Resources

Most of the information on this page is taken from the website of Christoph Kronenberg who I thank you for putting together such an useful list of resources.

Data Science

• Analyzing US Census Data by Kyle Walker
• EC 607 course by Grant McDermott
• Data Visualization: A practical introduction by Kieran Healy
• R for Data Science by Garrett Grolemund and Hadley Wickham
• Advanced R by Hadley Wickham
• Geocomputation with R by Robin Lovelace, Jakub Nowosad and Jannes Muenchow
• Spatial Data Science by Edzer Pebesma and Roger Bivand
• R Markdown: The Definitive Guide by Yihui Xie, JJ Allaire, and Garret Grolemund

Econometrics

Free text books on econometric methods with focus on causal inference

• Causal Inference Book by Jamie Robin and Miguel Hernan
• Causal Inference: The Mixtape by Scott Cunningham
• Econometrics by Bruce E. Hansen
• Data science for economists by Grant McDermott
• Library of Statistical Techniques (LOST) by Nick Huntington-Klein

Free video resources on econometric methods with a causal inference focus

• Causality - Inferring Causal Effects from Data by Jason Roy
• Introduction to the Causal Inference Bootcamp by Matt Masten
• Mastering Econometrics by Joshua Angrist
• Nick Huntington-Klein has several playlist covering Micro, Stata, R and Causality
• Ashley Hodgson has several playlist including Micro, Health Econ and Identification Strategies
• Andrew Baker's blog post on Difference in Differences
• Andrew Baker's slides on Difference in Differences
• DiD Resources from Jonathan Roth

Free coding resources

• Beautiful plots in R
• Stata Cheat Sheets
• Replication of Mostly Harmless Econometrics in Stata, R, Python and Julia.
• Fixest by Laurent Berge
• Library of Statistical Techniques (LOST)
• Torch-Choice: A PyTorch Package for Large-Scale Choice Modelling with Python

Other useful links

• PhD Guidance: How to Research by Garrett Johnson
• Flowchart to explain clustering and standard error issues in difference-in-differences by Patrick Button
• 10 things to know about many topics relating to causal inference
• DAGitty - a tool to draw DAGs and see testable implications, assumptions, etc. spelled out
• EZgif - a simple free online tool to make animated gifs (e.g. same graph over time for a presentation)
• Draw.io - a simple free online tool to make conceptual diagrams

Academic citizenship

• How to be a good discussant by Chris Blattmann
• Academic Presenting by Rachel Meager
• Refereeing 1 by Marc F. Bellemare
• Refereeing 2 by Tatyana Deryugina
• How to be Productive in Academia by Tatyana Deryugina
• Amanda Y. Agan has a good collection of writing and presentation advice on her web page
• Jennifer Doleac has an extensive and well-maintained resources section on her web page
• How to read papers like a professor by Michael Nelson

Academic writing

• Introduction Formula by Keith Head
• "Middle Bits" Formula by Marc F. Bellemare
• Conclusion Formula by Marc F. Bellemare
• The Ten Most Important Rules of Writing Your Job Market Paper by Claudia Goldin and Lawrence Katz - also applies to non-JMPs
• Plain English Campaign
• Reverse Outlining a guide to reverse outlining by the Writing Center of U. of Wisconsin-Madison
• Paper writing gone Hollywood by Jeffrey J. McDonnell in Science (2017)

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