Overview

For courses in introductory econometrics. An approach to modern econometrics theory and practice through engaging applications. Ensure students grasp the relevance of econometrics with Introduction to Econometrics—the text that connects modern theory and practice with engaging applications. The third edition builds on the philosophy that applications should drive the theory, not the other way around, while maintaining a focus on currency.

Full Product Details

Author:   James H. Stock ,  Mark W. Watson
Publisher:   Pearson Education (US)
Imprint:   Pearson Education (US)
Edition:   3rd edition
ISBN:  

9780132105583

ISBN 10:   0132105586
Pages:   840
Publication Date:   28 January 2011
Audience:   College/higher education ,  Tertiary & Higher Education
Replaced By:   9781408264331
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   Out of stock  

Table of Contents

Part I. Introduction and Review Chapter 1. Economic Questions and Data Chapter 2. Review of Probability Chapter 3. Review of Statistics Part II. Fundamentals of Regression Analysis Chapter 4. Linear Regression with One Regressor Chapter 5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals Chapter 6. Linear Regression with Multiple Regressors Chapter 7. Hypothesis Tests and Confidence Intervals in Multiple Regression Chapter 8. Nonlinear Regression Functions Chapter 9. Assessing Studies Based on Multiple Regression Part III. Further Topics in Regression Analysis Chapter 10. Regression with Panel Data Chapter 11. Regression with a Binary Dependent Variable Chapter 12. Instrumental Variables Regression Chapter 13. Experiments and Quasi-Experiments Part IV. Regression Analysis of Economic Time Series Data Chapter 14. Introduction to Time Series Regression and Forecasting Chapter 15. Estimation of Dynamic Causal Effects Chapter 16. Additional Topics in Time Series Regression Part V. The Econometric Theory of Regression Analysis Chapter 17. The Theory of Linear Regression with One Regressor Chapter 18. The Theory of Multiple Regression

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