As part of a recent review of our surveys and publications, we have decided to discontinue data collection for rents, vacancies and services for the Seniors’ Housing Survey. This data will no longer be available going forward.
This decision is part of a broader initiative to review our entire housing surveys program and their alignment to our work on affordability.
CMHC conducts the annual Seniors’ Housing Survey in February. This survey became national in scope in 2009, covering all centres in the 10 provinces. Both private and non-profit residences are included in the survey universe.
To be eligible for inclusion in the survey results, a residence must:
- have at least 1 unit that is not subsidized (in the Atlantic provinces, Quebec and Ontario)
- have been in operation for at least 1 year (for example, it must have started operation before January 2012 to be included in the 2013 survey)
- have at least 10 rental units (in Quebec, Ontario and the Prairies) or 5 rental units (in the Atlantic provinces and British Columbia)
- offer an on-site meal plan
- not mandate high levels of health care (defined as 1.5 hours or more of care per day) to all of its residents; nursing homes and long-term care homes are examples of residences that were not included in the survey
- offer rental units; life lease units and owner-occupied units are excluded from this survey
- have at least 50% of its residents who are 65 years of age or older
The Seniors’ Housing Survey is a census and not a sample survey — all seniors’ residences in Canada that meet the criteria are part of this survey. The survey universe in Quebec may include private residences that don’t meet the conditions for obtaining a certificate of compliance.
Survey data were obtained through a combination of telephone interviews and fax and e-mail responses from the residence owner, manager or administrator. Survey results reflect market conditions at the time of the survey. Survey results have been weighted to adjust for non-responses, in order to ensure that they are reflective of the universe. The level of statistical reliability is noted in the tables below.
The statistics published include residences that have been in operation for at least 1 year. Information on new market supply has been excluded from the results.
- A space is a residential area that is rented out. This includes half of a semi-private unit, a private or bachelor unit, a 1-bedroom unit or a 2-bedroom unit.
- *In most cases, a space is the same as a unit. The exception is the case where a unit has been divided to rent to multiple residents. Semi-private and ward units are an example of this. Unless otherwise indicated, data for spaces are for all unit types.
- Standard space:
- A space where the resident does not receive high-level care (less than 1.5 hours of care per day) or is not required to pay an extra amount to receive high-level care. Regional terms for this type of space may vary across the country.
- Heavy care space:
- A space where the resident is paying an extra amount to receive high-level care (1.5 hours or more of care per day).
- Respite space:
- A space used to provide temporary accommodation for a senior who normally resides elsewhere and not at the residence.
- Non-market or subsidy space:
- A space where the rent received for the unit is less than market rent or where the resident occupying the unit is subsidized.
- The actual amount a resident pays per month for his or her accommodation space and all mandatory services. For vacant spaces, the rent is the amount the owner is asking for the space.
- A space is considered vacant if it is physically unoccupied and available for immediate rental at the time of the survey.
- Capture rate:
- People aged 75 and up are the main age group living in seniors’ residences. The capture rate is the ratio of the total number of residents living in the survey universe divided by its estimated 75+ population and is expressed as a percentage.
The Seniors’ Housing Survey could not have been conducted without the co-operation of the residence owners and their staff. CMHC acknowledges their time and assistance in providing accurate information. As a result of their contribution, CMHC is able to provide data and analysis that benefits the entire industry.
All information provided through this survey is kept strictly confidential. It’s used only by CMHC to generate statistics and data sets that don’t allow for the identification of individuals, households, businesses or buildings.
Data Reliability Measures
CMHC doesn’t publish a statistic if its reliability is too low or if publication of a statistic would violate confidentiality rules. The ability to publish an estimate is generally determined by its statistical reliability. CMHC currently uses the coefficient of variation.
A letter code representing the statistical reliability for each estimate is provided to indicate the data reliability. The coefficient of variation of an estimate is defined as the ratio of the standard error of the estimate to the estimate itself. It is generally expressed as a percentage. For example, let the average rent for 1-bedroom apartments in a given metropolitan centre be x̄ and its standard error be σx̄. Then the coefficient of variation — or CV — is given by CV = σx̄ / x̄.
Reliability Codes for Proportions
CMHC uses coefficient of variation, 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)
- ** — 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 %|
|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|
|(1.5, 3)||Excellent||Excellent||Excellent||Very Good||Good||**||**|
|(3, 6)||Excellent||Excellent||Very Good||Good||Poor||**||**|
|(6, 10)||Excellent||Excellent||Very Good||Good||**||**||**|
Reliability Codes for Averages and Totals
CMHC uses the coefficient of variation to determine the reliability level of the estimates of average rents anda coefficient of variation cut-off of 10% for publication of total sand 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 (coefficient of variation’s are given in percentages):
- A — If the coefficient of variation is greater than 0 and less than or equal to 2.5 then the level of reliability is Excellent.
- B — If the coefficient of variation is greater than 2.5 and less than or equal to 5 then the level of reliability is Very Good.
- C — If the coefficient of variation is greater than 5 and less than or equal to 7.5 then the level of reliability is Good.
- D — If the coefficient of variation is greater than 7.5 and less than or equal to 10 then the level of reliability is Poor.
- ** — If the coefficient of variation is greater than 10 then the level of reliability is **. (We don’t publish this.)