Survey of the Taxi and Limousine Services Industry

Detailed information for 2005





Record number:


The survey collects financial and operating data needed to produce statistics for the Canadian taxi and limousine services industry.

Data release - June 13, 2008


The survey results represent fiscal year estimates of financial statistics for the Canadian Taxi and Limousine Services Industry.

Results from this survey provide information on the major categories of revenue and expenses.

The results are used to produce national and provincial / territorial economic production estimates in Canada. They are also used by regulatory organizations to evaluate the financial health of the industry and private sector businesses for industry performance measurement.

Statistical activity

The survey is administered as part of the Unified Enterprise Survey program (UES). The UES program has been designed to integrate, gradually over time, the approximately 200 separate business surveys into a single master survey program. The UES aims at collecting more industry and product detail at the provincial level than was previously possible while avoiding overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content. The unified 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.

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: 12 month fiscal period for which the final day occurs on or between January 1st and December 31st 1998


  • Business performance and ownership
  • Financial statements and performance
  • Transportation
  • Transportation by road

Data sources and methodology

Target population

Classified under the North American Industrial Classification System (NAICS) code 4853, this industry comprises establishments primarily engaged in providing passenger transportation by taxi and limousine, not operated on regular schedules or routes. Taxicab fleet owners and organizations that provide dispatch services are included, regardless of whether drivers are hired, rent their cabs or are otherwise compensated. Owner-operated taxicabs (self-employed drivers) are also included.

Instrument design

Complete questionnaire design was undertaken for the first time with the 1997 survey and reviewed in details with the 1999 survey. Major users and major respondents were consulted. The questionnaire content should not be changed for future years.

This questionnaire satisfies the statistical requirements for financial information as expressed by the national accounts, the Transportation departments and the businesses and association operating in the taxi industry.


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 and extracted from administrative files.

Questionnaires were mailed to establishments selected in the sample and identified as employers on the Business Register. Tax records were used for establishments selected in the sample and identified as non-employers (mostly self-employed owner-operators).

In addition to the mail-out / mail-back questionnaire approach, the survey was also conducted using Computer Assisted Telephone Interviews (CATI) for data collection, capture, edit and follow-up.

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

Error detection

At the collection stage, reported data are examined for completeness and inconsistencies using automated edits coupled with analytical review.


The tax file of incorporated enterprises is passed through an edit and imputation system that balances the financial data. Also, for units not received from Canada Revenue Agency, or with very poor data, donor imputation was used to create a complete and balanced financial statement.


A census of and unincorporated enterprises is obtained from tax data. The values of all incorporated enterprises belonging to a given estimation domain are summed to obtain the estimates. For unincorporated enterprises, we used a statistic model based on the E-file (respondents using electronic declaration) to estimate the share of information not available (respondents using paper declaration). Then, the values of the estimated part (paper respondents) and the received part (electronic respondents) belonging to a given estimation domain are summed to obtain the estimates for unincorporated enterprises (see document "Estimation T1 - SAT-2006"(Oyarzun, 2007)). The final industry estimates are obtained by combining the final estimates for incorporated and unincorporated enterprises.

Quality evaluation

Prior to dissemination, survey results are analyzed for comparability; in general, this includes a detailed review of individual responses (especially for the largest companies), general economic conditions, 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.

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 program, 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 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.

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.

Coefficients of variation (CV) of the final estimates are computed. The quality of the estimates are classified as follows:

* Excellent CV is 0.01% to 4.99%
* Very good CV is 5.00% to 9.99%
* Good CV is 10.00% to 14.99%
* Acceptable CV is 15.00% to 24.99%
* Caution CV is 25.00% to 34.99%
* Unreliable CV is larger than 35.00%

Based on these ratings, the total revenue estimates for the whole industry were judged to be good at the national and provincial/territorial levels.

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