Basic Econometrics
5th Edition
Published on 16. November 2008
Book
Hardback
944 pages
978-0-07-337577-9 (ISBN)
Description
Gujarati and Porter's Basic Econometrics provides an elementary but comprehensive introduction to econometrics without resorting to matrix algebra, calculus, or statistics beyond the elementary level. With the addition of over 100 new data sets, as well as significantly updated research and examples, the Fifth Edition responds to important developments in the theory and practice of econometrics. Basic Econometrics is widely used by students of all fields as the expanded topics and concrete applications throughout the text apply to a broad range of studies.
More details
Edition
5th edition
Language
English
Place of publication
United States
Publishing group
McGraw-Hill Education - Europe
Target group
Professional and scholarly
Illustrations
56 Illustrations
Dimensions
Height: 262 mm
Width: 229 mm
Thickness: 36 mm
Weight
1837 gr
ISBN-13
978-0-07-337577-9 (9780073375779)
Schweitzer Classification
Other editions
New editions
Damodar N. Gujarati
Basic Econometrics (Int'l Ed)
Book
01/2009
5th Edition
McGraw Hill Higher Education
€77.98
Article not available
Persons
After teaching for more than 28 years at the City University of New York, He is currently a professor of Economics in the Department of Social Sciences at the U.S. Military Academy at West Point, New York. Dr. Gujarati received his M.Com. degree from the University of Bombay in 1960, his M.B.A. degree from the University of Chicago in 1963, and his Ph.D. degree from the University of Chicago in 1965. Dr. Gujarati has published extensively in recognized national and international journals, such as the Review of Economics and Statistics, the Economic Journal, the Journal of Financial and Quantitative Analysis, the Journal of Business, the American Statistician, and the Journal of Industrial and Labor Relations.
Content
Part I: Single-Equation Regression Model
Chapter 1: The Nature of Regression Analysis
Chapter 2: Two-Variable Regression Analysis: Some Basic Ideas
Chapter 3: Two Variable Regression Model: The Problem of Estimation
Chapter 4: Classical Normal Linear Regression Model (CNLRM)
Chapter 5: Two-Variable Regression: Interval Estimation and Hypothesis Testing
Chapter 6: Extensions of the Two-Variable Linear Regression Model
Chapter 7: Multiple Regression Analysis: The Problem of Estimation
Chapter 8: Multiple Regression Analysis: The Problem of Inference
Chapter 9: Dummy Variable Regression Models
Part II: Relaxing the Assumptions of the Classical Model
Chapter 10: Multicollinearity: What happens if the Regressor are Correlated
Chapter 11: Heteroscedasticity: What Happens if the Error Variance is Nonconstant?
Chapter 12: Autocorrelation: What Happens if the Error Terms are Correlated
Chapter 13: Econometric Modeling: Model Specification and Diagnostic Testing
Part III: Topics in Econometrics
Chapter 14: Nonlinear Regression Models
Chapter 15: Qualitative Response Regression Models
Chapter 16: Panel Data Regression Models
Chapter 17: Dynamic Econometric Model: Autoregressive and Distributed-Lag Models.
Part IV: Simultaneous-Equation Models
Chapter 18: Simultaneous-Equation Models.
Chapter 19: The Identification Problem.
Chapter 20: Simultaneous-Equation Methods.
Chapter 21: Time Series Econometrics: Some Basic Concepts
Chapter 22: Time Series Econometrics: Forecasting
Appendix A: Review of Some Statistical Concepts
Appendix B: Rudiments of Matrix Algebra
Appendix C: The Matrix Approach to Linear Regression Model
Appendix D: Statistical Tables
Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA
Appendix F: Economic Data on the World Wide Web
Chapter 1: The Nature of Regression Analysis
Chapter 2: Two-Variable Regression Analysis: Some Basic Ideas
Chapter 3: Two Variable Regression Model: The Problem of Estimation
Chapter 4: Classical Normal Linear Regression Model (CNLRM)
Chapter 5: Two-Variable Regression: Interval Estimation and Hypothesis Testing
Chapter 6: Extensions of the Two-Variable Linear Regression Model
Chapter 7: Multiple Regression Analysis: The Problem of Estimation
Chapter 8: Multiple Regression Analysis: The Problem of Inference
Chapter 9: Dummy Variable Regression Models
Part II: Relaxing the Assumptions of the Classical Model
Chapter 10: Multicollinearity: What happens if the Regressor are Correlated
Chapter 11: Heteroscedasticity: What Happens if the Error Variance is Nonconstant?
Chapter 12: Autocorrelation: What Happens if the Error Terms are Correlated
Chapter 13: Econometric Modeling: Model Specification and Diagnostic Testing
Part III: Topics in Econometrics
Chapter 14: Nonlinear Regression Models
Chapter 15: Qualitative Response Regression Models
Chapter 16: Panel Data Regression Models
Chapter 17: Dynamic Econometric Model: Autoregressive and Distributed-Lag Models.
Part IV: Simultaneous-Equation Models
Chapter 18: Simultaneous-Equation Models.
Chapter 19: The Identification Problem.
Chapter 20: Simultaneous-Equation Methods.
Chapter 21: Time Series Econometrics: Some Basic Concepts
Chapter 22: Time Series Econometrics: Forecasting
Appendix A: Review of Some Statistical Concepts
Appendix B: Rudiments of Matrix Algebra
Appendix C: The Matrix Approach to Linear Regression Model
Appendix D: Statistical Tables
Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA
Appendix F: Economic Data on the World Wide Web