EMINN implementation of Krusell-Smith model with neural network solutions.

End-to-End Python implementation of Dávila-Fernández & Sordi's (2025) methodology for FX-constrained growth modeling (in emerging markets). Features Bayesian state-space estimation via Gibbs sampling with FFBS algorithm, heterogeneous agent simulation (fundamentalists/chartists), and nonlinear dynamics analysis.

End-to-End Python replication of Camara & Aublin's (2025) monetary spillover analysis methodology. Implements rotational-angle decomposition, Bayesian VAR with Normal-Wishart priors, sign restrictions for shock identification, and a full robustness suite for international macroeconomic analysis.