Using AI to Predict the Future Cost of Rent

Imagine paying $5,600 a month in rent in Toronto by 2032. In this episode, Giacomo Ladas hosts Erkan Yönder, Associate Professor at Concordia’s John Molson School of Business, to unpack this projection and its far-reaching impacts. Using advanced AI models, Erkan’s recent study forecasts steep rental increases in Canada’s largest cities, driven by immigration, high demand, and supply constraints. Surprisingly, even a growing supply hasn’t eased rents due to overwhelming demand, creating an unsustainable market. Erkan and Giacomo explore potential solutions, including targeted job creation in smaller regions and flexible zoning laws to distribute growth beyond Toronto, Vancouver, and Montreal. With AI’s ability to trace complex patterns in rental trends, Erkan offers a glimpse into how rent could reshape Canadian cities over the next decade. Tune in for a deeper understanding of the housing challenges ahead and the partnerships needed to keep living costs manageable.

Key Points From This Episode: • Introducing today’s guest Erkan Yönder and his research. • Why rents in Toronto could hit $5,600 per month by 2032. • The surprising correlation between supply increases and rising rents. • Why high demand outpaces rental supply in big cities. • How immigration policies and other factors impact housing demand and rental prices. • Why Toronto, Vancouver, and Montreal face unique rental market pressures. • Erkan’s perspective on job creation to draw people to smaller regions. • The role of zoning laws in expanding housing beyond major cities. • Why certain areas experience higher rent growth than others in Canada. • Ways that advanced AI models enhance real estate predictions and analysis. • Advice to landlords and renters for navigating changing rental markets. • How investors and government can work together to improve housing.

Quotes:

“Then the question becomes, why do we have more immigrants in Toronto than many other regions across Canada? The reason is there are – more available jobs.” — @erkanyonder [0:14:11]

“AI can help us in certain aspects, especially when it comes to projections and predictions. So, why not have that information on the table and try to make more sophisticated decisions?” — @erkanyonder [0:28:23]

“Capital from the government won’t be enough to build this much, – we need institutional investors to come to these markets and invest in those property companies, invest directly.” — @erkanyonder [0:33:10] “In the long run, it’s a very simple solution, we need to build more, and in order to build more, we need capital investors, real estate companies, and local governments and the government involved in this problem.” — @erkanyonder [0:35:03]

Links Mentioned in Today’s Episode:

Erkan Yönder

Erkan Yönder at Concordia

Erkan Yönder on LinkedIn

Erkan Yönder on X

‘AI-Driven Insights into Key Factors Influencing Canada’s Rental Market’Concordia’s John Molson School of Business

Giacomo Ladas on LinkedIn

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