Survey of the Taxi and Limousine Services Industry

Detailed information for 2000

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

Data release - December 11, 2002

• Description
• Data sources and methodology
• Data accuracy

Description

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

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: Most recent 12 month fiscal period

Subjects

• 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.

• Additional documentation

Instrument design

This methodology does not apply.

Sampling

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

The sampling unit used is the establishments of one enterprise that operate in the same industry and the same province. The sampling unit is referred to as a "cluster of establishments".

Two sources of data are used to derive the estimates:
-a census of incorporated enterprises, using financial data as reported on the Canada Customs and Revenue Agency tax records for which the 1,726 establishments of incorporated enterprises were selected;
-a probability sample of unincorporated enterprises on Statistics Canada's business register, the Central Frame Data Base (CFDB), using financial data as reported on Canada Customs and Revenue Agency tax records (T1 individual income tax returns). In total 1,406 units were selected.

Data sources

Data are extracted from administrative files.

Canada Revenue Agency captures a sample of paper filed returns. Tax Data Division of Statistics Canada extracts the remaining sample from the sub-universe of electronically filed returns.

Error detection

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

Imputation

The sample is passed through an edit an imputation system that balances the financial data. Also, for units that are sampled but not received from Revenue Canada, or units that are received but with very poor data, donor imputation was used to create a complete and balanced financial statement. In total, 24% of the records went through the imputation process for the 2000 reference year.

Estimation

Since only a sample of unincorporated enterprises is collected, the individual values are weighted to represent the entire population of unincorporated enterprises within the scope of the industry. The value for each unincorporated enterprise in the sample is multiplied by its sampling weight, and then the weighted data from all sampled unincorporated enterprises belonging to a given estimation domain are summed to obtain the estimates for unincorporated enterprises. Variance estimates are obtained using the Taylor linearization method.

A census of incorporated enterprises is collected. The values of all incorporated enterprises belonging to a given estimation domain are summed to obtain the estimates for incorporated enterprises.

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

The confidentiality of the reported statistics is protected under the provisions of the Statistics Act. Accordingly, statistics are released in aggregate only, with no potential identification of individually reported information.

Statistics Canada is prohibited by law from publishing any statistics which would divulge information obtained from this survey that relates to any identifiable business without the previous consent in writing of that business. The disclosure of data likely to reveal specific information on the activity of a particular company is systematically and rigorously controlled and regulated to prevent the publication or disclosure of any information deemed confidential.

Standard confidentiality rules are applied to all data appearing in the released tables and on CANSIM. Confidential data are marked with an "X" and related data are suppressed to avoid residual disclosure.

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 excellent at the national level and very good to excellent at the provincial/territorial level in 2000.