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ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

bmr

Bayesian Macroeconometrics in R

bootcamp2019

Repository of syllabi, lecture notes, Jupyter notebooks, code, and problem sets for OSE Lab Boot Camp 2019

bvar_

Bayesian VAR toolbox for MATLAB

compeconworkshop_2017

deepbsde

Deep BSDE solver in TensorFlow

deepequilibriumnets

deepham

dse2023

Lectures and conference materials for the DSE2023 at the University of Lausanne, Switzerland

dsge_mod

A collection of Dynare models

dynamic-factor-model

Python code for dynamic facctor model. (Preliinary and in progress)

econpdes.jl

Solve semi-linear parabolic PDEs

financial-frictions

Interactive guide to Fernández-Villaverde, Hurtado, and Nuño (2019): "Financial Frictions and the Wealth Distribution".

forecasting

Time Series Forecasting Best Practices & Examples

gensim

Topic Modelling for Humans

hadsge

Code for Bayesian estimation of a heterogeneous agent DSGE model (MATLAB) using the Reiter (2009) solution method.

hank

Replication of Heterogeneous Agent New Keynesian (HANK) model in MATLAB

hark

Heterogenous Agents Resources & toolKit

housing-boom-bust

Replication materials for Kaplan, Mitman and Violante (2020): "The Housing Boom and Bust: Model Meets Evidence" published in the Journal of Political Economy

macro_ml

Course Website on Macroeconomic Analysis with Machine Learning and Big Data

ml_codes

Empirical Data and Some Simulation Codes

models

Models and examples built with TensorFlow

nber-workshop-2022

Code for the Spring 2022 heterogeneous-agent macro workshop

numerical_continuous_time

optionpricing

phact

quantecon.notebooks

Jupyter notebooks contributed by QuantEcon developers, users and the community

ra_hetagents

restaurant

sequence-jacobian

Interactive guide to Auclert, Bardóczy, Rognlie, and Straub (2019): "Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models".