A Guide to Modern Econometrics, 3rd Edition

by Marno Verbeek
John Wiley and Sons, 2008

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RATS examples from A Guide to Modern Econometrics

In his Preface, Verbeek notes that modern software tools have made it relatively easy for researchers to apply the latest econometrics techniques, without necessarily understanding them well enough to be aware of potential problems inherent in these techniques. He notes that a gap exists between introductory econometrics texts, which tend not cover these techniques at all (or only deal with idealized cases), and more advanced texts, which are often too advanced to be useful to many practitioners. This book is designed to help fill that gap.

According to Verbeek, "the goal of this book is to familiarize the reader with a wide range of topics in modern econometrics, focusing on what is important for doing and understanding empirical work. This means that the text is a guide to (rather than an overview of) alternative techniques. Consequently, it does not concentrate on the formulae behind each technique (although the necessary ones are given) nor on formal proofs, but on the intuition behind the approaches and their practical relevance. This book covers a wide range of topics that is usually not found in textbooks at this level. In particular, attention is paid to cointegration, the generalized method of moments, models with limited dependent variables and panel data models. As a result, the book discusses developments in time series analysis, cross-sectional methods as well as panel data modelling. Throughout, a few dozen full-scale empirical examples and illustrations are provided, taken from fields like labour economics, finance, international economics, consumer behavior, environmental economics and macro-economics. In addition, a number of exercises are of an empirical nature and require the use of actual data."

The Third Edition

In this new Third Edition, Verbeek builds on the strengths of the second edition and brings the text completely up-to-date. For difficult subjects like multicollinearity and instrumental variables, the exposition is further improved, and much new material is added, for example on panel data, pseudo panels and instrumental variables. This edition also contains several new empirical illustrations on dynamic panel modeling, discrete choice models, model selection and forecasting. The book's website now provides more than 25 real-life data sets used for illustrations and exercises, plus new supplementary material for instructors, including PowerPoint slides and solutions to selected exercises.


  1. Introduction.
  2. An Introduction to Linear Regression.
  3. Interpreting and Comparing Regression Models.
  4. Heteroskedasticity and Autocorrelation.
  5. Endogeneity, Instrumental Variables and GMM.
  6. Maximum Likelihood Estimation and Specification Tests.
  7. Models with Limited Dependent Variables.
  8. Univariate Time Series Models.
  9. Multivariate Time Series Models.
  10. Models Based on Panel Data.
  11. Vectors and Matrices.
  12. Statistical and Distribution Theory.
  13. Bibliography.
  14. Index.