Managing GDP tail risk

We propose a novel framework to analyze how policy-makers can manage risks to the median projection and risks specific to the tail of gross domestic product (GDP) growth. By combining a quantile regression of GDP growth with a vector autoregression, we show that monetary and macroprudential policy shocks can reduce credit growth and thus GDP tail risk. So policymakers concerned about GDP tail risk would choose a tighter policy stance at the expense of macroeconomic stability. Using Canadian data, we show how our framework can add tail event information to projection models that ignore them and give policy-makers a tool to communicate the trade-offs they face.