Asymptotic Theory in Economics I am interested in deepening my Asymptotic Theory understanding. My current knowledge is that of a typical PhD student (from a decent University), say at the level of Green's textbook. Are there any good book(s) that you would recommend?
Much appreciated. 
 A: Ferguson's A Course in Large Sample Theory is the best concise introduction to the topic, and it is written in a nice didactic way of having an equivalent of a week's lecture course material in a chapter followed by a strong set of exercises. (Ferguson introduced GMM in 1968 under the name of the minimum $\chi^2$, and it is tucked in as one of the exercises in that book). Van der Vaart's Asymptotic Statistics, recommended by others, is great, too, but it's going off in weird directions (for an economist). Another relatively easy introduction to the first-order asymptotics is Lehmann's Elements of Large Sample Theory. I would argue though that you would get a better mileage out of a book like Smith & Young's Essentials of Statistical Inference, as it will teach you about how statisticians think (sufficiency, UMPT, Cramer-Rao bound, etc.).
Of course you won't find the odd econometric asymptotics such as unit roots or weak instruments. Few statisticians have heard of them, and these are wa-a-ay too exotic for them. However, you would definitely want to revisit these unusual papers to shake off the wrong belief that everything asymptotic is asymptotically normal at $\sqrt{n}$ rate (you can find disturbing counterexamples here and there, too).
A: Since you mention Greene's book, I assume you are interested in more in-depth understanding of asymptotic statistics. Then I can recommend A. van der Vaart's "Asymptotic statistics" and H. White's "Asymptotic theory for econometricians". Also J. Wooldridge's "Econometric Analysis of Cross Section and Panel Data" has nice chapters on asymptotic theory.
A: "Asymptotic theory for econometricians" by Halbert White. "Asymptotic Theory of Statistics and Probability", by Anirban DasGupta.
