Quarterly Survey of Financial Statements (QSFS)

Detailed information for third quarter 2016





Record number:


Information collected as part of the Quarterly Financial Statistics for Enterprises program provides data used to measure the financial position and performance of incorporated businesses by industry aggregations. It also provides information on financial holdings and transactions in the Canadian System of Macroeconomic Accounts (CSMA) sector accounts.

Data release - November 24, 2016


The data collected by the Quarterly Financial Statistics for Enterprises program comprise financial statements prepared by incorporated businesses to record their financial position and performance. The data include asset, liability and equity items encompassed in a quarterly balance sheet, revenue and expense items as reported on a quarterly income statement and elements of Other Comprehensive Income along with additional supplementary items.

Information collected under the Quarterly Financial Statistics for Enterprises program serves two broad objectives. The first measures the financial position and performance of incorporated businesses by industry aggregations. The statistics are used by a wide variety of economists and industry analysts, including federal and provincial regulatory bodies that monitor financial and other institutions in Canada. This information is also a critical input into the measure of corporate profits and capital consumption allowances in the Canadian System of Macroeconomic Accounts (CSMA).

The second broad objective is to provide information on financial holdings and transactions in the CSMA sector accounts. The accounts comprise the National Balance Sheet Accounts and the Financial Flow Accounts. Within the CSMA, the Canadian economy is composed of the financial corporation sector, the non-financial corporation sector, the general governments sector, the non-residents sector, the household sector and the non-profit institutions serving households sector. The Quarterly Survey of Financial Statements data are combined with additional information for the business and other sectors in order to produce complete economy-wide accounts (Quarterly Financial Statistics for Enterprises) which show the creation and distribution of wealth as well as the financing of economic activity. This is made possible by presenting considerable detail on financial institutions within the sector accounts framework.

In addition, the flow of funds and outstanding positions between Canadian residents and non-residents is measured in Canada's Balance of International Payments and in Canada's International Investment Position, respectively. Both of these releases make use of the Quarterly Financial Statistics for Enterprises program data in measuring corporate financial activity with non-residents.

Reference period: Quarter

Collection period: 30 days after the end of the quarter


  • Business performance and ownership
  • Financial statements and performance

Data sources and methodology

Target population

The statistical unit used in this survey is the enterprise. An enterprise can be a single corporation or a family of corporations under common ownership and/or control, for which consolidated financial statements are produced.

In the case of simple enterprises, the enterprise and the establishment coincide and both are classified to the same industry. However, there exist many multi-establishment enterprises whose establishments may belong to one or more industries. Such enterprises are classified to the predominant industry of their establishments. For example, a petroleum enterprise may be involved in exploration, mining, refining, shipping and retailing of petroleum products. Under NAICS, such an enterprise is classified to the individual NAICS code that relates to the activity that provides the most value-added.

The target population for the program is incorporated financial and non-financial business enterprises operating in the Canadian economy. They amount to roughly 1.5 million enterprises. Excluded are business enterprises controlled by governments, non-profit enterprises and the industry of management of companies and enterprises.

The target population consists of two components: a sampled portion and a non-sampled portion. The sampled population is determined through the use of thresholds - asset and operating revenues thresholds for non-financial enterprises; asset thresholds for financial industries. The sample target population captures the largest enterprises within an industry. The size of the sample target population is roughly 25,000 enterprises.

Instrument design

The survey questionnaires comprise financial statements typically prepared by incorporated businesses. Corporate activities across the economy are extremely diverse, resulting in the utilization of a variety of unique financial reporting variables. To accommodate the diversity in financial reporting across all industries, 14 different questionnaires are used. The majority of items on the questionnaires have remained unchanged for several years. However, periodically situations arise necessitating the modification of questionnaires. These changes are proposed through a review committee and are field tested with respondents and data users to ensure that the changes are reasonable and sustainable. Once a final version of the revised questionnaire is approved, the revision date of the form is updated.


This is a sample survey with a cross-sectional design.

The frame used for sampling purposes is Statistics Canada's Business Register (BR). A stratified random sample is drawn from this frame based on the size of the unit as measured by assets and by operating revenues for the non-financial industries and assets only for the finance and insurance industries.

Sample results are multiplied by a weighting factor to represent the survey population from which the sample was drawn. The sampling weight is based on the probability of the unit being selected in the sample.

For businesses below the sampling threshold (the non-sampled portion), estimates are derived by applying the quarter to quarter movement of sample responses to annual data compiled from Canada Revenue Agency financial statements. These estimates are referred to as take-none estimates as they are derived from administrative data. The model projects the value of the take-none portion of the population by the most detailed industry aggregation using estimates from the surveyed population and other parameters.

The total sample size is approximately 6,000 enterprises.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents, extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.

Administrative tax data are used for the non-survey portion. Company financial statements and online data sources are used as supplemental information to help address non-response.

The survey is collected on a quarterly basis. Survey questionnaires are sent to the sampled enterprises approximately one week prior to the quarter-end. The survey is directed to the financial reporting department to be completed.

The objective of the survey is to cover a calendar reference period (i.e., quarters ending in March, June, September or December). However, the data collected for each enterprise usually cover fiscal quarters (which may not coincide with calendar quarters). Estimates for a calendar quarter are prepared by combining individual data for enterprises with different fiscal quarters. The calendar period is estimated by including all of the fiscal quarters ending in the calendar quarter. For example, the estimates for the second quarter include all fiscal quarters ending in either April, May or June.

The respondent has 30 days after the end of the quarter to complete and return the questionnaire to Statistics Canada. Follow-up on non-reporters is done throughout the collection period.

