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...

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...

This paper empirically examines the theoretically ambivalent relationship between socially responsible investing (SRI) and stock performance. It extends the existing literature by considering both the US and the entire European stock markets as well as by using consistent world-wide corporate...

This paper studies the dynamics of international consumption risk sharing among the G7 countries. Based on the dynamic conditional correlation model due to Engle (2002), we construct a time-varying, consumption-based measure of risk sharing. We find that although the exposure to country-specific...