Econometrics lecture notes, slides and books
Here you can find links to resource about Econometrics and related fields, including statistics, probability and machine learning!
(Last update: June 2023)
Time Series Econometrics
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Alex Aue's Time Series Analysis
Friendly introduction to Time Series Analysis, covering key principles (including spectral methods) and examples in R. PDF
Bruce Hansen's Advanced Time Series and Forecasting
Set of slides on time series econometrics and forecasting, covering most aspects on this topic. Link
Frank Diebold's Time-Series Econometrics: a concise course
A modern and concise master's or PhD-level bookin econometric time series PDF
John Cochrane's Time Series for Macroeconomics and Finance
Evergreen notes introducing time series econometrics to economists. PDF
Peter Phillips' Lectures on Unit roots, Cointegration and Nonstationarity
Hand-written notes on theoretical time series econometrics, covering the classics (FCLTs, stoch. calculus, unit roots, etc.) PDF
Frank Diebold's Forecasting in Economics, Business, Finance and Beyond
A textbook on forecasting, mainly in a time series setting. PDF
Suhasini Subba Rao's Introduction to Time Series Analysis
A book covering modeling, prediction, nonlinear, frequency domain & coding in R. PDF
Jim Stock & Mark Watson's Time Series Econometrics
Slides covering time series, IV, dynamic factor models, HAC inference and more. PDF
Ambrogio Cesa-Bianchi's Primer on Vector Autoregressions
Slides covering the macroeconometrics of structural vector autoregressions. PDF
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Econometrics (general)
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Russell Davidson & James MacKinnon's Econometric Thory and Methods
The classic 2004 econometrics book, now freely downloadable. PDF
Russell Davidson & James MacKinnon's Foundations of Econometrics, vol I
An upgraded and shortened version of James and Russell's 2004 masterpiece. PDF
Russell Davidson & James MacKinnon's Foundations of Econometrics, vol II
The second spin-off from their 2004 econometrics book, covering the theory of nonlinear models and estimators. PDF
Russell Davidson & James MacKinnon's Estimation and inference in Econometrics
The classic 1993 econometrics book, now freely downloadable. PDF
Ivan Canay's Introduction to Econometrics
Slides and notes from a graduate econometrics course, covering a lot of topics. PDF
Frank DiTraglia's Advanced Econometrics
Slides and notes from a graduate course, covering model/moment selection in high dimensions & more. Link
Manuel Arellano's Class Notes
Rich set of lecture notes covering many topics in Econometrics. Link
Michael Creele's Econometrics
Graduate-level notes (1000 pp.) including examples in Julia and Gretl. PDF
Jack Lucchetti's Basic Econometrics
A book on foundational #Econometrics with matrix calculus. PDF
Grace McCormack's Notes on Econometrics I
Concise notes on statistics & econometrics for 1st-year PhDs in economics & political science. PDF
Victor Chernozhukov & Ivan Fernandez-Val Econometrics
Lecture notes covering GMM, bootstrap, program evaluation, treatment effects and much more. Link
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Microeconometrics/Causal Inference
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Paul Goldsmith-Pinkham's Applied Empirical Methods
PhD-level slides covering econometrics, from causal inference to applied MachineLearning. Link
Peng Ding's A first course in Causal Inference
Undergrad notes about the #statistics and #econometrics of causal inference. arXiv page
Michael Knaus' Causal machine learning course
A course at the master/PhD level with focus on program evaluation. Link
Scott Cunningham's Causal inference
A classic, easy-and-fun to read book on causal inference. Link
Miguel Hernan & Jamie Robins' Causal inference: what if
Online book by epidemiologists, presenting concepts of, and methods for, causal inference. Link
Peter Hull's Applied Metrics course
PhD-level slides covering econometrics, with emphasis on treatment effects and identification. Link
Nick Huntington-Klein's The Effect
Introductory book on causal inference based on observational data. Link
Christophe Gaillac's Machine learning for Econometrics
Notes focusing on high-dimensional methods, treatment effects and synthetic controls. PDF
Jonas Peters, Dominik Janzing, and Bernhard Scholkopf's Elements of Causal Inference
A book on causal inference and learning by a team of statisticians. PDF
Matt Blackwell's User guide to statistical inference and regression
online tutorial for learning the fundamentals of regression. Link
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Financial Econometrics
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Kevin Sheppard's Financial Econometrics Notes
600 pages of econometrics, covering cross-sectional & time series data, with a special emphasis on financial applications. PDF
Alois Geyer's Basic Financial Econometrics
Set of introductory lecture notes covering the basics - from regression to state space models - with many financial applications. PDF
Todd Gormley's Empirical Methods in Corporate Finance
Lecture notes covering cross-sectional and panel data methods, with emphasis on financial applications. PDF
Paul Soderlind's Notes in Financial Econometrics
Lecture notes covering the econometrics of volatility modeling, asset pricing and risk management. PDF
Christophe Hurlin's Introduction to Financial Econometrics
1000 master-level slides on financial econometrics. PDF
Paul Soderlind's Econometrics for Finance
PhD-level Lecture notes with a finance-oriented approach to classic Econometrics. PDF
Ralph Koijen & Stijn Van Nieuwerburgh's Empirical Asset Pricing
Lecture notes giving an introduction to empirical asset pricing. Link to course page.
