Annual Survey of Service Industries: Commercial and Industrial Machinery and Equipment Rental and Leasing
Detailed information for 2007
This survey collects the financial and operating data needed to develop national and regional economic policies and programs.
Data release - June 22, 2009
This annual sample survey collects data required to produce economic statistics for the Commercial and Industrial Machinery and Equipment Rental and Leasing industry in Canada.
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.
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
- 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 (NAICS) during the reference year. The Commercial and Industrial Machinery Equipment and Rental sector covers three NAICS: 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.
The financing arm of the commercial and industrial machinery and 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.
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 2007 was 474 collection entities.
Data collection for this reference period: 2008-02-29 to 2008-09-28
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).
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.
As part of the estimation process survey data are weighted and combined with administrative data to produce final industry estimates.
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.
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 (73%), but its contribution to the overall industry revenue is only about 12%. 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.
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.
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 89%, 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 2007 Commercial and Industrial Machinery 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
CVs were calculated for each estimate. The CVs are available upon request.