In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

This discussion paper resulted in a publication in the <A href="http://people.few.eur.nl/hkvandijk/PDF/Bos_Mahieu_and_Van_Dijk_2000_JoAE_daily_exchange_rate.pdf">'Journal of Applied Econometrics'</A>, 2000, 15(6), 671-696.<P> We construct models which enable a decision-maker to analyze the implications oftypical timeseries patterns of daily exchange rates for currency risk management. Ourapproach is...</p></a>

Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

We argue that the failure to disentangle the evolution of the Canadian currency from the U.S. currency leads to potentially incorrect conclusions regarding the case of Dutch disease in Canada. We propose a new approach that is aimed at extracting both currency components and energy- and...

This discussion paper resulted in a publication in (I. Edward George (eds.)), 2001, Bayesian methods with applications to science, policy and official statistics, Eurostat, 31-40.<P> Internationally operating firrns naturally face the decision whether or not to hedge the currencyrisk implied by...</p>

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this article it is argued that one...

This discussion paper led to a publication in the 'Journal of Applied Econometrics', 2000, 15(6), pages 671-696.<P> Exchange rates typically exhibit time-varying patterns in both means andvariances. The histograms of such series indicate heavy tails. In thispaper we construct models which enable a...</p>

We examine recursive out-of-sample forecasting of monthly postwarU.S. core inflation and log price levels. We use theautoregressive fractionally integrated moving average model withexplanatory variables (ARFIMAX). Our analysis suggests asignificant explanatory power of leading indicators...

When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on realised or bipower variation are applied. This article instead starts from a continuous time diffusion model and derives a parametric analog at high frequency for it, allowing...

A key application of long memory time series models concerns inflation. Long memory implies that shocks have a long-lasting effect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for inflation,...