Summary Of The Book Econometric Analysis presents all the topics that are needed for a one-year course in the field of econometrics. The primary aim of this book is to provide elementary knowledge of the subject to the readers. It also adds the support of a large number of models that can be utilized in case the linear model turns out to be inappropriate or inadequate. The content has been designed to ensure that the readers thoroughly understand the models outlined. This is to ensure that in future they can easily recognize new forms of these models as natural extensions. In total, there are 22 chapters and each one covers different aspects of econometric analysis. The chapters presented include Nonspherical Disturbances - The Generalized Regression Model, Large Sample Properties Of The Least Squares And Instrumental Variables Estimators, Estimation Frameworks In Econometrics, Limited Dependent Variable And Duration Models, Simultaneous-Equations Models, and Functional Form And Structural Change. There are also 7 appendices at the end. They are Statistical Tables, Computation And Optimization, Estimation And Inference, Matrix Algebra, Large Sample Distribution Theory, and Probability And Distribution Theory. This edition, the fifth one, has been updated to make it easier to understand concepts, in-depth information of panel data, and time series, and to outline major advancements in the field. Readers are also provided with numerous solved examples, which give them a better understanding of the computations. Additionally, a balance has been created between theoretical aspects and practical ones, providing advanced students with challenging examples. Econometric Analysis also contains a link to a downloadable software application named EA/ LimDep, which is utilized extensively by government organizations and industries. This software can be used for carrying out most of the computations given in the chapters. It comes along with extra exercises and answers.

Table of Contents Introduction. The Classical Multiple Linear Regression Model. Least Squares. Large Sample Properties of the Least Squares and Instrumental Variables Estimators. Inference and Prediction. Functional Form and Structural Change. Specification Analysis and Model Selection. Nonlinear Regression Models. Nonspherical Disturbances—The Generalized Regression Model. Heteroscedasticity. Serial Correlation. Models for Panel Data. Simultaneous-Equations Models. Estimation Frameworks in Econometrics. Maximum Likelihood Estimation. The Generalized Method of Moments. Models with Lagged Variables. Time-Series Models. Models for Discrete Choice. Limited Dependent Variable and Duration Models

Includes bibliographical references (p. 959-994) and indexes.