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Introductory Econometrics "A Modern Approach"

Introductory Econometrics "A Modern Approach"

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  • ISBN:9781337558860
  • Editorial: Cengage Learning Inc
  • Fecha de la edición:
  • Número de la edición: 7
  • Encuadernación:
  • Nº Pág.:816
  • Idiomas:Inglés

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Give students an understanding of how econometrics can answer questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. Students see the importance of what they're learning as this practical, yet professional, approach demonstrates how today's empirical researchers apply econometric methods to answer questions across a variety of disciplines. The author organizes information around the type of data being analyzed and uses a systematic approach that introduces assumptions only when needed to obtain a certain result, making it easier for students to follow. Updated applications and examples demonstrate impact on today's policy and support or disprove contemporary economic theories. More than 100 data sets are available in different formats. MindTap resources, a comprehensive Instructor's Manual, PowerPoint® and Scientific Word® slides and a Data Set Handbook are available to support your teaching.

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.
20. Advanced Causal Estimation Methods (MindTap Only)

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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