Annual Survey of Service Industries: Heritage Institutions

Detailed information for 2005

This survey collects the financial and operating data needed to produce statistics on Heritage Institutions in Canada.

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

Data release - March 29, 2007

• 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 Heritage Institutions 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 heritage institutions in Canada. The results from this survey provide data to governments and cultural associations on heritage institutions 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 heritage sector.

For purposes of research and analysis, heritage institutions have 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

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: March to September

Subjects

• Arts, entertainment and recreation
• Business, consumer and property services
• Business performance and ownership
• Culture and leisure
• Financial statements and performance
• Information and culture
• Museums, historic sites, archives and other heritage institutions

Data sources and methodology

Target population

The target population consists of all establishments classified as heritage institutions (NAICS 712) and archives (NAICS 519122) during the reference year according to the North American Industry Classification System (NAICS).

The survey covers those publicly and privately owned heritage institutions whose purpose is to preserve, interpret, and make accessible to the public, objects, specimens, documents, buildings, and land areas of educational and cultural value, including artistic, scientific, historical, technological and nature-related material. Heritage institutions include museums and non-commercial art galleries, archives, historic sites, buildings, parks or communities and nature parks and conservation areas with interpretation or educational programs. Also surveyed are exhibition centres, planetariums, observatories, aquariums, zoos, botanical gardens and arboretums.

• Additional documentation

Instrument design

The survey questionnaires comprise generic modules that have been designed to cover several service industries. For 2005, a shorter questionnaire, designed to collect only core financial data (revenues and expenses), was used for this industry. The questionnaire was sent only to a subset of businesses with complex operational structures. Data for the remaining businesses selected in sample were compiled using administrative data.

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. For this reference year, only revenue and expense variables are being produced. Questionnaires are only being sent to a subset of businesses with complex operational structures. The remaining businesses will be estimated using administrative data only.

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 (province/territory)). 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 on the basis of 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 sample size for reference year 2005 was 787 entities.

Data sources

Data collection for this reference period: 2006-03-01 to 2006-09-28

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 electronic filing methods

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

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

Error detection

Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Every effort is made to minimize the non-sampling errors of omission, duplication, reporting and processing. Several checks are performed on the collected data. These checks look for internal consistency such as: section totals must be equal to the components; if employees are reported, personnel costs must be greater than zero; the main source of income must be consistent with the assigned NAICS code; identification of extreme values; etc.

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 comparability. In general, this includes a detailed review of individual responses (especially for the largest companies), general economic conditions, 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 115 mailed sampled units contributing to the estimate, the weighted response rate was 83% in terms of revenue, after accounting for firms that have gone out of business, have been reclassified to a different industry, are inactive, or are duplicates on the frame.

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.

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

CVs were calculated for each estimate. The CVs are available upon request.