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Econometric Analysis (4th Edition)

William H. Greene

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ISBN 10: 0130132977 / ISBN 13: 9780130132970
Published by Prentice Hall 1999-07-28, 1999
Used Condition: Good Hardcover
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Bibliographic Details

Title: Econometric Analysis (4th Edition)

Publisher: Prentice Hall 1999-07-28

Publication Date: 1999

Binding: Hardcover

Book Condition:Good

Edition: 4th.

About this title

Synopsis:

For graduate-level courses in Introduction to Econometrics. A standard text/reference in courses that include basic techniques in regression analysis and extensions used when linear models prove inadequate or inappropriate. Areas of application include Economics, Sociology, Political Science, Medical Research, Transport Research, and Environmental Economics. This book introduces students to the broad field of applied econometrics. An effective bridge to both on-the-job problems and to the professional literature, it features extensive applications and presents sufficient theoretical background to enable students to recognize new variants of the models that they learn about here as merely natural extensions that fit within a common body of principles.

From the Back Cover:

An effective bridge to both on-the-job problems and to the professional literature, this volume is recognized as a standard reference on economictrics for Economics, Sociology, Political Science, Medical Research, Transport Research, Environmental Economics, etc. Featuring extensive applications and sufficient theoretical background, it surveys the broad field of applied econometrics--including basic techniques in regression analysis and some of the rich variety of models that are used when the linear model proves inadequate or inappropriate. Includes a substantive review of appropriate matrix algebra, statistical theory, and mathematical statistics. Offers a customized version of LIMDEP and a large number of sample data sets. Computation and Optimization. The Classical Multiple Linear Regression Model--Specification and Estimation. Inference and Prediction. Functional Form, Nonlinearity, and Specification. Large Sample Results and Alternative Estimators for the Classical Regression Model. Nonlinear Regression Models. Nonspherical Disturbances, Generalized Regression and GMM Estimation. Heteroscedasticity. Autocorrelated Disturbances. Models for Panel Data. Systems of Regression Equations. Simultaneous Equations Models. Regressions with Lagged Variables. Time-Series Models. Models with Discrete Dependent Variables. Limited Dependent Variable and Duration Models. A reference for analysts, consultants, and researchers in many fields.

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