A researcher from Concordia University, Erkan Yönder, plunged into the world of artificial intelligence to anticipate the evolution of rents in several large Canadian cities. And the results will leave you speechless…
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His predictions are impressive: in less than ten years, the rent for a two-bedroom apartment could reach $5,600 in Toronto and $7,750 in Vancouver.
Montreal, for its part, would not be left behind, with a cost of $4,325 per month for a similar apartment in 2032. These figures raise crucial questions about the future of housing in Canada.
“The idea of this project is to consider the market on a neighborhood scale,” explained the associate professor of finance and real estate at the John Molson School of Management. By taking a closer look at 427 census subdivisions, we can see what drives rent prices for certain demographic groups.”
According to Mr. Yönder, Canada’s immigration and housing policies are out of sync. In 2023, for example, Canada would have more than 1.2 million new Canadians, but only 200,000 new housing units.
“Every year we welcome new people to Canada, which has the effect of exploding the demand for housing. We must be able to stimulate supply in an equivalent manner to stabilize the cost of rent.”
The annual housing completion rate today is between 1 and 3% in Canada, which means that four to ten times more housing would need to be built, he explained.
“This is fundamentally a local issue,” concludes Erkan Yönder. Our research provides the detailed data needed to understand what needs to be done at the neighborhood level, which is the first step in developing a plan that works for all current and future residents.”
The AI technology used for this study is a neural network, which would increase the accuracy of predictions by 30%, according to Erkan Yönder. The system was trained using existing data from the Canada Mortgage and Housing Corporation as well as Statistics Canada, and demographic and immigration projections from the Government of Canada.
This project was commissioned by the Equiton Real Estate Research Fund of the John Molson School of Business.
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