Jupyter Notebooks for Quantitative Economics with Julia

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

or

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.