Annual Survey of Service Industries: Specialized Design
Detailed information for 1999
The survey collects financial and operating data needed to produce statistics for the Canadian specialized design industry.
Data release - December 20, 2001
This survey collects the financial and operating data needed to produce statistics on the Specialized Design Industry in Canada. These data are aggregated with information from other sources to produce official estimates of national and provincial economic production in Canada. The estimates are used by government for national and regional programs and policy planning and by the private sector for industry performance measurement and market development.
The data were produced as part of Statistics Canada's Unified Enterprise Survey (UES), the main purpose of which is to ensure Statistics Canada receives consistent and integrated data from many types of surveys and sizes of businesses with enough detail to produce accurate provincial statistics.
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.
This survey is part of the Service Industries Program. The survey data gathered are used to compile aggregate statistics for over thirty service industry groupings. Financial data, including revenue, expense and profit statistics are available for all of the surveys in the program. In addition, many compile and disseminate industry-specific information.
Reference period: Calendar year
Collection period: November to August
- Business, consumer and property services
- Business performance and ownership
- Financial statements and performance
- Professional, scientific and technical services
Data sources and methodology
The target population consists of all statistical establishments (sometimes referred to as firms or units) classified as Specialized Design according to the North American Industry Classification System during the reference year.
This is a sample survey with a cross-sectional design.
Two sources of data were used to derive the estimates:
· a probability sample survey of establishments in the Specialized Design Services industry with an annual gross business revenue above survey thresholds;
· taxation data to estimate for businesses with an annual gross business revenue below survey thresholds.
In most provinces and territories, the survey thresholds stood at $30,000-$45,000 for Specialized Design Services. By comparison, survey thresholds were at $50,000 for all establishments and all provinces in 1997 .
The "sampling unit" used in the probability survey is the establishments of a given enterprise that operate in the same industry and the same province. The sampling unit can be thought of as a "cluster of establishments."
The overall sampling rate for the 1999 Specialized Design Services survey was at 13% of eligible establishments in the target population.
Responding to this survey is mandatory.
Data are collected directly from survey respondents and extracted from administrative files.
Questionnaires were mailed to establishments selected in the sample in the spring of 2000. Establishments were asked to report information for their most recent 12-month fiscal period. 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. The collection period ended in October 2000.
View the Questionnaire(s) and reporting guide(s) .
Reported data were examined for completeness and inconsistencies using automated edits coupled with analytical review. Another automated system was used to impute data for refusals, non-response and unable to contact units, partially with the assistance of administrative data. This imputation process was coupled with a manual analytical review. In total, 34% of survey records went through the imputation process in 1999. The 1999 rate is considered to be fairly good, by business survey standards.
The sampling weights derived from the sample survey design were 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 were derived by combining the survey estimates and the taxation data estimates mentioned in the sampling methodology summary.
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.
While considerable effort was made to ensure high standards throughout all collection and processing operations, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: sampling and non-sampling .
Non-sampling errors may occur for many reasons. For example, non-response, is an important source of non-sampling error. Population coverage, differences in the interpretation of questions, incorrect information from respondents, mistakes in recording, coding and processing of data are other examples of non-sampling errors.
The response rate for this survey was 63%, after taking into account the fact that some firms were no longer in business, or had changed their primary business activity.
Sampling errors can occur because estimates are derived from a sample of the population rather than the entire population. These errors depend on factors such as sample size, sampling design and the method of estimation. An important property of probability sampling is that sampling errors can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). Over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all the units would be less than twice the coefficient of variation, 95 times out of 100. The sample estimate plus or minus twice the CV is referred to as the 95% confidence interval.
The quality rating of the estimates with respect to CV's are classified as follows:
CV rating CV range
Excellent 0.01% to 4.99%
Very good 5.00% to 9.99%
Good 10.00% to 14.99%
Acceptable 15.00% to 24.99%
Use with caution 25.00% to 34.99%
Unreliable larger than 35.00%
Based on these ratings and as depicted in Table A below, the total revenue estimates at the NAICS (541320 & 5414) level were judged to be very good at the national level and good to excellent at the provincial/territorial level in 1999.
Province CV rating
SASK Very good
ALB Very good
BC Very good