Introduction to Econometrics, Global Edition

Series
Pearson
Author
James H. Stock / Mark W. Watson  
Publisher
Pearson
Cover
Softcover
Edition
4
Language
English
Total pages
800
Pub.-date
May 2019
ISBN13
9781292264455
ISBN
1292264454
Related Titles



Description

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 EditionGlobal 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™ Economics is not included. Students, if Pearson MyLab Economics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Economics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

 

Reach every student by pairing this text with Pearson MyLab Economics

MyLab™ is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student. The 4th Edition features expanded exercise sets in Pearson MyLab Economics, offering more flexibility to instructors as they build assignments.

Features

This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content, which is especially relevant to students outside the United States.

 

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:

  1. 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.
  2. Next, the methods for assessing empirical studies are applied to the ongoing example in the book.
  3. Lastly, students get hands-on practice with robust data sets, software, and empirical exercises. Data sets and software are available through Pearson MyLab Economics or at www.pearsonglobaleditions.com.

Prepare students to work with modern applications and very large data sets, including applications that predict consumer choices and work with nonstandard data (e.g., text data).

·    New - A new Chapter 14 is dedicated to big data and machine learning methods. In economics, many applications focus on the “many-predictor” problem, where the number of predictors is large relative to the sample size. This chapter introduces students to methods beyond the ordinary least squares method that can help them have much lower out-of-sample prediction errors.

·    New - Chapter 17 extends the many-predictor focus of Chapter 14 to time series data. Using the dynamic factor model and a 131-variable set of US quarterly macroeconomic data, students learn how to forecast future values -- an important skill to have as professionals in the field of econometrics.

·    New - Regression is now introduced with a parallel treatment of prediction and causal inference, to expose students to the different demands on how data can be collected (i.e., randomized vs. controlled variables).

 

Keep students engaged with a full array of pedagogical material, tools, and resources

·    Updated - General Interest boxes provide students with interesting insight into related topics, while also highlighting real-world studies. The 4th Edition now extends discussion of the historical origins of instrumental variables regression (Chapter 12).

·    Chapter Introductions provide real-world context and a useful roadmap for each chapter to help students navigate the material.

·    Key Concept boxes at regular intervals and End-of-Chapter Summaries recap key ideas, helping students study more efficiently.

·    Updated - Exercise sets provide instructor flexibility in setting up assignments. Review the Concepts questions allow students to check their understanding. In addition to Exercises that provide intensive practice, Empirical Exercises allow students to apply what they have learned to answer real-world empirical questions.

 

 

MyLab™ Economics is not included. Students, if Pearson MyLab Economics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Economics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

 

Reach every student with MyLab

·    Teach your course your way: Your course is unique. So whether you’d like to build your own assignments, teach multiple sections, or set prerequisites, MyLab gives you the flexibility to easily create your course to fit your needs.

·    Empower each learner: Each student learns at a different pace. Personalized learning pinpoints the precise areas where each student needs practice, giving all students the support they need -- when and where they need it -- to be successful.

·    Deliver trusted content: You deserve teaching materials that meet your own high standards for your course. That’s why we partner with highly respected authors to develop interactive content and course-specific resources that you can trust -- and that keep your students engaged.

o   Expanded - The 4th Edition features more exercises covering more topics to allow instructors greater flexibility in assigning exercises that provide instant, personalized feedback to students.

·    Improve student results: When you teach with MyLab, student performance improves. That’s why instructors have chosen MyLab for over 15 years, touching the lives of over 50 million students.

New to this Edition

Prepare students to work with modern applications and very large data sets, including applications that predict consumer choices and work with nonstandard data (e.g., text data).

·    New General Interest Boxes. More than 6 new boxes that provide supplementary insights to topics related to econometrics. In Chapter 12, one of the boxes discusses when Instrumental Variables Regression (IVR) was invented in relation to who invented it.

·    A new section in Chapter 12 discusses whether economic institutions affect economic development. The single question that has troubled economists since Adam Smith the most is why some nations are rich while others remain poor. This chapter looks at measures of potential settler mortality as valid instruments for measuring the effects in addition to TSLS and OLS.

·    A new Chapter 14 is dedicated to big data and machine learning methods. In economics, many applications focus on the “many-predictor” problem, where the number of predictors is large relative to the sample size. This chapter introduces students to methods beyond the ordinary least squares method that can help them have much lower out-of-sample prediction errors.

·    Chapter 17 extends the many-predictor focus of Chapter 14 to time series data. Using the dynamic factor model and a 131-variable set of US quarterly macroeconomic data, students learn how to forecast future values -- an important skill to have as professionals in the field of econometrics.

·    Regression is now introduced with a parallel treatment of prediction and causal inference, to expose students to the different demands on how data can be collected (i.e., randomized vs. controlled variables).

 

Keep students engaged with a full array of pedagogical material, tools, and resources

·    General Interest boxes provide students with interesting insight into related topics, while also highlighting real-world studies. The 4th Edition now extends discussion of the historical origins of instrumental variables regression (Chapter 12).

·    Exercise sets provide instructor flexibility in setting up assignments. Review the Concepts questions allow students to check their understanding. In addition to Exercises that provide intensive practice, Empirical Exercises allow students to apply what they have learned to answer real-world empirical questions.

 

MyLab™ Economics is not included. Students, if Pearson MyLab Economics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Economics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

 

·    The 4th Edition features more exercises covering more topics to allow instructors greater flexibility in assigning exercises that provide instant, personalized feedback to students.

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