James H. Stock, Mark W. Watson

Introduction to Econometrics, Global Edition (eBook, PDF)

• Format: PDF

Produktbeschreibung

For courses in introductory econometrics.

Engaging applications bring the theory and practice of modern econometrics to life

Ensure students grasp the relevance of econometrics with Introduction to Econometrics - the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition, Global Edition, maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.

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Produktdetails

• Verlag: Pearson HigherEducation
• Seitenzahl: 800
• Erscheinungstermin: 21. Februar 2019
• Englisch
• ISBN-13: 9781292264523
• Artikelnr.: 56950684

Autorenporträt

James Harold Stock is an American economist, professor of economics, and vice provost for climate and sustainability at Havard University.

Mark W. Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University.

Inhaltsangabe

PART I: INTRODUCTION AND REVIEW
1. Economic Questions and Data
2. Review of Probability
3. Review of Statistics
PART II: FUNDAMENTALS OF REGRESSION ANALYSIS
1. Linear Regression with One Regressor
2. Regression with a Single Regressor: Hypothesis Tests and Confidence
Intervals
3. Linear Regression with Multiple Regressors
4. Hypothesis Tests and Confidence Intervals in Multiple Regression
5. Nonlinear Regression Functions
6. Assessing Studies Based on Multiple Regression
PART III: FURTHER TOPICS IN REGRESSION ANALYSIS
7. Regression with Panel Data
8. Regression with a Binary Dependent Variable
9. Instrumental Variables Regression
10. Experiments and Quasi-Experiments
11. Prediction with Many Regressors and Big Data
PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA
12. Introduction to Time Series Regression and Forecasting
13. Estimation of Dynamic Causal Effects
14. Additional Topics in Time Series Regression
PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS
15. The Theory of Linear Regression with One Regressor
16. The Theory of Multiple Regression