The following is a list of free online resources created by leading economists and used in degree programmes at top universities. They cover everything from real analysis to data analysis with Python and R, helping you deepen your understanding of theoretical macroeconomics, econometrics, and mathematics courses while bridging the gap between theory and applied research. I hope they prove just as valuable to you as they did to me.
QuantEcon
Prof Thomas Sargent and John Stachurski's lecture notes on quantitative economic modeling with Python.
DIY Macroeconomic Model Simulation
Prof Karsten Kohler & Franz Prante's online textbook on macroeconomic model simulation with Python and R.
Macroeconomics: Institutions, Instability and Inequality
Prof Wendy Carlin & David Soskice's advanced undergraduate textbook from University College London.
Advanced Macroeconomics
David Murakami's notes from Oxford’s 2nd-year MPhil course.
PhD Macro Book
A comprehensive textbook in modern macroeconomics for 1st-year PhD students.
Recursive Macroeconomics
Prof Thomas Sargent's lectures from 2nd-year PhD course at New York University
Distributional Macroeconomics
Prof Benjamin Moll’s lecture notes from 1st and 2nd-year PhD courses at Harvard and Princeton.
Advanced Macroeconomic Theory
Prof Eric Sims' lecture notes from the 1st-year PhD course at the University of Notre Dame.
Coding for Economists
Dr Athur Turrell's online guide for economists on coding with Python and R.
Econometrics Academy
Dr Ani Katchova's lectures on graduate applied econometrics with STATA and R.
ML4Econ
Prof Itamar Caspi's lecture notes and code repository on applied machine learning for economics using R.
Econometrics
Prof Ben Lambert's lectures and problem sets covering undergraduate and graduate econometric theory.
Advanced Econometrics
Prof Felix Pretis' lecture notes from Oxford's 2nd-year MPhil course.
Machine Learning & Causal Inference
Prof Susan Athey's lectures on machine learning methods for causal inference in economics.
Grant Sanderson's lectures on the essence of linear algebra.
Dr Casey Rodriguez's lectures from undergraduate real analysis at Massachusetts Institute of Technology.
Stochastic Calculus
Prof John Cochrane's lectures on stochastic differential equations from the University of Chicago.
All resources listed here are publicly available and are not my own work. Full credit is given to the original authors and contributors for producing and sharing these valuable resources.