Obtaining reliable estimates of the volatility of interest rates and exchange rates is a necessary condition to evaluate issues related to monetary independence and fear of floating. In this paper we use methods which explicitly account for structural breaks in the volatility dynamics in order...

We use Bayesian Model Averaging (BMA) to evaluate the robustness of determinants of economic growth in a new dataset of 255 European regions in the 1995-2005 period. We use three different specifications based on (1) the cross-section of regions, (2) the cross-section of regions with country...

We use a Bayesian dynamic latent factor model to extract world, regional and country factors of real interest rate series for 22 OECD economies. We find that the world factor plays a privileged role in explaining the variance of real rates for most countries in the sample, and accounts for the...

If oil exporters stabilize the purchasing power of their export revenues in terms of imports, exchange rate developments (and particularly, developments in the US dollar/euro exchange rate) may contain information about oil price changes. This hypothesis depends on three conditions: (a) OPEC has...

Panel data is used to investigate the extent of R&D spillovers between OECD countries, and the importance of barriers to technology adoption in affecting the benefits of such spillovers. Our results indicate that countries with less regulated goods and labour markets benefit more from foreign R&D.

We propose exploiting the term structure of relative interest rates to obtain estimates of changes in the timing of a currency crisis as perceived by market participants. Our indicator can be used to evaluate the relative probability of a crisis occurring in one week as compared to a crisis...

We analyze the performance of Bayesian model averaged exchange rate forecasts for euro/US dollar, euro/Japanese yen, euro/Swiss franc and euro/British pound rates using weights based on the out-of-sample predictive likelihood. The paper also presents a simple stratified sampling procedure in the...

We tackle explicitly the issue of model uncertainty in the framework of binary variable models of currency crises. Using Bayesian model averaging techniques, we assess the robustness of the explanatory variables proposed in the recent literature for both static and dynamic models. Our results...

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved components model with an asymmetric cyclical component. The asymmetric cycle is defined as a sine-cosine wave where the frequency of the cycle depends on past oil price...

In this paper we put forward a Bayesian Model Averaging method dealing with model uncertainty in the presence of potential spatial autocorrelation. The method uses spatial filtering in order to account for different types of spatial links. We contribute to existing methods that handle spatial...