impressions from Princeton

This one-day trip to Princeton was quite profitable thanks to the exchanges I had with the members of the econometrics department there. In particular, I really appreciated the interactive way the Gregory Chow seminar was run and the way the audience got quickly focused on the central issue of ABC, namely running inference under limited information (provided by the summary statistics). What is most interesting (to me) is that (a) the discussants focused on the limiting normal distribution as a way to bypass (in)sufficiency and (b) they did not seem to deem the use of an insufficient summary statistics a major drawback of the method. I also took advantage of this trip to correct a restricted and misguided impression on the existence of unbiased estimators, to discuss about loss functions for set estimation and empirical likelihood, and to mention the interesting paradox of the normal mean norm (Example 4.2.8 in The Bayesian Choice) where the MLE based on the distribution of the estimator of the norm improves upon this initial estimator…