Detailed information for March 2023
The monthly survey, Asphalt Roofing, measures quantities of selected asphalt roofing products that are produced, shipped and exported by Canadian manufacturers, including destination of shipments by province.
Data release - May 5, 2023
This survey measures, on a monthly basis, the quantities of selected asphalt roofing products that are produced, shipped and exported by Canadian manufacturers and the destination of shipments by province.
The quantities of asphalt roofing products produced and shipped are used as an indicator of the economic condition of this industry and trends in the housing market, as an input to Canada's Gross Domestic Product and as an input into macro- and micro-economic studies to determine market shares and industry trends. Data are used by the business community, trade associations (including the Canadian Asphalt Shingle Manufacturers' Association), federal and provincial departments and international organizations.
Reference period: Each month
Collection period: During the month following the reference month.
- Construction materials
- Petroleum and coal
Data sources and methodology
The target population is comprised of all establishments in Canada engaged in manufacturing asphalt roofing products as defined in the North American Product Classification System (NAPCS) - Canada 2017 variant 1.0, and classified with industry code 324122 in the North American Industry Classification System Canada 2017. The observed population is made of the establishments in the target population that have the highest revenues (those establishments account for more than 99% of the total revenue generated by the industry).
The questionnaire was developed in collaboration with the Canadian Asphalt Shingle Manufacturers' Association in order to fulfill their needs. Regular dialogue is maintained with the association and the respondents, and every effort is made to ensure that the questions asked are relevant and can be answered by the manufacturers.
This survey is a census with a cross-sectional design.
The sampling unit is the establishment as defined on the Statistics Canada Business Register.
Sampling and sub-sampling:
Sample was determined by selecting the most important establishments allowing to cover 99% of the industry total revenue. The sample size for reference period January 2023 is 12 establishments.
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data are collected each month from survey respondents using an electronic questionnaire. A link to the questionnaire is sent to respondents through e-mail, once completed the respondent submits the data electronically. Data capture and preliminary editing are performed simultaneously to ensure validity of the data. Businesses from whom no response has been received or whose data may contain errors are followed-up by telephone or fax.
Under normal circumstances, data are collected, captured, edited, tabulated and published within 4 weeks after the reference month.
View the Questionnaire(s) and reporting guide(s) .
In order to detect errors and internal inconsistencies, automated edits are applied to captured data to verify that totals equal the sum of components and that the data are consistent with the previous month's data. Data that fail the edits are subject to manual inspection and possible corrective action.
In addition, subject matter experts analyze the data at a more aggregate level to detect and verify any large month-to-month or year-over-year changes for the industry.
When non-response occurs, when respondents do not completely answer the questionnaire, or when reported data are considered incorrect during the error detection steps, imputation is used to fill in the missing information and modify the incorrect information. Many methods of imputation may be used to complete a questionnaire, including manual changes made by an analyst. The automated, statistical techniques used to impute the missing data include the replacement using historical data (with a trend calculated, when appropriate) and the replacement based on known data relationships for the sample unit. Usually, key variables are imputed first and are used as anchors in subsequent steps to impute other related variables.
All units in the observed population are being surveyed. Estimation of totals is done by simple aggregation of the values of all estimation units that are found in the domain of estimation. Estimates are computed for one domain of interest which is Canada, based on the most recent classification information available for the estimation unit and the survey reference period. It should be noted that this classification information may differ from the original sampling classification since records may have changed in size, industry or location. Changes in classification are reflected immediately in the estimates.
Survey results are analyzed to ensure comparability with patterns observed in the historical data series and the economic condition of the industry. Information available from other sources, such as the Monthly Survey of Manufacturing (record number 2101), the Building Permits survey (record number 2802), the media, other government organizations, and industry associations, are also used in the validation process.
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.
Confidentiality analysis includes the detection of possible direct disclosure, which occurs when the value in a tabulation cell is composed of a few responses or when the cell is dominated by a few companies.
Revisions and seasonal adjustment
Data may be revised to include amended information or reports from respondents that are received after the end of a collection cycle. Revisions are disseminated in subsequent periods and reflected in the Common Output Data Repository.
The methodology of this survey has been designed to promote data accuracy. Since data are collected from all Canadian producers of asphalt roofing products as defined in the observed population, the resulting estimates are not subject to sampling error. However, the results are still subject to the non-sampling errors associated with coverage, non-response, inaccurate reporting, and processing. Errors relating to coverage and non-response can be measured. All attempts are made to control inaccurate reporting and processing errors.
The collection response rate for this survey for the 12 months of 2023 is set at 100 %.
Some respondents may be unable to provide data for numerous reasons (i.e., fire, theft, strike, economic hardship, etc.), while others may be late in responding. To minimize non-response, delinquent respondents are followed up rigorously by phone or fax. Data for non-responding units are imputed using industry trends and other related information. Data are revised at a later date, if completed questionnaires are received after the end of a collection cycle.
Non-response rate is calculated using the number of non-responses in the year divided by the number of total expected responses in the year.
Coverage errors consist of omissions, erroneous inclusions, duplications and misclassification of units in the survey frame.
Statistics Canada's Business Register (BR) provides the frame for the Asphalt Roofing survey. The BR is a data service centre updated through a number of sources including administrative data files, feedback received from conducting Statistics Canada business surveys, and profiling activities including direct contact with companies to obtain information about their operations and Internet research findings. Using the BR will ensure quality, while avoiding overlap between surveys and minimizing response burden to the greatest extent possible.
Other non-sampling errors:
These errors may occur at various stages of processing such as coding, data entry, verification, editing, weighting, tabulation, etc. Non-sampling errors are difficult to measure. More important, non-sampling errors require control at the level at which their presence does not impair the use and interpretation of the results.
Measures have been undertaken to minimize the non-sampling errors. For example, units have been defined in a most precise manner and the most up-to-date listings have been used.
Questionnaires have been carefully designed to minimize different interpretations. As well, detailed acceptance testing has been carried out for the different stages of editing and processing and every possible effort has been made to reduce the non-response rate as well as the response burden.
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