Active labour market programme type influences youth employment integration in Morocco

Abstract Active labour market programmes (ALMPs) are central to Morocco’s employment strategy, yet comparative evidence on their relative association with youth labour-market insertion remains scarce. Using harmonised administrative microdata on 4500 beneficiaries (2016–2024), this study compares three flagship programmes IDMAJ (wage subsidies), TAEHIL (vocational training), and FORSA (entrepreneurship and placement support) through binomial logistic regression on pre-treatment characteristics, complemented by propensity score matching and a five-fold cross-validated benchmark against five machine-learning algorithms. Relative to IDMAJ, TAEHIL shows consistently lower insertion odds (OR = 0.683, $$p<0.001$$ ; $$\approx $$ 9.7 percentage points), a gap confirmed by matching estimates (ATT = 12.7 pp); FORSA’s association weakens once post-treatment covariates are included. Secondary-qualifying education is the strongest positive predictor of insertion (OR = 1.41), and programme effects concentrate among male beneficiaries. No algorithm outperforms logistic regression (AUC: 0.509-−0.530), indicating that available administrative records lack the informational richness required for individual-level targeting. Findings support intensified post-programme matching assistance and investment in richer demand-side data before predictive targeting tools are deployed.

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Publication Details

Journal
Discover Global Society
Published
2026-07-26
DOI
https://doi.org/10.1007/s44282-026-00520-5
Primary Topic
Advanced Causal Inference Techniques
Type
article
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article

Active labour market programme type influences youth employment integration in Morocco

Abdeljabbar Abdouni, Said Maizzou, Sara Haddouche, Ali Raigat et al.
Discover Global Society
Advanced Causal Inference Techniques
article

Active labour market programme type influences youth employment integration in Morocco

Abdeljabbar Abdouni, Said Maizzou, Sara Haddouche, Ali Raigat, Youness Ezzaaime, El Amine Rouaga
article en

Abstract

Abstract Active labour market programmes (ALMPs) are central to Morocco’s employment strategy, yet comparative evidence on their relative association with youth labour-market insertion remains scarce. Using harmonised administrative microdata on 4500 beneficiaries (2016–2024), this study compares three flagship programmes IDMAJ (wage subsidies), TAEHIL (vocational training), and FORSA (entrepreneurship and placement support) through binomial logistic regression on pre-treatment characteristics, complemented by propensity score matching and a five-fold cross-validated benchmark against five machine-learning algorithms. Relative to IDMAJ, TAEHIL shows consistently lower insertion odds (OR = 0.683, $$p<0.001$$ ; $$\approx $$ 9.7 percentage points), a gap confirmed by matching estimates (ATT = 12.7 pp); FORSA’s association weakens once post-treatment covariates are included. Secondary-qualifying education is the strongest positive predictor of insertion (OR = 1.41), and programme effects concentrate among male beneficiaries. No algorithm outperforms logistic regression (AUC: 0.509-−0.530), indicating that available administrative records lack the informational richness required for individual-level targeting. Findings support intensified post-programme matching assistance and investment in richer demand-side data before predictive targeting tools are deployed.

Discover Global SocietyVol. 4(1)
Université Hassan 1er (MA)
Decent work and economic growth
Openalex Percentile: Top 6%
Advanced Causal Inference Techniques
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Active labour market programme type influences youth employment integration in Morocco — Abdeljabbar Abdouni, Said Maizzou, et al. · Discover Global Society (2026) | TGRS Research Map | TGRS