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 led to an article in <I>Statistica Neerlandica</I> (2003). Vol. 57, issue 4, pages 439-469.<P> The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this...</p></i>

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

We examine monetary policy options for a small open economy where sovereign default might occur due to intertemporal insolvency. Under interest rate policy and floating exchange rates the equilibrium is indetermined. Under a fixed exchange rate the equilibrium is uniquely determined and...

This paper examines equilibrium determination under different monetary policy regimes when the government might default on its debt. We apply a cash-in-advance model where the government does not have access to non-distortionary taxation and does not account for initial outstanding debt when it...

In this paper we develop and estimate a behavioral model of inflation dynamics with monopolistic competition, staggered price setting and heterogeneous firms. In our stylized framework there are two groups of price setters, fundamentalists and naive. Fundamentalists are forward-looking in the...

Since dollarized countries import US monetary policy, identifying US monetary shocks through sign restrictions on US variables only, does not use all available information. In this paper we therefore include dollarized countries,which enable us to restrict more variables and leave the responses...

Traditional ways of analyzing the effects of monetary policy shocks via structural vector autoregressions require the use of unrealistic identifying assumptions: they either do not allow for a response of output and prices on impact of the shock, or they exclude contemporaneous values of these...

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...