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Book Synopsis


Table of Contents
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. 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.

Introductory Econometrics

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A Hardback by Jeffrey Wooldridge

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    View other formats and editions of Introductory Econometrics by Jeffrey Wooldridge

    Publisher: Cengage Learning, Inc
    Publication Date: 04/01/2019
    ISBN13: 9781337558860, 978-1337558860
    ISBN10: 1337558869
    Also in:
    Business, Finance & Law Econometrics and economic statistics

    Description

    Book Synopsis


    Table of Contents
    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. 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.

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