In this article we use spatial birth-death processes to estimate the number of states k of a switching model. Following Preston (1976) and Stephens (1998) matching the detailed balance condition for the underlying birth-death process results in an unique invariant probability measure with the...

This paper studies the dynamics of an asset pricing model based on simple deterministic agents.

In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC...

In the present paper we consider Bayesian estimation of a finite mixture of models with random effects which is also known as the heterogeneity model. First, we discuss the properties of various MCMC samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing.(...)

In this paper we carry out fully Bayesian analysis of the general heterogeneity model, which is a mixture of random effects model, and its special cases, the random coefficient model and the latent class model. Our application comes from Conjoint analysis and we are especially interested in what...

In this paper, we compare the empirical properties of closed- and open-economy DSGEmodels estimated on Euro area data. The comparison is made along several dimensions;we examine the models in terms of their marginal likelihoods, forecasting performance,variance decompositions, and their...

A small strand of recent literature is occupied with identifying simultaneity in multipleequation systems through autoregressive conditional heteroscedasticity. Since thisapproach assumes that the structural innovations are uncorrelated, any contemporaneousconnection of the endogenous variables...

In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

A huge body of empirical and theoretical literature has emerged on the relationship between foreign exchange (FX) uncertainty and international trade. Empirical findings about the impact of FX uncertainty on trade figures are at best weak and often ambiguous with respect to its direction. Almost...