RA Computational Work in Economics
A Student's Guide to Efficient Comp Econ Lectures
- Hans-Martin von Gaudecker - Effective programming practices for economists
- Jesús Fernández-Villaverde - Computational Methods for Economists
- Richard W. Evans, et al. - Open Source Economics Laboratory (OSE Lab) Boot Camp 2019, 2018, 2017
- Richard W. Evans -
- Perspectives on Computational Modeling for Economics 2020
- Perspectives on Computational Research in Economics 2020
- Structural Estimation 2020
- Git and GitHub tutorial
- Jason DeBacker - Computational Methods for Economists 2017, 2019
- Jeppe Druedahl - Introduction to Programming and Numerical Analysis
- Tyler Ransom - Data Science for Economists 2020
- Fedor Iskhakov - Dynamic programming and structural estimation
- Grant McDermott - Data science for economists
- Kenneth Judd - Computational Economics 2020
Data & Code & Reproducibility
- Gentzkow, M., & Shapiro, J. M. (2014). Code and data for the social sciences: A practitioner’s guide. Chicago, IL: University of Chicago.
- Knittel, C. R., & Metaxoglou, K. (2016). Working with Data: Two Empiricists’ Experience. Journal of Econometric Methods, 7(1).
- Christensen, Garret S. and Edward Miguel, "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, 56:3 pp. 920-980 (Sep. 2018).
- Coding for Economists: A Language-Agnostic Guide to Programming for Economists - Ljubica Ristovska
- Templates for Reproducible Research Projects in Economics
- Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L., & Teal, T. K. (2017). Good enough practices in scientific computing. PLoS computational biology, 13(6), e1005510.
- The Plain Person’s Guide to Plain Text Social Science - Kieran Healy
- Data and Code Guidance by Data Editors (also see the AEA guidance on Data and Code)
- Best Practices when Writing Code
Mac OS
- macOS Setup Guide (a little outdated)
- The Unix Shell - Software Carpentry (see also python, git, r, etc.)
- Corey Schafer's youtube channel (very beginner-friendly videos for almost all basic things about mac, python, git, etc.)
- Terminal: here, here, here
Python
- QuantEcon (also here)
- QuantEcon DataScience
- Python Data Science Handbook - Jake VanderPlas (also his A Whirlwind Tour of Python)
- Introduction to Python for Econometrics, Statistics and Numerical Analysis - Kevin Sheppard
- NYU-Data-Bootcamp
- Data Analysis in Python
- Modern Pandas
- Introduction to Python for Science
- Computational Statistics in Python
- Python computational labs
- Real Python Tutorials
- Scipy Lecture Notes
- Hypermodern Python
Julia
- QuantEcon
- Computational Economics with Data Science Applications - Paul Schrimpf
- UBCECON567 - Paul Schrimpf
- Think Julia: How to Think Like a Computer Scientist - Ben Lauwens
- Econometrics lecture notes with examples using the Julia language - Michael Creel
- Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence - H.Klok, Y.Nazarathy
R
- Advanced Econometrics and Machine Learning: 2019, 2000 - Maximilian Kasy
- collection of useful computation links on R and ML - Maximilian Kasy
- Economics, Causality, and Analytics - Nick Huntington-Klein
- Library of Statistical Techniques - Nick Huntington-Klein
- Statistical Learning and Causal Inference for Economics - Francis J. DiTraglia
- Causal-Inference-for-Beginning-Undergraduates - Tom O'Grady
Git
- git for social science students (not software developers) - Shiro Kuriwaki
- Version Control for Economists - Wei Yang Tham
- Git for Economists - Frank Pinter
- Git, GitHub, and Version Control - QuantEcon
- Git and GitHub tutorial chapter - Richard Evans
- Bryan, J. (2018). Excuse me, do you have a moment to talk about version control?. The American Statistician, 72(1), 20-27.
- git + LaTeX workflow - stackoverflow
- Pro Git book - Scott Chacon & Ben Straub
- Git Tutorials and Training - Atlassian
- Using Git & GitHub Guides - github
- Git & Version Control FAQ - git-tower
- Happy Git and GitHub for the useR - Jenny Bryan
- Git for Scientists - Miles McBain
- Flight rules for git
- Collaborative Models in GitHub / Collaborating on GitHub / GitHub for Collaboration On Open Projects / Development workflow / GitHub Standard Fork & Pull Request Workflow / Git mergetool tutorial
Latex
- The Not So Short Introduction to LATEX - Tobias Oetiker
- A simple guide to LaTeX - Step by Step
- Overleaf guides to LaTeX
- Tips + Tricks with Beamer for Economists - Paul Goldsmith-Pinkham
- Template-based introductory guide to LaTeX for Economics
Markdown
- The Markdown Guide
- Markdown Reference - typora (some Japanese introduction on typora)
Regex
Visualization
- Schwabish, J. A. (2014). An economist's guide to visualizing data. Journal of Economic Perspectives, 28(1), 209-34.
- Some Data visualizations in Python
- Python Plotting for Exploratory Data Analysis
- from Data to Viz - The Python Graph Gallery / The R Graph Gallery
Machine Learning
- Data Science & Artificial Intelligence - Chris Albon (and a lot of other stuffs)
- A course in machine learning for economists
Unsorted
Other Econ Lectures on Github
- Microeconometrics - Analysis of Human Capital
- Labor Economics - Analysis of Human Capital
- Econometrics of Human Capital - Analysis of Human Capital
- Introduction to Econometrics with R
- Advanced Macro - Joao B. Duarte
Links to more general Econ resources
- Advice for current and aspiring academic economists - Jennifer Doleac
- Writing, Presentation, and Refereeing Advice - Amanda Y. Agan
- Resource - Ryan B Edwards
- Tips 4 Economists - Masayuki Kudamatsu
- Research resources that I recommend - Jonathan Dingel
- Data Science and Economics