Using Econometrics
A Practical Guide
3rd Edition
Published on 12. February 1997
Book
Mixed media product
670 pages
978-0-673-52486-7 (ISBN)
Description
This revolutionary text covers single-equation linear regression analysis in an easy-to-understand format that emphasizes real-world examples and exercises. This intuitive approach avoids matrix algebra and relegates proofs and calculus to the footnotes. Clear, accessible writing and numerous exercises provide students with a solid understanding of applied econometrics. This new approach is accessible to beginning econometrics students as well as experienced practitioners.
More details
Edition
3rd edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Width: 241 mm
Thickness: 38 mm
Weight
985 gr
ISBN-13
978-0-673-52486-7 (9780673524867)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Book
08/2000
4th Edition
Pearson
€54.55
Article exhausted; check for reprint
Content
I. THE BASIC REGRESSION MODEL.
1. An Overview of Regression Analysis.
2. Ordinary Least Squares.
3. Learning to Use Regression Analysis.
4. The Classical Model.
5. Basic Statistics and Hypothesis Testing.
III. VIOLATIONS OF THE CLASSICAL ASSUMPTIONS.
6. Specification: Choosing the Independent Variables.
7. Specification: Choosing a Functional Form.
8. Multicollinearity.
9. Serial Correlation.
10. Heteroskedasticity.
11. A Regression User's Handbook.
III. EXTENSIONS OF THE BASIC REGRESSION MODEL.
12. Time-Series Models.
13. Dummy Dependent Variable Techniques.
14. Simultaneous Equations.
15. Forecasting.
1. An Overview of Regression Analysis.
2. Ordinary Least Squares.
3. Learning to Use Regression Analysis.
4. The Classical Model.
5. Basic Statistics and Hypothesis Testing.
III. VIOLATIONS OF THE CLASSICAL ASSUMPTIONS.
6. Specification: Choosing the Independent Variables.
7. Specification: Choosing a Functional Form.
8. Multicollinearity.
9. Serial Correlation.
10. Heteroskedasticity.
11. A Regression User's Handbook.
III. EXTENSIONS OF THE BASIC REGRESSION MODEL.
12. Time-Series Models.
13. Dummy Dependent Variable Techniques.
14. Simultaneous Equations.
15. Forecasting.