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 analyze the interaction between monetary policy in the US and the global economy, using a global vector autoregressive model with time-varying parameters and stochastic volatility (TVP-SV-GVAR). We find that a contractionary US monetary policy shock leads to a persistent fall in international...

This study investigates exchange rate movements in the Exchange Rate Mechanism (ERM) of the European Monetary System (EMS) and in the Exchange Rate Mechanism II (ERM-II). On the basis of the variant of the target zone model proposed by Bartolini and Prati (1999) and Bessec (2003), we set up a...

We study empirically how various labor market institutions - (i) union density, (ii) unemployment benefit remuneration, and (iii) employment protection - shape fiscal multipliers and output volatility. Our theoretical model highlights that more stringent labor market institutions attenuate both...

Assessing the robustness of the results of econometric analysis is a long standing subject of lively research. The majority of the literature focuses on sensitivity to model specification, while the quantification of sensitivity to sets of influential observations has received relatively...

We assess the role that nontradable goods play as a determinant of fiscal spending multipliers, making use of a two-sector model. While fiscal multipliers increase with the share of nontradable goods, an inverted U-shaped relationship exists between multiplier size and the import share....

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsimonious mixture modeling that allows for fat-tailed errors...