Ana Trisovic's Practical guide to Climate Econometrics
An online tutorial providing an introduction to the econometrics of climate change. Link
Probability, Statistics and Machine Learning
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Jesús Fernández-Villaverde's Machine Learning for Macroeconomics
Comprehensive slides journey, covering most crucial topics. Link to Jesus' page
Michael Gutman's Pen-and-paper exercises in machine learning
A collection of (mostly) pen-and-paper exercises in machine learning. PDF
Kevin Patrick Murphy's Probabilistic Machine Learning: an introduction
An introduction to Machine Learning via probabilistic modeling and decision theory. PDF
Kevin Patrick Murphy's Probabilistic Machine Learning: advanced topics
Follow up book on Machine Learning via probabilistic modeling and decision theory. PDF
Trevor Hastie, Rob Tibshirani and Jerome Friedman's Elements of Statistical Learning
The most famous introduction to statistical learning. PDF
Mykel Kochenderfer, Tim Wheeler & Kyle Wrayichael Gutman's Algorithms for decision making
A broad introduction to algorithms for decision making under uncertainty. Not targeting economists. PDF
Suhasini Subba Rao's Advanced statistical inference
Free book covering the essential concepts as well as non-standard problems. PDF
Lars Peter Hansen and Tom Sargent's Risk, Uncertainty, and Value
A rigorous treatment of stochastic process theory for economists. PDF
Marco Lippi's notes on Discrete Stochastic Processes
Set of notes covering various aspects of time series econometrics. Twitter thread for links here.
Rick Durrett's Essentials on Stochastic Processes
A book on the theory of stochastic processes, from Markov Chain to applications in math finance. PDF
Rick Durrett's Probability (theory and examples)
A wonderful free book on probability. PDF
James Norris' Probability lecture notes
Introductory and advances sets of lecture notes on probability. Twitter thread
Gilbert Strang's "Zoomnotes" for Linear Algebra
Introductory notes on linear algebra from the "master". PDF
Frank Pinter's Linear Algebra for Econometrics
Introductory notes on linear algebra targeted to econometric applications. PDF
Software for Econometrics
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Kevin Sheppard's Introduction to Python for Econometrics, Statistics and Data Analysis
A book for learning Python, dedicated to econometricians and statisticians. PDF
Kevin Sheppard's Econometrics and Statistics Analysis in MatLab
A book for learning Matlab, dedicated to econometricians and statisticians. PDF
Fabian Raters' Python for Econometrics
Material on numerical programming with Python, with simple examples and real-world applications. Link
Florian Heiss & Daniel Brunner's Using Python for Introductory Econometrics
Introductory econometrics book based on coding in Python. PDF
Christopher Hanck et al. Introduction to Econometrics with R
A complement to Stock & Watson's textbook based on coding in R. PDF
Florian Heiss' Using R for Introductory Econometrics
Introductory econometrics book based on coding in R. PDF
Lisa Schopohl, Robert Wichmann & Chris Brooks' R guide to Introductory Econometrics for Finance
A guide complementing Chris' book with R codes. PDF
Christoph Scheuch, Stefan Voigt & Patrick Weiss' Tidy Finance with R
A financial Economics online book which integrates applied finance (including MachineLearning) with R coding. Link
Jesse Perla, Tom Sargent and John Stachurski's Quantitative Economics with Julia
A set of lecture notes on quantitative economic modeling, based on coding in Julia. Link
Florian Heiss & Daniel Brunner's Using Julia for Introductory Econometrics
Introductory econometrics book based on coding in Julia. PDF
Lisa Schopohl, Robert Wichmann & Chris Brooks' STATA guide to Introductory Econometrics for Finance
A guide complementing Chris' book with STATA codes. PDF
Lee Adkins's Using gretl for Principles of Econometrics
A book for learning econometrics using GRETL. PDF
Arthur Turrell's Coding for Economists
Online guide on the general principles of computer programming for economists, which can later be applied to any language. Link
Grant McDermott's Data Science for Economists
An online guide full of practical tools & techniques essential to any economic project involving data. Link