Mastering 'Metrics: The Path from Cause to Effect (英語) ペーパーバック – 2014/12/21
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Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung futhemed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful.
The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse.
Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect.
- Shows why econometrics is important
- Explains econometric research through humorous and accessible discussion
- Outlines empirical methods central to modern econometric practice
- Works through interesting and relevant real-world examples
"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
"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
"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
"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
"The writing is lively and engaging, with quotes, anecdotes and jokes scattered throughout. . . . I have become a big fan of this new textbook, and I am thinking about how we can use it in our econometrics courses at the ANU. . . . In my view, the emphasis on thinking about parameters of interest and identification before discussing technical matters is a huge improvement on traditional teaching approaches. Instructors may have to spend more time preparing lectures and tutorials, but I predict significant benefits in terms of students' learning and appreciation of applied econometrics."---Tue Gørgens, Economic Record
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.
I highly recommend. I use this (and their companion Mostly Harmless Econometrics) in my PhD econometrics course
Econometrics is hard to learn. It is rare to find textbooks teaching econometrics in an intuitive, accessible and empirical and application focused way. This book really fills the gap.
The authors also wrote Mostly Harmless Econometrics (MHE), which is a more advanced treatment mostly for graduate students and researchers. I would highly recommend reading this book first.
Lastly, thank you the two masters writing this book. It is remarkable. I wish they keep writing another book that is filling the gap between this one and MHE.