Gasoline and Other Petroleum Fuels Sold

Detailed information for 2016

Status:

Active

Frequency:

Annual

Record number:

2746

This survey collects data from provincial and territorial ministries of Finance on the sales of gasoline, diesel fuels and liquefied petroleum gas (LPG) for which road taxes were paid.

Data release - August 11, 2017

Description

The purpose of this survey is to collect data on gasoline and other petroleum fuels sold in Canada. These data are used by the Department of Finance for the calculation of fiscal equalization payments to the provinces pursuant to the Federal-Provincial Fiscal Arrangements Act and Territorial Financing for the territories. This information is also used by various levels of government for the planning and development of transportation infrastructure and by special interest groups for marketing strategies. Your information may be used by Statistics Canada for other statistical and research purposes.

Statistical activity

This statistical activity is part of a set of surveys measuring various aspects of activities related to the movement of people and goods. These surveys are grouped as follows:

Transportation by air includes records related to the movement of aircraft, passengers and cargo by air for both Canadian and foreign air carriers operating in Canada as well as the financial and operating characteristics of Canadian air carriers. These data are produced by the Aviation Statistics Centre.

Transportation by rail includes records relating to rail transportation in Canada and between the United States and Canada.

Transportation by road includes records relating to all road transport in Canada. In addition to surveying carriers and owners of registered motor vehicles, certain programs rely on aggregation of provincial and territorial administrative records.

Reference period: Calendar year

Subjects

  • Economic accounts
  • Government financial statistics
  • Transportation
  • Transportation by road

Data sources and methodology

Target population

All provinces and territories in Canada.

Instrument design

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

Sampling

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

Data are collected for all units of the target population, therefore no sampling is done.

Data sources

Data collection for this reference period: 2016-04-01 to 2017-07-31

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data are collected by means of a questionnaire submitted monthly to each province and territory. Telephone, e-mail and fax follow-up is conducted to resolve edit problems with questionnaires and to collect data from respondents who have not returned the questionnaire.

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

Error detection

At the micro level, several checks are performed on the data to verify internal consistency and identify extreme values. At the macro level, the data are subjected to a detailed quality review process, including a comparative analysis to prior year. Material errors are thereby identified and corrected.

Imputation

This methodology type does not apply to this statistical program.

Estimation

This methodology type does not apply to this statistical program.

Quality evaluation

The combined survey results are analyzed before dissemination. In general, this includes a detailed review of the data, a review of general economic conditions as well as 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. Data for a specific industry or variable may be suppressed (along with that of a second industry or variable) if the number of enterprises in the population is too low.

Revisions and seasonal adjustment

Monthly estimates are provided for the reference month. The data for the previous month are revised if necessary. Seasonal adjustments are not done.

Data accuracy

The methodology of this survey has been designed to control errors and to reduce the potential effects of these. However, the results of the survey remain subject to a certain degree of non-sampling error. Examples of non-sampling error are coverage error, data response error, non-response error and processing error. A discussion of these types of errors and the steps taken to address them follows.

Coverage error can result from incomplete listing and inadequate coverage of the provinces and territories. However, the population of this survey is comprised of the ten provinces and three territories, as such this type of error is unlikely to happen.

Data response error may be due to questionnaire design, the characteristics of a question, inability or unwillingness of the respondent to provide correct information, misinterpretation of the questions or definitional problems. These errors are controlled through careful questionnaire design, the use of simple concepts and consistency checks.

Non-response error is related to respondents that may refuse to answer, are unable to respond or are too late in reporting. However, the response rate has always been very high for this survey, being 100% for most variables on the questionnaire. Also, the staff remains in close contact with the respondents throughout the year to avoid any late data reporting.

Processing error may occur at various stages of processing such as data entry, editing and tabulation. Measures have been taken to minimize these errors. Data entry and edit are performed simultaneously due to the spreadsheet design which allows errors to be quickly seen. Historical ratios also aid in eliminating outliers created by data entry. Tabulation is automated to eliminate human error.

Documentation

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