Introduction to Econometrics / Edition 3

by Christopher Dougherty

Overview

Retaining the student-friendly approach of previous editions, Introduction to Econometrics, Fifth Edition, uses clear and simple mathematics notation and step-by step explanations of mathematical proofs to help students thoroughly grasp the subject. Extensive exercises throughout build students' confidence and provide them with hands-on practice in applying techniques.

The fifth edition features a comprehensive revision guide to all the essential statistical concepts needed to study econometrics, additional Monte Carlo simulations, new summaries, and non-technical introductions to more advanced topics at the end of chapters.

This book is supported by an Online Resource Centre, which includes:

For lecturers:

* Instructor's manual for the text and data sets, detailing the exercises and their solutions
* Customizable PowerPoint slides

For students:

* Data sets referred to in the book
* A comprehensive study guide offers students the opportunity to gain experience with econometrics through practice with exercises
* Software manual
* PowerPoint slides with explanations

Product Details

ISBN-13:	9780199280964
Publisher:	Oxford University Press, USA
Publication date:	03/30/2007
Edition description:	REV
Pages:	480
Product dimensions:	9.60(w) x 7.30(h) x 0.90(d)

About the Author

Christopher Dougherty, Associate Professor in Economics at the London School of Economics

Dr Christopher Dougherty is an Associate Professor in Economics at the London School of Economics.

Table of Contents

Introduction
Review: Random Variables, Sampling, and Estimation
1. Simple Regression Analysis
2. Properties of Regression Coefficients and Hypothesis Testing
3. Multiple Regression Analysis
4. Transformations of Variables
5. Dummy Variables
6. Specification of Regression Variables
7. Heteroscedasticity
8. Stochastic Regressors and Measurement Errors
9. Simultaneous Equations Estimation
10. Binary Choice Models and Maximum Likelihood Estimation
11. Models Using Time Series Data
12. Autocorrelation
13. Introduction to Nonstationary Time Series
14. Introduction to Panel Data Models