Annual Survey of Service Industries: Management, Scientific and Technical Consulting Services
Detailed information for 1998
Status:
Active
Frequency:
Annual
Record number:
4717
The survey collects financial and operating data needed to produce statistics for the Canadian management, scientific and technical consulting industry.
Data release - March 01, 2001
Description
This survey collects the financial and operating data needed to produce statistics on the Management, Scientific and Technical Consulting Services 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.
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.
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
Subjects
- Business, consumer and property services
- Business performance and ownership
- Financial statements and performance
- Professional, scientific and technical services
Data sources and methodology
Target population
The target population consists of all statistical establishments (sometimes referred to as firms or units) classified as management, scientific or technical consultants (NAICS 5416) according to the North American Industry Classification System (NAICS) during the reference year.
Sampling
This is a sample survey.
Target Population:
The target population for this survey is all establishments classified to NAICS 541611 (Administrative Management and General Management Consulting Services), 541612 (Human Resource and Executive Search Consulting Services) or 541619 (Other Management Consulting Services) or 541620 (Environmental Consulting Services) or 541690 (Other Scientific and Technical Consulting Services) on Statistics Canada's Business Register (BR) and operating for at least one day during the reference year 1998. Included in the target population are those self-employed, unincorporated individuals, as reported by T1 data from Canada Customs and Revenue Agency (CCRA), who are not on the Business Register.
Sample design:
The survey design was based on probability sampling and covered only the portion of the firms subject to direct data collection. Each sampled firm represented a number of other, similar firms in the industry, based on the probability of being surveyed. The largest firms were included in the sample with certainty due to their significant contribution to industrial performance.
The firms selected for this survey represent only a small portion of the entire survey frame; therefore, in order to make the sample as efficient as possible, the sampled units were stratified by province/territory and industry at the NAICS 4 digit level. For each province/territory/NAICS, sampling units were stratified in four size strata that were defined by the total revenue of the sampling unit. For the size stratification, there is one take-all stratum for the large sampling units, two take-some strata for the medium ones (a large and a small), and one take-none stratum for the small ones. The sample was selected using simple random sampling within the strata; therefore, each cluster of establishments had the same chance of selection within a stratum.
In order to compensate for non-response (for example, companies which cannot be contacted because they have moved or gone out of business) the size of the sample was increased. The resulting sample drawn for the surveyed portion alone totalled 1,512 companies.
Data sources
Responding to this survey is mandatory.
Data are collected directly from survey respondents and extracted from administrative files.
During the Spring of 1999, questionnaires were mailed to sampled establishments. Establishments were asked to report information for their 12-month fiscal period for which the final day occurs on or between January 1st and December 31st 1998. In addition to the mail-out / mail-back questionnaire approach, the survey employed Computer Assisted Telephone Interviews (CATI) for data collection, capture, edit and follow-up. The collection period ended in November 1999.
View the Questionnaire(s) and reporting guide(s).
Imputation
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, 31% of survey records went through the imputation process in 1998. The 1998 rate is considered to be fairly good, by business survey standards.
Estimation
The sampling weights derived from the sample design were modified and improved using post stratification. Estimates were derived using the final weight calculated by the sample design weight multiplied by the adjustment weight. The adjusted weight is a function of the information used at the design stage, the information received from the respondent, and new information on the frame. This is possible because the Business Register was updated with more accurate information in the time between when the sample was selected and the estimates were produced. The final set of weights reflects as closely as possible the characteristics of the population in this industry.
Three sources of data were used to derive the estimates:
* a probability survey sample of management, scientific and technical consulting establishments with an annual gross business revenue $30,000 and above,
* taxation data to estimate for businesses with an annual gross business revenue below $30,000 and
* a sample from the Supplementary file for T1 businesses with an annual gross business revenue of $30,000 or more, not found on the BR
Combining survey and tax data estimates produced the final estimates. These combined results were analysed before being released. The analysis, in general, included a detailed review of the individual responses (especially for the largest companies), a review of general economic conditions and a comparison with tax data information and other administrative sources such as industry and trade associations.
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.
Data accuracy
While Statistics Canada uses a variety of methods to ensure high standards throughout all collection and processing operations the results are always subject to a certain degree of error.
* Sampling errors can occur due to the fact that the estimates are derived from a sample of the population as opposed to the entire population. These errors depend on factors such as sample size, sampling design and the method of estimation.
* Non-sampling errors may occur for many reasons that are unrelated to sampling. Non-response and misclassification of the business (out of scope) are the most common factors. Some examples of other non-sampling errors are incorrect or incomplete information from respondents, differences in interpretation of the questions, errors in capturing, coding and processing of reported data. Every effort was made to minimize the non-sampling error of omission, duplication, reporting and processing.
Since this survey was based on probability sampling the potential for error caused by sampling can be measured. A standard measure of sampling error is the coefficient of variation (CV). The qualities of CVs are rated as follows:
* 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 35.00% or higher
Province CV rating
NFL Very good
PEI Very good
NS Very good
NB Very good
QUE Very good
ONT Very good
MAN Very good
SASK Good
ALB Very good
BC Very good
YUK Very good
NWT Very good
NUN Census
CANADA Excellent
- Date modified: