Introductory econometrics : a modern approach
Author(s)
Bibliographic Information
Introductory econometrics : a modern approach
South-Western, Cengage Learning, c2009
4th, international student ed
- : package
- : pbk
Available at / 58 libraries
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Research Institute for Economics & Business Administration (RIEB) Library , Kobe University図書
330.01-18-4-C081200900141
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Note
Includes bibliographical references (p. 830-834) and index
Package includes access code card to online resources
Description and Table of Contents
- Volume
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: package ISBN 9780324585483
Description
Wooldridge uses a systematic approach motivated by the major problems facing applied researchers. This text provides important understanding for empirical work in many social sciences, as well as for carrying out research projects.
- Volume
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: pbk ISBN 9780324788907
Description
INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4e International Edition illustrates how empirical researchers think about and apply econometric methods in real-world practice. The text's unique approach reflects the fact that undergraduate econometrics has moved beyond just a set of abstract tools to being genuinely useful for answering questions in business, policy evaluation, and forecasting environments. The systematic approach, which reduces clutter by introducing assumptions only as they are needed, makes absorbing the material easier and leads to better econometric practices. Its unique organization separates topics by the kinds of data being analyzed , leading to an appreciation for the important issues that arise in drawing conclusions from the different kinds of data economists use. Packed with relevant applications, INTRODUCTORY ECONOMETRICS offers a wealth of interesting data sets that can be used to reproduce the examples in the text or as the starting point for original research projects.
Table of Contents
1. The Nature of Econometrics and Economic Data. PART 1: 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: Binary (or Dummy) Variables. 8. Heteroskedasticity. 9. More on Specification and Data Problems. PART 2: 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 3: 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. Carrying out an Empirical Project. APPENDICES. Appendix A: Basic Mathematical Tools. Appendix B: Fundamentals of Probability. Appendix C: Fundamentals of Mathematical Statistics. Appendix D: Summary of Matrix Algebra. Appendix E: The Linear Regression Model in Matrix Form. Appendix F: Answers to Chapter Questions. Appendix G: Statistical Tables. References. Glossary. Index.
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