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In the face of the COVID-19 pandemic, Queen’s University economists are helping policymakers build a roadmap for economic recovery efforts. The focus is on providing local and provincial leaders with the best available high-frequency economic projections to use alongside health projections when making decisions.  

Through , a Kingston-based research and analytics firm, the group of Queen’s researchers has developed a COVID-19 policy analysis tool. Already adapted for Ontario the preliminary  estimates imply that COVID-19 led to a loss in Ontario’s GDP of 9.4 per cent in March, 23.7 per cent in April, and 26 per cent in May compared to what would have been expected. This implies a loss of over $40 billion across the province or $7,500 per household. 

“These are huge numbers, and that is just where we are after May,” said Huw Lloyd-Ellis (Economics). “Losses will accumulate going forward. How big they end up being depends on how quickly the province can relax restrictions on various industries, and how the behavior of firms and consumers change going forward.” 

The team refers to their framework as the STUDIO model, a flexible framework that can be adapted for a wide variety of scenarios. The acronym stands for “Short-Term Under-capacity Dynamic Input-Output” model, reflecting its intended use for month-to-month scenario building during economic disasters. 

“We don’t pretend that we can predict the future in terms of how the disease will spread, or how government policy, and consumer and firm behavior will change in the coming months,” says Christopher Cotton (Economics), the Jarislowsky-Deutsch Chair in Economic & Financial Policy at Queen’s. “The strength of STUDIO is in its flexibility, and its ability to provide economic projections for any number of alternative scenarios that we may throw at it.”  

The model produces an array of projections to show what will happen to the economy in different situations, depending on how the disease spreads, and how governments, consumers and firms respond to it. Understanding how economic outcomes respond to policy choices under alternative scenarios will help governments plan their response to COVID-19 over the coming months.  

Even under a very optimistic scenario, where the economy reopens rapidly and largely recovers by the end of the year, the preliminary estimates are that Ontario will experience a 9.9 per cent loss in its annual GDP, which amounts to over $83 billion in total or almost $15,000 per household. While, as always, these estimates are subject to considerable uncertainty, they are consistent with several other private and public sector forecasts.  

Potential jumps in the transmission of the disease or delays in reopening the economy could easily increase these numbers. The model’s projections under a more pessimistic schedule for reopening the economy shows an average GDP loss exceeding $20,000 per Ontario household.  

The researchers are also extending their analysis to the local level and breaking down the results by industrial sector. For Kingston and Frontenac County, for example, the projected GDP losses are slightly less than the Ontario average, but certain industries such as those related to travel and healthcare, are taking a big hit. Such insights can help policymakers direct support to the places and the people that need it most. 

The team has made some of their projections available through an .  

“The dashboard provides just a taste of what the model can do,” says Bahman Kashi (Economics), President of Limestone Analytics. “We are expanding our analysis across regions, provinces and states in North America, and we are adapting our models for use in developing countries. We are also partnering with several organizations and other groups at Queen’s to build a comprehensive policymaking dashboard that will bring together both economic and health projections in one place for all of Canada.” 

The team has worked closely with members of the  to understand the data needs of local leaders, and  to help support graduate student participation on the project.