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Introductory econometrics: a modern approach

서명/저자사항
Introductory econometrics: a modern approach
판사항
6th ed
개인저자
Wooldridge, Jeffrey M. 1960-
발행사항
Boston, MA.: Cengage Learning, 2016.
형태사항
xxi, 789 p. : ill. ; 24 cm.
ISBN
9781305270107
주기사항
Includes bibliographical references (p. 750-755) and index
주제어
Econometrics
소장정보소개관련정보
소장정보
위치등록번호청구기호 / 출력상태반납예정일
이용 가능 (1)
자료실WM020092대출가능-
이용 가능 (1)
  • 등록번호
    WM020092
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책 소개
Discover how empirical researchers today actually consider and apply econometric methods with the practical approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 6E. Unlike traditional texts, this book uniquely demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions in business, policy evaluation, and forecasting. INTRODUCTORY ECONOMETRICS is organized around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 intriguing data sets, available in six formats. Updates introduce the latest emerging developments in the field. Gain a full understanding of the impact of econometrics in practice today with the insights and applications found only in INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 6E.

목차

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: Binary (or Dummy) Variables. 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. 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 Exploring Further Chapter Exercises. Appendix G: Statistical Tables. References. Glossary. Index.