Mastering 'Metrics: The Path from Cause to Effect

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Posing several well-chosen empirical questions in social science, Mastering 'Metrics develops methods to provide the answers and applies them to interesting datasets. When I build up the courage to tackle an academic and educational book, these are the types of books I look for. Modern econometrics is more than just a set of statistical tools–causal inference in the social sciences requires a careful, inquisitive mindset. Metrics, that is, the field of applied econometrics, encompasses the statistical methods economists use to untangle cause and effect in human affairs. Angrist and Pischke use case examples to focus on five core econometric topics: random assignments, regression, instrumental variables, regression discontinuity, and differences in differences.

There is no sense of direction as to why am I reading about an issue and where do the connections matter - in terms of comprehending the entire topic, the reader is left on his own. I'll probably be keeping this book near my desk at all times -- it really is an invaluable reference. This valuable book connects the dots between mathematical formulas, statistical methods, and real-world policy analysis. Few fields of statistical inquiry have seen faster progress over the last several decades than causal inference. Economists view data scientists as regression monkeys (probably the worst insult you can give someone in economics).Unfortunately, practitioners’ actual statistical and econometric knowledge and intuition may be more limited than their level of academic exposure would suggest.

The material covered on causal inference is as follows: randomized trials, regression, instrumental variables, regression discontinuity design, and differences-in-differences.Here we address the questions of whether the quality and the credibility of empirical work have increased since Leamer’s pessimistic assessment.

But to those who want to understand what most economists do these days and what are their methods - I think this book is a neat introduction.this is an excellent book as an introduction to econometrics, focusing on the conceptual stuff and giving specific and appealing examples. Modern econometrics is more than just a set of statistical tools—causal inference in the social sciences requires a careful, inquisitive mindset. The first empirical application in Hill, Griffiths, and Lim (2011: 49) explores the correlation between food expenditure and income. The Population Bomb 123 Masters of 'Metrics: The Remarkable Wrights 139 Appendix: IV Theory 142 4 Regression Discontinuity Designs 147 4. I started reading this book as a 'forced formula' in a standard Labor Economics course but never ended up reading the whole thing, until I decided to pick it up again.