Industrial Chemicals and Synthetic Resins

Detailed information for 2016





Record number:


The annual survey, Industrial Chemicals and Synthetic Resins, measures quantities of selected industrial chemicals and new virgin resins (excluding compounding or colouring ingredients) that are produced by Canadian manufacturers.

Data release - July 19, 2017


This survey measures, on an annual basis, the quantities of selected industrial chemicals and new virgin resins (excluding compounding or colouring ingredients) that are produced by Canadian manufacturers.

The quantities produced of industrial chemicals and new virgin resins are used as an indicator of the economic condition of the chemical manufacturing industry. They are also used 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 Chemical Producers' Association), federal and provincial departments, and international organizations.

Reference period: The calendar year.

Collection period: January to April of the year following the reference period.


  • Chemicals, plastics and rubber
  • Manufacturing

Data sources and methodology

Target population

The target population for this survey includes manufacturers in Canada of industrial chemicals and synthetic resins as defined in the Standard Classification of Goods (SCG), that report these products to the Annual Survey of Manufacturing and Logging Industries (ASML) [record number 2103]. This means that estimates from this annual survey do not cover the entire universe of industrial chemicals and synthetic resins producers in Canada, because the ASML does not survey all businesses. Instead, the ASML uses administrative data to cover the small and medium-sized establishments. These manufacturers are not part of this annual survey.

Instrument design

The questionnaire for this survey has remained stable over the years, although the format and wording has been modified to maintain its relevance based on feedback from survey respondents and data users.

Regular dialogue is maintained with the Canadian Chemical Producers' Association (CCPA) 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.

No sampling is done for this statistical program.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data are collected annually using a mail-out / mail-back process. 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 captured, edited, tabulated and published within 12 weeks after the end of the collection period (April 21).

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

Error detection

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 year'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 year-over-year changes for the industry.


Missing data for the current year are imputed automatically by applying the previous year's value. However, an option exists for analysts to manually override this imputation with a better estimate based on pertinent knowledge about the industry or the business.


This methodology type does not apply to this statistical program.

Quality evaluation

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 media, other government organizations, and industry associations, are also used in the validation process.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which 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.

Direct disclosure may occur when the value in a tabulation cell is composed of a few responses or when the cell is dominated by a few companies. Residual disclosure may occur when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

Data may be revised to include amended information or reports from respondents that are received after the end of the collection cycle. Revisions are disseminated in a subsequent period and reflected in the CANSIM series.

Data accuracy

The methodology of this survey has been designed to promote data accuracy. Since data are collected from all Canadian producers of industrial chemicals and synthetic resins, as defined in the target 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.

Response rates
The collection response rate for the 2015 survey is 96.2%.

Non-response bias
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 the following year, if completed questionnaires are received after the end of the collection cycle.

Non-response error is calculated using the number of non-responses in the year, divided by the number of total expected responses in the year.

Coverage error
There is a degree of undercoverage (referred to as coverage error) in the survey results as there is generally a lag between the time a new business comes into existence and when it is included in the universe of this survey. This is due to the fact that the list of companies surveyed is derived from the latest available survey results of the ASML which are not available until 15 months after the reference period.

This error is kept at a minimum by identifying new survey units by using advance information from the ASML, feedback from the Monthly Survey of Manufacturing (MSM) [record number 2101] and information from other sources such as the Canadian Chemical Producers' Association, trade journals and newspaper articles.

Other non-sampling errors
Inaccurate responses
Inaccuracy may result from poor questionnaire design, an inability on the part of respondents to provide the requested information, or from misinterpretation of the survey questions. To reduce such errors the format and wording in the questionnaire are reviewed from time to time and modified based on feedback from survey respondents and data users. Respondents are also reminded of the importance of their contribution and the need for accurately reported information.

Processing errors
These errors may occur at various stages in the processing of survey data such as data entry, verification, editing and tabulation. Data are examined for such errors using automated edits along with an analytical review by subject matter experts. Several checks are performed on the collected data to verify internal consistency and comparability over time.

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