Mastering 'Metrics: The Path from Cause to Effect

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Statistics is second only to accounting among the technical skills necessary for engaging in modern finance and is fundamental for anyone who considers quantitative work a core element of finance. Admitting that the academic way keeps the writing clean, but then it also makes the reader lose interest.

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. 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. Albeit generally unrelated to finance, these are all fascinating topics for anyone interested in critical policy issues. Readers who seek core insights into finance will be disappointed, but what the book lacks in financial specifics, it makes up for with clear thinking. This to me seems disconnected and you don't really get the flow in the argument while reading the book.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. apos;Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. But Mastering 'Metrics doesn't actually give you any of the tools you would need to *do* causal inference. One of the many strengths of Mastering ‘Metrics is the use of various cases to illustrate problems, tools and outcomes … the lucid and intuitive approach used by the authors is refreshing compared with the text-book style of writing we have become accustomed to in ‘metrics.

As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. But the IV chapter was better in terms of the details whereas RDD chapter isn't as heavy on those details.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. Consider a standard econometrics textbook - say Wooldridge - it actually draws a framework where you know - no matter what the empirical problem is, you need to think in terms of identification, endogeneity and the underlying logic of counter-factuals. No one willingly reads a book on econometrics to close this knowledge gap, so technical skills atrophy rather than advance with money management experience.