The main purpose of this paper is to develop generalized 'State Dependent Models' (SDM) in a multivariate framework for empirical analysis. This significantly extends the existing SDM which only allow univariate analysis following a simple AR process. The extended model enables greater possibility for empirical analysis of economic relationships. The principle advantage of SDM is that it allows for a general form of non-linearity and can be fitted without any specific prior assumption about the form of non-linearity. We describe the general structure of the SDM and the problem of its identification is also considered. Finally, we apply the algorithm to show the impact of sentiment and income when modelling US consumption.