Canadian Freight Analysis Framework (CFAF)

Detailed information for 2011 to 2017

Status:

Active

Frequency:

Annual

Record number:

5264

The database can be used in a variety of analyses including, for example, assessing highway capacity and forecasting traffic, evaluating investments in infrastructure, examining trade flows, and analyzing policies such as road pricing and multimodal freight programs.

Data release - May 14, 2020

Description

The Canadian Freight Analysis Framework integrates data from several sources to create a comprehensive picture of freight flows across the country by geography, commodity and mode of transport. The framework database estimates tonnage, value, and tonne-kilometres by origin and destination, by commodity type, and by mode.

Reference period: The calendar year, or the 12-month fiscal period for which the final day occurs on or between April 1st of the reference year and March 31st of the following year.

Subjects

  • Transportation by air
  • Transportation by rail
  • Transportation by road

Data sources and methodology

Target population

Not applicable.

Instrument design

Not applicable.

Sampling

Not applicable.

Data sources

Data are collected from other Statistics Canada surveys and/or other sources.

Data are collected from other Statistics Canada surveys and/or other sources.
The Canadian Freight Analysis Framework provides data on shipment value, commodity, origin, destination, distance, number of shipments, weight transported, tonne-kilometres and revenue earned for different modes of transportation in Canada.

Shipment value
Transaction-level records of goods exported to the United States are used to estimate the value of goods shipped, by commodity, mode of transport and year. These estimates are used for all modes of transportation, namely air, for-hire trucking and rail.

A shipment represents the movement of a single commodity from an origin to a destination for the air and for-hire truck industries, while it represents the number of cars for rail.

Transportation by air
The Airport Activity Survey and the Quarterly Civil Aviation Survey are the sources of the air mode data.

The Airport Activity Survey collects data via the Electronic Collection of Air Transportation Statistics from air carriers operating in Canada. The survey provides data on origin, destination and weight from scheduled and charter air carriers. Distance is modelled as the great-circle distance between the origin and destination airports. Tonne-kilometres are derived from the weight and distance data. No commodity detail is currently available for the air mode.

The Quarterly Civil Aviation Survey uses an electronic questionnaire to collect financial and operating data for scheduled and charter services from the Canadian Level I and II air carriers. Revenue per kilogram is modelled from the aggregate revenue and weight data collected by this survey. Revenue earned is then derived by multiplying these values by the weight transported from the Airport Activity Survey.

Data on air freight for certain city pairs were suppressed to meet the confidentiality requirements of the Statistics Act. As a result, data from the Canadian Freight Analysis Framework underestimate total commodity shipments by air.

Transportation by road
The Trucking Commodity Origin and Destination Survey collects data on commodity, origin, destination, weight and revenues from the Canadian for-hire trucking industry. Distance is modelled using commercial software (PC*Miler) along with the collected origin and destination data. Tonne-kilometres are derived from the weight and distance data.

Data for the for-hire trucking industry exclude trucking activities undertaken by businesses classified to other industries, such as manufacturing or retail sales. The size of the sample requires a methodology that includes a four-stage sampling design to adequately capture the population. As a result, data users should use caution when comparing year-over-year changes between commodity groups and /or detailed geography.

Transportation by rail
The rail data are derived from the Rail Commodity Origin and Destination Statistics survey obtained from Transport Canada. The survey collects data on railway commodities carried by Canadian National (CN), Canadian Pacific (CP), carriers that interline with CN and CP, as well as a number of regional and short-haul carriers that do not interline with either CN or CP.

The survey provides data on commodity, origin, destination, distance, weight and revenue earned. Distance is collected for domestic shipments. Distance for transborder shipments (between Canada and the United States or Mexico) are modelled as the great-circle distance between the origin and destination. Tonne-kilometres are derived from the weight and distance data. The revenue data have been modelled due to the presence of a small number of large carriers for the rail mode so that the revenues are not specific to a carrier, a geography or a specific commodity but will add up to the overall reported revenue.

Error detection

Not applicable.

Imputation

Not applicable.

Estimation

Not applicable.

Quality evaluation

Not applicable.

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

Not applicable.

Data accuracy

Not applicable.

Report a problem on this page

Is something not working? Is there information outdated? Can't find what you're looking for?

Please contact us and let us know how we can help you.

Privacy notice

Date modified: