Annual Survey of Commercial and Industrial Machinery and Equipment Rental and Leasing
Detailed information for 1999
The survey mandate is to collect financial and non-financial data on the Commercial and Industrial Machinery and Equipment Rental and Leasing industry, as defined by the North American Industry Classification System, on an annual basis.
Data release - December 18, 2001
The survey objective is the collection and dissemination of data necessary for the statistical analysis of the Commercial and Industrial Machinery and Equipment Rental and Leasing industry.
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.
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
- Business, consumer and property services
- Business performance and ownership
- Financial statements and performance
- Rental and leasing and real estate
Data sources and methodology
The target population consists of all statistical establishments (sometimes referred to as firms or units) classified as Commercial and Industrial Machinery and Equipment Rental and Leasing (NAICS 5324) according to the North American Industry Classification System 1997 (NAICS 1997) during the reference year. The Commercial and Industrial Machinery Equipment and Rental sector covers three NAICS 1997: Construction, Transportation, Mining and Forestry Equipment Rental and Leasing Rental (NAICS 53241), Office Machinery and Equipment Rental and Leasing (NAICS 53242) and Other Commercial and Industrial Machinery and Equipment Rental and Leasing (NAICS 53249).
The Commercial and Industrial Machinery and Equipment Rental and Leasing survey covers establishments primarily engaged in renting or leasing commercial and industrial machinery and equipment, without operator. The types of establishments included in this industry group are generally involved in providing capital/investment-type equipment that clients use in their business operations. These establishments typically serve businesses and do not generally operate a retail-like or store-front facility.
This is a sample survey with a cross-sectional design.
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) .
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.
Prior to estimation, data for companies with production in more than one province or territory were allocated to the provincial level The survey data collected from the sample were then weighted using the inverse of the probability of selection of each sampled unit to produce estimates representative of the target population. Administrative data were used to estimate the portion that was excluded from survey activity (i.e. unincorporated firms and incorporated firms with revenue less than $50,000).
The combined survey results were analyzed before publication; in general this included a detailed review of the individual responses (especially for the largest companies), a review of general economic conditions as well as historic trends and comparisons with tax data information and other administrative data sources (e.g. industry and trade associations).
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.
While considerable effort was made to ensure high standards throughout all collection and processing operations, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: sampling and non-sampling.
Non-sampling errors are 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, mistakes in recording, coding and processing of data are other examples of non-sampling errors.
The response rate for this survey was 62%, after taking into account the fact that some firms were no longer in business, or had changed their primary business activity.
Sampling errors can occur because estimates are derived from a sample of the population rather than the entire population. These errors depend on factors such as sample size, sampling design and the method of estimation. An important property of probability sampling is that sampling errors can be computed from the sample itself by using a statistical measure called the coefficient of variation (CV). Over repeated surveys, the relative difference between a sample estimate and the estimate that would have been obtained from an enumeration of all the units would be less than twice the coefficient of variation, 95 times out of 100. The sample estimate plus or minus twice the CV is referred to as the 95% confidence interval.
For the 1999 Survey of Commercial and Industrial Machinery and Equipment Rental and Leasing, 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%). These CVs are available upon request.