Feb 28, 2024 to Dec 31, 2024
Funding Agency:
Focus Area(s):
Human Development, Labor Markets, and Poverty
Project Director:
Diola, Douglas Kurt Gregor A. ; Melad, Kris Ann M. ; Abrigo, Michael Ralph M.

The proposed research aims to contribute to the growing literature on the 4Ps impacts and heterogeneity analysis. The study utilizes machine learning techniques, specifically the causal forest methodology to provide a comprehensive analysis of the heterogeneous effects of the 4Ps. By doing so, it seeks to contribute to a deeper understanding of how the program's impacts vary across different subpopulations, thereby offering valuable insights for policy refinement and enhancement. This study also explores the potential of using sophisticated analytical techniques in evaluating programs like the 4Ps.

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