This paper discusses new development in nonparametric econometric approaches related to empirical modeling of demand decisons. It shows how diverse recent approaches are, and what new modeling options arise in practice. We review work on nonparametric identification using nonseparable functions, semi-and nonparametric estimation approaches involving inverse problems, and nonparametric testing approaches. We focus on classical consumer demand systems with continuous quantities, and do not consider approaches that involve discrete consumption decisions as are common in empirical industrial organization. Our intention is to give a subjective account on the usefulness of these various methods for applications in the field.