Essentials of Econometrics + Data CD
3rd Edition
Published on 16. March 2005
Book
496 pages
978-0-07-313594-6 (ISBN)
Description
This text provides a simple and straightforward introduction to econometrics for the beginner. The author's intent is to provide the student with a "user friendly," non-intimidating introduction to econometric theory and techniques. The book motivates students to understand econometric techniques through extensive examples, careful explanations, and a wide variety of problem material. The audience is undergraduate economics, agricultural economics, and business administration majors, MBA students and others in the social and behavioral sciences where econometric techniques, especially the techniques of linear regression analysis, are used.
More details
Edition
3rd edition
Language
English
Place of publication
United States
Publishing group
McGraw-Hill Education - Europe
Dimensions
Height: 229 mm
Width: 178 mm
Thickness: 25 mm
Weight
1030 gr
ISBN-13
978-0-07-313594-6 (9780073135946)
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Schweitzer Classification
Person
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
Chapter 1The Nature and Scope of EconometricsPART IBasics of Probability and StatisticsChapter 2 Review of Statistics I: Probability and Probability DistributionsChapter 3Characteristics of Probability DistributionsChapter 4Some Important Probability DistributionsChapter 5Statistical Inference: Estimation and Hypothesis TestingPART IIThe Linear Regression ModelChapter 6Basic Ideas of Linear Regression: The Two-Variable ModelChapter 7The Two-Variable Model: Hypothesis TestingChapter 8Multiple Regression: Estimation and Hypothesis TestingChapter 9Functional Forms of Regression ModelsChapter 10Dummy Variable Regression ModelsChapter 11Model Selection: Criteria and TestsPART IIIRegression Analysis In PracticeChapter 12Multicollinearity: What Happens if Explanatory Variable Are CorrelatedChapter 13Heteroscedasticity: What Happens If The Error Variance Is NonconstantChapter 14Autocorrelation: What Happens If Error Terms Are CorrelatedPART IVIntroduction to Simultaneous Equation ModelsChapter 15Simultaneous Equation ModelsChapter 16Selected Topics in Single Equation Regression Models