Financial Performance Data (FPD)
Detailed information for 2022
The Financial Performance Data present selected revenue, expense, profit and balance sheet items as well as financial ratios on small business in Canada.
Data release - October 24, 2023
The Financial Performance Data present selected revenue, expense, profit and balance sheet items as well as financial ratios on small business in Canada. These profiles comprise Innovation, Science and Economic Development Canada's Financial Performance Data, available on the Internet at http://www.ic.gc.ca/eic/site/pp-pp.nsf/eng/home.
Reference period: Calendar year
Collection period: January to December of the following year
- Business performance and ownership
- Financial statements and performance
- Small and medium-sized businesses
Data sources and methodology
The target population consists of small and medium-sized businesses which are defined as those having annual revenue between $30,000 to $5 million and $5 million to $20 million. The information is presented by industry using the North American Industrial Classification System (NAICS) to the 6 digit level.
This methodology does not apply.
This survey is a census with a cross-sectional design.
Data are collected for all units of the target population, therefore no sampling is done.
Data are extracted from administrative files.
This component of the population is defined as all unincorporated businesses on the T1 return file for the reference year whose annual revenues are $30,000 to $5 million, inclusive, and for whom complete geographical and industrial classifications are available.
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 and medium-sized businesses within the T2 statistical universe file is available, all with complete geographical and industrial classifications.
Data are available on a census basis for both portions of the population.
Once the data are collected and captured by CRA, they are sent to Statistics Canada. There, 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 appropriate action. At this stage of corporate processing, all industries are handled similarly. A second set of edits is also applied to the data after capture to eliminate basic inconsistencies, such as subtotals not adding to totals.
Imputation is performed 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 a data point. In both cases, the records requiring imputation (recipient records) are assigned values based on the data of records with more complete data (donor records).
Donor records are selected using the 'nearest neighbour' method: using matching variables, the donor record determined to be most similar to the recipient record is identified. Matching variables included revenue, expenses, and inventory. Additionally, donors are restricted to the same industry group as the recipient records.
Once edit and imputation are complete, no weighting is necessary because the T1 and T2 data are available on a census basis. 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 that violate confidentiality rules, are identified and removed.
The half and quartile boundaries are calculated for each business type by industry and by area. For one set of estimates, 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.
For the other set of estimates, the businesses are ranked from lowest to highest operating profit. The half boundary will be the total operating profit value from the record that lies exactly on the mid-point (0.50). The quartile boundaries will be the total operating profit 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.
Revisions and seasonal adjustment
This methodology type does not apply to this statistical program.
The data accuracy activities are carried out by Tax Data Division using standard corporate procedures in developing the database that is used by the Centre for Special Business Projects to create the Small business profiles database.
Quality indicators were produced to provide data users with information on the accuracy of the published estimates. As the published data are drawn from a census, there is no associated sampling error. The quality indicators are based on the amount of imputation performed on each published data point.