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Project README
Guide to Efficient
RA
Computational Work in Economics
Comp Econ Lectures
(programming-language-neutral)
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
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. (
Github manual
)
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).
Ljubica Ristovska -
Coding for Economists: A Language-Agnostic Guide to Programming for Economists
Benjamin Vatter & Gaston Illanes -
Coding Primer: A Reference Guide
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.
Kieran Healy -
The Plain Person’s Guide to Plain Text Social Science
Best Practices when Writing Code
Patrick Ball -
The Task Is A Quantum Of Workflow
and
Principled Data Processing
The Turing Way
(a lightly opinionated guide to reproducible data science)
Fernando Hoces -
Accelerating Computational Reproducibility in Economics
The Good Research Code Handbook
(see
replication
for more)
Tips or Lectures for Structural Econ
Michael Keane -
Practical Issues in Structural Estimation
Chris Taber -
Estimation of Policy Counterfactuals
/
Structural Estimation
Tony Smith -
Tips for Doing Computational Work in Economics
Dynamic Structural Econometrics
Summer School & Conference Series
Robert A. Miller -
STRUCTURAL ECONOMETRICS
Applied Microeconometrics & Casual Inference
Paul Goldsmith-Pinkham -
Applied Empirical Methods
Scott Cunningham -
Causal Inference The Mixtape
/
Mixtape-Sessions
Nick Huntington-Klein -
The Effect: An Introduction to Research Design and Causality
/
Library of Statistical Techniques
Christine Cai -
Literature on Recent Advances in Applied Micro Methods
mostly-harmless-replication in Stata, R, Python and Julia
Hernán MA, Robins JM (2020).
Causal Inference: What If.
Brady Neal -
Introduction to Causal Inference from a Machine Learning Perspective
David Childers -
Causal Econometrics
Kosuke Imai -
Causal Inference with Applications
Matheus Facure Alves -
Causal Inference for The Brave and True
Awesome Causal Inference (resource)
(see
inference
for more)
Python - Econ Lectures
QuantEcon - Python
(also
here
)
QuantEcon DataScience
Richard W. Evans - Perspectives on Computational Modeling for Economics
2020
Richard W. Evans - Perspectives on Computational Research in Economics
2020
Richard W. Evans - Structural Estimation
2020
Jason DeBacker - Computational Methods for Economists
2017
,
2019
,
2021
Fedor Iskhakov -
Dynamic programming and structural estimation
Fedor Iskhakov -
Foundations of Computational Economics
Jeppe Druedahl -
Introduction to Programming and Numerical Analysis
Kevin Sheppard -
Introduction to Python for Econometrics, Statistics and Numerical Analysis
NYU-Data-Bootcamp
Matheus Facure -
Python Causality Handbook
OpenSourceEconomics -
Scientific Computing
OpenSourceEconomics -
Data Science (Microeconometrics)
CompEcon: A Python version of Miranda and Fackler's CompEcon toolbox
Jan Boone -
Doing economics with python
Arthur Turrell -
Coding for Economists
/
Econometrics (with Machine Learning) in Python
Alfred Galichon -
'math+econ+code' masterclasses
NBER -
Spring 2022 heterogeneous-agent macro workshop
Python - Other Tutorials
Research Software Engineering with Python: Building software that makes research possible
Reproducible and Collaborative Data Science
Jake VanderPlas -
Python Data Science Handbook
/
A Whirlwind Tour of Python
Nick Eubank -
Data Analysis in Python
Tom Augspurger -
Modern Pandas
Introduction to Python for Science
Computational Statistics in Python
Python computational labs
Real Python Tutorials
Scipy Lecture Notes
Nicolas P. Rougier -
From Python to Numpy
Introduction to Mathematical Computing with Python and Jupyter
Introduction to Data Science and Programming
Cliburn -
Computational Statistics and Statistical Computing
The Hitchhiker's Guide to Data Science for Social Good
Geographic Data Science with Python
Julia - Econ Lectures
QuantEcon - Julia
Paul Schrimpf - Computational Economics with Data Science Applications
2019
,
2020
Paul Schrimpf -
UBC ECON567 IO
Ivan Rudik -
Environmental and Resource Economics (computational methods for economics / Dynamic Optimization)
Tyler Ransom - Econometrics III (structural estimation, machine learning)
2020
,
2021
Michael Creel -
Econometrics lecture notes with examples using the Julia language
Bradley J. Setzler -
An Introduction to Structural Econometrics in Julia
Florian Oswald -
Computational Economics for PhDs
(
2021
)
Tutorials on Topics in Julia Programming
Lutz Hendricks -
Julia for Economists
/
Notes on the Julia Programming Language
Jamie Cross -
Introduction to Bayesian Econometrics
Cameron Pfiffer -
Julia for Economists Bootcamp
Sergio Ocampo -
Advanced Macroeconomics II
Julia - Other Tutorials
Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence
- H.Klok, Y.Nazarathy
Think Julia: How to Think Like a Computer Scientist
- Ben Lauwens
Introduction to Computational Thinking
- MIT
Tutorials for Scientific Machine Learning and Differential Equations
Algorithms for Decision Making
From zero to Julia!
