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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

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

 

Econometrics (general)

Herman Bierens' Econometrics Lecture Notes

Notes covering undergrad, panel data, time series, semi- & non-parametric econometrics. [Unfortunately the Link is down]

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

 

Microeconometrics/Causal Inference

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

Matheus Facure's Causal inference for the brave and true

An online book on causal inference, MHE style. Link

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

Matias Cattaneo, Nicolas Idrobo & Roco Titiunik's Practical Introduction to Regression Discontinuity Designs

Accessible and practical guide for the analysis and interpretation of RDDs. Vol I (Foundations) PDF and Vol II (Extensions) PDF

Matt Blackwell's User guide to statistical inference and regression

online tutorial for learning the fundamentals of regression. Link

 

Financial Econometrics

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

Jesus Gonzalo's Unit root land

Introductory slides to the econometrics of non-stationary time series. PDF (handwritten), PDF

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

Jean-Marie Dufour's Properties of moments of random variables

Essential short notes for the econometrician's toolbox (more stuff on JM's page). 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

 

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

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