For-Hire Trucking Survey

Detailed information for first and second quarters 2000

The purpose of this survey is to measure outputs of the Canadian for-hire trucking industry by providing estimates of inter-city commodity movements.

Data release - June 1, 2001

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

Description

The For-hire Trucking Survey has been re-designed and will be replaced by the Trucking Commodity Origin and Destination Survey beginning with reference year 2004.

The purpose of this survey is to measure outputs of the Canadian for-hire trucking industry by providing estimates of inter-city commodity movements. Information is provided for shipments, revenue, weight, and distance. The survey complements the results of the Motor Carriers of Freight Survey by providing additional information. The data are used by federal and provincial governments, trucking associations, members of the industry, universities and research institutions. The statistics are also used by planning boards to determine the amount of traffic on certain highways.

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.

Subjects

• Transportation
• Transportation by road

Data sources and methodology

Target population

Canada-based for-hire trucking companies with annual operating revenues of one million dollars or more, the major part of which is derived from long-distance deliveries.

Instrument design

Not applicable.

Sampling

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

The For-hire Trucking Survey is a sample survey and the sample design is based on a two-stage sample of approximately 800,000 shipments made by the inter-city for-hire carriers. Once the population has been stratified according to areas of operation, type of services, commodities carried and revenue class, the first-stage consists of selecting, in each stratum, a number of firms corresponding to the desired number of firms determined at the sample selection stage. The sample of firms is then converted to a sample of Document Storage Location Point (DSLP) by including in the latter sample all DSLP's of the selected firms. The second stage of the sample design consists of selecting a systematic sample of shipments from the files of each selected DSLP. The data collection is made by interviewers from Statistics Canada Regional Operations Offices across Canada. The interviewers visit each selected DSLP, determine the apparent size of the files (number of shipments) and, using the appropriate sampling interval from a table, transcribe the data from the shipping documents.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

The following information is collected for each sampled shipment: the origin and destination of the shipment, a description of the commodity or commodities carried, the shipment weight and the transportation revenue earned. This information about shipments is either transcribed from documents, or obtained from computer tapes provided by some respondents. Once all necessary information for the survey is collected, a series of verifications takes place to ensure that the records are consistent and that collection and capture of the data did not introduce errors. Missing values and data found in error are imputed. A complete description of the procedures applied to the survey data is available upon request from the Transportation Division.

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

Error detection

Non-response errors can occur when a respondent does not respond at all (total non-response) or responds only to some questions (partial non-response). These errors can have a serious effect if non-respondents are systematically different from respondents in survey characteristics and/or the non-response rate is high.

Response errors occur when a respondent provides incorrect information due to misinterpretation of the survey questions or lack of correct information, gives wrong information by mistake, or is reluctant to disclose the correct information. Large response errors are likely to be caught during editing. However, others may simply go through undetected.

Apart from coverage, response and non-response errors described above, errors that occur during the processing of the data constitute another component of the non-sampling error. Processing errors can arise in data capture, coding, transcription, editing, imputation, outlier detection and treatment, and other types of data handling.

A coding error occurs when a field is coded erroneously because of misinterpretation of coding procedures or bad judgment (e.g. errors in commodity coding). A data capture error occurs when data are misinterpreted or keyed incorrectly.

Once data are coded and captured, they are subject to editing and imputation of missing or erroneous values. The quality of the data depends on the amount of imputation and the difference between the imputed and the true, but unknown, values. Using wrong assumptions when developing the imputation system could result in bias in the imputed data.

The non-sampling error as a whole is only one part of the total survey error but its contribution may be important. To minimize the effect of this type of error, a quality assurance program is carried out for each survey. For instance, follow-ups of non-respondents are conducted to obtain information from the total non-respondents or to complete partially unanswered questionnaires for questions that are deemed essential. Various quality assurance procedures are exercised at the data capture step. The data editing procedures identify some inconsistencies in the data structure and the imputation procedures correct the identified inconsistencies.

Some non-sampling errors will cancel over a large number of observations, but systematically occurring errors (i.e. those that do not tend to cancel) will contribute to a bias in the estimates. For example, if carriers consistently tend to under-report their revenues, then the resulting estimate of the total revenues will be below the true population total. Any such biases are not reflected in the estimates of standard error.

Estimation

Since the sample is selected in two steps, the sampling weight is also calculated in two steps. The first-stage sampling weight is calculated for each carrier in the first-stage sample. Then the second-stage sampling weight is calculated for each shipment selected from the carrier in the first-stage sample. Finally these two weights are multiplied together to obtain the final weight. The weighted values obtained by multiplying the final weights and the collected values are aggregated to produce the estimates.

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

The survey methodology changed over the time. The methodology described is the current one used for the survey, which has been implemented for the reference year 1997.

Time series analysis would require consistent and comparable data over the time. The data series of this survey have been subject to break in the series due to methodology changes that occurred. Please reach the contact people of the survey to get copy of the previous survey methodology.