This paper introduces the family of Dynamic Kernel models. These models approximate the predictive density function of a time series through a weighted average of kernel densities possessing a dynamic bandwidth. A general specification is presented and several particular models are studied in...

This paper introduces the family of Dynamic Kernel models. These models approximate the predictive density function of a time series through a weighted average of kernel densities possessing a dynamic bandwidth. A general specification is presented and several particular models are studied in...

The paper investigates the macroeconomic and financial effects of oil prices shocks in the euro area since its creation in 1999, with a special focus on the recent slump. The analysis is carried out episode by episode, within a time-varying parameter framework, consistent with the view that "not...

The paper investigates the macroeconomic and financial effects of oil prices shocks in the euro area since its creation in 1999, with a special focus on the recent slump. The analysis is carried out episode by episode, within a time-varying parameter framework, consistent with the view that "not...

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....