This article discusses the use of Integrated Nested Laplace Approximations (INLA) in inference procedures and construction of unit root tests in stochastic volatility models. This approach allows to obtain accurate analytical approximations for the parameters and latent volatities, representing...

In this article we introduce a new methodology for modeling curves with a dynamic structure, using a non-parametric approach formulated as a state space model. The non-parametric approach is based on the use of penalized splines, represented as a dynamic mixed model. This formulation can capture...

In this paper we analyze a maximum likelihood estimator using data cloning for stochastic volatility models.This estimator is constructed using a hybrid methodology based on Integrated Nested Laplace Approximations to calculate analytically the auxiliary Bayesian estimators with great accuracy...

This paper presents new evidence on the role of cognitive skills in promoting economic growth rate. The novelties in this paper are that we use a within country dataset (Brazilian state and municipality levels data) and a new methodology, a nonparametric kernel regression estimation with mixed...

The paper discusses the use of statistical methods in the comparison of investment fund performance indicators. The analysis is based on the robust statistics proposed by Ledoit and Wolf (2008), for the pairwise comparison of funds and two generalizations for sets of multiple investment funds....

This paper assesses the relation between the yield curve and the main macroeconomic variables in the U.S. between early 1970s and 2000. We revisit the macro-finance model of Diebold et al. (2006) with the inclusion of a stochastic volatility structure for the latent factors and macroeconomic...

This paper discusses Bayesian procedures for factor selection in dynamic term structure models through simulation methods based on Markov Chain Monte Carlo. The number of factors, besides influencing the fitting and prediction of observed yields, is also relevant to features such as the...

This article discuss the use of Bayesian methods for inference and forecasting in dynamic term structure models through Integrated Nested Laplace Approximations (INLA). This method of analytical approximations allows for accurate inferences for latent factors, parameters and forecasts in dynamic...