Using Econometrics
A Practical Guide: United States Edition
5th Edition
Published on 28. June 2005
Book
Hardback
656 pages
978-0-321-31649-3 (ISBN)
Description
Combining single-equation linear regression analysis with intuitive real-world examples and exercises is key to the success of Using Econometrics. Clear writing and a practical approach to econometrics that eschews the use of complex matrix algebra and calculus evidence this essential text's accessibility.
As the subtitle, A Practical Guide, implies, this book is aimed not only at beginning econometrics students, but also at regression users looking for a refresher and at experienced practitioners who want a convenient reference.
As the subtitle, A Practical Guide, implies, this book is aimed not only at beginning econometrics students, but also at regression users looking for a refresher and at experienced practitioners who want a convenient reference.
More details
Edition
5th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 239 mm
Width: 204 mm
Thickness: 29 mm
Weight
1170 gr
ISBN-13
978-0-321-31649-3 (9780321316493)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
A. Studenmund | A. H. Studenmund
Practical Guide to Using Econometrics, A, Global Edition
Book
01/2017
7th Edition
Pearson Education Limited
€105.99
Shipment within 10-20 days
Previous edition
Book
08/2000
4th Edition
Pearson
€100.43
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. Hypothesis Testing.
II. 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.
16. Statistical Principles.
1. An Overview of Regression Analysis.
2. Ordinary Least Squares.
3. Learning to Use Regression Analysis.
4. The Classical Model.
5. Hypothesis Testing.
II. 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.
16. Statistical Principles.