Introduction to Scientific Computing
Julia language: a concise tutorial
Programming of Simulation, Analysis, and Learning Systems
Julia Data Science
Introduction to Datascience: Learn Julia Programming, Math & Datascience from Scratch.
Scientific Programming in Julia
/
Julia for Optimization and Learning
R - Econ Lectures
Maximilian Kasy - Advanced Econometrics and Machine Learning:
2019
,
2020
,
2021
,
2023
/ collection of
useful computation links on R and ML
Nick Huntington-Klein -
Economics, Causality, and Analytics
/
R resources
/
Causal Inference
/
DataCommSlides
Francis J. DiTraglia -
Statistical Learning and Causal Inference for Economics
Tom O'Grady -
Causal-Inference-for-Beginning-Undergraduates
Grant McDermott -
Data science for economists
/
Big Data in Economics
Christoph Hanck, et al. -
Introduction to Econometrics with R
Ed Rubin - PhD Econometrics (III) with R
2020
,
2022
/
Masters-level applied econometrics with R
/
Introduction to Econometrics with R
Tyler Ransom -
Econometric Analysis (U)
Hans H. Sievertsen -
Applied Economics with R
/
Introduction to R
Matt Woerman -
Topics in Advanced Econometrics
Sebastian Kranz -
Empirical Economics with R
/
Market Analysis with Econometrics and Machine Learning
Florian Oswald, et al. -
Introduction to Econometrics with R
/
Advanced Econometrics
David Childers -
Econometrics II (U)
/
Causal Econometrics
Nick Hagerty -
Advanced Data Analytics in Economics
R - Other Tutorials
Garrett Grolemund & Hadley Wickham -
R for Data Science
(
2ed
)
Hadley Wickham -
Advanced R
The tidyverse style guide
dlab-berkeley -
R-Fundamentals
/ ...