View the Questionnaire(s) and reporting guide(s).

Error detection

Most reporting and data entry errors are corrected through the application of data editing procedures. This is the application of checks to detect missing, invalid or inconsistent entries or to point to data records that are potentially in error. Some of these edits involve the adherence to basic accounting principles. In addition, collected data are also checked against historical data, at the aggregate level, as well as against other sources of related data and information.


Units which do not respond in the current period are imputed, that is, their characteristics are estimated. For those units for which partial data have been collected, these partial data are used to estimate the missing data for the unit. For those units for which no current data have been collected, but for which historical data exist, these historical data, taken in conjunction with current economic conditions, are used to calculate current-period estimates. For those units for which no current data have been collected, and for which no historical data exist, a donor imputation system is used. That is, estimates are created based on information from a similar-sized respondent.


Estimates of aggregate corporate balance sheet and income statement items are produced using a blend of survey data, administrative data and publicly available information. The survey data represent the sample portion of the program, while the non-sample portion is derived using the administrative data.

The proportion of the financial estimates derived from the survey component varies by industry, ranging from 5% to 100% for both revenue and assets items.

Quality evaluation

A process of reconciliation is used to ensure that the quarterly series is consistent with the levels of the annual Financial and Taxation Statistics for enterprises program (AFTS). The AFTS is based on a census of information from surveyed and administrative sources. Every year, with the release of the first quarter, the quarterly series is reconciled to the most recently available AFTS data.

In addition, the quarterly series is continually evaluated through trend analysis, as well as through comparisons to other data sources, to assess the quality of the data and to ensure consistency.

Disclosure control

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

Revisions to data are processed based on a pre-determined schedule. Each year, with the release of the first quarter estimates, balance sheet and income statement data are first reconciled between our quarterly and annual programs estimates for enterprises common to both. This reconciliation is done for the two-year period starting three years prior to the current quarter as annual data are not yet available for the preceding year. Then the quarterly industry estimates are benchmarked to the annual estimates for that three-year period. Finally, revisions are made to the fourth quarter estimates of the previous year as a result of receipt of new survey data from respondents.

For the second, third and fourth quarter releases, revisions are made to all prior quarter estimates of the current year. So, for the second quarter release, revisions are made to the first quarter estimates of the current year. For the third quarter release, revisions are made to the first and second quarter estimates of the current year. For the fourth quarter release, revisions are made to the first, second and third quarter estimates of the current year.

The seasonal adjustment method used is a computerized ratio-to-moving-average method in widespread use at Statistics Canada. It is based on the U.S. Bureau of the Census Method II, but has some additional features. Beginning with the first quarter of 2009, the Quarterly Financial Statistics for Enterprises series uses X12 ARIMA for "end-point" seasonal adjustment, which recalculates seasonal factors each quarter as more recent data become available.

Series containing no significant seasonality have not been seasonally adjusted. In these cases, the unadjusted series are used in the place of seasonally adjusted data.

Data accuracy

Sample surveys are designed to provide the highest sampling efficiency (the smallest sample that will produce a sampling error of a given size). This optimization is usually performed for only a few variables, limited by the data items that are available at the time of sample design and selection, the resources available, and the complexity introduced by trying to optimize for many variables at one time. The sample used for these statistics was designed to produce a reasonable level of accuracy for assets and revenue by industry group. Consequently, other items in the aggregated financial statements may be less accurately estimated.

A measure of the sampling error is the standard error. This measurement is based upon the idea of selecting several samples, although in reality only one sample is drawn. Sampling variability can also be expressed relative to the estimate itself. The standard error as a percentage of the estimate is called the coefficient of variation (CV), or the relative standard error. Small CVs are desirable, since the smaller the CV, the smaller the sampling variability relative to the estimate. CANSIM table 187-0001, which may be accessed through the "CANSIM" link under the RELATED PRODUCTS tab on this web page, provides CVs for the key variables of this program.

There are no objective measures of non-sampling errors applied to these statistics. However, most reporting and data entry errors are corrected as a result of computer capture and edit procedures applied to the data. This is particularly effective for financial data where accounting relationships are established and balancing is required. However, most financial data collected are derived from audited financial statements resulting in minimal errors and inconsistencies. As well, the Quarterly Financial Statistics for Enterprises utilizes trained accounting staff to review and analyze reported data to minimize the frequency of non-sampling errors.

One source of non-sampling error is the non-response error. There are several measures that can help the user evaluate this type of error, including the response rate.

The response rate is a measure of the proportion of the sample units which have responded in time for inclusion in the estimate. Weighted data response rates consider that units in sample represent more than themselves through weighting factors. Some units contribute more to the estimates than other units when weights are applied. The attached link will provide a summary of the response rates. Additional information on the response rate may be referenced in a footnote in CANSIM table 187-0001, which may be accessed through the "CANSIM" link under the RELATED PRODUCTS tab on this web page.

Starting on January 1, 2011, Canadian publicly accountable enterprises are required to replace Canadian Generally Accepted Accounting Principles (CGAAP) with International Financial Reporting Standards (IFRS) when preparing their financial statements for fiscal years starting on or after January 1, 2011. Canadian private enterprises are required to replace CGAAP by Accounting Standards for Private Enterprises or IFRS. The adoption of new accounting standards by some enterprises since the beginning of 2011 may affect comparability with prior periods.

Quarterly financial statistics for the first quarter 2010 forward are based on the 2012 North American Industry Classification System (NAICS). For the period prior to the first quarter 2010, the financial statistics are based on the 2007 NAICS.

Consult "Additional documentation" section for response rate.

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