Introduction to Econometrics (Paperback)

Book Summary of Introduction To Econometrics
Introduction to Econometrics has been one of the most important textbooks in its field influencing several generations of students. G.S Maddala died in 1999 whilst he was completing the manuscript for the third edition. The time is right for a new edition and Kajal Lahiri is the ideal person to update the text. He was one of Maddala's closest colleagues and also has a high profile in the econometrics profession and is particularly noted for his work on panel data. The third edition of Introduction to Econometrics has been translated into Hungarian, Japanese and Portuguese.

Special Feature
Thorough revision of one of the leading international textbooks on econometrics A fresh, accessible and well-written introduction to econometrics. A pedagogical framework which sets it apart from its competitors. Contains a large number of worked examples. Kajal Lahiri is ideally placed to revise the text as he was one of G.S. Maddala's Closest colleagues and has used the book for many years. The web-based supplements, which include an instructor's manual and data sets, are revised. About The Author
G.S.Maddala was one of the leading figures in field of econometrics for more than 30 years until he passed away in 1999. At the time of his death, he held the University Eminent Scholar Professorship in the Department of Economics at Ohio State University. His previous affiliations include Stanford University, University of Rochester and University of Florida.
Kajal Lahiri is Distinguished Professor of Economics, and Health Policy, and Management and Behaviour at the State University of New York, Albany where he is also Director of the Econometric Research Institute. Professor Lahiri is an Honorary Fellow of the International Institute of Forecasters.

Table Of Contents
Part I Introduction and the Linear Regression Model
o What is Econometrics?
o Statistical Background and Matrix Algebra
o Simple Regression
o Multiple Regression
Part II Violation of the Assumptions of the Basic Regression Model
o Heteroskedasticity
o Autocorrelation
o Multicollinearity
o Dummy Variables and Truncated Variables
o Simultaneous Equation Models
o Diagnostic Checking, Model Selection, and Specification Testing
o Errors in Variables
Part III Special Topics
o Introduction to Time-Series Analysis
o Models of Expectations and Distributed Lags
o Vector Autoregressions, Unit Roots, and Cointegration
o Panel Data Analysis
o Small-Sample Inference: Resampling Methods
o Appendix
o Index