The aim of this paper is to identify the different sources of persistence of output fluctuations. We propose an unobserved components model that allows us to decompose GDP series into a trend component and a cyclical component. We let the drift of the trend component to switch between different...

In the literature of risk analysis different synthetic indices are built on the bases of some indicators and in this work we propose to use, alternatively to PCA, a combination statistical procedure. The univariate indices that we use are those proposed by _V-lab_ using a nonparametric...

We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible...

This paper analyses features of 28 provincial growth-cycles in China’s economy from March 1989 to July 2009. We study the multivariate synchronization of provincial cycles and the selection of the number of cycles phases’ by means of panel Markov-switching models. We obtain evidence that...

Interactions between eurozone and United States booms and busts and among major eurozone economies are analyzed by introducing a panel Markov-switching VAR model. The model is well suitable for a multi-country cyclical analysis and accommodates changes in low and high data frequencies and...

In high-dimensional vector autoregressive (VAR) models, it is natural to have large number of predictors relative to the number of observations, and a lack of efficiency in estimation and forecasting. In this context, model selection is a difficult issue and standard procedures may often be...

Relatively small sectoral productivity shocks could lead to sizable macroeconomic variability. Whereas most contributions in the literature analyze the issue of aggregate sensitivity using simple general equilibrium models, a novel approach is proposed in this paper, based on stochastic...

We introduce a new class of adaptive Metropolis algorithms called adaptive sticky algorithms for efficient general-purpose simulation from a target probability distribution. The transition of the Metropolis chain is based on a multiple-try scheme and the different proposals are generated by...

A new Bayesian multi-chain Markov Switching GARCH model for dynamic hedging in energy futures markets is developed by constructing a system of simultaneous equations for the return dynamics on the hedged portfolio and futures. More specifically, both the mean and variance of the hedged portfolio...

Recent studies have showed that it is troublesome, in practice, to distinguish between long memory and nonlinear processes. Therefore, it is of obvious interest to try to capture both features of long memory and non-linearity into a single time series model to be able to assess their relative...