House price indices are key data systems that lenders need to pay attention to when monitoring the Canadian real estate market. Depending on the producer of the index, information might be different and that is often a result of three things:
. The source of the data
. How the data is being analyzed
. What data is reported
For example, some house price indices report information from MLS data, while others, like the Teranet–National Bank National Composite House Price Index™, report data directly from the provincial land databases. Some may report on month over month gains, while others may compare the current month to the same month in a previous year. Some may use slightly different methods as it relates to interpreting and calculating the data.
One of Canada’s most relied upon house price indices is the Teranet–National Bank National Composite House Price Index™. Economists, lenders, investment firms, journalists and the media alike rely on its data when reporting on gains and losses in the Canadian housing market. Each month a report is released which reports the month over month rate of change as it relates to the rate of change of Canadian single-family home prices.
These measurements are based on the property sales records of public land registries, lending accuracy and trustworthiness to the index. The monthly indices currently cover Victoria, Vancouver, Calgary, Edmonton, Winnipeg, Hamilton, Toronto, Ottawa-Gatineau, Montréal, Québec City and Halifax, which are then combined to form a coast-to-coast composite index.
The Teranet–National Bank National Composite House Price Index™ monitors price changes and trends by neighbourhood or region, by different price tiers or housing types, at the smallest scales or the largest.
In addition to the monthly indices that form the composite index, sub-indices are available for markets across Canada. These sub-indices are an independent representation of the rate of change of Canadian single-family home prices and provide a more accurate and granular analysis at the local level. The measurements are based on the property records of public land registries, grouped into individual Forward Sortation Areas (or clusters of FSAs). Sub-indices can be further segmented by property type (all types vs. single-family homes vs. condominiums) in areas where this data is available.