Annual Survey on Rail Transportation (AR)

Detailed information for 2017

Status:

Active

Frequency:

Annual

Record number:

2734

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 Canada's 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 - March 29, 2019

Description

The survey collects annual financial, operating and employment data on railways operating in Canada. The data are used as input to the Canadian System of National Accounts, by Transport Canada, other federal and provincial departments, and 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

The survey is administered as part of the Integrated Business Statistics Program (IBSP). The IBSP program has been designed to integrate approximately 200 separate business surveys into a single master survey program. The IBSP aims at collecting industry and product detail at the provincial level while minimizing overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content.

The integrated approach makes reporting easier for firms operating in different industries because they can provide similar information for each branch operation. This way they avoid having to respond to questionnaires that differ for each industry in terms of format, wording and even concepts. The combined results produce more coherent and accurate statistics on the economy.

Reference period: 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
  • Transportation by rail

Data sources and methodology

Target population

Common carrier railways operating in Canada that provide passenger and freight services. Excluded from the survey are companies that provide rail support services (bridge and terminal service etc.) and sightseeing tours.

Instrument design

The survey questionnaire was developed in collaboration with specialists from Statistics Canada, Transport Canada and the Canadian railway industry. It comprises financial characteristics such as sources of revenue, expense detail and employment characteristics. Based on contacts with respondents and data users, some modifications have been incorporated into the questionnaires in order to reflect the nature of the industry surveyed. The changes were field tested to ensure that they were reasonable and sustainable. This questionnaire was reviewed to reduce response burden from respondents.

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. The information on all Canadian rail companies is maintained on the Business Register. Specific fields are used to select carriers for the survey and to group them by homogeneous cells.

Data sources

Data collection for this reference period: 2018-07-09 to 2018-09-05

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Financial and operating statistics are collected from an electronic questionnaire census of common carrier railways operating in Canada. Companies falling under federal jurisdiction report data on schedules or forms, specified by Transport Canada directly to Transport Canada. Other railway carriers report directly to Statistics Canada on the same schedules or forms. Individual reports undergo comprehensive review upon receipt and are edited for consistency and reliability.

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

Error detection

A lot of rules have been incorporated to the electronic questionnaire to make sure the submitted data are consistent. Inconsistencies will be corrected during the edit and imputation process. Other inconsistent data can be identified and corrected manually, after verification with the respondent.

Imputation

Various methods for imputation are used, such as historical imputation, with or without trends, and donor imputation. When needed, data are manually imputed by survey analysts.

Estimation

The survey uses the Generalized Estimation System (G-Est) developed at Statistics Canada to produce its domain estimates and quality indicators. It is a SAS based application for producing estimates for domains of a population based on a sample and auxiliary information. Estimates are computed at several levels of interest, based on the most recent classification information for the statistical entity and the survey reference period. Population totals and population ratios of totals are calculated, as well as breakdowns by domains of interest.

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.

Users are advised to consult the Uniform Classification of Accounts for concepts and reporting definitions as survey results may be misconstrued or improperly interpreted without prior knowledge of the accounts. For example, carriers may report total traffic over their tracks, hence operating statistics, such as passenger car-kilometers and freight car-kilometers may be duplicated.

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

Annual estimates are provided for the reference year. The data for the previous reference year are revised if necessary. As this is an annual survey, seasonal adjustments are not applicable.

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. For the survey, final response rate is very high - approaching 100%; however, slow reporting is sometimes an issue.

NON-RESPONSE BIAIS
In addition to increased variance, non-response can result in biased estimates if non-respondents have different characteristics from respondents. Non response is addressed through imputation and follow-up with respondent.

COVERAGE ERROR
Coverage error is minimized by keeping the frame up to date using survey and administrative sources. Coverage rates are monitored during sampling process.

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