Survey of Service Industries: Sound Recording and Music Publishing

Status:
Active
Frequency:
Biennial
Record number:
3115

This survey collects the financial and operating data needed to develop national and regional economic policies and programs.

Detailed information for 2013

Data release - Data will be available in 2015.

Description

This survey collects data required to produce economic statistics for the Sound Recording and Music Publishing Industry in Canada.

Data collected from businesses are aggregated with information from other sources to produce official estimates of national and provincial economic production for this industry.

Survey estimates are made available to businesses, governments, investors, associations, and the public. The data are used to monitor industry growth, measure performance, and make comparisons to other data sources to better understand this industry.

Statistical activity

The survey is administered as part of the Integrated Business Statistics Program (IBSP). The IBSP program has been designed to integrate approximately 200 separate business surveys into a single master survey program. The IBSP aims at collecting industry and product detail at the provincial level while avoiding overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content. The integrated 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. The combined results produce more coherent and accurate statistics on the economy.

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
  • Culture and leisure
  • Information and culture
  • Sound recording

Data sources and methodology

Target population

The target population consists of all statistical establishments (sometimes referred to as firms or units) classified to the Sound Recording Industries according to the North American Industry Classification System (NAICS 2012) during the reference year.

Instrument design

The survey questionnaire contains generic modules designed to cover several service industries. These include revenue and expense modules.

In order to reduce respondent burden smaller firms receive a characteristics questionnaire (shortened version) that is industry-specific which does not include the revenue and expense modules. This shortened version is designed to collect both financial and non-financial characteristics, while revenue and expense data are extracted from administrative files.

Sampling

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

The frame is the list of active enterprises and establishments that were selected for Statistics Canada's Business Activity, Expenditure and Output Survey. This frame provides basic information about each firm, including address, industry classification, and information from administrative data sources. This information, initially coming from Statistics Canada's Business Register, has also been updated and expanded through Statistics Canada's Business Activity, Expenditure and Output Survey.

Prior to the selection of a random sample, enterprises are classified into homogeneous groups (i.e., groups with the same NAICS codes and same geography) based on the characteristics of their establishments. Then, each group is divided into sub-groups (i.e. small, medium, large) called strata based on the annual revenue of the enterprise.

Following that, a sample, of a predetermined size, is allocated into each stratum, with the objective of optimizing the overall quality of the survey while respecting the available resources. The sample allocation can result in two kinds of strata: take-all strata where all units are sampled with certainty, and take-some strata where a sample of units are randomly selected.

The total sample size for this survey is approximately 410 enterprises.

Data sources

Data collection for this reference period: 2014-04-28 to 2014-10-24

Responding to this survey is mandatory.

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

Data are collected primarily through electronic questionnaire, while providing respondents with the option of receiving a paper questionnaire, replying by telephone interview or using other electronic filing methods. Follow-up for non-response and for data validation is conducted by email, telephone or fax.

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.

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 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.

Revisions and seasonal adjustment

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

Data accuracy

While considerable efforts are 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.

The weighted response rate represents the proportion of the total revenue accounted for by units that responded to the survey. Of the sampled units contributing to the estimate, the weighted response rate was 86.2% for 2011, 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.