Resources for Students

• Considering a PhD and/or a career in academia?
  I recommend reading Katabasis by R.F. Kuang and, if you are so inclined, Principle of Mathematical Analysis by Walter Rudin 

• Want to get a taste of first year PhD level econometrics cousework?
  Try the first 10 chapters in Bruce E. Hansen's Econometrics and some topics of interest from Applied Causal Inference Powered by ML and AI by Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, and Vasilis Syrgkanis

• Interested in becoming an econometrician?
  Here are some lecture videos, notes, and textbooks that I found rather helpful for my line of work. 

  • Lecture videos on Probability Theory and Stochastic Processes by Todd Kemp

  • Empirical Process Theory and Advanced Probability for Statisticians by Kengo Kato

  • High-Dimensional Probability by Roman Vershynin

  • Decoupling: from Dependence to Independence by Victor de la Peña and Evarist Giné