The Small Business Profiles present selected revenue, expense, profit and balance sheet items as well as financial ratios on small business in Canada.
Data release – December 6, 2012
The Small Business Profiles present selected revenue, expense, profit and balance sheet items as well as financial ratios on small business in Canada. These profiles comprise Industry Canada's SME Benchmarking Tool, available on the Internet at
The target population consists of small businesses which are defined as those having annual revenue between $30,000 and $5,000,000. The information is presented by industry using the North American Industrial Classification System (NAICS) to the 6 digit level.
This survey is a census with a cross-sectional design.
This component of the population is defined as all unincorporated businesses on the T1 return file for reference year 2010 such that their annual revenues are between $30,000 and $5 million inclusive, and complete geographical and industrial classifications are available. For reference year 2010, a total of 871,340 units are included.
This component of the population is defined as all incorporated businesses on the T2 Balance Sheet and T2 Income Statement tables maintained by Tax Data Division of Statistics Canada. Therefore a complete census of GIFI schedules for small businesses within the T2 statistical universe file (961,808 businesses) is available, all with complete geographical and industrial classifications.
Data are available on a census basis for both portions of the population.
Data are extracted from administrative files.
The profiles are produced using information extracted from tax returns submitted to the Canada Revenue Agency (CRA) for the corresponding tax year. Tax Data Division of Statistics Canada maintains files that provide income and expenses from self-employment for unincorporated businesses as well as GIFI schedules (Balance Sheets and Income Statements) for incorporated businesses.
Once the data are collected and captured by CRA, they are sent to Statistics Canada where a team of subject matter specialists in tax data processing run edit programs which identify errors, inconsistencies and extreme values. Data that fail to meet predetermined criteria are referred to analysts for the appropriate action. At this stage of corporate processing, all industries are handled in a similar fashion. A second set of edits is also applied to the data after capture to ensure that basic inconsistencies, such as sub-totals not adding to totals, do not appear.
Imputation is the process whereby records with missing data (recipient records) have values assigned based on the data of records with more complete data (donor records).
Imputation of data on unincorporated businesses (T1)
Imputation is done using the "nearest neighbour" method - using matching variables, the donor record determined via appropriate statistical methods to be most like the recipient record is identified and the information from this donor record is trended to the current year level and used. The Matching variables include industry, total revenue and total expenses. Imputation is used in two cases - when a data point reported by a business is judged to fall outside the limits of statistically coherent values or when a business fails to itemize all or part of the information.
Imputation of data on incorporated businesses (T2)
The most common method used to impute missing data from businesses is historical imputation. When possible, data on the Goods and Services Tax (GST) are used. If a business has to be imputed historically and its income for the reference year and the previous year are available in the GST file, a trend is calculated for each record and is applied to the data on the previous year's income. As for expenses, the imputation method used is the expense/income ratio.
After edit and imputation have been completed, since the T1 and T2 data are available on a census basis, no weighting is necessary. Estimation methods are used to calculate the values for each financial variable in each industry, area and revenue grouping combination. Estimates deemed of unacceptable quality, or which violate confidentiality rules, are identified and removed.
The half and quartile boundaries are calculated for each business type by industry and by area. The businesses are ranked from lowest to highest operating revenue. The half boundary will be the total revenue value from the record that lies exactly on the mid-point (0.50). The quartile boundaries will be the total revenue values from the records which lie on the 0.25, 0.50 and 0.75 points. Average data for the expense, balance sheet and other variables are then calculated using only those businesses allocated to each half or quartile group.
An historical trend analysis was carried out at aggregated industry and geographic levels to identify potential issues in the data. Due to definition and methodological changes over time, only extreme values or trends were verified in detail. Internal consistency checks were applied to derived totals and ratios.
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.
Data suppressed due to confidentiality will appear as a lowercase x in the cell in a profile. The revenue ranges will also be a lowercase x in the cell.
The data accuracy activities are carried out by Statistics Canada's Tax Data Division using standard corporate procedures in developing the database that is used by the Statistics Canada Centre for Special Business Projects (CSBP) in creating the SME profiles database.
Quality Indicators are available to provide data users with information on the accuracy of the published estimates.