Annual Survey of Personal Services

Annual Survey of Personal Services
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Detailed information for 1999

Status:

Inactive

Frequency:

Annual

Record number:

2424

The survey objective is the collection and dissemination of data necessary for the statistical analysis of personal and laundry services industries.

Data release - November 29, 2001

Description

The survey objective is the collection and dissemination of data necessary for the statistical analysis of personal and laundry services industries.

The information from the survey can be used by businesses for market analysis, by trade associations to study performance and other characteristics of their industries, by government to develop national and regional economics policies, and by other users involved in research and policy making.

Statistical activity

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

Subjects

  • Business, consumer and property services
  • Business performance and ownership
  • Financial statements and performance
  • Personal services

Data sources and methodology

Target population

Under the North American Industrial Classification System (NAICS), this industry is comprised of establishments primarily engaged in many groups in Personal Services. The target population consists of all statistical establishments classified to sub-sector 812 according to the North American Industrial Classification System (NAICS) during the reference year. These establishments provide personal care services, funeral services, laundry services and other services, such as pet care and photo finishing. Operators of parking facilities are also included.

Sampling

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

The Survey is a Sample Survey with a take-all portion.

Even though the basic objective of the survey is to produce estimates for the whole industry --- incorporated and unincorporated--- the portion of the population eligible for sampling was defined as all incorporated statistical establishments with revenue above $50,000. Some exceptional unincorporated units were also added to direct data collection if their contribution was deemed significant. The same principle applies to unincorporated units belonging to complex enterprises. The main motivation for the exclusion of unincorporated firms and incorporated firms below $50,000 from direct data collection was to achieve major reductions in the response burden. The excluded portion represents a substantial proportion of the whole industry in terms of number (68%) but its contribution to the overall estimate is modest (22%). Firms below the exclusion thresholds are still part of the universe but their contribution is accounted for in the final estimates through the use of administrative records as proxy data. Only basic information can be obtained from this source that is; total revenue, expenses, depreciation and wages, salaries and benefits. For the 1999 reference year, the administrative data used to estimate for unincorporated firms was restricted to data that could be directly linked to the frame. This is expected to improve the quality of the unincorporated firm estimate. This change necessitated historical data revisions for some industries. Detailed characteristics such as client base, revenue by type of service and detailed expenses items can only be obtained for firms in the direct data collection portion.

The survey design covered only the portion of the frame subject to direct data collection. Prior to the selection of a random sample, units are grouped in homogeneous groups defined using industrial (NAICS) and geographic (province/territory) attributes. Similar quality requirements are targeted for each group which is then divided into four sub-group called strata: must-take, take-all, large take-some and small take-some.

The take-all stratum includes the largest firms in terms of industrial performance which are selected in the sample with certainty making such units self-representing. The must-take stratum is also comprised of self-representing units that have a complex structure (multi-establishments, multi-legal, multi-NAICS or multi-province enterprises). Units in the two take-some strata are subjected to a random sample where each sampled firm represents a number of other, similar firms in the industry/province combination according to the inverse of their probability of selection.

Finally, the size of the sample was increased to compensate for such situations as non-response and firms which cannot be contacted because they have moved or gone out of business. The resulting sample size for this survey after removing firms that should not have been included in the frame (out of scope, duplicate records or out of business) was 1497 companies.

Data sources

Responding to this survey is mandatory.

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

Data are collected through a mail-out/mail-back process, while attempting to provide respondents with the option of telephone or other electronic filing methods as required. Even though the sampling unit was the statistical establishment, the statistical company was chosen as the collection entity in order to reduce respondent burden and simplify collection procedures. Therefore, companies with production at more than one locale were mailed only one questionnaire, and were instructed to report for all their operations in the surveyed industry. Summary data were collected for each province or territory in which the company operated.

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

Imputation

Several checks are performed on the collected data to verify internal consistency and identify extreme values. Where information is missing, imputation is performed using either a "nearest neighbour" procedure (donor imputation), using historical data where available or finally, using administrative data as a proxy for reported data.

Estimation

Prior to estimation, data for companies with production in more than one province or territory were allocated to the provincial level The survey data collected from the sample were then weighted using the inverse of the probability of selection of each sampled unit to produce estimates representative of the target population. Administrative data were used to estimate the portion that was excluded from survey activity (i.e. unincorporated firms and incorporated firms with revenue less than $50,000).

The combined survey results were analyzed before publication; in general this included a detailed review of the individual responses (especially for the largest companies), a review of general economic conditions as well as historic trends and comparisons with tax data information and other administrative data sources (e.g. 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 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 are not related to sampling and 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 73.9%, 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. Confidence intervals can be constructed around the estimate using the CV's. First, we calculate the standard error by multiplying the sample estimate by the CV. The sample estimate plus or minus twice the standard error is then referred to as 95 % confidence interval.

For the 1999 Annual Survey of Personal Services CVs were calculated for each estimate. Generally, the more commonly reported variables obtained very good CVs (10% or less) while the less commonly reported variables were associated with higher but still acceptable CVs (under 25%). These CVs are available upon request.

Documentation

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