I assign Angrist and Pischke’s Mostly Harmless Econometrics in virtually all of my graduate courses … But it’s still a very hard book… What’s been needed for some time is a more casual introduction. And it has arrived. Mastering Metrics is a more intuitive, example-strewn introduction to methods for figuring out causality in statistics.
Chris Blattman, Columbia University
Read all of Kung Fu 'Metrics on Chris's Blog
“Few fields of statistical inquiry have seen faster progress over the last several decades than causal inference. With an engaging, insightful style, Angrist and Pischke catch readers up on five powerful methods in this area. If you seek to make causal inferences, or understand those made by others, you will want to read this book as soon as possible.”
Gary King, Harvard University
This is a microeconometrics textbook quite out of the ordinary . . . there is certainly no better introduction to modern microeconometrics than this book.
Walter Krämer, TU Dortmund University
Read Walter's entire review in Statistical Papers
One of the many strengths of Mastering ‘Metrics is the use of various cases to illustrate problems, tools and outcomes … the lucid and intuitive approach used by the authors is refreshing compared with the text-book style of writing we have become accustomed to in ‘metrics.
“Modern econometrics is more than just a set of statistical tools–causal inference in the social sciences requires a careful, inquisitive mindset. Mastering ‘Metrics is an engaging, fun, and highly accessible guide to the paradigm of causal inference.”
David Deming, Harvard University
…this book has been very well received and is hard to fault … what students will learn most is that Econometrics is not only an empirical science, but also an art to be mastered.
Undergraduate Aspiring Master Simeon Paton, University of East Anglia
Read Simeon Paton's entire review here
… this is an excellent book as an introduction to econometrics, focusing on the conceptual stuff and giving specific and appealing examples.
Psychology Master Edgar Kausel
Read Edgar's entire review here
“Written by true ‘masters of ‘metrics,’ this book is perfect for those who wish to study this important subject. Using real-world examples and only elementary statistics, Angrist and Pischke convey the central methods of causal inference with clarity and wit.”
Hal Varian, chief economist at Google
“Ideal for students, ideal for older economists who privately admit they could do with brushing up their econometric knowledge a bit, as they look at the figures generated by their software packages. I’ll find this a very useful book, not least when it comes to reading other economists’ papers.”
Diane Coyle, Enlightenment Economics
Read all of Diane's review on The Enlightened Economist
“Posing several well-chosen empirical questions in social science, Mastering ‘Metrics develops methods to provide the answers and applies them to interesting datasets. This book will motivate beginning students to understand econometrics, with an appreciation of its strengths and limits.”
Gary Chamberlain, Harvard University
“Best intro book on Metrics I have ever read! I do not teach undergrad econometrics but in my Development Class I cover two weeks of methods. Definitely, I am adopting the book for those lectures.”
Sebastian Galiani, University of Maryland
“… the book has a lovely style and I had to force myself to put it down.
Not a bad compliment for an econometrics book!”
Orley Ashenfelter, Princeton University
“Focusing on five econometric tools, Mastering ’Metrics presents key econometric concepts. Any field that uses statistical techniques to conduct causal inference will find this book useful.”
Melvyn Weeks, University of Cambridge
“This valuable book connects the dots between mathematical formulas, statistical methods, and real-world policy analysis. Reading it is like overhearing a conversation between two grumpy old men who happen to be economists–and I mean this in the best way possible.”
Andrew Gelman, Columbia University
“With humor and rigor, this book explores key approaches in applied econometrics. The authors present accessible, interesting examples–using data-heavy figures and graphic-style comics–to teach practitioners the intuition and statistical understanding they need to become masters of ‘metrics. A must-read for anyone using data to investigate questions of causality!”
Melissa S. Kearney, University of Maryland and the Brookings Institution
I would be hard pressed to name another econometrics book that can be read for enjoyment yet provides useful quantitative insights.
