Badi H. Baltagi

Econometrics (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

"A most useful text for an econometrics course. There are not many introductions to econometrics which approach the relevant material so consistently from the viewpoint of the student. The book is also well suited for self study and can be recommended to everybody who is in need to quickly acquire the basics of the field."

Prof. Walter Krämer, University of Dortmund

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 410
• Erscheinungstermin: 25. Mai 2011
• Englisch
• ISBN-13: 9783642200595
• Artikelnr.: 44133751

Autorenporträt

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.

Inhaltsangabe

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.