Survey of Suppliers of Business Financing
Detailed information for 2000
Status:
Active
Frequency:
Annual
Record number:
2514
The Survey of Suppliers of Business Financing is the result of a commitment made in 1999 by the Government of Canada to improve the information available about the financing of small- and medium-sized enterprises (SME) in Canada.
Data release - January 29, 2002
Description
The Survey of Suppliers of Business Financing is the result of a commitment made in 1999 by the Government of Canada to improve the information available about the financing of small- and medium-sized enterprises (SME) in Canada. Data are collected from the major suppliers of business financing including domestic banks and other banks, credit unions and caisse populaires, finance companies (including some Government Business Enterprises), portfolio managers, venture capital companies, financial funds, insurance companies, and leasing companies. The types of financing covered include debt, factoring and leasing. Business clients are classified by four variables: authorization level, type of instrument used, province or territory, and industry (including a subset for knowledge-based industries).
The survey contributes baseline statistics to the SME Financing Data Initiative (SME-FDI), a partnership with Industry Canada and Finance Canada. Policy makers use the information to determine whether and where financing problems exist in order to assess, identify and improve policy measures. Suppliers of SME financing may use the results to identify areas for improvement or opportunities for profitable SME financing.
Reference period: December 31
Collection period: November to June
Subjects
- Business performance and ownership
- Small and medium-sized businesses
Data sources and methodology
Target population
The universe includes all enterprises that meet either of the following criteria:
· The enterprise, or one of its establishments, has a two-digit NAICS code of either 52 or 53 and the enterprise is incorporated and for-profit.
· The enterprise appears on a list of venture capital units provided to the Business Register for the survey.
Unincorporated and non-profit enterprises are excluded.
The target population is a subset of the universe. The following additional criteria are applied to the universe to create the target population.
· Unless the enterprise appears on the venture capital list, it must have assets of $5 million or more.
· The enterprise, or one of its establishments, must have one of the following 4-digit NAICS codes: 5221 (banks, credit unions, caisses populaires), 5222 (finance companies, factoring companies), 5239 (venture capital companies, portfolio managers), 5241 (insurance companies), 5269 except 526912, 526913, 526914, 526916 and 526981 (financial funds), 5321 (vehicle leasing companies) and 5324 (equipment leasing companies).
Instrument design
The content and design of the survey was developed in consultation with Industry Canada, Finance Canada, twelve respondent organizations (including the Canadian Bankers Association and the Credit Union Central of Canada) and about 25 individual respondents.
Sampling
This survey is a census with a cross-sectional design.
Frame
The frame is the list that identifies the firms classified to the industry in question. The frame is maintained by Statistics Canada's Business Register, using taxation account information (i.e. income tax, goods and services tax and payroll deductions records) submitted to the Canadian Custom & Revenue Agency
Survey Design
Prior to the selection of a random sample, the frame units are grouped in homogeneous groups defined using industrial (NAICS) attributes. Similar quality requirements are targeted for each group which is then divided into four sub-groups called strata: must-take, take-all, large take-some and small take-some.
The take-all stratum includes the largest firms in terms of assets which are selected in the sample with certainty making such units self-representing. The must-take stratum is also comprised of self-representing units that have special attributes: Venture Capital units, Federal Crown Financial Institutions and enterprises where the enterprise's NAICS starts with something other than 5221, 5222, 5239, 5241, 5269, 5321, 5324 but at least one establishment is coded to this activity. Units in the two take-some strata are subjected to a random sample where each sampled firm represents a number of other, similar firms in the industry according to the inverse of their probability of selection.
The resulting sample size for this survey was 3,487 enterprises.
Data sources
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Data are collected through a mail-out/mail-back process for the majority of the units. Approximately one tenth of the population receives an electronic questionnaire which is returned by electronic mail. Follow-ups are conducted via the telephone.
Error detection
Edits are pre-programmed and applied automatically.
Reported data are examined for completeness and consistency using automated editing coupled with analytical review. Extreme values or mandatory items that are left blank are listed for manual inspection and follow-up. Additional edits ensure data coherence in each section of the questionnaire. Units that fail edit are prioritized for follow-up.
Imputation
For partial non-response, imputation is performed using two methods: imputation with historical data for enterprises where historical data are available (with a certain level of quality) and a "nearest neighbour" procedure (donor imputation) using available auxiliary information to substitute the data from a company with similar characteristics. For a given questionnaire, historical imputation is used prior to donor imputation.
Estimation
The design weights, calculated as the inverse of the probability of selection, were slightly increased to represent total non-respondents. The survey data collected from the sample were then weighted to produce estimates representative of the target population.
Quality evaluation
Survey results are analyzed before publication. This includes a detailed review of the individual responses (especially for the largest respondents), a review of general economic conditions as well as historic trends and comparisons with administrative data sources.
Extensive validation of the aggregate data, including analysis of top contributors, is also performed to detect outliers and ensure consistency in the disseminated estimates.
Disclosure control
Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.
The confidentiality of the reported statistics to the survey is protected under the provisions of the Statistics Act. Accordingly, statistics are released in aggregate only, with no potential identification of individually reported information. The confidentiality provisions of the Statistics Act override the provisions of the Access to Information Act to guarantee the confidentiality of reported data of individual respondents.
Revisions and seasonal adjustment
This methodology does not apply to this survey.
Data accuracy
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 88%, 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. Confidence intervals can be constructed around the estimate using the CV's. 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 the 95% confidence interval.
For the 2000 Survey of Suppliers of Business Financing, CVs were calculated for each estimate. Generally, the more commonly reported variables obtained good CVs (15% or less) while the less commonly reported variables were associated with higher CVs. These CVs are available upon request. A letter code is associated to each estimate corresponding to the CV of the estimate, based on the following legend:
Code Description CV Range
A Excellent 0.00% to 4.99%
B Very Good 5.00% to 9.99%
C Good 10.00% to 14.99%
D Acceptable 15.00% to 24.99%
E Use with Caution 25.00% to 49.99%
F Unreliable (50.00%
Documentation
- Survey of Suppliers of Business Financing 2000 - Project Overview
- Date modified: