Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics.

Covers the full breadth of econometric theory and methods with mathematical rigor while emphasizing intuitive explanations that are accessible to students of all backgrounds
Draws on integrated, research-level datasets, provided on an accompanying website
Discusses linear econometrics, time series, panel data, nonparametric methods, nonlinear econometric models, and modern machine learning
Features hundreds of exercises that enable students to learn by doing
Includes in-depth appendices on matrix algebra and useful inequalities and a wealth of real-world examples
Can serve as a core textbook for a first-year PhD course in econometrics and as a follow-up to Bruce E. Hansen’s Probability and Statistics for Economists

Includes bibliographical references (pages 1021-1031) and index.

"An introductory PhD-level textbook for one of the first and most foundational courses every economics graduate student must take"-- Provided by publisher.