation analysis will be combined to study how the programmes shape skills, how these are differentially rewarded in the labour market and their social spillovers (e.g. risky behaviours, partnership quality and intimate partner violence). This innovative methodology will go beyond the ‘effect of a cause’ (i.e. the treatment effect) and investigate the ‘cause of the effect‘ (i.e. the channels through which the effect on final outcomes is manifested).

The study will involve 7-year follow-up data collection on two youth skills-development and entrepreneurship interventions in Uganda, which were both evaluated at scale as randomised controlled trials.

This study aims to inform the debate on the optimal combination of soft and hard skills in the design of entrepreneurship training programmes. It will help develop a better understanding of which skills and underlying mechanisms are important for the development of entrepreneurship in communities.

• Design paper: Machine learning methods to uncover mechanisms underlying the impacts of two long-term evaluations of youth skills training programs in Uganda (8-year follow up)
• Working paper: Making Entrepreneurs: Returns to Training Youth in Hard Versus Soft Business Skills (Presented at Online BREAD conference on the economics of Africa (July 7th-9th 2021) – hosted by the International Growth Centre and co-organized with the African Economic Research Consortium, the African School of Economics, and the Global Poverty Research Lab at Northwestern University)
• Presentation: Making Entrepreneurs: Effect of Training Youth in Business Skills on Enterprise and Employment Creation (Presentation in USC Economics Department, Fall 2021 Development Seminar (September 29th)
• Research Project Paper 10 – Empowering Women: Teaching Leadership Skills to Youth in Uganda
• Research Project Paper 11 – Making Entrepreneurs: The Return to Training Youth in Hard versus Soft Business Skills