Many prominent economists have argued that Canada is in a housing bubble, while the real estate associations and other economists predict that house prices may continue to accelerate. Setting opinions aside, house prices in Canada have more than tripled from 2005 to 20221, while median household incomes have only increased by 50% 2,3. This means that the average family went from needing to spend 4.4 years of average household earnings over 10 years in 2022. This divergence between house prices and incomes is striking.
Aggregate house prices have fallen 16% since their peak in March of 2022, and based on data from the Canadian Bankers Association, mortgage delinquencies in Ontario and British Columbia have increased recently such that they are above their 2019 levels (pre-COVID levels). Many lenders have loans that are secured by housing. There is a risk that in a housing downturn losses may worsen if the value of that collateral falls below the value of the loan. We are not making a prediction that Canada house prices are set to fall - but having a framework to understand housing valuations can help lenders take proactive steps to mitigate potential losses.
How can we determine if house prices are overvalued?
We want to understand if house prices are at risk of a correction. An asset bubble is typically characterized by a quick run up in asset prices followed by a correction. During the time when asset prices are elevated they are said to be trading at a price which greatly exceeds the assets ‘Intrinsic Value’. The challenging part is determining if houses are overvalued before a price correction occurs. Payson uses a straight-forward framework to help lenders assess these valuation risks:
Intrinsic Value vs. Market Dynamics
Intrinsic value factors we believe determine the underlying value of housing. Measuring these is critical to determine if price differences are a result of changes in fundamentals or a result of short term forces or speculation.
Buy to Own and Use and Buy to Rent Out
For both of these factors the value of the property is determined by its location, attractiveness, access to amenities, along with many others. These values are also tied to the income and wealth of the buyer since this determines their ability to afford the property. Thus we believe measuring the value of properties vs. incomes is critical in determining its intrinsic value.
Putting this in terms many of us can relate to, we’ve probably all seen a property listed in some far off place at an affordable price, but it's hard to justify a move there without access to the amenities of a city, and good jobs to afford for the mortgage or rent.
Long Term Demand and Supply
When I started at my first job some very smart analysts I knew were talking about shorting the Toronto housing market. This was in 2013, and they had built their belief based on house price-to-income ratios reaching levels of cities involved in the US 2008 bubble. What I think they missed was that there were very few opportunities to build more detached houses within a reasonable commute of Toronto, meaning long term supply was heavily constrained or inelastic.
In the US 2008 housing bubble the authors of the book ‘House of Debt’ found that one of the deciding factors in house price appreciation and depreciation was whether or not housing in a city was elastic or inelastic (Supply Constrained). Some examples include Chicago and New York, which are constrained from building more housing, that were relatively spared by the downturn in house prices.
Because it is very challenging to build new housing supply in New York and Chicago, prices only fell 13 and 28% respectively from peak to trough.
Cities like Las Vegas do not have these same geographic constraints and hence face a higher risk that house prices may correct following a rapid appreciation.
Cities like Las Vegas where the housing supply was elastic were found to have a much larger decrease in the US 2008 housing bubble.
How can Lenders use this to Assess their Mortgage Risk?
Two key factors lenders can assess to determine their housing valuation risk:
- Changes in the house price-to-income ratio of in cities they serve
- Assessing whether a city has inelastic or elastic demand to determine if house price appreciation is at a higher risk of correcting
An example city is Niagara Falls in Ontario, which has seen house prices increase by a factor of 2.4x relative to incomes. We also believe that long term supply constraints are low in Niagara Falls.
Payson’s Key Takeaway for Lenders
Given recent trends in Canadian housing we believe that lenders should have a framework in place to assess the valuation risk of their lending portfolios. Assessing a loan book based on changes in their home price-to-household income ratios, along with an assessment of supply elasticity, will help lenders understand their exposure. Companies can adjust their pricing and underwriting policies to ensure they are resilient in the event delinquencies increase.
At Payson Solutions, we specialize in delivering bespoke data solutions to help lenders grow their business and mitigate risks. If you would like to learn more or discuss your housing valuation framework, drop us a line and we would be happy to chat!
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