Annual Survey of Service Industries: Performing Arts

Detailed information for 2006

This survey collects the financial and operating data needed to produce statistics on the Performing arts industry in Canada.

These data are aggregated with information from other sources to produce official estimates of the national and provincial economic production of the Performing arts industry in Canada. Data on this and other industries together contribute to the accurate measurement of national and provincial economies.

Data release - June 17, 2008

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

This annual sample survey collects the financial and operating data needed to produce statistics on Performing Arts in Canada. Commencing with reference year 2004 and every two years thereafter, the survey also collects detailed information on the characteristics of the businesses, such as attendance and sources of funding.

These data are aggregated with information from other sources to produce official estimates of the national and provincial economic production of all performing arts establishments in Canada. The results from this survey provide data to governments and cultural associations on not-for-profit performing arts in Canada, to help in the development of policies, the conducting of program evaluations and policy reviews, and in the area of advocacy in the performing arts sector.

For purposes of research and analysis, the performing arts sector has been grouped into two components: not-for-profit and for-profit. The not-for-profit component used to be surveyed under the auspices of the Culture Statistics Program. Commencing with reference year 2004, this new survey, which now comprises both the for-profit and not-for-profit establishments, is administered by the Service Industries Program, in collaboration with the Culture Statistics Program. Historical time series data from the previous Culture Statistics Program are available in The Guide to Culture Statistics (online, free of charge, at catalogue number 87-008-GIE). It should be noted that data from this historical time series should not be compared with data from this new survey due to significant differences in coverage and methodology.

As of 2004, the survey covers a somewhat different set of businesses than in previous years so that data generally cannot be expected to be comparable. The list of names and addresses of businesses is now drawn from a central Statistics Canada data base. Also, a much more rigorous delineation of those companies that are considered part of the culture sector has been applied through the implementation of the North American Industry Classification System (NAICS). This industry-based classification is a departure from the activity-based classification that was used previously. In addition to these changes in coverage, commencing with 2004, the data are based on a sample of businesses which has affected our ability to publish in detail some culture variables.

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: January to June

Subjects

• Arts, entertainment and recreation
• Business, consumer and property services
• Business performance and ownership
• Culture and leisure
• Financial statements and performance
• Information and culture
• Performing and visual arts

Data sources and methodology

Target population

The target population consists of all establishments classified to the Performing arts industry, (NAICS 711111, 711112, 711120, 711130, and 711190) according to the North American Industry Classification System (NAICS) during the reference year. This industry comprises establishments primarily engaged in the live performing arts industry.

• Additional documentation

Instrument design

The survey questionnaires comprise generic modules that have been designed to cover several service industries. These modules include revenues, expenses, and employment, as well as an industry-specific module designed to ask for financial and non-financial characteristics that pertain specifically to this industry.

Sampling

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

The frame is the list of establishments from which the portion eligible for sampling is determined and the sample is taken. The frame provides basic information about each firm including address, industry classification, and information from administrative data sources. The frame is maintained by Statistics Canada's Business Register and is updated using administrative data.

The basic objective of the survey is to produce estimates for the whole industry - incorporated and unincorporated businesses. The data come from two different sources: a sample of all businesses with revenue above or equal to a certain threshold (note: the threshold varies between surveys and sometimes between industries and provinces in the same survey) for which either survey or administrative data may be used; and administrative data only for businesses with revenue below the specified threshold. It should be noted that only financial information is available from businesses below the threshold; e.g., revenue, and expenses such as depreciation and salaries, wages and benefits. Detailed characteristics are collected only for surveyed establishments.

Prior to the selection of a random sample, establishments are classified into homogeneous groups (i.e., groups with the same NAICS codes and same geography). Quality requirements are targeted, and then each group is divided into sub-groups called strata: take-all, must-take, and take-some.

The take-all stratum represents the largest firms in terms of performance (based on revenue) in an industry. The must-take stratum is comprised of units selected based on complex structural characteristics (multi-establishment, multi-legal, multi-NAICS, or multi-province enterprises). All take-all and must-take firms are selected to the sample. Units in the take-some strata are subject to simple random sampling.

The effective sample size for reference year 2006 was 702 collection entities.

Data sources

Data collection for this reference period: 2007-02-01 to 2007-10-31

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 providing respondents with the option of telephone or other electronic filing methods.

Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period.

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

Error detection

Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Where possible, data will be verified using alternate sources.

Imputation

Partial records are imputed to make them complete. Data for non-respondents are imputed using donor imputation, administrative data, or historical data.

Estimation

As part of the estimation process, survey data are weighted and combined with administrative data to produce final industry estimates.

Quality evaluation

Prior to dissemination, combined survey results are analyzed for overall quality; in general, this includes a detailed review of individual responses (especially for the largest companies), an assessment of the general economic conditions portrayed by the data, historic trends, and comparisons with other data sources.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that 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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

There is no seasonal adjustment. Data from previous years may be revised based on updated information.

Data accuracy

While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: non-sampling and sampling.

Non-sampling error is 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, and mistakes in recording, coding, and processing data are other examples of non-sampling errors.

Of the units contributing to the estimate, the weighted response rate was 92.8%.

Sampling error occurs because population estimates are derived from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. An important property of probability sampling is that sampling error can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). The assumption is that over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all units in the universe would be less than twice the CV, 95 times out of 100. The range of acceptable data values yielded by a sample is called a confidence interval. Confidence intervals can be constructed around the estimate using the CV. 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 a 95% confidence interval.

CVs were calculated for each estimate.

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

The CVs are available upon request.