Badi H. Baltagi

Solutions Manual for Econometrics

• Broschiertes Buch

Produktbeschreibung

This Fourth Edition updates the "Solutions Manual for Econometrics" to match the Sixth Edition of the Econometrics textbook. It adds problems and solutions using latest software versions of Stata and EViews. Special features include empirical examples replicated using EViews, Stata as well as SAS. The book offers rigorous proofs and treatment of difficult econometrics concepts in a simple and clear way, and provides the reader with both applied and theoretical econometrics problems along with their solutions. These should prove useful to students and instructors using this book.

Produktdetails

• Classroom Companion: Economics
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-80157-1
• 4. Aufl.
• Seitenzahl: 444
• Erscheinungstermin: 8. Dezember 2022
• Englisch
• Abmessung: 235mm x 155mm x 24mm
• Gewicht: 668g
• ISBN-13: 9783030801571
• ISBN-10: 3030801578
• Artikelnr.: 61967300

Autorenporträt

Badi H. Baltagi is a Distinguished Professor of Economics and Senior Research Associate at the Center for Policy Research, The Maxwell School, Syracuse University (USA). Professor Baltagi is the current editor of Economics Letters, having previously served as the editor of Empirical Economics (1999-2018) and as the replication editor for the Journal of Applied Econometrics (2003-2018). He is a fellow of the Journal of Econometrics as well as Econometric Reviews and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory, as well as the Distinguished Authors Award from the Journal of Applied Econometrics.

Inhaltsangabe

What Is Econometrics?.- A Review of Some Basic Statistical Concepts.- Simple Linear Regression.- Multiple Regression Analysis.- Violations of the Classical Assumptions.- Distributed Lags and Dynamic Models.- 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.