Mastering 'Metrics: The Path from Cause to Effect

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The more gnarly statistical proofs seem to be left to their other more advanced book Mostly Harmless Econometrics. Though personally I like the Kung Fu Panda and I feel the idea was interesting and even well placed - its implementation did not flow through. But Mastering 'Metrics doesn't actually give you any of the tools you would need to *do* causal inference. If you seek to make causal inferences, or understand those made by others, you will want to read this book as soon as possible.

Like their other book, the key goal the authors have in mind is for budding econometricians to be able to extract causal estimates of relationships from a variety of data.

Unfortunately, practitioners’ actual statistical and econometric knowledge and intuition may be more limited than their level of academic exposure would suggest. Angrist and Jörn-Steffen Pischke, Mastering ’Metrics helps readers avoid the use of brute-force computing power to analyze data. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Econometrics courses promise to equip our students with the powerful tools economists use to understand the economic relationships hidden in data.

By using the Web site, you confirm that you have read, understood, and agreed to be bound by the Terms and Conditions.Understanding the dependencies within the data will strongly influence the choice of strategies for devising useful models.

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. The Population Bomb 123 Masters of 'Metrics: The Remarkable Wrights 139 Appendix: IV Theory 142 4 Regression Discontinuity Designs 147 4. Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Following our instrumental variable regression chapter, built around three interesting uses of instrumental variable regression to capture causal effects, we tackle regression discontinuity designs and differences-in-differences methods. Hal Varian, chief economist at Google "Few fields of statistical inquiry have seen faster progress over the last several decades than 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. Using real-world examples and only elementary statistics, Angrist and Pischke convey the central methods of causal inference with clarity and wit.

Experiments can also be used as benchmarks for framing one’s thinking - as an econometrician, consider what experiment you would like to run, then try to mimic it with available statistics as best as possible. The underlying theory is clearly articulated in the text, as well as explored in more (mathematical) detail in the appendix to each chapter. Melvyn Weeks, University of Cambridge "Posing several well-chosen empirical questions in social science, Mastering 'Metrics develops methods to provide the answers and applies them to interesting datasets.

A breezy presentation of very general topics, it is nevertheless packed with good, commonsense advice on how to perform econometric analysis. Introducing 5 powerful econometric tools, the book well explains how to build a valid counterfactual and intuitions behind regressions.