Monthly Railway Carloadings Survey

Detailed information for April 2010

This survey collects data from common carrier railways operating in Canada which are essential for the analysis of the Railway Transport Industry and the assessment of its contribution to the Canadian economy. These data provide input into the Canadian System of National Accounts for the calculation of the gross domestic product and are used by various government departments to develop policy and to monitor the industry.

Data release - June 30, 2010

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

The survey presents essential data for timely analysis of the Rail Transport Industry and its contribution to the Canadian economy.

The data are used by Statistics Canada as input to the System of National Accounts, by Transport Canada and other federal and provincial departments, by transportation companies, consulting firms, universities and foreign governments. The information is used for the analysis of transportation activity, for marketing and economic studies, as well as industry performance measures.

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: Month

Subjects

• Transportation
• Transportation by rail

Data sources and methodology

Target population

Common carrier railways operating in Canada and providing for-hire freight service.

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

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Approximately 28 rail carriers report each month on their total intermodal (Intermodal operations involve more than one mode of transport to complete the movement of shipments. Goods are carried in a highway trailer or freight container, which is transferred between a rail car and some other mode, usually a truck or a ship) and non-intermodal traffic of the previous month. For non-intermodal traffic, the carriers report the number of cars and tonnes by commodity of revenue-generating freight that they have loaded in Canada. For intermodal freight, the carriers report the number of units and tonnes for containers-on-flat-cars (C.O.F.C.) and trailers-on-flat-cars (T.O.F.C.), with no commodity data. The carriers also report the total tonnage of revenue freight received from United States connections.

The data are collected via questionnaires and electronic reports that are filed with Statistics Canada eight working days after the reference month. These questionnaires are captured and edited and the data are then aggregated to produce tables for all of Canada and the Eastern and Western divisions of Canada.

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 does not apply.

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 individual responses, 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

Estimates are provided for the reference month and the previous 12 months are revised if necessary. The data are not seasonally adjusted.

Data accuracy

While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: non-sampling and sampling. Since the survey is a census of the target population, only non-sampling errors are possible.

Non-sampling errors may occur for many reasons. For example, non-response is an important source of non-sampling error. Population coverage, differences in the interpretation of questions, incorrect information from respondents, and mistakes in recording, coding and processing data are other examples of non-sampling errors.

Non-sampling errors are controlled through a careful design of the questionnaire, the use of a minimal number of simple concepts and consistency checks. Coverage error was minimized by using multiple sources to update the frame. Measures such as response rates are used as indicators of the possible extent of non-sampling errors.

The response rate for this survey has been slightly above 95% for the last several years.