second shows the relevance of the adaptive mixture procedure through the Bayesian estimation of a mixture of ARCH model …

Simulated Likelihood, Expectation Maximization Algorithm and Bayesian MCMC simulators, are proposed and compared via generated … data experiments. The chief finding is that Bayesian approach outperforms others in terms of accuracy, speed and stability …

mixedeffect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for …

analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and …

Forecasting errors pose a serious problem of identification, often neglected in empirical applications. Any attempt of …

This paper addresses a fundamental identification problem in the structural estimation of dynamic oligopoly models of … estimated model, despite the non-separate identification of the three primitives. Third, we show that there is a general class … illustrates how ignoring the non-identification of these counterfactuals (i.e., making a `normalization assumption' on some of the …

Forecasting errors pose a serious problem of identification, often neglected in empirical applications. Any attempt of …

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with …

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with …