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Summary
Summary
This is the perfect (and essential) supplement for all econometrics classes--from a rigorous first undergraduate course, to a first master's, to a PhD course.
Explains what is going on in textbooks full of proofs and formulas Offers intuition, skepticism, insights, humor, and practical advice (dos and don'ts) Contains new chapters that cover instrumental variables and computational considerations Includes additional information on GMM, nonparametrics, and an introduction to waveletsAuthor Notes
Peter Kennedy is Professor of Economics at Simon Fraser University. In addition to A Guide to Econometrics , he is author of Macroeconomic Essentials: Understanding Economics in the News, 2e (2000), and is Associate Editor of the International Journal of Forecasting , the Journal of Economic Education , and Economics Bulletin .
Reviews (1)
Choice Review
The exceptional success of this work is due to its clarity and economy of expression and the accessibility of the subject matter to a broad range of scholars. Now in its sixth edition, this guide brings practitioners and researchers up to date on the popular techniques in estimation. Texts in econometrics range from overly simplistic "do this and get that" to advanced mathematical proofs of the properties of estimators. Kennedy (Simon Fraser Univ.) succeeds in covering the ground where most researchers find themselves. His work allows one to quickly compare estimation procedures; places the procedure in the broader context; and provides references for advanced study. It holds a unique position among econometric texts. It is the book this reviewer consults first when considering an estimation procedure and the one looked to when interpreting estimates. The format of this edition is the same as the others, but the inclusion of a chapter on instrumental variable estimation is a welcome addition. The broad outline goes back at least to Arthur S. Goldberger's Econometric Theory (1964). Summing Up: Highly recommended. Upper-division undergraduate through professional collections. J. F. O'Connell emeritus, College of Holy Cross
Table of Contents
| Preface |
| Dedication |
| 1 Introduction |
| 2 Criteria for Estimators |
| 3 The Linear Regression Model |
| 4 Interval Estimation and Hypothesis Testing |
| 5 Specification |
| 6 Violating Assumption One: Wrong Regressors, Nonlinearities, and Parameter Inconstancy |
| 7 Violating Assumption Two: Nonzero Expected Disturbance |
| 8 Violating Assumption Three: Nonspherical Disturbances |
| 9 Violating Assumption Four: Instrumental Variable Estimation |
| 10 Violating Assumption Five: Measurement Erros and Autoregression |
| 11 Violating Assumption Six: Simultaneous Equations |
| 12 Violating Assumption Seven: Multicollinearity |
| 13 Incorporating Extraneous Information |
| 14 The Bayesian Approach |
| 15 Dummy Variables |
| 16 Qualitative Dependent Variables |
| 17 Limited Dependent Variables |
| 18 Panel Data |
| 19 Time Series Econometrics |
| 20 Forecasting |
| 21 Robust Estimation |
| 22 Applied Econometrics |
| 23 Computational Considerations |
| General Notes |
| Technical Notes |
| Appendix A Sampling Distributions, the Foundation of Statistics |
| Appendix B All about Variance |
| Appendix C A Primer on Asymptotics |
| Appendix D Exercises |
| Appendix E Answers to Even-Numbered Questions |
| Glossary |
| Bibliography |
| Name Index |
| Subject Index |