This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the...

We address the problem of parameter estimation for diffusion driven stochastic volatility models through Markov chain Monte Carlo (MCMC). To avoid degeneracy issues we introduce an innovative reparametrisation defined through transformations that operate on the time scale of the diffusion. A...

We contribute to the growing empirical literature on monetary and fiscal interactions by applying a sign restriction identification scheme to a structural TVP-VAR in order to disentangle and evaluate the policy shocks and policy transmissions. This in turn allows us to study the Great Recession...

We contribute to the growing empirical literature on monetary and fiscal interactions by applying a sign restriction identification scheme to a structural TVP-VAR in order to disentangle and evaluate the policy shocks and policy transmissions. This in turn allows us to study the Great Recession...

We analyse the Generalised Hyperbolic distribution as a model for fat tails and asymmetries in multivariate conditionally heteroskedastic dynamic regression models. We provide a standardised version of this distribution, obtain analytical expressions for the log-likelihood score, and explain how...

We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form with regard to the 'news impact' function. We propose an...

We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form with regard to the 'news impact' function. We propose an...

We consider a semiparametric distributed lag model in which the “news impact curve” m is nonparametric but the response is dynamic through some linear filters. A special case of this is a nonparametric regression with serially correlated errors. We propose an estimator of the news impact...

We use information from two prospective British birth cohort studies to explore the antecedents of adult malaise, an indicator of incipient depression. These studies include a wealth of information on childhood circumstances, behaviour, test scores and family background, measured several times...

Probably not. First, allowing the probabilities attached to the states of the economy to differ from their sample frequencies, the Consumption-CAPM is still rejected by the data and requires a very high level of Relative Risk Aversion(RRA) in order to rationalize the stock market risk premium....