Research
Before Grad School
- Should you get a PhD? (by Tatyana Deryugina)
- Econ RA Guide (by Coly Elhai et al.)
- Tips for Applied Micro RAs (by Livia Alfonsi)
- Guide to Applying for Ph.D. programs in Econ (by Lakshya Narula et al.)
- PhD Application Tips (by Riccardo Di Cato)
Grad School and the Job Market
- Advice for Phd Students in Economics (by Chris Roth & David Schindler)
- Advice for Academic Research (by Ricardo Dahis)
- Keeping track of the literature (by Eugene Katsevich)
- The 12 Step Program for Grad School (by Eric Zwick)
- Slides on public speaking for academic economists (especially for grad students) (by Rachael Meager)
- How to Give an Applied Micro Talk (by Jesse M. Shapiro)
- LaTeX’s Beamer slides template (by Kyle Butts)
- Writing and Presentation Advice (by Amanda Yagan)
- Writing Tips for Economics Research Papers (by Plamen Nikolov)
- Writing a JMP (by Tatyana Deryugina)
- How I Learned to Stop Worrying and Love the Job Market (by Eric Zwick)
- General resources: writing paper, the editorial process, and job (market) advice (by Jan Sauermann)
- Job market debrief (by Kerry Siani & Kim Fe Cramer)
After Grad School
- How to be a productive researcher (by Tatyana Deryugina)
- Tips for new tenure-track professors in R1 economics departments (by Tyler Ransom)
- How to know which journal to submit your manuscript to (by Tatyana Deryugina)
- How to write a good referee report (by Tatyana Deryugina)
- When to give up on a paper (by Tatyana Deryugina)
- What to do after a rejection (by Tatyana Deryugina)
- Mentoring Reading Materials (by the American Economic Association)
Applied Econometrics
- Course videos and slides: Applied Empirical Methods (by Paul Goldsmith-Pinkham)
- Grad Econometrics lecture slides (by Peter Hull)
- DiD resources (by Jonathan Roth)
- Current literature on diff-in-diff (by Asjad Naqvi)
- Data science for economists (by Grant R. McDermott)
- Causal ML for Policy Evaluation/Learning (by Michael Knaus)
- Machine Learning and Economics: An Introduction (by Susan Athey, Jann Piess, and Stefan Wager)
- Text Data in Economics (by Elliott Ash)
- Causal Inference (by Stefan Wager)
- Four Lectures on Causality (by Jonas Peters)
- Nonlinear Econometric Analysis (by Maximilian Kasy)