Gross Domestic Product by Industry - National (Monthly)

Detailed information for February 2001





Record number:


This activity provides information for current economic analysis, from an industry point of view.

Data release - April 30, 2001


NOTE: The content of record number 1302 - "Gross Domestic Product by Industry - Annual" is included in this description.

This activity provides information for current economic analysis, from an industry point of view. Gross Domestic Product (GDP) by industry at factor cost is a measure of the economic production which takes place within the geographical boundaries of Canada. The term "gross" in GDP means that capital consumption costs, that is the costs associated with the depreciation of capital assets (buildings, machinery and equipment), are included. The production estimates are prepared using the 1980 Standard Industrial Classification (SIC).

The GDP by industry measures serve as a check of the Gross Domestic Product (GDP), income and expenditures, prepared by Income and Expenditure Accounts Division, and as an extension (on a monthly basis) of the System of National Accounts Input-Output Tables.

Statistical activity

The Canadian System of National Accounts (CSNA) provides a conceptually integrated statistical framework for studying the state and behavior of the Canadian economy. The accounts are centered on the measurement of activities associated with the production of goods and services, the sales of goods and services in final markets, the supporting financial transactions, and the resulting wealth positions.

To produce financial statistics, the CSNA measures the economic dimensions of the public sector of Canada, including the financial inter-relationships among the thousands of entities that make up the three levels of government in Canada (federal, provincial and territorial, and local). In order to carry out this program, the CSNA maintains a universe of all public sector entities including their complex inter-relationships.

The Input-Output tables are calculated at the national and provincial and territorial level, but on an annual basis only. They are available about two and half years after the end of the reference year; this is because of the delay in obtaining the needed source data and by the complex nature of producing such a detailed account. As a means of providing more up-to-date information to users for current analysis, two industry-based programs - one producing the country's current monthly GDP figures (record no. 1301), the other annual provincial-territorial estimates (record no. 1303) have been set up. These two programs, which can be viewed as extensions of the I-O tables, use a set of indicators to project the GDP by industry benchmarks from the I-O tables.


  • Economic accounts
  • Gross domestic product
  • Input-output accounts

Data sources and methodology

Target population

The target population consists of all establishments in Canada. The establishment is the level at which the accounting data required to measure production is available. The establishment, as a statistical unit, is defined as the most homogeneous unit of production for which the business maintains accounting records from which it is possible to assemble all the data elements required to compile the full structure of the gross value of production (total sales or shipments, and inventories), the cost of materials and services, and labour and capital used in production.

Instrument design

This methodology does not apply.


This methodology does not apply.

Data sources

Data are collected from other Statistics Canada surveys and/or other sources.

The GDP measures rely heavily on a wealth of information from various areas of Statistics Canada, from other federal departments and agencies, from provincial government departments, and from private industry sources. This large amount of information is compiled, integrated, and analyzed as part of the complex process of arriving at GDP by industry.

For example, data from the Monthly Survey of Manufacturing are used for most (but not all) manufacturing industries. Data from the Survey of Employment, Payrolls and Hours (SEPH) are used for many service industries.

Error detection

Data at the working level industry, the lowest level of industry detail for which GDP estimates are compiled directly, are verified for large month-to-month percentage changes and potential issues arising from source data as well as analyzed for time series consistency, links to current economic events and with respect to coherence with related economic indicators not used in the derivation of the GDP estimates.


This methodology does not apply.


The current price estimates of Gross Domestic Product (GDP) at basic prices (or value added) by industry can be measured directly by summing the factor incomes and depreciation or indirectly by deducting the cost of the intermediate goods and services used in the production process from the value of gross production or output; see Catalogue no. 15-201-X, The Input-Output structure of the Canadian Economy.

Constant price estimates of GDP by industry measure economic growth of industries with the effect of inflation removed. The constant price estimates of GDP are obtained by the double-deflation method, as described in publication Catalogue no. 15F0077G, A guide to deflating the input-output accounts: sources and methods.

Both the current and constant price estimates of GDP by industry however can only be derived annually within the framework of the Input-Output tables, and for all but the most recent two or three years. For the years following the most recent IO tables, and for the monthly estimates, real GDP by industry can only be obtained from projecting the relationship between real gross output and real valued added, which holds over short periods of time. That is, the volume of value added generated from a given volume of output for a specific industry is generally constant over short periods of time, as major technological changes are required to change significantly this relationship.

To estimate on a monthly basis the real value added by an industry, indicators of real output, employment, or real inputs are used to project the relationship between these characteristics and value added, as determined from the deflated Input-Output tables. See the document Catalogue no. 15-547-X, Gross Domestic Product by Industry: Sources and Methods for an overview of the general approach and of the various statistical techniques used in the derivation of monthly GDP. The document Catalogue no. 15-548-X, Gross Domestic Product by Industry: Sources and Methods with Industry Details provides a detailed description of the data sources used for each industry.

Quality evaluation

Data at the working level industry is analyzed for time series consistency, links to current economic events, issues arising from the source data and with respect with coherence. As well, the growth rates of total GDP by industry are compared with the growth rates of total expenditure based GDP (record no. 1901) on a quarterly basis, and divergences are reconciled and minimized.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that 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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

Revisions arise from updates to benchmark data, projectors and seasonal adjustment. The revision policy is to revise back to previous year for the January to June reference months; for the July reference month, back to January of the fifth previous year; and for the August to December reference months, back to January of the current year. Historical revisions are carried out usually once per decade.

Statistical revisions are carried out in order to incorporate the most recent information from surveys, taxation statistics, public accounts, censuses, etc., as well as new methodologies, data sources, concepts or definitions and the annual benchmarking process to the Input-Output Accounts.

The monthly data are adjusted by a factor that reflects variations in the number of trading days within each month to derive the seasonally unadjusted data and by a seasonal adjustment factor to derive the seasonally adjusted data. The seasonal adjustment factors are derived using the X-11-ARIMA method. Any trading day adjustments generated by this program are based not only on the number of days in the month but also on the relative importance of each day of the week.

Data accuracy

The monthly measures are projections of the annual estimates of constant price Gross Domestic Product at factor cost by industry. It is generally true that there are fewer data available to prepare the monthly estimates than to prepare the annual measures and these monthly data are usually not as reliable as the annual data. The relationship between annual and monthly measures in the period for which both are available is used to estimate necessary adjustments to the monthly data in the current period.


  • Latest Developments in the Canadian Economic Accounts
    For further information please refer to "Latest developments in the Canadian economic accounts", Statistics Canada, Catalogue no. 13-605-X.

    The side bar menu of this electronic publication includes: chronology of events, conceptual changes, classification changes, and data revisions.
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