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Overview
International MindTap Instant Access for Wooldridge’s “Introductory Econometrics: A Modern Approach," is the online learning platform that powers students from memorization to mastery. It gives you complete control of your course to provide engaging content, challenge every individual and build their confidence. Empower students to accelerate their progress with MindTap. MindTap: Powered by You.
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All online text media materials accessible through this access code are available in EMEA, Latin America, Asia and India only.
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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. Advanced Methods for Causal Inference.
20. 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.
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. Advanced Methods for Causal Inference.
20. 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.