*"In fact, the validity of linear regression as an empirical tool does not turn on linearity either...The statement that regression approximates the CEF lines up with our view of empirical work as an effort to describe the essential features of statistical relationships, without necessarily trying to pin them down exactly."*- Mostly Harmless Econometrics, p. 26 & 29

I really like

*Mostly Harmless Econometrics*. I started reading it some time ago. I have had several formal courses in econometrics, mathematical statistics, and experimental design, and have spent a lot of time in the pages of Golberger's

*A Course in Econometrics*., Greene's

*Econometric Analysis*, and Kennedy's

*A Guide to Econometrics*, as well as Hastie, Tibshirani, and Friedman's

*Elements of Statistical Learning: Data Mining, Inference, and Prediction*, but Angrist and Pishke's book really speaks to me in the every day empirical work that I find myself caught up in. The other textbooks are great, maybe essential for a student, but Mostly Harmless Econometrics is a must have for the practitioner. MHE is not a substitute for a solid econometrics background, in fact, it would not have made sense to me without it, but it wouldn't have as much meaning either without some prior experience. I find myself re-reading sections because on the job data challenges continue to make this book more relevant every day. The other textbooks get you started with the theory (again very important). They are great for 'highway' use, when your are coasting on the smooth surfaces of textbook ideals. MHE gives you that push you need when you get bogged down on the very muddy roads of real life empirical work. Its the off-road backwoods survival manual for practitioners.