Alan Lujan's Projects
Official content for the Fall 2014 Harvard CS109 Data Science course
Data directory for the CS109 Data Science course
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).
Config files for my GitHub profile.
Repository of syllabi, lecture notes, Jupyter notebooks, code, and problem sets for OSE Lab Boot Camp 2019
Tested for Apple Silicon, Apple Multipass, Ubuntu 20.04
Theoretical Foundations of Buffer Stock Saving
Solve and simulate consumption-saving models in Python (optimized with Numba) and C++
Jupyter Notebook examples of the ConSav package
Official content for Harvard CS109
Datasets for CS109
Demonstrations of how to use material in the Econ-ARK
The Distribution of Wealth and the Marginal Propensity to Consume
Teaching materials from DSE2019 summer school at Chicago Booth
General tools for econ-ark, packaged up
Estimagic is a Python package for nonlinear optimization with or without constraints. It is particularly suited to solve difficult nonlinear estimation problems. On top, it provides functionality to perform statistical inference on estimated parameters.
EGM using fast upper-envelope scan
Public version of HAFiscal project
Heterogenous Agents Resources & toolKit
Notebooks that support https://python-advanced.quantecon.org