Basic Econometrics
6th Edition
Will be published approx. on 1. December 2017
Book
Paperback/Softback
960 pages
978-981-4636-24-7 (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 Sixth 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.
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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