Annual Trucking Survey (ATS)

Detailed information for 2010





Record number:


The purpose of this survey is to measure the size, structure and economic performance of the trucking industry and to analyze its impact on the Canadian economy.

Data release - February 16, 2012 (This is the final year for which data are available. The Annual Trucking Survey has been discontinued.)


The Annual Trucking Survey (ATS) is the most complete source of information on the financial performance and characteristics of the trucking industry in Canada. The results are used as inputs to the Canadian System of National Accounts. Federal and provincial governments use the data to formulate policies and to monitor the trucking industry in Canada. Trucking companies and associations use the published statistics for benchmarking purposes.

The survey is a redesigned version of two former annual surveys: the Survey of Small For-Hire Carriers and Owner Operators (SFHOO, record number 2800) and the Annual Motor Carriers of Freight survey (AMCF).

Statistical activity

The Quarterly Trucking Survey (QTS) is the first component of the redesigned trucking financial surveys. It is complemented by an annual survey, the Annual Trucking Survey (ATS), which replaces the annual supplement of QMCF, namely the Annual Motor Carriers of Freight survey, and the Annual Survey of Small For-Hire Carriers of Freight and Owner-Operators.

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: 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

Collection period: March through July


  • Transportation
  • Transportation by road

Data sources and methodology

Target population

The survey covers all businesses located in Canada with at least one establishment classified to "Truck Transportation" according to the North American Industrial Classification System (484 - Truck Transportation (NAICS 2007)) provided that the annual revenue from the trucking establishments is $30,000 or more.

Instrument design

The questionnaire for this survey has been designed starting with the reference year 2009. Although the Annual Trucking Survey (ATS) content is as brief as possible, it is more extensive than the questionnaire for the Quarterly Trucking Survey (QTS, record number 2748). It includes more detailed financial variables and characteristics data in order to obtain a more complete picture of the trucking industry.


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

ATS uses the same sample as the fourth quarter (Q4) of the same reference year of the Quarterly Trucking Survey (QTS), updated to reflect some changes between the fourth quarter survey population and the survey population of the annual survey (e.g., the death of a given unit).

The companies (or clusters of establishments) are first grouped (stratified) by cell (industry group by province/territory). Special reporting arrangement units and companies having establishments in more than one province are flagged as must-take units and are assigned to the must-take stratum within each cell. Also, the smallest units from each cell, representing, in aggregate, 5% of the total estimated annual revenue for that cell, are assigned to the take-none stratum within that cell. For the remainder of the units residing on the frame, stratification boundaries are determined based on cell-level target coefficients of variation (CVs) to sub-stratify each cell by size.

The size classes consist of ranges applied to the measure of size, which is based on estimated annual trucking revenue derived from tax data. For reasons of efficiency, there are five size classes (strata): one must-take stratum, one take-all and/or large take-some, two take-some and one take-none stratum per province and NAICS group.

The sample allocation is then determined using the Generalized Sampling System (GSAM), by province, type of activity (NAICS group) and size class.

Data sources

Data collection for this reference period: 2011-03-09 to 2011-07-03

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

At the end of each year, an ATS questionnaire is sent to each sampled company. The data are collected by mail-out/mail-back, with telephone and fax follow-up. The survey data are captured using an imaging application (KFI or key from image) and checked for errors and inconsistencies. If required, inconsistent, questionable or missing data are referred back to the respondent for clarification or revision.

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

Error detection

The survey data are captured and checked for errors and inconsistencies. If required, inconsistent, questionable or missing data are referred back to the respondent for clarification or revision. Editing is done with the use of the generalized edit and imputation system, Banff.


Fields requiring imputation are imputed using the generalized edit and imputation system (Banff). The system imputes the data using different imputation methods and taking into account criteria such as the size and the activity (NAICS) of the carriers, as well as the type of data to be imputed.


Since only a sample of carriers is contacted, the individual values are weighted to make inferences for the surveyed population. However, the initial design weights of the respondents are adjusted i) to compensate for complete non response, ii) to reflect the contribution of the take-none portion in terms of counts and revenue and iii) calibrated based on auxiliary information available for all units on the frame. Domain estimates and coefficients of variation (CVs) are obtained using the estimation software StatMx.

Quality evaluation

The survey results are analyzed before dissemination. In general, this includes a detailed review of the individual responses (especially for the largest enterprises), a review of general economic conditions as well as historic trends and comparisons with industry averages and ratios.

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.

Non-sampling error is not related to sampling and 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 is 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.

Two weighed response rates are provided in Table 1 (see the link below): the total response rate and the total contribution rate. The higher these rates, the more representative of the population are the published estimate. The total response rate represents the proportion of the revenue of the target population accounted for by the units that responded to the survey. The total contribution rate represents the proportion of the revenue of the target population accounted for by the units that responded to the survey plus those units that did not respond to the survey but were modelled from tax data.

Sampling error occurs because population estimates are derived from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. An important property of probability sampling is that sampling error can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). The assumption is that over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all units in the universe would be less than twice the CV, 95 times out of 100. The range of acceptable data values yielded by a sample is called a confidence interval. Confidence intervals can be constructed around the estimate using the CV. First, we calculate the standard error by multiplying the sample estimate by the CV. The sample estimate plus or minus twice the standard error is then referred to as a 95% confidence interval.

CVs were calculated for each estimate. A coefficient of variation (CV) for total operating revenue at the Canada level is presented in Table 1 (see the link below). CV's for other estimates may be obtained from the Transportation Division upon request. Note that the provided CV estimates do not consider the fact that some of the data were imputed and thus may underestimate the true CV's. The CV and the relative imputation rate should be considered simultaneously to make an assessment of the reliability of an estimate.

The qualities of CVs are rated as follows:

. Excellent 0.01% to 4.99%
. Very good 5.00% to 9.99%
. Good 10.00% to 14.99%
. Acceptable 15.00% to 24.99%
. Use with caution 25.00% to 34.99%
. Unreliable 35.00% or higher


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