Canada - House Price Value for Existing Homes

Canada: House Price Value for Existing Homes

Mnemonic HPLX.ICAN
Unit Index Jun 2005=100, NSA
Adjustments Not Seasonally Adjusted
Monthly 2.07 %
Data Oct 2022 303.44
Sep 2022 309.84

Series Information

Source Teranet-National Bank
Release Teranet - National Bank National Composite House Price Index
Frequency Monthly
Start Date 3/31/1999
End Date 10/31/2022

Canada: Real Estate

Reference Last Previous Units Frequency
House Price Index Oct 2022 125.57 125.88 Index Dec2016=100, SA Monthly
House Price Index for New Homes Oct 2022 125.7 126 Index Dec2016=100, NSA Monthly
House Price Value for Existing Homes Oct 2022 303.44 309.84 Index Jun 2005=100, NSA Monthly
Housing Starts Oct 2022 267.06 298.81 Ths. #, SAAR Monthly
Building Completions 2022 Q3 58,114 54,210 #, NSA Quarterly
Building Permits Sep 2022 10,217,502 12,390,609 Ths. CAD, SA Monthly
Residential Building Permits Sep 2022 21,481 25,567 #, SA Monthly
Dwelling Stocks 2021 16,284,235 # Annual

Release Information

For Canada, the national bank house price index (produced by Teranet and National Bank of Canada) is an estimated index that measeures the increase/decrease in the value of properties over time by tracking home sale prices for properties that have been sold twice, allowing the source to calculate the increase or decrease in the value of the home over a given time period. 

  • Measurements:
    • Count
    • Index
  • Adjustment:
  • Native frequency: Monthly
  • Start date:
  • Geo coverage:
    • Country
    • CMA (11x ICAN_M^^^)

The source trackes the registered home sale prices over time, looking for properties that have been sold at least twice, making it possible to see the increase or decrease in the value or the property over a period of time. 

A constant level quality of each property is assumed, however some properties do not meet requirments for this assumption and are therefore removed from the survey. Factors that could cause a property to be removed from the sample include a non-arms-length-sale, renovations that occured between salles that changed the value of the property, data error, and high turnover frequency. 

The source then uses a linear regression algorithm to estimate the index using the qualifying properties. 

The source also uses a process to weight poperties differently in the index. This weighting process uses geographical area of interest, frequency of the percent change of the property in the set, and time interval between sales. 

It is noted that the above weighting schemes may not be exactly representative of the reality because there are many unknown factors.

The repeat sales index construction is based on a simple linear regression model, whose regression coefficient is the reciprocal of the desired index.

The source uses three different estimators to calculate all pre base period indices simulataneously. These estimators include least squares (LS), instrumental variables (IV), and generalized method of moments (GGM).

The source then refines the initial weights and downweights data flagged as an outlier. 

Further reading

At the source:


Copyright: Teranet – National Bank House Price IndexTM

Source: Teranet Inc. and National Bank of Canada