When is growth at risk?
Prepared for the Spring 2020 edition of the Brookings Papers on Economic Activity [Link]
This paper empirically evaluates the potentially non-linear nexus between financial indicators and the distribution of future GDP growth, using a rich set of macroeconomic and financial variables covering 13 advanced economies. We evaluate the out-of-sample performance including a fully real time exercise based on a flexible non parametric model and then use a parametric model for estimating the moments of the distribution of GDP conditional on financial variables and evaluating their in-sample estimation uncertainty. Our overall conclusion is pessimistic: moments other than the conditional mean are poorly estimated and no predictors we consider provide robust and precise advance warnings of tail risks or indeed about any features of the GDP growth distribution other than the mean. In particular, financial variables contribute little to such distributional forecasts, beyond the information contained in real indicators.