Annual Survey of Automotive Equipment Rental and Leasing

Detailed information for 2003

The survey mandate is to collect financial and non-financial data on the Automotive Equipment Rental and Leasing industry, as defined by the North American Industry Classification System, on an annual basis.

Data release - April 1, 2005

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

Description

The survey objective is the collection and dissemination of data necessary for the statistical analysis of the Automotive Equipment Rental and Leasing industries.

The information from the survey can be used by businesses for market analysis, by trade associations to study performance and other characteristics of their industry, by government to develop national and regional economic policies, and by other user involved in research or policy making.

Statistical activity

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 1997 (NAICS 1997) during the reference year. The Automotive Equipment Rental and Leasing sector covers two NAICS 1997: 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.

• Additional documentation

Instrument design

The survey questionnaires comprise financial characteristics such as revenue, broken down by the sources of revenue; expenses, broken down by operating and non-operating expenses; number of employees and distribution of revenue by type of client. Based on contacts with respondents and data users, some modifications have been incorporated to the questionnaires since 1998 in order to reflect the nature of the industry surveyed. The changes are field tested to ensure that they are reasonable and sustainable.

Sampling

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

The survey design is based on probability sampling and covers that portion of businesses subject to direct data collection.

The basic objective of the survey is to produce estimates for the entire industry -- all the incorporated and unincorporated businesses. The data come from two sources: survey data for sampled businesses with revenue above or equal to a set 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 administrative sources provide only financial information; e.g., revenue, and expenses such as depreciation, and salaries, wages and benefits. Information about characteristics; such as, client base and revenue by type of service is collected for surveyed establishments only.

A list of businesses or frame is maintained by Statistics Canada's Business Register and is updated using administrative data. 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.

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, or they are inactive or duplicates on the frame. After removing such firms, the sample size for 2003 was 234 collection entities.

Data sources

Data collection for this reference period: January 12, 2004 to July 16, 2004

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. The statistical establishment is used as the sampling unit, but selected establishments belonging to the same company and the same industry are aggregated to create a collection entity. This reduces respondent burden and simplifies collection. Therefore, companies with production in more than one establishment are mailed one questionnaire and instructed to report for all Canadian operations.

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

Where information is missing, imputation is performed using a "nearest neighbour" procedure (donor imputation), using historical data where available, using averages based on responses from a set of similar establishments, or using administrative data as a proxy for reported 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

Even though the basic objective of the survey is to produce estimates for the whole industry--all incorporated and unincorporated businesses--not all businesses are surveyed. Rather, a sample is surveyed and the portion eligible for sampling is defined as all statistical establishments with revenue above a certain threshold. (Note: the threshold varies between surveys and sometimes between provinces in the same survey). The excluded portion represents a substantial proportion of the industry in terms of number of establishments (62%), but its contribution to the overall industry revenue is only about 11%. These excluded establishments are accounted for in the final estimates through the use of administrative data. However, only basic information is obtained from administrative sources; i.e., total revenue, expenses, depreciation and salaries, wages and benefits. Detailed characteristics such as client base, revenue by type of service, and detailed expense items are collected only for surveyed establishments.

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 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 response rate for this survey was 77% in reference year 2003.

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. 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%). The CVs are available upon request.