finite covariate dependent mixture models, in which the mixing probabilities are proportional to a product of a constant and …-breaking processes for modeling the mixing probabilities. We show that the posterior in these two models is weakly and strongly …

In nonlinear state-space models, sequential learning about the hidden state can proceed by particle filtering when the … not hold in complex environments, such as the incomplete-information equilibrium models considered in financial economics … state-observation sampling (SOS) filter, for general state-space models with intractable observation densities. Second, we …

statistical models. This trend is also true for economic data, where high-dimensional and nonlinear/nonparametric inference is the … is particularly important for inference in modern models of high dimensions and increased complexity.We begin with a … can be extended in a straightforward way to various classes of interesting econometric models. In particular, the …

In this paper we provide a brief overview of some of the most recent empirical research on spatial econometric models … econometric models. We also examine some diagnostic measures to evaluate the spatial autocorrelation of the pseudo … spatial econometric models: Spatial Lag combined with two versions of regression trees: non-spatial regression tree and …

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method …

(DSGE) models with a special emphasis on Bayesian methods. First, I discuss the evolution of DSGE models over the last … couple of decades. Second, I explain why the profession has decided to estimate these models using Bayesian methods. Third, I … briefly introduce some of the techniques required to compute and estimate these models. Fourth, I illustrate the techniques …

policy analysis, portfolio allocations, or risk-management decisions. Use of multiple models does not necessarily solve the … various techniques for combining or averaging alternative models in the context of forecasting the Canadian term structure of … of four empirical term structure models: this includes the Diebold and Li (2003) approach and three associated …

policy analysis, portfolio allocations, or risk-management decisions. Use of multiple models does not necessarily solve the … various techniques for combining or averaging alternative models in the context of forecasting the Canadian term structure of … of four empirical term structure models: this includes the Diebold and Li (2003) approach and three associated …

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method …

(DSGE) models with a special emphasis on Bayesian methods. First, I discuss the evolution of DSGE models over the last … couple of decades. Second, I explain why the profession has decided to estimate these models using Bayesian methods. Third, I … briefly introduce some of the techniques required to compute and estimate these models. Fourth, I illustrate the techniques …