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Methodology

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 usually 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, the 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-G). 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.

Since 2004, the survey has covered 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.

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.

Instrument design

The survey questionnaires comprise generic modules that have been designed to cover several service industries. For 2006, 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 basic objective of the survey is to produce estimates for the whole industry -incorporated and unincorporated businesses. For this reference year, only revenue and expense variables are being produced. Questionnaires were, therefore, only sent to a subset of businesses with complex operational structures. The remaining businesses were estimated using administrative data only.

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 other administrative information. The frame is maintained by Statistics Canada's Business Register, and is updated using administrative data.

Prior to the selection of a random sample, establishments are classified into homogeneous groups (i.e., groups with the same NAICS codes, same geography (province/territory) and same status as for-profit or not-for-profit.

The sample size for reference year 2006 was 569 collection entities.

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 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.

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; extreme values must be identified and investigated, etc.

Imputation

Where information is missing, imputation is performed using a "nearest neighbour" procedure (donor imputation), using historical data where available, using averages based on responses from a set of similar establishments, or using administrative data as a proxy for reported data.

Estimation

As part of the estimation process, survey data are weighted because some units in the sample represent a certain number of establishments that were not selected in the sample. These data are then combined with administrative data to produce final industry estimates.

Quality evaluation

Prior to publication, combined survey results are analyzed for quality. In general, this includes a detailed review of individual responses (especially for the largest companies), of general economic conditions and historic trends, and comparisons with other data sources.

Disclosure control

Statistics Canada is prohibited by law from releasing any data that would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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 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 223 mailed sampled units contributing to the estimate, the weighted response rate was 79% of total industry 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. 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:

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