Mastering ‘Metrics: The Path from Cause to Effect

Author: Angrist Joshua D.

Brand: Princeton University Press

Edition: with French flaps

Number Of Pages: 304

Details: Review

“I would be hard pressed to name another econometrics book that can be read for enjoyment yet provides useful quantitative insights.” ― 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. . . . 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

Product Description

From Joshua Angrist, winner of the Nobel Prize in Economics, and Jörn-Steffen Pischke, an accessible and fun guide to the essential tools of econometric research

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 fu–themed 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

Review

“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 sta

Release Date: 21-12-2014

Package Dimensions: 21x218x347