Annual Oil Pipeline Financial Survey (OPFS)
Detailed information for 2020
This annual survey collects data on the general position of Canadian companies primarily engaged in the gathering and transportation of crude oil and other petroleum products.
Data release - March 30, 2022
This annual survey collects data on the general position of Canadian companies primarily engaged in the gathering and transportation of crude oil and other petroleum products. The survey collects financial, employment, income and balance sheet information as well as engineering and operating statistics.
These data are required for integration into the input-output sector of the Canadian System of Macroeconomic Accounts. Data are intended for use by survey respondents, federal departments and agencies, provincial ministries and authorities, industry associations, industry analysts, the media and the general public to assess trends in the crude oil and petroleum products pipeline sector of the Canadian economy.
Reference period: Calendar year
- Business performance and ownership
- Financial statements and performance
Data sources and methodology
The target population is comprised of all establishments in Canada engaged in the operation of Pipeline transportation of crude oil and other liquid petroleum products. These companies are classified to subsectors 4861 (Pipeline transportation of crude oil) and 4869 (Other pipeline transportation) in the North American Industry Classification System (NAICS) 2017. The survey frame is comprised of all establishments in Statistics Canada's Business Register that are identified currently engaging in the operation of Pipeline transportation of crude oil and other liquid petroleum products.
The questionnaire was designed using Statistics Canada questionnaire design standards. The design was done in consultation with the survey's partners.
The questionnaire is subject to regular revision to reflect changes in industry classification and information requirements.
Data are collected for all units of the target population, therefore no sampling is done.
Data collection for this reference period: 2021-05-14 to 2021-11-12
Responding to this survey is mandatory.
Data are collected directly from survey respondents and extracted from administrative files.
Collection method (and method of initial contact): Electronic questionnaire
Data capture method: The data from the questionnaire are processed directly into the Integrated Business Statistics Program (IBSP).
Follow-up method: Follow-up for non-response and for data validation is conducted by telephone or e-mail in order to reach the survey target response rate of 100%.
Languages offered to respondents: English and French
Time given to complete the questionnaire: 20 days
Average time required to complete questionnaire: 6 hours
View the Questionnaire(s) and reporting guide(s) .
Error detection is an integral part of both collection and data processing activities. Automated edits are applied to data records during collection to identify reporting and capture errors. These edits identify potential errors based on year-over-year changes in key variables, totals, and ratios that exceed tolerance thresholds, as well as identify problems in the consistency of collected data (e.g. a total variable does not equal the sum of its parts). During data processing, other edits are used to automatically detect errors or inconsistencies that remain in the data following collection. These edits include value edits (e.g. Value > 0, Value > -500, Value = 0), linear equality edits (e.g. Value1 + Value2 = Total Value), linear inequality edits (e.g. Value1 >= Value2), and equivalency edits (e.g. Value1 = Value2). When errors are found, they can be corrected using the failed edit follow up process during collection or via imputation. Extreme values are also flagged as outliers, using automated methods based on the distribution of the collected information. Following their detection, these values are reviewed in order to assess their reliability. Manual review of other units may lead to additional outliers identified. These outliers are excluded from use in the calculation of ratios and trends used for imputation, and during donor imputation. In general, every effort is made to minimize the non-sampling errors of omission, duplication, misclassification, reporting and processing.
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 deterministic imputation, replacement using historical data (with a trend calculated, when appropriate), replacement using auxiliary information available from other sources, replacement based on known data relationships for the sample unit, and replacement using data from a similar unit in the sample (known as donor imputation). Usually, key variables are imputed first and are used as anchors in subsequent steps to impute other, related variables.
Imputation generates a complete and coherent microdata file that covers all survey variables.
This methodology type does not apply to this statistical program.
In order to ensure the accuracy and consistency of the data, the results of the survey are reconciled with other energy surveys such as the Monthly Energy Transportation and Storage Survey (survey ID # 5300).Other federal departments, provincial and territorial authorities routinely monitor the data.
Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.
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.
An exception to the general rule of confidentiality under the Statistics Act is the disclosure, at the discretion of the Chief Statistician, of identifiable information relating to public utilities, which includes undertakings supplying petroleum or petroleum products by pipeline, and undertakings supplying, transmitting or distributing gas, electricity or steam. This applies to the dissemination of aggregate survey results at the provincial or territorial level where only one or two public utilities may have reported data or where one dominates the industry in a particular province or territory.
Micro data is only shared or disclosed to organizations with whom Statistics Canada has an official data sharing agreement in place. All company records are removed for any respondent who has written the Chief Statistician to object to the sharing of their data.
Revisions and seasonal adjustment
Revisions may be performed for previous years.
The survey is a census of the target population. As a consequence, under-coverage is minimal, and minimal bias resulting from non-response is introduced. Major revisions are incorporated as required.