End-to-End Python implementation of Azcue et al.'s (2025) stochastic optimal control framework for social protection policy design. Solves PDMP-based Hamilton-Jacobi-Bellman equations using analytical closed-form solutions and Monte Carlo simulation to minimize government intervention costs (through the use of cash transfers and microinsurance).
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Updated
Nov 16, 2025 - Jupyter Notebook