Introduction to Econometrics, Global Edition + MyLab Economics with eText (4e) : 9781488658198

Introduction to Econometrics, Global Edition + MyLab Economics with eText (4e)

Stock & Watson
 
Edition
 
4
ISBN
 
9781488658198
ISBN 10
 
1488658196
Published
 
20/11/2019
Published by
 
Pearson Australia
Pages
 
Format
 
Available once published
 
Title type
Value Pack
$143.99
 
 
 
Description
This pack contains 1 copy of Introduction to Econometrics, Global Edition and 1 printed access card to MyLab Economics with eText

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.

Pearson MyLab™ is the world's leading online self-study, homework, tutorial and assessment product designed with a single purpose in mind: to improve the results of all higher education students, one student at a time.

Please note: The duration of access to a MyLab is set by your instructor for your specific unit of study. To access the MyLab you need a Course ID from your instructor.

Table of contents
  • PART I: INTRODUCTION AND REVIEW
  • 1. Economic Questions and Data
  • 2. Review of Probability
  • 3. Review of Statistics
  • PART II: FUNDAMENTALS OF REGRESSION ANALYSIS
  • 4. Linear Regression with One Regressor
  • 5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
  • 6. Linear Regression with Multiple Regressors
  • 7. Hypothesis Tests and Confidence Intervals in Multiple Regression
  • 8. Nonlinear Regression Functions
  • 9. Assessing Studies Based on Multiple Regression
  • PART III: FURTHER TOPICS IN REGRESSION ANALYSIS
  • 10. Regression with Panel Data
  • 11. Regression with a Binary Dependent Variable
  • 12. Instrumental Variables Regression
  • 13. Experiments and Quasi-Experiments
  • 14. Prediction with Many Regressors and Big Data
  • PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA
  • 15. Introduction to Time Series Regression and Forecasting
  • 16. Estimation of Dynamic Causal Effects
  • 17. Additional Topics in Time Series Regression
  • PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS
  • 18. The Theory of Linear Regression with One Regressor
  • 19. The Theory of Multiple Regression
Features & benefits
  • Teach methods through real-world questions and applications, and at a mathematical level appropriate for an introductory course.
  • A modern treatment gives students enough econometric theory to understand the strengths and limitations of the tools, making the fit between theory and applications as tight as possible, while keeping the mathematics at a level that requires only algebra.
  • Students learn how to use the tools of regression analysis and how to assess the validity of empirical analyses through a threefold process:
    • Immediately after introducing the main tools of regression analysis, Chapter 9 is devoted to the threats to internal and external validity of an empirical study.
    • Next, the methods for assessing empirical studies are applied to the ongoing example in the book.
    • Lastly, students get hands-on practice with robust data sets, software, and empirical exercises.
  • Prepare students to work with modern applications and very large data sets, including applications that predict consumer choices and work with nonstandard data
Pack Items