Jeffrey Arnold -
R Code for Mastering ’Metrics
Gina Reynolds -
R Flipbook Textbook
R for Health Data Science
A ModernDive into R and the Tidyverse
Andrew Heiss -
Program Evaluation for Public Service
/
Data Visualization
R Data Science Tutorials
(resources)
Telling Stories With Data
Pere A. Taberner -
List of open source books about R
(resources)
Kyle Walker -
Analyzing US Census Data: Methods, Maps, and Models in R
Summer Institutes in Computational Social Science
Jenny Bryan -
Data wrangling, exploration, and analysis with R
Machine Learning - Econ Lectures
Dario Sansone -
Machine Learning for Economists
(Resources)
Tyler Ransom - Data Science for Economists
2020
,
2021
(R) /
Introduction to machine learning for social scientists
Ed Rubin - Prediction and machine-learning in econometrics
2020
2023
(R)
Itamar Caspi -
Machine Learning for Economists
(R)
Stephen Hansen -
machine_learning_economics
/
text-mining-tutorial
(Python)
Jérémy L'Hour -
Machine Learning for Econometrics
(R)
Le Wang -
Machine Learning and Causal Inference
(R)
Tyler Folkman -
Applied Machine Learning
(Python)
Kathy Baylis et al. - Machine learning in applied economics
2020
,
2021
(Python)
Dawie van Lill -
Data Science for Economics
(Python)
Economics and Data Science
(Resources)
Jonathan Hersh -
Introduction to Machine Learning
(R)
Melissa Dell -
Unleashing Novel Data at Scale
(Python) /
Deep Learning for Economics
Susan Athey's
video on youtube
/
Machine Learning & Causal Inference: A Short Course
Macroeconomic Analysis with Machine Learning and Big Data
Jesús Fernández-Villaverde - Machine Learning for Macroeconomics (
slide
;
video
)
Simon Scheidegger -
Advanced Methods in Computational Economics
Goutham Gopalakrishna -
mini lecture on Deep Learning and Macro-Finance Models
European Central Bank Machine Learning Training -
Machine learning for econometricians
(R)
Applied Causal Inference Powered by ML and AI
(Python; R)
Zhigang Feng -
Machine Learning for Quant Macro
Machine Learning - Other Tutorials
Chris Albon -
Data Science & Machine Learning
(Python)
Andreas C. Müller -
Applied Machine Learning Spring 2020
(Python)
Jeff Heaton -
Applications of Deep Neural Networks
(Python)
UCB -
Computational Social Science
(Python & R)
Harvard -
Introduction to Data Science
(Python)
Bradley Boehmke, Brandon Greenwell -
Hands-On Machine Learning with R
(R)
Bloomberg -
Foundations of Machine Learning
fast.ai:
Deep Learning / Practical Data Ethics / Computational Linear Algebra / NLP
(Python)
Klaus-Robert Müller -
Julia programming for ML
(Julia)
Stata
Fundamentals of data analysis and visualization
Economics Lesson with Stata
Statistical Analysis
- UCLA
Statistics cheatsheet (R, Python, Stata)
- QuantEcon
Stata to Python Equivalents
- Daniel M. Sullivan
Pandas comparison with Stata
Stata Coding Guide
- Julian Reif
The Stata Guide on Medium
/
Stata-schemes
- Asjad Naqvi
Germán Rodríguez -
Stata + R + GLMs + Multilevel + Survival + Demography
Stata instructions for research projects
Quick Stata Tips
Top 25 Stata Visualizations With Full Code
Bayesian Statistics
Richard McElreath -
Statistical Rethinking: A Bayesian Course with Examples in R and Stan (& PyMC3 & brms & Julia)
Aki Vehtari -
Bayesian Data Analysis course
(R)
Robert Tucci -
Bayesuvius: a visual dictionary of Bayesian Networks and Causal Inference
Basic CS Lectures
The Missing Semester of Your CS Education
Software Carpentry
Harvard CS50
NormConf: The NormCore Tech Conference
MIT:
Introduction To Computer Science And Programming
/
Introduction To Computer Science And Programming In Python
/
Software Construction
/
Introduction To Computational Thinking And Data Science
Bash
pure bash bible
useful bash scripts shared by economists:
Ed Rubin
,
John Horton
OS
macOS Setup Guide
Mac Setup
The Unix Shell
- Software Carpentry
Corey Schafer's youtube channel
(very beginner-friendly videos for almost all basic things about mac, python, git, etc.)
Terminal:
here
,
here
,
here
The Art of Command Line
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.
Bruno, R. (2016).
Version control systems to facilitate research collaboration in economics
. Computational Economics, 48(3), 547-553.
