The uncertainty surrounding economic forecasts is generally related to multiple sources of risks, of both domestic and foreign origin. This paper studies the predictive distribution of Italian GDP growth as a function of selected risk indicators, relating to both financial and real economic developments. The conditional distribution is characterized by expectile regressions. Expectiles are closely related to the Expected Shortfall, a well-known measure of risk with desirable properties. Here a decomposition of Expected Shortfall in terms of the contributions of different indicators is proposed, which allows the main drivers of risk to be tracked over time. Our analysis of the predictive distribution of GDP confirms that financial conditions are relevant for the left tail of the distribution but it also highlights that indicators of global trade and uncertainty have strong explanatory power for both the left and the right tail. Their usefulness is also supported in a pseudo real-time predictive context. Overall, our findings suggest that Italian GDP risks have been driven mostly by foreign developments throughout the Great Recession, by the domestic financial conditions at the time of the sovereign debt crisis and by economic policy uncertainty in more recent years.