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Predicting impact

A year after UK lockdown, the Cambridge Centre for Risk Studies calls for probability-based scenario approach to forecasting crises due to unreliability of well-established models.

Businesswoman wearing a face mask as she stares into the distance out of an office block window.

The unreliability of well-established macroeconomic models at times of upheaval such as the COVID-19 pandemic point out the need for a new ‘probability’-based scenario approach to forecasting economic output in crises, says the Cambridge Centre for Risk Studies at Cambridge Judge Business School.

A year after the first UK lockdown, the Centre calls for an approach that reflects a spectrum of circumstances in which various economic forecasts representing different scenarios are assigned a probability weighting – based on historical precedent, expert judgement, secondary economic models or statistical analysis.

“Scenarios enable companies to minimise regret in their crisis management,” says a blogpost posted on the Centre’s blog by Dr Scott Kelly, Senior Risk Researcher at the Cambridge Centre for Risk Studies. The blogpost is entitled “How Well did Economic Models Perform in the COVID-19 Economic Crisis?”

The Centre has in recent years used four variants of risk scenario for pandemics, labelled L1 to L4 from least to most impactful, and applied these brackets to 19 national economies comprising 80% of world GDP for use by businesses in contingency planning.

In comparing forecasts of the pandemic’s impact on the economy to actual results over the past year, national economies generally performed better than models expected them to – due in part to massive government stimulus packages.

The Centre found further that 17 of the 19 national economies performed within the range of the four scenarios, so “companies that used the scenario variants for contingency planning around the range of potential outcomes were not caught out by the actuality.” (There were two outliers owing to pre-pandemic structural conditions in their economies: Italy recovered faster than the most optimistic projections, and India has failed to meet even the most pessimistic expectations.)

“Our approach suggests that a scenario risk-based approach is better than following a best-estimate projection,” the blogpost concludes. “Scenarios are able to place an envelope around possible outcomes and are useful for preparedness, contingency planning, communicating assumptions and uncertainty, and exploring options for what-ifs. Businesses using a range of scenarios are less likely to find themselves surprised by projection failures. In decision science this is known as minimising regret in planning. The 19 economies covered  by the Centre’s research on this topic are: India, Russia, Brazil, Indonesia, Turkey, Mexico, Spain, Switzerland, the Netherlands, South Korea, United Kingdom, Canada, Italy, Japan, France, Australia, Germany, United States and China.