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Introductory Econometrics: A Modern Approach, 8th Edition

Jeffrey M. Wooldridge

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Introductory Econometrics: A Modern Approach 8th Edition by Jeffrey M. Wooldridge

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What's New
Features
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Overview

Give students an understanding of how econometrics can answer questions in business, policy evaluation and forecasting with the practical approach found in Wooldridge’s “Introductory Econometrics: A Modern Approach” 8th Edition.

Meet the Authors

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Jeffrey M. Wooldridge

Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University, where he has taught since 1991. From 1986 to 1991, he was an assistant professor of economics at the Massachusetts Institute of Technology. He received his bachelor of arts, with majors in computer science and economics, from the University of California, Berkeley, in 1982, and received his doctorate in economics in 1986 from the University of California, San Diego. He has published more than 60 articles in internationally recognized journals, as well as several book chapters. He is also the author of Econometric Analysis of Cross Section and Panel Data, second edition. His awards include an Alfred P. Sloan Research Fellowship, the Plura Scripsit award from Econometric Theory, the Sir Richard Stone prize from the Journal of Applied Econometrics, and three graduate teacher-of-the-year awards from MIT. He is a fellow of the Econometric Society and of the Journal of Econometrics. He is past editor of the Journal of Business and Economic Statistics, and past econometrics coeditor of Economics Letters. He has served on the editorial boards of Econometric Theory, the Journal of Economic Literature, the Journal of Econometrics, the Review of Economics and Statistics, and the Stata Journal. He has also acted as an occasional econometrics consultant for Arthur Andersen, Charles River Associates, the Washington State Institute for Public Policy, Stratus Consulting, and Industrial Economics, Incorporated.

What's New

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REFINED COVERAGE HIGHLIGHTS THE LATEST DEVELOPMENTS IN THE FIELD. Recent examples cover the latest advances in econometrics, illustrating how concepts add value to practice in the business world. Optional short segments demonstrate how to obtain regression models from potential outcomes setting. A new online-only chapter covers advanced causal estimation methods, including regression with dummy variables and binary response models, providing an introduction to other treatment effects methods.
DATA SETS IN FLEXIBLE FORMATS DELIVER HANDS-ON PRACTICE. Introduce students to the information they need to complete assignments using the format you prefer. This edition's 100+ data sets provide information in different formats: R, Stata®, Minitab®, Excel® and EViews. Instantly access data in the format you prefer to use while teaching. All data sets are available on the book's companion website.
Video Walk-Throughs of a Problems and Computer Exercise are found at the end of each chapter. These step-by-step videos assist students in resolving key questions. Both R and Stata software are used to solve a Computer Exercise problem in each chapter, helping students administer and interpret the analysis.
NEW CHAPTER: Chapter 19: Advanced Methods for Causal Inference. The treatment is at a level accessible to advanced undergraduates that is not available elsewhere. These methods are used routinely by empirical researchers in economics, business and other fields that undertake sophisticated data analysis.

Features

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UPDATED DATA SET HANDBOOK MAKES USING THE DATA SETS SIMPLE AND CONVENIENT. This unique online handbook lists all data sets from the latest edition of the text for quick reference. Each data set entry indicates the original source when possible and lists where the data appears in the text. When applicable, the handbook guides you in using the data set to generate new homework exercises, exam problem or term projects. The author also provides suggestions on improving the data sets.
REVISED INSTRUCTOR'S MANUAL WITH SOLUTIONS SAVES TIME IN PREPARATION AND GRADING. The online Instructor's Manual with solutions contains answers to all exercises in this edition. Teaching tips provide suggestions for presenting each chapter's material. The Instructor's Manual also contains sources for each of the data files with suggestions for using the data to develop problem sets, exams and term papers. The Instructor's Manual is password-protected and available for download on the book's companion website.
COMPREHENSIVE COVERAGE ENSURES UNDERSTANDING IN CRITICAL AREAS OF ECONOMETRICS. This edition continues to offer trusted, comprehensive coverage with expanded discussions of prediction after transformation, missing data, unbalanced panel data sets, weak instruments and causal effects.
PRACTICAL APPLICATIONS PREPARE STUDENTS TO USE ECONOMETRICS TO RESOLVE CHALLENGES IN NUMEROUS AREAS OF BUSINESS TODAY. This unique, practical book applies econometrics to actual business problems in a variety of disciplines. The author demonstrates how each method answers a particular issue facing researchers who are analyzing non-experimental data.
UNIQUE ORGANIZATION PIONEERED BY THE AUTHOR CLEARLY PRESENTS APPLICATIONS FOR TODAY'S STUDENTS. This complete econometrics text was the first to explicitly cover cross-sectional applications in initial chapters, followed by time series applications and panel data applications in the advanced chapters.
The text includes newly digitized versions of the popular Computer Exercise questions for Chapters 1 to 19. These new questions require students to analyze a data set using their Stats software of choice and apply their understanding. Much like the current Homework sets, these assignable exercises provide students with robust and detailed feedback and can be set to allow a student to take another variant of the question up three times.
Each chapter offers an assignable Homework problem set that assesses students mastery of the theory in that chapter. Students receive robust feedback instantly upon submission. The problem sets can be set to allow students to take another variant of the question up three times.

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1. The Nature of Econometrics and Economic Data.
Part I: REGRESSION ANALYSIS WITH CROSS-SECTIONAL 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.
8. Heteroskedasticity.
9. More on Specification and Data Problems.
Part II: REGRESSION ANALYSIS WITH TIME SERIES DATA.
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.
Part III: ADVANCED TOPICS.
13. Pooling Cross Sections Across Time: Simple Panel Data Methods.
14. Advanced Panel Data Methods.
15. Instrumental Variables Estimation and Two Stage Least Squares.
16. Simultaneous Equations Models.
17. Limited Dependent Variable Models and Sample Selection Corrections.
18. Advanced Time Series Topics.
19. Advanced Methods for Causal Inference.
20. Carrying Out an Empirical Project.
Math Refresher A: Basic Mathematical Tools.
Math Refresher B: Fundamentals of Probability.
Math Refresher C: Fundamentals of Mathematical Statistics.
Math Refresher D: Summary of Matrix Algebra.
Math Refresher E: The Linear Regression Model in Matrix Form.
Answers to Exploring Further Chapter Exercises.
Statistical Tables.
References.
Glossary.
Index.