A Panorama of Advances in Econometric Analysis

Abstract

The purpose of this paper is to spell out current interests in advanced statistical methods for statistics in general, and econometrics in particular, in the spirit of credible and efficient statistics. By pointing out these advances, the hope is to make researchers aware of them, so that future research will be credible and significant. The panorama of recent advances covered in this paper consists of Bayesian assett allocation (Black-Litterman model), copula theory, partial identification of statistical models, the role of random set theory in set estimation, the optimal transport methods, and the quantum modeling in economics.