Commercial Rents Services Price Index (CRSPI)

Detailed information for fourth quarter 2018

Status:

Active

Frequency:

Quarterly

Record number:

5123

The Commercial Rents Services Price Index measures monthly price changes over time for leased commercial space in Canada; the estimates are produced on a quarterly basis.

Data release - April 4, 2019

Description

The Commercial Rents Services Price Index (CRSPI) measures monthly price changes over time for leased commercial space in Canada; the estimates are produced on a quarterly basis. Prices collected are the average rents measured in price per square foot for a sample of commercial buildings. The price index for the industry can be used in conjunction with other service price indexes to monitor inflation and is also used by the Canadian System of National Accounts to deflate this sector of the economy.

Statistical activity

These indexes are a part of the Services Producer Price Index program (SPPI) at Statistics Canada.

The SPPI program develops and produces price indexes for a wide range of business service categories. This initiative fills an important data gap in the area of economic statistics and has resulted in a more comprehensive set of service price indexes. It also allows Statistics Canada to produce more accurate estimates of real value added of the Gross Domestic Product and changes in productivity.

Reference period: The time period for which the CRSPI equals 100; currently this is the year 2011.

Collection period: Data are collected quarterly for monthly prices in the quarter following the reference quarter.

Subjects

  • Business, consumer and property services
  • Prices and price indexes
  • Rental and leasing and real estate
  • Service price indexes

Data sources and methodology

Target population

The target population consists of all active establishments classified to 531120 - Lessors of non-residential buildings (except mini-warehouses) in Canada, engaged in the provision of space to others for rent. Rental space used as a residence, dwelling or Mini-warehouse is excluded from this definition.

Instrument design

Questionnaire modifications are ongoing. Pricing methodologies and questionnaire design were researched and developed based on international practices and improved through the efforts of Statistics Canada's Questionnaire Design Resource Centre. Focus groups with respondents were also conducted.

Sampling

This is a sample survey with a cross-sectional design and a longitudinal follow-up.

A probability sample of establishments of various sizes, classified to code 531120 - Lessors of non-residential buildings (except mini-warehouses) according to the North American Industry Classification System (NAICS) was selected across Canada, from a Statistics Canada internal statistical survey frame (Business Register). The sample tracks over 700 buildings across the country.

Frame
The sampling frame is drawn from Statistics Canada's Business Register for all establishments classified to code 531120 - Lessors of non-residential buildings (except mini-warehouses) in Canada, engaged in the provision of space to others for rent.

Sampling unit
Non-residential buildings (retail, office, or industrial and warehousing), based on their predominant source of leasing revenue and assigned to a geographical region, are identified as the sampling unit.

Stratification method
Sampling units are divided in three strata based on 2018 establishment revenue: take-all, take-medium, and take-small.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data is collected from respondents through an electronic questionnaire, while telephone correspondence (computer-assisted telephone interviewing) is used for non-response and partial data follow-up.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Error detection is conducted both at the time of collection and during post collection editing, through a system of data validity specifications. Failing records are reviewed for editing and correction when necessary.

Imputation

Missing price data for a lessor are imputed using parental imputation.

Estimation

The Commercial Rents Services Price Index (CRSPI) uses the enterprise revenues as its weighting sources.

Enterprise revenue data are derived from Statistics Canada's Business Register (BR).

The weight reference period is currently 2010.

Weights are updated during a sample/basket update which typically occurs every 5 years.

Estimates are produced by calculating a weighted average of price relatives by industry, which are chained together to form an index series. The CRSPI is a Laspeyres chain linked index, available at the Canada level only.

With the introduction of a new basket, historical estimates are linked to the new basket by maintaining the same historical period-to-period changes. This is done by calculating a link factor for each index series as the ratio of the new index series (2011=100) in the overlap period to the old index series (2006 =100). This link factor is then applied to the old index series to bring it up or down to the level of the new index series.

The overlap period for Commercial Rents Services Price Index is currently June 2012 .

Quality evaluation

The data is subject to collection and processing validations on all key variables and non-essential data. Analysis is then performed at the index level at all aggregation stages. Quality evaluation is achieved using an internationally developed service and producer price framework that considers aspects such as the type of price being used, timeliness and relevance.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Collected data are converted to price indexes and data are released as such, so that it is not possible to identify the suppliers of raw prices.

Revisions and seasonal adjustment

Data for the most recent quarter are preliminary. The previous quarter of the series is subject to revision. The series is also subject to an annual revision released with second quarter data of the following reference year. The index is not seasonally adjusted.

Data accuracy

The survey uses a methodology designed to control for errors and reduce their potential effects on estimates. However, the survey results remain subject to both sampling and non-sampling error. Sampling error results when observations are made only on a sample and not on the entire population. All other errors arising from the various phases of a survey are referred to as non-sampling errors. For example, these types of errors can occur when a respondent provides incorrect information or does not answer certain questions; when a unit in the target population is omitted or covered more than once; when an out of scope unit is included by mistake or when errors occur in data processing, such as coding or capture errors.

Response rate:
The survey achieved an average response rate of 84.8% for 2018.

Non-sampling error:
Non-sampling error detection is conducted both at the time of data collection and also during post collection processing, using a set of systematized error detection procedures to identify outliers and possible reporting anomalies. Records that fail these edits are reviewed for editing and correction when necessary or edit failure may trigger a follow-up with the respondent.

Non-response bias:
A systematized imputation process is used to impute for the non-response portion of the sample, achieving an effective 100% coverage. Non-response bias is also minimized during the same process.

Coverage error:
A systematized imputation process is used to impute for the non-response portion of the sample, achieving an effective 100% coverage. Non-response bias is also minimized during the same process.

Other non-sampling errors:
This methodology does not apply.

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