Introduction To Econometrics 3 / Edition 3

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Overview

Introduction to Econometrics has been significantly revised to include new developments in the field. The previous editions of this text were renowned for Maddala's clear exposition and the presentation of concepts in an easily accessible manner.
Features:
* New chapters have been included on panel data analysis, large sample inference and small sample inference
* Chapter 14 Unit Roots and Cointegration has been rewritten to reflect recent developments in the Dickey-Fuller (DF), the Augmented Dickey-Fuller (ADF) tests and the Johansen procedure
* A selection of data sets and the instructor's manual for the book can be found on our web site
Comments on the previous edition:
'Maddala is an outstanding econometrician who has a deep understaning of the use and potential abuse of econometrics...'
'The strengths of the Maddala book are its simplicity, its accessibility and the large number of examples the book contains...'
'The second edition is well written and the chapters are focused and easy to follow from beginning to end. Maddala has an oustanding grasp of the issues, and the level of mathematics and statistics is appropriate as well.'

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Product Details

  • ISBN-13: 9780471497288
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 4/24/2001
  • Edition description: REV
  • Edition number: 3
  • Pages: 664
  • Product dimensions: 1.41 (w) x 9.25 (h) x 7.50 (d)

Meet the Author

G.S. MADDALA passed away in June 1999 and had been a leading figure in the econometrics profession for more than three decades. At the time of his death, he held the University Eminent Scholar Professorship in the Department of Economics at Ohio State University. His previous university affiliations include Stanford University, University of Rochester and University of Florida.

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Table of Contents

Foreword.

Preface to the Second Edition.

Preface to the Third Edition.

Obituary.

INTRODUCTION AND THE LINEAR REGRESSION MODEL.

What is Econometrics?

Statistical Background and Matrix Algebra.
Simple Regression.
Multiple Regression.
VIOLATION OF THE ASSUMPTIONS OF THE BASIC MODEL.

Heteroskedasticity.
Autocorrelation.
Multicollinearity.
Dummy Variables and Truncated Variables.

Simultaneous Equations Models.
Nonlinear Regression, Models of Expectations, and Nonnormality.
Errors in Variables.
SPECIAL TOPICS.

Diagnostic Checking, Model Selection, and Specification Testing.
Introduction to Time-Series Analysis.
Vector Autoregressions, Unit Roots, and Cointegration.

Panel Data Analysis.
Large-Sample Theory.
Small-Sample Inference: Resampling Methods.
Appendix A: Data Sets.
Appendix B: Data Sets on the Web.
Appendix C: Computer Programs.
Index.

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