TY  - GEN
AU  - Studenmund, A. H. 
AU  - Johnson, Bruce K.
TI  - A practical guide to using econometrics
SN  - 9789332584914
U1  - 330.154 
PY  - 2017///
CY  - Noida
PB  - Pearson India
KW  - Econometrics
N2  - Using Econometrics: A Practical Guide offers students an innovative introduction to elementary econometrics. Through real-world examples and exercises, the book covers the topic of single-equation linear regression analysis in an easily understandable format.
The Seventh Edition is appropriate for all levels: beginner econometric students, regression users seeking a refresher, and experienced practitioners who want a convenient reference. Praised as one of the most important texts in the last 30 years, the book retains its clarity and practicality in previous editions with a number of substantial improvements throughout.

• The book’s intuitive approach omits matrix algebra and relegates proofs and calculus to the footnotes or exercises to make core concepts easier to grasp.
• An example-oriented approach helps students practice and understand applied economics.
• New! Expanded econometric content includes new tests and procedures, such as the Breusch-Pagan test and the Weinstein-Prais Approach to Generalized Least Squares.
• New! Stata, the economic software package of choice among economists, is used throughout the text. All text examples and exercises are estimated with Stata, and an explanation of the software is included in the appendix and on the website.
• Interactive Regression Learning Exercises help students simulate economic analysis by giving them feedback on various decisions without much computer time or instructor supervision.
• Updated! Answers to exercises in the text have been tripled and can be found in the appendices, allowing students to learn on their own.



Table of Contents

1. An Overview of Regression Analysis
2. Ordinary Least Squares
3. Learning to Use Regression Analysis
4. The Classical Model
5. Hypothesis Testing and Statistical Inference
6. Specification: Choosing the Independent Variables
7. Specification: Choosing a Functional Form
8. Multicollinearity
9. Serial Correlation
10. Heteroscedasticity
11. Running Your Own Regression Project
12. Time-Series Models
13. Dummy Dependent Variable Techniques
14. Simultaneous Equations
15. Forecasting
16. Experimental and Panel Data

Appendix A: Answers
Appendix B: Statistical Tables
ER  -