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Mastering ’Metrics: The Path from Cause to Effect Paperback – Dec 21 2014

5.0 out of 5 stars 2 customer reviews

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Product Details

  • Paperback: 304 pages
  • Publisher: Princeton University Press (Dec 21 2014)
  • Language: English
  • ISBN-10: 0691152845
  • ISBN-13: 978-0691152844
  • Product Dimensions: 14.2 x 1.8 x 21.3 cm
  • Shipping Weight: 318 g
  • Average Customer Review: 5.0 out of 5 stars 2 customer reviews
  • Amazon Bestsellers Rank: #11,431 in Books (See Top 100 in Books)
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Product Description

Review

"I would be hard pressed to name another econometrics book that can be read for enjoyment yet provides useful quantitative insights."--M.S.R., Financial Analysts Journal

From the Back Cover

"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

"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

"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

"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

"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

"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

"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

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Bonnes explications!
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: HASH(0xa002d9d8) out of 5 stars 25 reviews
18 of 18 people found the following review helpful
HASH(0x9ffcc438) out of 5 stars Like a Seminar Class March 11 2015
By Reader - Published on Amazon.com
Format: Paperback Verified Purchase
Imagine that you are taking a senior undergraduate seminar class, and the professor has picked out about a dozen recent social science papers (1/3 authored by Angrist) with econometric analyses in order to teach the various statistical methods that you learned in your econometrics class. That is what this book feels like. The topics of the papers try to answer causal questions such as, “Does low cost or free health insurance improve health outcomes?”, “Does attending a highly selective private university lead to higher earnings compared to a less competitive public university?”, and “Do charter schools increase student test scores?” The authors introduce the background for each paper then describe their favored econometric techniques to determine the answers (randomized trial, regression, instrumental variable, regression discontinuity, and differences-in-differences). The first 3 techniques are covered extensively in most introductory econometrics textbooks, while the last 2 are much less covered. A few other econometrics topics are sprinkled throughout the text.

For those with an economics degree or a very good grasp of statistical analysis, this book can be a nice refresher on econometric techniques used to determine causal effects through experiments or quasi-experiments. A more advanced treatment (with linear algebra and calculus) of the same topics can be found in the authors’ other book “Mostly Harmless Econometrics”.

For those that are upper level economics or social science majors in college, this book can serve as a supplement to an econometrics or advanced statistics class by providing real examples of econometrics in action and act as a bridge to understanding econometrics research articles. The book seems to be aimed at the college student that has had at least 1-2 classes of college level statistics. Even though the hard core math that would be found in an econometrics textbook is left to the appendices, there are plenty of equations and mathematical constructs in the main text that require a fairly solid understanding of math to fully appreciate the analysis.

For the general public that may have had a statistics class in high school or less, the analysis will likely be too difficult, however the introductory comments and conclusions for each paper may be of interest. This book is not likely to be found in most public libraries. There is some humor and historical notes to offset the heaviness of the material.
12 of 13 people found the following review helpful
HASH(0x9ffcc684) out of 5 stars For those who have a good background, it enhances the comprehensibility of the connections ... Jan. 2 2015
By J. M. SINGH - Published on Amazon.com
Format: Paperback Verified Purchase
A very well-written book. Clear, interesting and an enjoyable read. There is sufficient mathematical formulaic representations without overwhelming those who are new to the literature. For those who have a good background, it enhances the comprehensibility of the connections between formulas and methods involved in causal inferential statistics.
5 of 6 people found the following review helpful
HASH(0x9ffcc648) out of 5 stars like Mostly Harmless is extremely well written Aug. 29 2015
By John - Published on Amazon.com
Format: Paperback
Short review: If you have their other book, "Mostly Harmless Econometrics," and find that one sensible, don't buy this book. This is a much simpler version of that book, in essence. Mastering 'Metrics, like Mostly Harmless is extremely well written, but this one is probably too simple to be useful past your 1st or maybe 2nd econometrics class.
2 of 2 people found the following review helpful
HASH(0x9ffccb40) out of 5 stars An Intuitive Approach to the Concepts of Applied Econometrics Nov. 29 2015
By Robert Tenorio - Published on Amazon.com
Format: Paperback Verified Purchase
This is a really good introduction to applied econometrics. The authors elect for a more intuitive approach than they take in their earlier book, Mostly Harmless Econometrics. The result is an entertaining and easy read that provides a nice conceptual understanding of the ideas behind applied econometrics. This would be a good book to read over the summer before taking an course in econometrics if you are completely new to the field. Readers with more experience and/or knowledge in the field will find the book a little light on the technical details, but nonetheless very interesting and useful as a refresher on the conceptual stuff.
2 of 2 people found the following review helpful
HASH(0x9ffcc9d8) out of 5 stars Good introduction to modern applied econometric methods June 25 2015
By Bryan B. - Published on Amazon.com
Format: Paperback Verified Purchase
Superb book. It's a simplified version of "Mostly Harmless Econometrics". Very clearly written. Good introduction to modern applied econometric methods. Can be followed by someone with only one semester of statistics, but would be of better value to someone who has had an introductory econometrics course.


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