We use cookies to enhance your experience on our website. By continuing to use our website, you are agreeing to our use of cookies. You can change your cookie settings at any time. Find out more
Instructor inspection copy request

E-book purchase
Choose a subscription

Downloaded copy on your device does not expire. Includes 4 years of Bookshelf Online.

close

Where applicable, tax will be added to the above price prior to payment.

E-book purchasing help

E-book purchase

E-books are granted under the terms of a single-user, non-transferable license, and may be accessed online from any location.

Contact information
E: Contact Us

Cover

Introduction to Econometrics

Fifth Edition

Christopher Dougherty

Publication Date - June 2016

ISBN: 9780199676828

632 pages
Paperback
9.7 x 7.4 inches

Taking a modern approach to the subject, this text provides students with a solid grounding in econometrics, using non-technical language wherever possible

Description

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

New to this Edition

  • All student examples and exercises have been updated with additional exercises included at the end of each chapter to maximize the opportunity for students to consolidate their learning
  • The book has been made more accessible to students by the addition of an opening outline at the start of each chapter, making sure that key results feature clearly in the index, and ensuring that the relevance of equations is always included
  • More problem solving exercises have been added
  • Mathematical content has been kept to a minimum with only core equations included so that students without a mathematics background are not overwhelmed
  • In the latter chapters short sections have been included which introduce the meaning and application of more advanced topics. Further information sources have then been included to encourage able students to develop their learning independently.

Features

  • Provides substantial hands-on practical experience
  • Mathematical demands on the student are kept to a minimum
  • A revision section at the start of the text ensures that all students are confident in basic statistics before embarking on the econometrics material, where mathematical demands on the student are kept to a minimum
  • Provides substantial hands-on practical experience in the form of regression exercises, including 50 exercises on the same dataset
  • A suite of useful online resources, such as a student study guide to help with revision; PowerPoint slides to aid lecture preparation; extensive datasets; an instructor's manual; and a guide to using software, support teaching and learning

About the Author(s)

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

Related Titles