Introductory Econometrics: A Modern Approach (Book Only) / Edition 4

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Overview

The modern approach of this book 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 content, the emphasis on examples gives a concrete reality to economic relationships and allows treatment of interesting policy questions in a realistic and accessible framework.
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Editorial Reviews

Booknews
Though it focuses on the use of cross-sectional data and time series data for regression analysis, this textbook also addresses advanced topics like panel data methods, instrumental variables estimation, simultaneous equations, limited dependent variable models, and the process of empirical research. Appendixes contain basic information on mathematical tools, probability, mathematical statistics, matrix algebra, and linear regression, as well as statistical tables and a glossary. Woolridge teaches at Michigan State University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780324660548
  • Publisher: Cengage Learning
  • Publication date: 4/15/2008
  • Edition description: Older Edition
  • Edition number: 4
  • Pages: 888
  • Product dimensions: 7.50 (w) x 9.30 (h) x 1.60 (d)

Meet the Author

Jeffrey M. Wooldridge is a University Distinguished Professor of Economics at Michigan State University, where he has taught since 1991. From 1986 to 1991, he served as Assistant Professor of Economics at the Massachusetts Institute of Technology. Dr. Wooldridge has published more than three dozen 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. His work has earned numerous awards, including the Alfred P. Sloan Research Fellowship, the Multa 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. A fellow of the Econometric Society and of the Journal of Econometrics, Dr. Wooldridge has been editor of the Journal of Business and Economic Statistics and econometrics co-editor of Economics Letters. He has also served on the editorial boards of the Journal of Econometrics and the Review of Economics and Statistics. Dr. Wooldridge received his B.A. with majors in computer science and economics from the University of California, Berkeley, and received his Ph.D. in economics from the University of California, San Diego.

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Table of Contents

Chapter 1 The Nature of Econometrics and Economic Data 1
Part 1 Regression Analysis with Cross-Sectional Data 21
Chapter 2 The Simple Regression Model 22
Chapter 3 Multiple Regression Analysis: Estimation 68
Chapter 4 Multiple Regression Analysis: Inference 116
Chapter 5 Multiple Regression Analysis: OLS Asymptotics 166
Chapter 6 Multiple Regression Analysis: Further Issues 182
Chapter 7 Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables 218
Chapter 8 Heteroskedasticity 257
Chapter 9 More on Specification and Data Problems 289
Part 2 Regression Analysis with Time Series Data 323
Chapter 10 Basic Regression Analysis with Time Series Data 324
Chapter 11 Further Issues in Using OLS with Time Series Data 360
Chapter 12 Serial Correlation and Heteroskedasticity in Time Series Regressions 391
Part 3 Advanced Topics 425
Chapter 13 Pooling Cross Sections Across Time. Simple Panel Data Methods 426
Chapter 14 Advanced Panel Data Methods 461
Chapter 15 Instrumental Variables Estimation and Two Stage Least Squares 484
Chapter 16 Simultaneous Equations Models 525
Chapter 17 Limited Dependent Variable Models and Sample Selection Corrections 553
Chapter 18 Advanced Time Series Topics 600
Chapter 19 Carrying out an Empirical Project 646
Appendices
Appendix A Basic Mathematical Tools 675
Appendix B Fundamentals of Probability 696
Appendix C Fundamentals of Mathematical Statistics 731
Appendix D Summary of Matrix Algebra 776
Appendix E The Linear Regression Model in Matrix Form 787
Appendix F Answers to Chapter Questions 802
Appendix G Statistical Tables 815
References 823
Glossary 831
Index 849
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