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Methodology for Rental Market Survey

Definitions and methodology of the survey.

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CMHC conducts the annual Rental Market Survey in October to estimate the relative strengths in the rental market. The survey is conducted on a sample basis in all urban areas with populations of 10,000 or more. It targets only privately initiated structures with at least 3 rental units, which have been on the market for at least 3 months.

The survey collects market rent levels, availability, turnover and vacancy unit data for all sampled structures. Data is collected using a combination of telephone interviews and site visits. Information is obtained from the:

  • owner
  • manager or
  • building superintendent

The survey is conducted during the first 2 weeks of October and the results reflect market conditions at that time. Note: The April survey was conducted for the last time in 2015. The availability rate was collected between 2005 and 2017 exclusively; this series was discontinued in 2018.

CMHC’s Rental Market Survey provides a snapshot of vacancy and turnover rates and average rents in both new and existing structures. We also provide a measure for the change in rent that is calculated based on existing structures only. The estimate is based on structures that were common to the survey sample. That is, for both the previous year and the current Rental Market Surveys.

The change in rent in existing structures is an estimate. It is the change in rent that the landlords charge and removes compositional effects on the rent level movement due to new buildings, conversions, and survey sample rotation.

The rent levels in new and existing structures are also published. The per cent change for the rent in existing structures published are statistically significant. The changes in rents that may be calculated based on new and existing structures rent levels may not have the same significance.

Difference between Percentage Change of Average Rents:

Percentage Change of Average Rents (New and Existing Structures)

This percentage comes from a calculation that shows an increase or decrease in average rents between 2 years. It’s impacted by changes in the composition of the rental universe and by the rent level movement.

Percentage Change of Average Rents from Fixed Sample (Existing Structures Only)

This is a measure that estimates the rent level movement. The estimate is based on structures that were common to the survey sample for both the previous year and the current Rental Market Surveys. (Some composition effects still remain. We can see this in things like the rental units renovated/upgraded or changing tenants because the survey does not collect data to such level of details.)

Definitions:

Universe:
consists of all row projects and apartment structures with three or more units. The universe is presented as a sum of all rental units.
Rental Apartment Structure: 
Any building containing 3 or more rental units, of which at least 1 unit is not ground oriented. Owner-occupied units are not included in the rental building unit count.
Rental Row (Townhouse) Structure: 
Any building containing three or more rental units, all of which are ground oriented with vertical divisions. Owner-occupied units are not included in the rental building unit count. These row units in some centres are commonly referred to as townhouses.
Vacancy: 
A unit is considered vacant if it is physically unoccupied and available for immediate rental (at the time of the survey).
Rent: 
The rent refers to the actual amount tenants pay for their unit. No adjustments are made for the inclusion or exclusion of amenities and services such as heat, hydro, parking or hot water. For available and vacant units, the rent is the amount the owner is asking for the unit. The average rents reported in this publication provide a sound indication of the amounts paid by unit size and geographical sector. Utilities such as heating, electricity and hot water may or may not be included in the rent.
Turnover: 
A unit is counted as being turned over if it was occupied by a new tenant that moved in during the past 12 months. A unit can be counted as being turned over more than once in a 12-month period.
Availability:
A rental unit is considered available if
  • the existing tenant has given, or has received, notice to move, and
  • a new tenant has not signed a lease; or the unit is vacant

Data Reliability Measures

CMHC does not publish a statistic if its reliability is too low or if publication of a statistic would violate confidentiality rules:

Unit counts (universe) are released. However, for confidentiality, all other estimates — such as vacancy rates and average rent — are released only if a given estimate is based on 4 or more responding entities.

For reliability, the ability to publish an estimate is determined by the coefficient of variation (CV) for that estimate. A letter code representing the statistical reliability (i.e., the CV) for each estimate is provided to indicate the data reliability. CV of an estimate is defined as the ratio of the standard error of the estimate to the estimate itself and the CV is generally expressed a percentage. For example, let the average rent for one bedroom apartments in a given CMA be x̄ and its standard error be σx̄. Then the Coefficient of Variation is given by CV = σx̄/x̄.

Reliability Codes for Proportions

CMHC uses CV, sampling fraction and universe size to determine the ability to publish proportions. The following letter codes are used to indicate the level of reliability of proportions:

  • A — Excellent
  • B — Very good
  • C — Good
  • D — Poor (use with caution)
  • ** — Data suppressed

The following tables indicate the level of reliability of proportions:

If the proportion is zero (0) and the sampling fraction is less than 100% then the following levels are assigned:

Sampling Fraction (%) range
Structures in Universe (0, 20]* (20, 40] (40, 60] (60, 80] (80, 100)
3 – 10 ** ** ** ** **
11 – 20 ** Poor Poor Poor Good
21 – 40 ** Poor Poor Good Very Good
41 – 80 ** Poor Good Good Very Good
81+ ** Good Good Very Good Very Good

*(0, 20] means sampling fraction is greater than 0% but less than or equal to 20%; others are similar

Otherwise, the following table is used to determine the reliability level of proportions:

Coefficient of Variation (CV) %
Percentage 0 (0, 5] (5, 10] (10, 16.5] (16.5, 33.3] (33.3, 50] 50+
(0, 0.75) Excellent Excellent Excellent Excellent Excellent Very Good Very Good
(0.75, 1.5) Excellent Excellent Excellent Excellent Excellent Poor **
(1.5, 3) Excellent Excellent Excellent Very Good Good ** **
(3, 6) Excellent Excellent Very Good Good Poor ** **
(6, 10) Excellent Excellent Very Good Good ** ** **
(10, 15) Excellent Excellent Good Poor ** ** **
(15, 30) Excellent Excellent Poor ** ** ** **
(30, 100) Excellent Excellent ** ** ** ** **

Reliability Codes for Averages and Totals

CMHC uses the CV to determine the reliability level of the estimates of average rents and a CV cut-off of 10% for publication of totals and averages. It is felt that this level of reliability best balances the need for high quality data and not publishing unreliable data.

CMHC assigns a level of reliability as follows (CV’s are given in percentages):

  • A — If the CV is greater than 0 and less than or equal to 2.5 then the level of reliability is Excellent.
  • B — If the CV is greater than 2.5 and less than or equal to 5 then the level of reliability is Very Good.
  • C — If the CV is greater than 5 and less than or equal to 7.5 then the level of reliability is Good.
  • D — If the CV is greater than 7.5 and less than or equal to 10 then the level of reliability is Poor (use with caution).
  • ** — If the CV is greater than 10 then the estimate is suppressed and not published.

Other symbols

Other denotations used in presenting Rental Market Survey data:

  • ++ Change in rent is not statistically significant. This means that the change in rent is not statistically different than zero (0). This applies only to “Estimate of Percent Change of Average Rent” tables.
  • - No units exist in the universe for this category
  • n/a Not applicable

See the Rental Market Survey — Data Tables

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Date Published: April 5, 2022

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