Introducing 5 powerful econometric tools, the book well explains how to build a valid counterfactual and intuitions behind regressions. I'll probably be keeping this book near my desk at all times -- it really is an invaluable reference. These cases include factors in the success of charter schools, drivers of SAT scores, and bank failures during the Great Depression. In contemporary econometric practice, the most widely-employed econometric tools are designed to capture specific causal relationships like the private-school earnings effect. Mastering 'Metrics is an engaging, fun, and highly accessible guide to the paradigm of causal inference.

There is also an effort at comparison of various techniques and lingering of the IV-2SLS; but I feel either the comparison should have flowed through the entire book, or should have been chapterized separately. On the stylistic front, the authors’ attempts to lighten the discussion by interjecting kung fu quips are not necessary to make the book worth reading and prove somewhat distracting. Becker and Greene (2001) surveyed econometrics texts and teaching at the turn of the millennium, arguing that “econometrics and statistics are often taught as branches of mathematics, even when taught in business schools.Angrist, JD, and J-S Pischke (2015), Mastering Metrics: The Path from Cause to Effect, Princeton University Press. Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. The first empirical application in Hill, Griffiths, and Lim (2011: 49) explores the correlation between food expenditure and income.

Jorn-Steffen Pischke is professor of economics at the London School of Economics and Political Science. Gary King, Harvard University "This valuable book connects the dots between mathematical formulas, statistical methods, and real-world policy analysis. It is found that students receive 9% higher earnings from going to a private university based on a simple regression methodology. Posing several well-chosen empirical questions in social science, Mastering 'Metrics develops methods to provide the answers and applies them to interesting datasets.Since economists don't think curve fitting is all that interesting or useful for doing economics, they scoff at neural networks and boosting. Andrew Gelman, Columbia University "With humor and rigor, this book explores key approaches in applied econometrics. Angrist and Pischke use case examples to focus on five core econometric topics: random assignments, regression, instrumental variables, regression discontinuity, and differences in differences.

However, my expectations from this book were more - especially since I like the papers written by Angrist etc. I do hope that most of my time in my data career I can jump straight to the gold standard of randomized controlled tests, but sometimes that's not feasible, and this book offers a wealth of alternative solutions. Very good exlanation of the problem of causal inference and ceteris paribus effects in applied economics.I worked off the Kindle edition which was extremely useful for highlights and saving notes, but considering picking up a physical copy to keep around since it's a relatively short book. I also appreciate the asides that provide historical context on the past masters who developed these techniques. I’ve always thought that understanding the underlying ideas of different regressions can help comprehend econometrics in a better way and these authors are great at doing it by providing lots of great examples throughout the book.