Undergraduate Textbooks
Introductory Econometrics: A Modern Approach
By Jeffrey M. Wooldridge (2025, 8th Edition) - This textbook contains a comprehensive treatment of undergraduate econometrics. The book is a bit more technical than some other undergraduate texts (like Stock and Watson's Introduction to Econometrics), but most of the advanced mathematics is left as optional material. Wooldridge explains concepts very clearly. The topic coverage goes well beyond the multiple regression model, hitting important topics like binary-choice models, panel-data models, and forecasting techniques. Examples are abundant, and many end-of-chapter exercises (based on real datasets) provide students the opportunity to fully absorb the book's material.
Using R for Introductory Econometrics
By Florian Heiss (2020, 2nd Edition) - This book provides an introduction to R by providing code and scripts that follow closely to the examples in Wooldridge's Introductory Econometrics textbook. This book provides a great way to give students a background in R, even if they do so on a self-study basis.
Using Python for Introductory Econometrics
By Florian Heiss (2024, 2nd Edition) - This book provides an introduction to Python by providing code that follows closely to the examples in Wooldridge's Introductory Econometrics textbook. This book provides a great way to give students a background in Python, even if they do so on a self-study basis.
Introduction to Econometrics
By James H. Stock and Mark W. Watson (2018, 4th Edition) - This textbook by Stock and Watson is an excellent option for a student's first exposure to econometrics. The book is extremely well-written, with interesting empirical examples used to motivate the importance of econometrics to the field of economics. The book is primarily targeted for a less theoretical course in econometrics, but there are several chapters that could be used in a more formal course.
Causal Inference: The Mixtape
By Scott Cunningham (2021) - This book by Cunningham is a recent entry among causal inference books for economists. It's a great alternative to Mostly Harmless Econometrics with very interesting applications (datasets and programs (Stata and R) all included). Additional resources: book website.
Mastering Metrics
By Joshua D. Angrist and Jörn-Steffen Pischke (2014) - This book by Angrist and Pischke is a gentler introduction to causal inference than their Mostly Harmless Econometrics (see below). The book can be used as a companion to Wooldridge or Stock-Watson in an undergraduate course or by itself as a standalone textbook in a second econometrics course. Additional resources: book website.
Graduate Textbooks
Econometric Analysis of Cross Section and Panel Data
By Jeffrey M. Wooldridge (2010, 2nd Edition) - Unlike many graduate econometrics textbooks, this book jumps right into the asymptotic treatment of linear regression models (rather than spending the first few chapters on finite-sample results). The topic coverage is impressive. The first part of the book devoted to estimation of linear regression models (single equation, multiple equation, with and without endogeneity). After a couple of chapters on the theory of different estimators (M-estimators, maximum likelihood estimators), the book proceeds to cover a wide range of models, including panel data models, binary choice models, censored/selection models, count data models, etc.
Econometric Analysis
By William H. Greene (2017, 8th Edition) - Greene's Econometric Analysis covers an impressive number of different topics, ranging from finite sample to asymptotic, cross-sectional to time-series, frequentist to Bayesian, and so on. The appendices themselves are extremely valuable, serving as review material on linear algebra and statistical theory (without having to reference other sources for these topics). Additional resources: book website.
Microeconometrics: Methods and Applications
By A. Colin Cameron and Pravin K. Trivedi (2005) - The authors cover an impressive amount of material in this textbook, covering nearly every model used in empirical microeconomics today. Illustrative examples and datasets are used throughout. Additional resources: Book website.
Mostly Harmless Econometrics
By Joshua D. Angrist and Jörn-Steffen Pischke (2005) - This book is not your standard econometrics textbook but is popular among empirical economists. Rather than focusing too much on theory and models, the authors use examples from published papers to illustrate some of the most common econometric techniques available to today's researchers. The book makes a nice companion to a more theoretical textbook. Additional resources: book website.
Bayesian Econometrics
Introduction to Modern Bayesian Econometrics
By Tony Lancaster (2004) - This book provides clear explanations and practical illustrations to introduce the Bayesian method for applied economists.
Contemporary Bayesian Econometrics and Statistics
By John Geweke (2005) - This book provides an introduction to Bayesian analysis that is grounded in the theory of inference and optimal decision making.
Bayesian Econometrics
By Gary Koop (2003) - The book focuses on models used by applied economists and the computational techniques necessary to implement Bayesian methods when doing empirical work.
Bootstrap
An Introduction to the Bootstrap
By Bradley Efron and R. J. Tibshirani (1994) - This book provides an easy-to-read introduction to the bootstrap.
An Introduction to Bootstrap Methods with Applications to R
By Michael R. Chernick and Robert A. LaBudde (2011) - This relatively short book provides a comprehensive guide to implementation of the bootstrap in the open-source statistical platform R.
Panel Data
Econometric Analysis of Panel Data
By Badi Baltagi (2021, 6th Edition) - This book covers a wide range of panel-data models (linear, non-linear, dynamic, etc) and their associated estimators.
Analysis of Panel Data
By Cheng Hsiao (2022, 4th Edition) - Prof. Hsiao has updated his classic book on panel data in this fourth edition and now covers many of the developments of the last 40 years.
Panel Data Econometrics
By Manuel Arellano (2003) - This book covers many panel-data topics, including a very complete treatment of dynamic linear panel-data models.
Time Series
Time Series Analysis
By James D. Hamilton (1994) - This book provides comprehensive treatments of vector autoregressions, generalized method of moments, unit roots, time-varying variances, and nonlinear time series models.
Analysis of Financial Time Series
By Ruey Tsay (2010) - This book provides a systematic introduction to financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data.
Applied Econometric Time Series
By Walter Enders (2014, 4th Edition) - This book introduces modern techniques and models for forecasting, interpreting, and testing hypotheses concerning economic data.
Introductory Econometrics for Finance
By Chris Brooks (2019, 4th Edition) - This book presents the most common empirical approaches in finance in a comprehensive manner that shows how econometrics is used in practice. It also includes detailed case studies to explain how the techniques are used in relevant financial contexts.
Additional Topics
Quantile Regression
By Roger Koenker (2005) - This book provides the first comprehensive treatment of quantile regression, encompassing many different models (linear vs nonlinear, parametric vs nonparametric).
An Introduction to Modern Econometrics Using Stata
By Christopher F. Baum (2006) - This book provides an excellent guide to econometrics using the Stata software package. Author's webpage for the book (including datasets, programs, and errata).
The Econometric Analysis of Network Data
By Bryan Graham and Aureo de Paula (2019) - This book serves as an entry point for advanced students, researchers, and data scientists seeking to perform analyze network data.