Survey of the Construction Industry

Detailed information for 1999





Record number:


The survey collects financial and operating data needed to produce statistics for the Canadian construction industry.

Data release - December 12, 2001


This survey objective is the collection and publication of financial and operating data on the Canadian construction industry. Survey results represent fiscal year estimates of financial statistics.

The information from the survey can be used by businesses and trade associations for market analysis and assessment of industry performance, operating characteristics and trends; by government to develop national and regional economic policies; by other users involved in research or policy making and by Statistics Canada for maintaining important data input in the preparation of the Canadian System of National Accounts.

Statistical activity

The survey is administered as part of the Unified Enterprise Survey program (UES). The UES program has been designed to integrate, gradually over time, the approximately 200 separate business surveys into a single master survey program. The UES aims at collecting more industry and product detail at the provincial level than was previously possible while avoiding overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content. The unified approach makes reporting easier for firms operating in different industries because they can provide similar information for each branch operation. This way they avoid having to respond to questionnaires that differ for each industry in terms of format, wording and even concepts.


  • Construction
  • Non-residential building construction
  • Residential construction

Data sources and methodology

Target population

Classified under the North American Industrial Classification System (NAICS) code 23, this industry comprises establishments primarily engaged in the building, renovating and repairing of all types of buildings and structures. These establishments were in operation for at least one day during the reference period. Both incorporated and non-incorporated businesses, as well as employer and non-employer enterprises are included in the survey.

Instrument design

Complete questionnaire design was undertaken for the 1999 survey (result: 9 slightly different questionnaires for the entire construction survey). Major users, including major associations, as well as a sample of respondents was consulted.

The questionnaires satisfy the statistical requirements for financial information as expressed by the national accounts and the businesses and association operating in the construction industry.


This is a sample survey with a cross-sectional design.

The frame for the selection of the probability sample is Statistics Canada's Business Register, which include all establishments that operated for at least one day during the reference period.

The sampling unit used is the establishments of one enterprise that operate in the same industry and the same province or territory. The sampling unit can be called a "cluster of establishments".

Two sources of data were used to derive the estimates:
- a probability sample survey for clusters of establishments with an annual gross business income revenue above survey thresholds (which would vary by industry and provinces)
- taxation data to estimate for clusters of establishments with an annual gross business revenue below survey thresholds

Data sources

Data collection for this reference period: March 2000 to December 2000

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

Questionnaires were mailed to establishments selected in the sample in the early months of 2000. Respondents were asked to report information for their 12-month fiscal period for which the final day occurs on or between January 1st 1999 and March 31st 2000 inclusively. Separate English and French questionnaires were used in data collection

In addition to the mail-out/mail-back questionnaire approach, the survey was also conducted using Computer Assisted Telephone Interviews (CATI) for data collection, capture, edit and follow up.

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

Error detection

At the collection stage, reported data are examined for completeness and inconsistencies using automated edits coupled with analytical review.


Records with partial responses were imputed to make them complete and were added to a donor pool along with completed records. Data for non-respondents, unable to locate and no contacts were imputed using nearest neighbour donor imputation.

This imputation process was also coupled with a manual analytical review.


General estimation system is used to provide estimates for the entire observed population.

In addition, the sampling weights derived from the sample survey design are modified and improved using updated information. This was possible because, during the passage of time since the sample was selected, the Business Register was updated further with more complete information. The final set of weights reflects as closely as possible the changing characteristics of the population in this industry.

The final estimates are derived by combining the survey estimates and the taxation data estimates.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.

Standard confidentiality rules are applied to all data appearing in the released tables and on CANSIM. Confidential data are marked with an "X" and related data are suppressed to avoid residual disclosure.


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