Yet they get no attention in Studenmund (2011) or Gujarati and Porter (2010), while Hill, Griffiths, and Lim (2011) and Wooldridge (2012) briefly attend to differences-in-differences only. Many of you are probably thinking that statement doesn't set a very high bar, because most econometrics books are drier than a particular arid corner of the Sahara, and almost impenetrable to anyone without high-level mathematics skills.

One of the limitations of finance is that randomized trials cannot be used to answer key questions; nevertheless, focusing on how to conduct randomized trials and formulate tests is critical to doing good econometric work. This showed that people receiving more healthcare were not significantly more healthy - which seemed a disappointing result.This valuable book connects the dots between mathematical formulas, statistical methods, and real-world policy analysis.

Omitted variables bias is the difference between this ideal regression and the regression you’ve got at hand. These questions are then answered with data and a focussed and carefully executed empirical analysis. I assign Angrist and Pischke’s Mostly Harmless Econometrics in virtually all of my graduate courses … But it’s still a very hard book… What’s been needed for some time is a more casual introduction. In places where the story of a DD is flowing, an IV comparison takes one off guard in terms of now being able to apply and compare. It is great that the author separate mathematical derivation and concept intuition, it really helps in understanding the concept.

Building on my introductory data analysis course, some of this is review, but in the context of bridging the quantitative we learned last quarter and connecting it accurately and thoroughly to the qualitative policy analysis we've been working on this quarter, its utility is essential. But the IV chapter was better in terms of the details whereas RDD chapter isn't as heavy on those details. Fortunately, Angrist and Pischke have a more accessible book that I just finished reading, Mastering 'Metrics. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. I'll probably be keeping this book near my desk at all times -- it really is an invaluable reference.

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. Another example relates to health insurance - at first glance, those with insurance seem healthier than those that don’t have it.Our views are necessarily colored by the areas of applied microeconomics in which we are active, but we look over the fence at other areas as well. Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. The disconnect between econometric teaching and econometric practice goes beyond questions of tone and illustration. There's lots of math to be found in the book, but the authors gently walk the reader through each equation; I'd say little more than a basic knowledge of algebra is required (although some fluency with probability wouldn't hurt). The methods that are covered are extremely important in social science and so having an idea of what they do and why we use them is helpful.