Using EViews for Principles of Econometrics / Edition 3

Using EViews for Principles of Econometrics / Edition 3

by William E. Griffiths, R. Carter Hill, Guay C. Lim
     
 

This book is a supplement to Principles of Econometrics, 4th Edition by R. Carter Hill, William E. Griffiths and Guay C. Lim (Wiley, 2011). It is designed for students to learn the econometric software package EViews at the same time as they are using Principles of Econometrics to learn econometrics. It is not a substitute for Principles of

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Overview

This book is a supplement to Principles of Econometrics, 4th Edition by R. Carter Hill, William E. Griffiths and Guay C. Lim (Wiley, 2011). It is designed for students to learn the econometric software package EViews at the same time as they are using Principles of Econometrics to learn econometrics. It is not a substitute for Principles of Econometrics, nor is it a stand-alone computer manual. It is a companion to the textbook, showing how to do all the examples in Principles of Econometrics using EViews Version 7. For most students, econometrics only has real meaning after they are able to use it to analyze data sets, interpret results, and draw conclusions. EViews is an ideal vehicle for achieving these objectives. Others who wish to learn and practice econometrics, such as instructors and researchers, will also benefit from using this book in conjunction with Principles of Econometrics, 4th Edition.

Product Details

ISBN-13:
9780471787112
Publisher:
Wiley
Publication date:
11/16/2007
Edition description:
Book & CD-ROM
Pages:
384
Product dimensions:
8.40(w) x 10.80(h) x 0.70(d)

Table of Contents

1. Introduction to EViews 7.1 1

2. The Simple Linear Regression Model 52

3. Interval Estimation and Hypothesis Testing 97

4. Prediction, Goodness-of-Fit, and Modeling Issues 118

5. The Multiple Linear Regression Model 138

6. Further Inference in the Multiple Regression Model 178

7. Using Indicator Variables 206

8. Heteroskedasticity 227

9. Regression with Time Series Data: Stationary Variables 257

10. Random Regressors and Moment-Based Estimation 292

11. Simultaneous Equations Models 313

12. Regression with Time Series Data: Nonstationary Variables 325

13. Vector Error Correction and Vector Autoregressive Models 333

14. Time-Varying Volatility and ARCH Models 338

15. Panel Data Models 350

16. Qualitative and Limited Dependent Variables 386

A. Review of Math Essentials 422

B. Statistical Distribution Functions 431

C. Review of Statistical Inference 449

Index 463

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