Introduction to Econometrics / Edition 4

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Overview


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

NEW TO THE FOURTH EDITION:

* An expanded review section at the beginning of the book offers a more comprehensive guide to all of the statistical concepts needed to study econometrics

* Additional exercises provide students with even more opportunities to put theory into practice

* More Monte Carlo simulations help students use visualization to understand the math

* New final sections at the end of each chapter contain summaries and non-technical introductions to more advanced topics

An updated and expanded Companion Website contains resources for students and instructors:

For students:

* Data sets
* Gretl, a free econometrics software application
* PowerPoint-based slides with explanations
* A study guide

For instructors:

* Instructor manuals for the text and data sets that detail the exercises and their solutions
* PowerPoint-based slides
* A "Contact the Author" link

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Product Details

  • ISBN-13: 9780199567089
  • Publisher: Oxford University Press
  • Publication date: 4/30/2011
  • Edition description: New Edition
  • Edition number: 4
  • Pages: 512
  • Sales rank: 465,215
  • Product dimensions: 7.40 (w) x 9.60 (h) x 1.40 (d)

Meet the Author

Dr. Christopher Dougherty is a Senior Lecturer in Economics at the London School of Economics.

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Table of Contents

Review: Random variables, sampling, and estimation
1. Simple regression analysis
2. Properties of regression coefficients and hypothesis testing
3. Multiple regression analysis
4. Transformation of variables
5. Dummy variables
6. Specification regression variables: a preliminary skirmish
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

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