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Introduction to Econometrics, Fourth Edition


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Authors:
James H. Stock and Mark W. Watson
Publisher: Pearson
Copyright: 2018
ISBN-13: 978-0-13-446199-1
Pages: 800; hardcover
Authors:
James H. Stock and Mark W. Watson
Publisher: Pearson
Copyright: 2018
ISBN-13:
Pages: 800; eBook
Authors:
James H. Stock and Mark W. Watson
Publisher: Pearson
Copyright: 2018
ISBN-13:
Pages: 800; Kindle

Comment from the Stata technical group

Introduction to Econometrics, Fourth Edition, by James H. Stock and Mark W. Watson, provides an outstanding introduction to econometrics. They use the principle that "interesting applications must motivate the theory and the theory must match the applications" to write a rigorous text that makes you want to keep reading to find out how the story ends. Using an ingenious set of real-world questions and answers, they produced an excellent introduction to estimation, inference, and interpretation in econometrics.

The text makes advanced statistical concepts easily understandable. For instance, the current econometric approach to analyzing linear models combines assumptions on the conditional moments of random variables and large-sample theory to derive estimators and their properties. This textbook provides an accessible introduction to this technique and its application to cross-sectional data, panel data, and time-series regression.

The text provides an excellent introduction to causal inference and to understanding the role of regression as a tool for causal inference.

The fourth edition provides an excellent introduction to prediction and to some key concepts and methods used in big-data analysis and machine learning. This edition distinguishes between econometrics for causal inference and econometrics for prediction early in the text. In the new chapter on prediction with many regressors and big data, the authors discuss some essential topics in prediction, including cross validation, ride regression, and the Lasso.

The coverage and level of this text make it an excellent choice for undergraduate study, as a supplement to advanced courses, or as a refresher course for researchers that want a quick introduction to modern parametric econometrics.

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