Forecasting under high uncertainty – Towards a fuller appreciation of the risk environment

Over recent weeks, several international institutions published their best guesses at quantifying the economic damage by the novel Coronavirus on national, regional and the global economy. One cannot go without noticing the considerable variation between projections and the frequency of revisions given the uncertainty ahead. Economic forecasting in a ’business-as-usual‘ environment is already challenging, let alone when confronted by a black swan event1 such as the COVID-19 outbreak.

Economists attempt to use their sophisticated econometric toolkit to model the severity of the decline in output and debate which shape – be it U, V or W – the economic recovery will assume. However, the uncertainty ahead warrants a caveat that these projections are subject to notable downside risks with economic repercussions which no model can possibly capture.

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