Annual Survey of Service Industries: Film, Television and Video Post-production

Detailed information for 2010

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

Data release - March 16, 2012

• 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 the Film, Television and Video Post-production industry in Canada. Commencing with reference year 2006 and every two years thereafter, the survey also collects detailed information on the characteristics of the businesses, such as type of revenue and type of client.

These data are aggregated with information from other sources to produce official estimates of the national and provincial economic production of the Film, Television and Video Post-production industry in Canada. The results from this survey provide data to businesses, governments, investors and associations. These data allow these groups to monitor the growth of the industry, measure performance, allow comparison across similar businesses and to better understand this industry to react to trends and patterns.

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

Subjects

• Business, consumer and property services
• Business performance and ownership
• Culture and leisure
• Film and video
• Financial statements and performance
• Information and culture

Data sources and methodology

Target population

The target population consists of all establishments classified to the film, television and video post-production industry (NAICS 512190) according to the North American Industry Classification System (NAICS) during the reference year. This industry comprises establishments primarily engaged in providing post-production services and services to the motion picture and video industries, including specialized motion picture or video post-production services, such as editing, film/tape transferring, dubbing, subtitling, creating credits, closed captioning, and producing computer graphics, animation and special effects, as well as developing and processing motion picture films.

• Additional documentation

Instrument design

The survey questionnaire contains generic modules designed to cover several service industries. These include revenue, expense, and employment modules. In order to reduce respondent burden, smaller firms receive a characteristics questionnaire (shortened version) which does not include the revenue and expense modules. For smaller firms, revenue and expense data are extracted from administrative files.

Sampling

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

The survey design was based on probability sampling and only covered the portion of the frame subject to direct data collection.

The basic objective of the survey is to produce estimates for the whole industry for 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 and administrative data for businesses with revenue below the threshold, which are excluded from sampling. The excluded portion represents a substantial proportion of the industry in terms of number of establishments, but its contribution to the overall industry revenue is only about 5%. It should be noted that for this excluded portion, only certain financial information is obtained from administrative sources; e.g., total revenue, expenses such as depreciation and salaries, wages and benefits. Characteristics such as detailed revenue by type of service and employment are collected only for surveyed establishments. (Note: the threshold varies between industries and between provinces in the same survey.)

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 referred to as the Business Register and is updated regularly using administrative data.

Prior to the selection of a random sample, establishments are classified into homogeneous groups (i.e., groups with the same industry, 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 structure characteristics (multi-establishment, multi-legal, multi-NAICS, or multi-province enterprises), as well as selected establishments whose particular industry characteristics make it essential that they be included. All take-all and must-take firms are selected to the sample. Units in the take-some strata are subject to simple random sampling.

Finally, the sample size is inflated to compensate for firms that are found to no longer belong in the industry, such as those that have gone out of business, changed their primary business activity, are inactive, or are duplicates on the frame. The effective sample size for reference year 2010 was 194 collection entities.

Data sources

Data collection for this reference period: 2011-01-18 to 2011-09-30

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 are 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 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.

Non-sampling errors are controlled through a careful design of the questionnaire, the use of simple concepts and consistency checks. Coverage error was minimized by using multiple sources to update the frame. Measures such as response rates are used as indicators of the possible extent 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 for 2010 was 94.5%, 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.