Introduction to Econometrics, Global Edition

For courses in introductory econometrics. Engaging applications bring the theory and practice of modern econometrics to life. Ensure students grasp th...
Publisher: Pearson D
ISBN: 9781292264523
$79.95
Your price: $75.95
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.

Features

  • 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

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Products specifications
Attribute nameAttribute value
FormatElectronic book text
AudienceProfessional and scholarly
Author(s)James H. Stock Mark W. Watson
Edition4