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Econometric Analysis, Eighth Edition


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Author:
William H. Greene
Publisher: Prentice Hall
Copyright: 2018
ISBN-13: 978-0-13-446136-6
Pages: 1,126  
Author:
William H. Greene
Publisher: Prentice Hall
Copyright: 2018
ISBN-13:
Pages: 1,126; eBook
Price: $0.00
Author:
William H. Greene
Publisher: Prentice Hall
Copyright: 2018
ISBN-13:
Pages: 1,126; Kindle
Price: $
Supplements:Author's website

Comment from the Stata technical group

William Greene’s Econometric Analysis has been the standard reference for econometrics among economists, political scientists, and other social scientists for almost thirty years. As of 2016, the book had been cited more than 60,000 times; in 2014, it was part of Google Scholar’s list of 100 most cited works over all fields and for all time. The newly released eighth edition is certain to continue that tradition. This book’s abundance of examples and emphasis on putting econometric theory to practical use make it valuable not only to graduate students taking their first course in econometrics, but also to students and professionals who engage in empirical research.

Part I of the book, chapters 1 to 6, covers regression modeling; properties of the least-squares estimator; inference and prediction; and tests for functional form and specification. Chapter 6 is of special interest. In this new edition, it introduces modern treatment effects concepts, such as regression discontinuity, as part of the basic analytical tool set in econometrics rather than a special topic to be presented in later chapters of the text.

Part II of the book, chapters 7 to 11, covers extensions and deviations of the basic framework presented in Part I. Chapter 7 covers nonlinear models and contains a new discussion of interaction effects. Chapter 8 covers instrumental variables and endogeneity and has been revised to include more current methods and applications. Chapters 9 and 10 generalize the linear regression model to allow for heteroskedasticity. Then, with the generalized least-squares (GLS) estimator already discussed in the context of nonspherical disturbances, Greene presents fixed- and random-effects panel-data models as straightforward extensions of least squares. Chapter 11, which deals with panel data, has many revisions relevant to current research and applications, much like Chapter 8.

Part III of the book, chapters 12 to 16, devotes one chapter to each of four popular estimation methods: the generalized method of moments, maximum likelihood, simulation, and Bayesian inference. Each chapter strikes a good balance between theoretical rigor and practical applications. Many newer discrete-choice models require evaluation of multivariate normal probabilities; to account for this, Chapter 15 includes a detailed discussion of the GHK simulator.

Part IV of the book, chapters 17 to 19, covers advanced techniques for microeconometrics. Chapter 17 details binary choice models for both cross-sectional and panel data. Part IV also includes bivariate and multivariate probit models; models for count, multinomial, and ordered outcomes; and models for truncated data, duration data, and sample selection.

Part V of the book, chapters 20 and 21, covers advanced techniques for macroeconometrics. Chapter 20, on stationary time series, describes estimation in the presence of serial correlation, tests for autocorrelation, lagged dependent variables, and ARCH models. Chapter 21, on nonstationary series, covers unit roots and cointegration. The chapters in Part V frequently use the results obtained in Part III on estimation. The book concludes with appendices on matrix algebra, probability, distribution theory, and optimization. These appendices are freely available at the book’s companion website.

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