Mastering 'Metrics: The Path from Cause to Effect

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Unfortunately, the book does not offer a more focused discussion of time series, given that this area is where causal reasoning is especially critical in finance. Wielding econometric tools with skill and confidence, Mastering ‘Metrics uses data and statistics to illuminate the path from cause to effect. Such questions are easily understood, and the answers to them have real consequences for real people, including, in many cases, for our students.

The ascendance of the five core econometric tools – experiments, matching and regression methods, instrumental variables, differences-in-differences and regression discontinuity designs – marks a paradigm shift in empirical economics. On the merit of how much does the book intend to give the reader the details on these things is another issue.

Posing several well-chosen empirical questions in social science, Mastering 'Metrics develops methods to provide the answers and applies them to interesting datasets.

While very readable and conversational in tone, it is still rather terse in some sections as if you're expected to already have seen most of the material here on a previous introductory course. With an engaging, insightful style, Angrist and Pischke catch readers up on five powerful methods in this area. This playful examination of core econometric concepts is an accessible and valuable tool for beginning econometricians. The disconnect between econometric teaching and econometric practice goes beyond questions of tone and illustration.They certainly bring in a lot of that - where they talk about apples-to-apples comparison; but the emphasis is not approached as a general method of empirical analysis and the book can go far if that is emphasized. Few fields of statistical inquiry have seen faster progress over the last several decades than causal inference. Even where random assignment is impractical, the notion of the experiment we’d like to run guides our choice of empirical questions and disciplines our use of non-experimental tools and data.