African Theoretical Statistics (Pure Science) | 20 December 2024
A Theoretical Framework for Causal Forests: Estimating Heterogeneous Treatment Effects in a Johannesburg Youth Employment Programme
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Abstract
This study addresses a current research gap in African Studies concerning Causal Forest Algorithms for Estimating Heterogeneous Treatment Effects of a Youth Employment Program in Johannesburg, South Africa in South Africa. The objective is to clarify key debates, identify practical implications, and outline a focused agenda for scholarship and policy. A qualitative approach was used, drawing on recent literature and policy sources to frame the analysis. This abstract is primarily indicative, outlining the scope and conceptual framing rather than reporting empirical results. The paper argues for context‑specific approaches and stronger empirical foundations in future research. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Causal Forest Algorithms for Estimating Heterogeneous Treatment Effects of a Youth Employment Program in Johannesburg, South Africa, South Africa, Africa, African Studies, theoretical This structured abstract provides a standardised summary to support rapid screening, indexing, and assessment of scholarly contribution.