As Deputy Chief Economist, Patrick Perrier is part of a team of housing economists and researchers working to improve our understanding in Canada of the enablers and cons of housing markets. housing and their impact property values on affordability. Patrick is also a member of a diverse national team of researchers and analysts studying barriers to housing supply and possible solutions.
From its peak in February 2022 through last August, the seasonally adjusted average MLS® price for the entire country declined 15.6%. This drop in housing prices was expected by forecasters – and CMHC – due to an anticipated return to more sustainable market conditions than those observed in 2020 and 2021 and the negative impact of the marked increase in housing prices. interest rate needed to bring inflation under control.
From this drop in the average housing price, the tendency would be to believe
However, it is important to understand that changes in the average price may also reflect a change in the composition of transactions across different price ranges.
In fact, this composition effect would explain a little more than half of the decline in the average price since last February for Canada.
The actual weakening of housing prices would therefore be less significant than what is suggested by the fall in the average price. However, this conclusion could change in the coming months as more data is released and as interest rate increases and the expected slowdown in the economy become fully felt.
What is a composition effect in the housing market?
In addition to supply and demand in a market, the individual characteristics of the units being sold also affect the sale price of properties. The size, location, appearance and other particularities of a property can impact its demand and price.
The measure of home price generally put forward is the average MLS® price which is calculated from sales made through a real estate broker. It is calculated by dividing the total value of transactions by their number.
A variation in the proportion of less expensive properties in total sales – due to the type or location of the properties transacted – creates a composition effect. If this variation is significant, the change in the average price could mainly reflect a change in the particularities of the properties transacted rather than a real variation in the value of the properties.
For example, an increase in the share of sales of condominiums, generally of lower value than single-family homes, could lower the average price of homes, even if the individual value of the homes remains unchanged.
Some price measures attempt to purge these composition effects. Among other things, the MLS® Home Price Index (PPI) is based on a hybrid model that combines the recurring sales approach and the hedonic pricing method (which reflects the impact of various quantitative and qualitative characteristics of housing on their price). 1
Price indexes that purge composition effects have fallen less
The 8 percentage point difference between the rate of decrease of the average MLS® price and that of the MLS® HPI could be explained by a shift in the composition of sales towards homes of lower value. In other words, more than half of the drop in the average MLS® price since February can be explained by a composition effect, the remainder by a real weakening of prices.
Toronto, Vancouver and Montreal all have seasonally adjusted average MLS® prices that reached record highs in early 2022.
For Montreal and Vancouver, the contribution of the composition effect of transactions to the drop in their average price was more significant than for Toronto.
In Vancouver, following its peak in February 2022, the average price decreased by 6.5% through August. During this period, the MLS® PPI decreased by only 3.5%. So a little more than 50% of this drop in the average price would be attributable to a real weakening of prices, and the other part to a composition effect.
For Montreal, the average MLS® price peaked a little later, in April. Since then, it has decreased by 5.5% while the MLS® PPI decreased by only 3.3%. So, approximately 60% of this drop in the average price in Montreal would come from a real weakening of prices, and 40% from the composition effect. 2
For Toronto, the average price decreased 12.0% from its February peak through July. For this period, the MLS® PPI decreased by 8.6%, so the real weakening of prices explains a little more than 70% of this drop in the average price in Toronto, while the composition effect had a lesser contribution.