Introduction to Econometrics, Global Edition + MyLab Economics with Pearson eText

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. 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.

To access the MyLab you need a Course ID from your instructor.


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

New to this edition



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., randomised vs. controlled variables).
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.
The 4th Edition features more exercises covering more topics to allow instructors greater flexibility in assigning exercises that provide instant, personalised feedback to students.