Add new lecture: Aiyagari model with Endogenous Grid Method#676
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This PR adds a new lecture aiyagari_egm.md that combines the Aiyagari model with the Endogenous Grid Method (EGM). Key Features: - Combines concepts from egm_policy_iter.md and aiyagari.md - Uses EGM to solve the household problem (avoiding costly root-finding) - Uses simulation to compute aggregate capital (instead of analytical stationary distribution) - EGM operator for the Aiyagari model - Corrected implementation, converges in ~90 iterations - Simulation-based aggregation - Simulates 10,000+ households via Monte Carlo - Equilibrium computation - Uses bisection to find equilibrium capital stock (K* ≈ 8) - Wealth distribution analysis - Histograms, Lorenz curves, and Gini coefficient - Educational content - Comparison with standard approach and four exercises 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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📖 Netlify Preview Ready! Preview URL: https://pr-676--sunny-cactus-210e3e.netlify.app (647e41e) 📚 Changed Lecture Pages: aiyagari, aiyagari_egm, endogenous_lake |
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📖 Netlify Preview Ready! Preview URL: https://pr-676--sunny-cactus-210e3e.netlify.app (6b3e4e5) 📚 Changed Lecture Pages: aiyagari, aiyagari_egm, endogenous_lake |
# Conflicts: # lectures/_toc.yml
Reworks the lecture so the EGM operator, the household solver and the cross-section simulation are all JIT-compiled and vectorized in JAX, matching the conventions in os_egm_jax. - Remove the broken @jax.jit `K_egm` (data-dependent Python branch) and the unusable jitted `simulate_households` (per-household Python loops); keep a single vectorized `K_egm` and one `simulate_cross_section`. - Solver now uses `jax.lax.while_loop`; simulation uses `jax.lax.fori_loop` with vmap-ed interpolation and inverse-CDF Markov transitions. - Drop the unused numba import; use deterministic PRNG keys so bisection sees a deterministic excess-demand function. - Use qe.lorenz_curve / qe.gini_coefficient instead of hand-rolled np.trapz. Runs end-to-end: K* = 8.15, r* = 0.031, Gini = 0.36, Euler residual 8e-07. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
📖 Netlify Preview Ready!Preview URL: https://pr-676--sunny-cactus-210e3e.netlify.app Commit: 📚 Changed LecturesBuild Info
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Summary
This PR adds a new lecture
aiyagari_egm.mdthat combines the Aiyagari model with the Endogenous Grid Method (EGM).Overview:
The lecture combines two important computational methods:
Key Features:
egm_policy_iter.mdandaiyagari.mdImplementation Details:
Fixes Applied:
Files changed:
lectures/_toc.yml- Added entry for new lecturelectures/aiyagari_egm.md- New lecture fileTest plan
🤖 Generated with Claude Code