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Introductory Econometrics : Modern Approach

Introductory Econometrics : Modern Approach - 3rd edition

ISBN13: 978-0324289787

Cover of Introductory Econometrics : Modern Approach 3RD 06 (ISBN 978-0324289787)
ISBN13: 978-0324289787
ISBN10: 0324289782
Cover type:
Edition/Copyright: 3RD 06
Publisher: South-Western Publishing Co.
Published: 2006
International: No

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Introductory Econometrics : Modern Approach - 3RD 06 edition

ISBN13: 978-0324289787

Jeffrey Wooldridge

ISBN13: 978-0324289787
ISBN10: 0324289782
Cover type:
Edition/Copyright: 3RD 06
Publisher: South-Western Publishing Co.

Published: 2006
International: No

The modern approach of this text recognizes that econometrics has moved from a specialized mathematical description of economics to an applied interpretation based on empirical research techniques. It bridges the gap between the mechanics of econometrics and modern applications of econometrics by employing a systematic approach motivated by the major problems facing applied researchers today. Throughout the text, the emphasis on examples gives a concrete reality to economic relationships and allows treatment of interesting policy questions in a realistic and accessible framework.


  • NEW! The author will carry several of the examples over multiple chapters: This increases the unity of the text by tying together various concepts. Many of the examples will still by stand-along cases, though. Thus we still have an advantage over those competitors who only use running examples, since we will have more total applications.
  • All the data sets are now available in a variety of formats: ASCII, Excel, Stata, Minitab, and student version of Eviews. These files are available on the Website.
  • Logical Progression: This text focuses first on multiple regression then leads in a straightforward manner to more advanced methods, such as simple panel data analysis and instrumental variables estimation.
  • In-Depth Data Coverage: Panel data methods and other new models are covered in greater detail than in other texts.
  • Meaningful Examples: This edition emphasizes examples intended to infer causality and to determine the effectiveness of policy, rather than just reporting descriptive regressions.
  • A Foundation for Social Science Research: This text provides students with important knowledge used for empirical work and carrying out research projects in a variety of applied social science fields, some outside of economics (e.g., political science, criminology, etc.).
  • NEW! Student Examples: The author will provide one or more examples of student papers for students and instructors to use as a model for their own assignments. This will help students and free-up time for professors.
  • NEW! Abundane of Real-World Examples: Many new real-world examples will be added to keep the text up-to-date and exciting for students.
  • NEW! Extensive, Up-to-Date Data Sets: More than 60 data sets, many of which come from very recent studies, accompany the text and are used in numerous examples and computer exercises.
  • NEW! Revised Math: In the Linear Regression Appendix E
  • Chapter 19 provides expanded coverage on guiding the students through empirical projects: The chapter now offers more examples and updated tips on writing a term paper with an expanded list of ''suggested topics''. This helps students go beyond the classroom.
  • Added material to the appendix in chapter 3: includes new insights on the omitted variables problems with clearer descriptions to help students understand the material better.
  • Empirical Examples: Updated using the most recent data which makes this the most up-to-date book on the market and motivates the discussion of topics.
  • End-of-chapter Problems: include new exercises using data sets.

Table of Contents

1. The Nature of Econometrics and Economic Data.


2. The Simple Regression Model.
3. Multiple Regression Analysis: Estimation.
4. Multiple Regression Analysis: Inference.
5. Multiple Regression Analysis: OLS Asymptotics.
6. Multiple Regression Analysis: Further Issues.
7. Multiple Regression Analysis with Qualitative information: Binary (or Dummy) Variables.
8. Heteroskedasticity.
9. More on Specification and Data Problems.


10. Basic Regression Analysis with Time Series Data.
11. Further Issues in Using OLS with Time Series Data.
12. Serial Correlation and Heteroskedasticity in Time Series Regressions.


13. Polling Cross Sections Across Time: Simple Panel Data Methods.
14. Advanced Panel Data Methods.
15. Instrumental Variables Estimation and Two State Least Squares.
16. Introduction to Simultaneous Equations Models.
17. Limited Dependent Variable Models and Sample Selection Corrections.
18. Advanced Time Series Topics.
19. Carrying Out an Empirical Project.

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