Justin Napolitano

This repository contains Jupyter notebooks used for quantitative economic modeling lectures, leveraging the Julia programming language. It serves as a companion resource to the online lectures hosted at julia.quantecon.org.

Features

Collection of interactive Jupyter notebooks covering quantitative economics topics
Organized content on dynamic programming, continuous time models, multi-agent models, and time series
Integration with Julia's package ecosystem for numerical computing and optimization
Ready-to-run notebooks via Binder for immediate exploration without local setup

Tech Stack

Julia programming language
Jupyter Notebook format for interactive content
QuantEcon Julia packages and related Julia ecosystem libraries

Getting Started

Prerequisites

Julia (version 1.6 or later recommended)
Jupyter Notebook or JupyterLab

Installation

Clone the repository:

git clone https://github.com/justin-napolitano/lecture-julia.notebooks.git
cd lecture-julia.notebooks

Install dependencies using Julia's package manager:

using Pkg
Pkg.activate(".")
Pkg.instantiate()

Running Notebooks

Launch Jupyter Notebook or JupyterLab from the repository root:

jupyter notebook

jupyter lab

Open any notebook (*.ipynb) to start exploring.

Alternatively, use Binder to run notebooks in a cloud environment without local setup: click the Binder badge above.

Project Structure

about_lectures.ipynb — Overview and context for the lecture series
intro.ipynb — Introduction to quantitative economics with Julia
status.ipynb, troubleshooting.ipynb, zreferences.ipynb — Support and reference materials
continuous_time/ — Notebooks covering continuous time economic models
dynamic_programming/ and dynamic_programming_squared/ — Dynamic programming methods and applications
getting_started_julia/ — Julia language fundamentals and setup
more_julia/ — Advanced Julia programming topics and packages
multi_agent_models/ — Models involving multiple interacting agents
problems/ — Exercises and problem sets
software_engineering/ — Tools and practices for software development in Julia
time_series_models/ — Time series analysis and modeling
tools_and_techniques/ — Supplementary computational techniques
Manifest.toml, Project.toml — Julia package environment files
README.md — This file

Future Work / Roadmap

Expand notebook coverage to include more advanced quantitative methods
Update content to align with latest Julia language features and package versions
Improve integration with online lecture materials and interactive platforms
Add automated testing and continuous integration for notebooks
Enhance documentation and examples for software engineering practices

This repository assumes familiarity with Julia and quantitative economics. For a full learning experience, consult the lectures at julia.quantecon.org.