Here are some resources that helped me tremendously (inspired by Javier Donna)

Job market candidates

• List compiled by Shoshana Vasserman

Computation

• Logit demand
  • Kenneth Train’s codes on mixed logit
  • Jason Blevin’s post on log sum of exponentials (what to do when my logit demand explodes?)
• Dynamic discrete choice
  • Victor Aguirregabiria’s compilation of codes on dynamic discrete choice
  • Jaap H. Abbring and Tobias J. Klein’s notes and codes on dynamic discrete choice
• Code optimization
  • Sparse grid for numerical integration
  • Ken Judd’s Computational Economics course on numerical methods
• Code repositories for published papers
  • AEA journals (AER, AEJ)
  • Econometrica
  • ReStud
  • Journal of Finance: scroll down on Wiley and click on supporting information
• Others
  • BU Research Computing Support’s guide on running batch jobs on a cluster and parallel computing with MATLAB
  • QuantEcon: a Jupyter notebook library for economics and finance
  • Matching data in financial databases

Notes

• Chris Conlon’s Panel Data Econometrics and IO
• Scott Cunningham’s Causal Inference: The Mixtape
• Jonathan Levin’s notes on market design and IO
• Kohei Kawaguchi’s IO

My go-to R packages

• Output LaTeX tables: stargazer, texreg (supports fixest), xtable
• Fixed effects for linear models: plm (at most 2-way, need clubSandwich for clustering, good for 1 fixed effect with many unique values), lfe (clustering, fast)
• Fixed effects for non-linear models: fixest (description), alpaca
• Data wrangling: dplyr, broom (turn regression results into a data frame), fastDummies