Econometrics
5th Edition
Published on 25. May 2011
XV, 410 pages
978-3-642-20059-5 (ISBN)
Description
This textbook teaches some of the basic econometric methods and the underlying assumptions behind them. It also includes a simple and concise treatment of more advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specification testing and time series analysis. Each chapter has a set of theoretical exercises as well as empirical illustrations using real economic applications. These empirical exercises usually replicate a published article using Stata or Eviews.
More details
Series
Edition
5th ed. 2011
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Primary & secondary/elementary & high school
Illustrations
XV, 410 p. 49 illus.
File size
5,10 MB
ISBN-13
978-3-642-20059-5 (9783642200595)
DOI
10.1007/978-3-642-20059-5
Schweitzer Classification
Other editions
Additional editions
Badi H. Baltagi
Econometrics
Book
05/2011
5th Edition
Springer
€64.19
Article exhausted; check for reprint
Previous edition
Person
Badi H. Baltagi is distinguished Professor of Economics, and Senior
Research Associate at the Center for Policy Research, Syracuse
University. He received his Ph.D. in Economics at the University of
Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas A&M University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory.
Research Associate at the Center for Policy Research, Syracuse
University. He received his Ph.D. in Economics at the University of
Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas A&M University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory.
Content
Part 1: What Is Econometrics?.- Basic Statistical Concepts.- Simple Linear Regression.- Multiple Regression Analysis.- Violations of the Classical Assumptions.- Distributed Lags and Dynamic Models.- Part 2: The General Linear Model: The Basics.- Regression Diagnostics and Specification Tests.- Generalized Least Squares.- Seemingly Unrelated Regressions.- Simultaneous Equations Model.- Pooling Time-Series of Cross-Section Data.- Limited Dependent Variables.- Time-Series Analysis.
