Annual Survey of Service Industries: Automotive Equipment Rental and Leasing

Detailed information for 2010

Status:

Active

Frequency:

Annual

Record number:

2442

This survey collects the financial and operating data needed to develop national and regional economic policies and programs.

Data release - February 2, 2012

Description

This annual sample survey collects data required to produce economic statistics for Automotive Equipment Rental and Leasing industry.

Data collected from businesses are aggregated with information from other sources to produce official estimates of national and provincial economic production for this industry.

Survey estimates are made available to businesses, governments, investors, associations, and the public. The data are used to monitor industry growth, measure performance, and make comparisons to other data sources to better understand this industry.

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 survey is part of the Service Industries Program. The survey data gathered are used to compile aggregate statistics for over thirty service industry groupings. Financial data, including revenue, expense and profit statistics are available for all of the surveys in the program. In addition, many compile and disseminate industry-specific information.

Reference period: Calendar year

Subjects

  • Business, consumer and property services
  • Business performance and ownership
  • Financial statements and performance
  • Rental and leasing and real estate

Data sources and methodology

Target population

The target population consists of all statistical establishments (sometimes referred to as firms or units) classified as Automotive Equipment Rental and Leasing (NAICS 5321) according to the North American Industry Classification System (NAICS) during the reference year. The Automotive Equipment Rental and Leasing sector covers two NAICS: Passenger Car Rental and Leasing (NAICS 53211) and Truck, Utility Trailer and RV (Recreational Vehicle) Rental and Leasing (NAICS 53212).

The Automotive Equipment Rental and Leasing survey comprises establishments primarily engaged in renting or leasing vehicles, such as passenger cars; passenger vans, trucks, truck tractors, buses, semi-trailers, utility trailers and RVs (recreational vehicles), without drivers. These establishments generally operate from a retail-like facility, some offer only short-term rental, others only longer-term leases, and some provide both type of services.

The financing arm of the Automotive Equipment Rental and Leasing industry is excluded from this survey. Data for these companies are found in NAICS 52222 because of their sales financing activities.

Instrument design

The survey questionnaire contains generic modules designed to cover several service industries. These include revenue, expense, and employment modules. In order to reduce respondent burden, smaller firms receive a characteristics questionnaire (shortened version) which does not include the revenue and expense modules. For smaller firms, revenue and expense data are extracted from administrative files.

Sampling

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

The survey design was based on probability sampling and only covered the portion of the frame subject to direct data collection.

The basic objective of the survey is to produce estimates for the whole industry -- incorporated and unincorporated businesses. The data come from two different sources: a sample of all businesses with revenue above or equal to a certain threshold (Note: the threshold varies between surveys and sometimes between provinces in the same survey) and administrative data for businesses with revenue below the specified threshold. It should be noted that only financial information is obtained from administrative sources; e.g., revenue, expenses such as depreciation and salaries, wages and benefits. Characteristics such as client base and revenue by type of service are collected only for surveyed establishments.

The frame is the list of establishments from which the portion eligible for sampling is determined and the sample is taken. The frame provides basic information about each firm including: address, industry classification and information from administrative data sources. The frame is maintained by Statistics Canada's Business Register and is updated using administrative data.

Finally the sample size is increased, mostly to compensate for firms that no longer belong in the industry: i.e., they have gone out of business, changed their primary business activity, they are inactive or are duplicates on the frame. After removing such firms, the sample size for 2010 was 312 collection entities.

Data sources

Data collection for this reference period: 2011-02-06 to 2011-08-06

Responding to this survey is mandatory.

Data are collected directly from survey respondents and extracted from administrative files.

Data are collected through a mail-out/mail-back process, while providing respondents with the option of telephone or other electronic filing methods.

Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period.

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

Error detection

Data are examined for inconsistencies and errors using automated edits coupled with analytical review. Every effort is made to minimize the non-sampling error of omission, duplication, reporting and processing. Several Checks are performed on the collected data. These checks look for internal consistency such as the total should equal the sum of the components; if there is a number of employees reported, there should be wages and salaries also reported; the main source of income has to be related to the NAICS code and does not come from the "Other" revenue category; identification of extreme values; etc.

Imputation

Partial records are imputed to make them complete. Data for non-respondents are imputed using donor imputation, administrative data or historical data.

Estimation

As part of the production of final numbers, data for companies operating in more than one province or territory are allocated to the provincial level. Administrative data are used to estimate for the portion of the industry that was excluded from survey activity (i.e. small firms whose revenues fell below cut-off thresholds). Sampled data are then weighted to produce estimates representative of the target population.

Prior to dissemination, combined 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 administrative data (e.g., income tax, goods and services tax, payroll deductions records, industry and trade association sources).

Quality evaluation

Prior to dissemination, combined survey results are analyzed for overall quality; in general, this includes a detailed review of individual responses (especially for the largest companies), an assessment of the general economic conditions portrayed by the data, 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

There is no seasonal adjustment. Data from previous years may be revised based on updated information.

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.

The weighted response rate represents the proportion of the total revenue accounted for by units that responded to the survey. Of the sampled units contributing to the estimate, the weighted response rate was 92%, after accounting for firms that have gone out of business, have been reclassified to a different industry, are inactive, or are duplicates on the frame.

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.

For the Automotive Equipment Rental and Leasing Survey, CVs were calculated for each estimate. Generally, the more commonly reported variables obtained very good CVs (10% or less), while the less commonly reported variables were associated with higher but still acceptable CVs (under 25%). Some data might not be released because of poor data quality. The CVs are available upon request.

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

Report a problem on this page

Is something not working? Is there information outdated? Can't find what you're looking for?

Please contact us and let us know how we can help you.

Privacy notice

Date modified: