Research into time series models of changing variance and covariance, which is often called volatility model, has exploded in the last 10 years. Financial series are characterized by periods of large volatility followed by periods of relative quietness. This type of clustering led to the idea...

This dissertation quantitatively evaluates selected labor market policies in a search-matching model with skill heterogeneity where high-skilled workers can take temporary jobs with skill requirements below their skill levels. The joint posterior distribution of structural parameters of the...

This paper presents the R-package <B>MitISEM</B> (mixture of <I>t</I> by importance sampling weighted expectation maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density kernel -- typically a posterior density kernel -- using an adaptive mixture...</i></b>

This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...

This work proposes the application of a stochastic volatility model with jumps to the BRL/USD exchange rate. This model decomposes the process into transitory and permanent components that capture the jumps in the level of the unobserved volatility process. The model estimation is done using...

Two connected extensions of the Fay–Herriot small area level model that are of practical and theoretical interest are proposed. The first extension allows for the sampling error to be non-symmetrically distributed. This is important for cases in which the sample sizes in the areas are not...

In this paper we consider bayesian semiparametric regression within the generalized linear model framework. Specifically, we study a class of autoregressive time series where the time trend is incorporated in a nonparametrically way. Estimation and inference where performed through Markov Chain...