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
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
A LaTeX Template for Economics Papers
LaTeX Table Hints and Tips
Modern LaTeX
Latex templates (Slide & Article)
- Kyle Butts
LaTeX Usage Notes
annotated_latex_equations
Draw DAGs with TikZ
For Beautiful Presentations - Use
PowerPoint
BEAMER
A LaTeX Power Up
/
A Basic Beamer Power Up
- Natalia Emanuel
latex-math tips
/
latex-paper template
(
explanation
) / [latex-slide template](LaTeX template for academic presentations) (
explanation
) - Pascal Michaillat
Beamer theme:
Jambro Beamer theme
Markdown
The Markdown Guide
Markdown Reference
- typora (some
Japanese
introduction
on typora)
Regex
Learn regex the easy way
Online regex tester and debugger
(also
this
)
AutoRegex
AI-Powered Regular Expression Solver
Visualization
Schwabish, J. A. (2014).
An economist's guide to visualizing data
. Journal of Economic Perspectives, 28(1), 209-34.
Nicolas P. Rougier -
Scientific Visualization – Python & Matplotlib
/
Scientific visualization Course
/
Matplotlib cheat sheet
Some Data visualizations in Python
Python Plotting for Exploratory Data Analysis
from Data to Viz
-
The Python Graph Gallery
/
The R Graph Gallery
Kieran Healy -
Data Visualization - A practical introduction
ggplot2: Elegant Graphics for Data Analysis
Claus O. Wilke -
Fundamentals of Data Visualization
Friends Don't Let Friends Make Bad Graphs
(R)
Unsorted
(a real)
Econ RA Guide
Aruoba, S. B., & Fernández-Villaverde, J. (2018).
A comparison of programming languages in economics
.
Awesome Scientific Writing
awesome-causality-algorithms
MATLAB–Python–Julia cheatsheet
Merely Useful
(python and r lecture)
Computing in Optimization and Statistics 2017
The Programming Historian
(lessons on digital tools, methods, and research processes)
GDSGE: A Toolbox for Solving DSGE Models with Global Methods
(matlab)
Course and program information for Agent-Based Computational Economics (ACE), Agent-Based Modeling (ABM), and related topics
Economics Simulations
(an interactive educational application developed to simulate and visualize various statistical concepts)
10 Fundamental Theorems for Econometrics
Numerical Tours of Data Sciences in Matlab, Python and Julia
Introduction to Modern Causal Inference
Other Econ Lectures on Github
Analysis of Human Capital
-
Labor Economics
/
Econometrics of Human Capital
Joao B. Duarte -
Advanced Macro
Bryan S. Graham -
Econometrics
Alfred Galichon -
Advanced Topics in Microeconometrics
Dietz Vollrath -
(UG) Growth
Ömer Özak -
Economic Growth and Comparative Development
/
Macroeconomics II
Jonathan Dingel -
International Macroeconomics and Trade
David Ubilava -
(UG) Agricultural Markets
Ivan Rudik -
Environmental and Resource Economics
José Luis Montiel Olea -
IntroEconometrics-Ph.D
/
TimeSeries-UG
Jonathan Conning -
Development Microeconomics
/
(UG) International Trade
Maximilian Kasy -
Labor Economics (UG)
/
Empirical research on economic inequality
Florian Oswald - graduate labor (
2018
)
Thibaut Lamadon -
Micro-econometric methods (UG)
/
Big data tools for economics (UG)
/
Topics in Labor (PhD)
Links to Other Econ Resources
Jennifer Doleac -
Advice for current and aspiring academic economists
Amanda Y. Agan -
Writing, Presentation, and Refereeing Advice
Ryan B Edwards -
Resource
Masayuki Kudamatsu -
Tips 4 Economists
Jonathan Dingel -
Research resources that I recommend
/
Advice resource
AEA-CSWEP -
Mentoring Reading Materials
/
Professional Development Resources
Mizuhito Suzuki -
Resources
Christoph Kronenberg -
Resources
Christine Cai -
Public Goods
Brendan Price -
Resources
Alex Albright -
(mainly R) Resources
Claes Bäckman -
Resources
Advice for Phd Students in Economics
Open Source Agenda is not affiliated with "Guide2EconRA" Project. README Source:
Alalalalaki/Guide2EconRA
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Dec 11, 2022
How to Choose Which Programming Language to Learn First?
From the blog
Dec 11, 2022
How to Choose Which Programming Language to Learn First?
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