GTA REALTORS® Introduce MLS® Home Price Index

GTA REALTORS® Introduce MLS® Home Price Index

TORONTO, February 6, 2012 — The Toronto Real Estate Board (TREB), Canadian Real Estate Association (CREA) and four other major real estate boards across Canada have developed a new system to measure and provide clarity on home prices and home price growth: the MLS® Home Price Index (MLS® HPI).

The MLS® HPI is calculated using a sophisticated statistical model that is a hybrid of both the repeat sales and hedonic price approaches.  The MLS® HPI takes into account a home’s quantitative attributes (e.g. the number of rooms it has; square footage etc.) and qualitative attributes (e.g., whether it has a finished basement, a view etc.).

The MLS® HPI approach provides a less volatile measure of price than averages and medians, which can swing dramatically in response to changes in the mix of home sales from one time period to the next (see Chart 1 on Page 2 of this release for a visual comparison).

Each month, there will be two key outputs published using the MLS® HPI:

1.       A series of price indices – The MLS® HPI price indices work in a similar fashion to the Consumer Price Index (Canada’s measure of consumer price inflation).  The indices have a base month/year of January 2005, where the indices are equal to 100.  In January 2012 TREB’s composite HPI was 143.6.  This means that the composite price index grew by 43.6 per cent between January 2005 and January 2012.  On a month-over-month basis, TREB’s composite HPI was up by 0.28 per cent compared to December 2011 and also up by 7.6 per cent year-over-year in comparison to January 2011.

2.       A series of benchmark home prices – The MLS® HPI has also been used to establish benchmark homes down to TREB’s Community level of geography for major home types including single family (detached and attached), townhouses and apartments.  A benchmark home is composed of a set of attributes typical of homes in the area where it is located, and remains constant over time.  This allows for an apples-to-apples comparison of price over time.

In the coming months, TREB will publish an increasing amount of data and analysis based on the MLS® HPI in its monthly Market Watch publication in a new section called “Focus on the MLS® Home Price Index”.  Eventually, the MLS® HPI will become TREB’s headline price number for release and reporting.  However, traditional average and median calculations will continue to be published in the Market Watch.

“The Toronto Real Estate Board is extremely excited to be launching the MLS® HPI.  This new approach will provide clarity for the consumer and prove to be a major improvement over any other method to measure home prices and home price change available in the marketplace today.  I look forward to discussing the many benefits and uses of the MLS® HPI in the coming months,” said TREB President Richard Silver.

More information about the MLS® HPI can be found in the TREB-specific tables and charts on Page 2 of this release, the Backgrounder beginning on Page 3 of this release and at



Backgrounder: MLS® Home Price Index

Background Materials


Go to to watch a short video about the MLS® Home Price Index and to use an interactive widget to find out more.



Q: How is the MLS® HPI calculated?

A: The MLS® HPI is calculated using multivariate regression analysis, a commonly used statistical technique.  Using a hybrid modeling approach that merges the Repeat-Sales and Hedonic Price approaches, the MLS® HPI model reflects contributions made by various quantitative and qualitative housing features toward the home price, including:

·         Number of rooms above the basement level

·         Number of bathrooms & half-bathrooms

·         Square footage for main living & basement areas

·         Whether it has a fireplace and/or finished basement

·         Lot size

·         The age of the property

·         Parking

·         How the home is heated

·         Foundation, flooring, siding & roofing types

·         Whether the property has waterfront or panoramic view

·         Whether the property has been sold previously (newly constructed and previously unsold, or repeat

·         sale)

·         Proximity to shopping, schools, hospitals, police stations, churches, sports centres, golf courses,

·         parks, and transportation (including the train station, railways, and airports)

The MLS® HPI can also be used to calculate the price for benchmark homes, whose features are typical of homes sold in a given area.

Q: What is a benchmark home?

A: A “Benchmark home” is one whose attributes are typical of homes traded in the area where it is located, with one benchmark being generated for each supported sub-area and home type.

Benchmark property descriptions are based on median values for quantitative property attributes (e.g. above ground living area in square feet), and the most commonly occurring value (i.e. modal value) for qualitative attributes (e.g. basement is not finished).

The attributes of Benchmark homes remain constant over time, allowing for an apples-to-apples comparison of price over time.

Q: How is the MLS® HPI different from average and median home price calculations?

A: The MLS® HPI is based on the value homebuyers assign to various housing attributes, which tend to evolve gradually over time.

This means that price changes calculated using the MLS® HPI are less volatile than those derived using common measures like average and median, which can swing dramatically in response to the changing mix of home sales over time.

It is often difficult to determine if average or median price fluctuations really reflect changes in buyers’ willingness to pay for certain housing attributes, or just changes in the volume of very expensive or inexpensive home sales from one time period to the next. The MLS® HPI removes that uncertainty.

Q: How can the MLS® HPI be used with average and median prices?

A: Comparing the MLS® HPI value for a given home type in a given market with the average selling price for the same home type and market can provide useful insights.

For example, if there is a change in the average home price that is well above the change in the MLS® HPI value, it may point to an increase in the proportion of high-end homes sold during a given period.