The fourth edition of Jeffrey Wooldridge’s textbook, Introductory Econometrics: A Modern Approach, lives up to its subtitle. This text exemplifies a modern approach to econometrics in its choice of topics and its treatment of standard material. Wooldridge recognizes that modern econometrics involves much more than ordinary least squares (OLS) with a few extensions to handle the special cases commonly encountered in econometric data. In addition to chapters on OLS, he includes chapters on current techniques of estimation and inference for time-series data, panel data, limited dependent variables, and sample selection. In his treatments of standard OLS and two-stage least squares, Wooldridge breaks new ground by concentrating on advanced statistical concepts instead of matrix algebra. A traditional approach to introductory econometrics would use advanced materials sections to give courses on matrix algebra and its applications in econometrics. In contrast, Wooldridge uses the advanced sections of his text to introduce recently developed statistical concepts and techniques. This approach leads to a text with greater breadth than is usual in books of this type. This book is equally useful for advanced undergraduate study, as the basis of a survey course at the graduate level, or as a conceptual supplement to advanced courses. The fourth edition contains new material on the smearing estimator after log-linear OLS, expanded treatments of least-absolute-deviations estimators, linear models for heteroskedastic data, Chow tests for panel data, and panel-data methods for cluster samples. The result is that an excellent introductory book has been made even better.