Gross Domestic Product by Industry - National (Monthly) (GDP)

Gross Domestic Product by Industry - National (Monthly) (GDP)
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Detailed information for September 2025

Status:

Active

Frequency:

Monthly

Record number:

1301

The purpose of this statistical program is to provide information for current economic analysis. It provides a measure of the economic production which takes place within the geographical boundaries of Canada from an industry point of view.

Data release - November 28, 2025

Description

The primary mandate of the Monthly Gross Domestic Product (GDP) by Industry program (MGDP) is to compile current measures of gross value added (GVA) by industry at the national level on a monthly basis. The value added of an industry equals the value of its output minus the value of its intermediate consumption of goods and services. GDP by industry at basic prices is the sum of the values added by all resident institutional units in Canada and is a measure of economic production within the geographical boundaries of Canada.

GDP at basic prices is also defined as the sum of wages and salaries, employers' social contributions, gross mixed income, gross operating surplus, and taxes less subsidies on production other than taxes and subsidies on products. 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. MGDP estimates are compiled for 174 detail-level industries, using the North American Industry Classification System (NAICS) Canada 2022 Version 1.0 as a basis. An additional 75 aggregates are compiled to provide a variety of levels of detail useful for analysis of industrial economic performance.

The MGDP program provides a measure of the economy that supplements the income- and expenditure-based GDP estimates, and helps policymakers monitor the evolution of the Canadian economy on a monthly basis, formulate policies to guide this evolution, and decide on the timing of their implementation.

Statistical activity

The Canadian System of Macroeconomic Accounts provides a conceptually integrated framework of statistics for studying the state and behaviour of the Canadian economy. The accounts are centered on the measurement of activities associated with the production and consumption of goods and services, the income generated through that production, the supporting financial transactions, and the resulting wealth positions. More information can be found in User Guide: https://www150.statcan.gc.ca/n1/en/catalogue/13-606-G.

Reference period: Month

Subjects

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

Data sources and methodology

Target population

The target population is all resident institutional units involved in the economic activity of producing goods and services.

The observed population consists of all establishments in Canada. The establishment is the level at which the accounting data required to measure production are available. The establishment, as a statistical unit, is defined as the most homogeneous unit of production for which a household, business or government maintains accounting records from which it is possible to assemble all the data elements required to compile the full structure 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 type does not apply to this statistical program.

Sampling

This methodology type does not apply to this statistical program.

Data sources

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

For example, data from the Monthly Survey of Manufacturing are used as indicators for most manufacturing industries. Data from the Survey of Employment, Payrolls and Hours are used for many service industries. A more complete list of sources and methods by industry may be found in National monthly gross domestic product by industry, summary of methods and data sources(https://www.statcan.gc.ca/en/statistical-programs/document/1301_D1_V6).

This large amount of information is compiled, integrated, and analyzed as part of the process of arriving at MGDP estimates.

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.

Imputation

This methodology type does not apply to this statistical program.

Estimation

Annual estimates of Gross Domestic Product (GDP) at basic prices (or value added) by industry can be measured directly from the benchmark Supply and Use Tables 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.

Constant price estimates of GDP by industry measure economic growth of industries with the effect of price variations removed. Annual 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 are derived annually within the framework of the Supply and Use tables, and for all but the most recent two or three years. For the years following the most recent Supply and Use tables, and for the monthly estimates, real GDP by industry can be estimated by 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 this relationship significantly.

To estimate the real value added of an industry on a monthly basis, 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 Supply and Use 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. A document containing an up-to-date summary of the data sources and methods used for compiling monthly national estimates of GDP by industry is included below in the documentation section.

Real measures of GDP by industry are calculated for individual industries and then aggregated to arrive at total economic growth. The monthly gross domestic product (GDP) by industry data are chained volume estimates with 2017 as their reference year. This means that the estimates for each industry and aggregate are obtained from a chained volume index multiplied by the industry's value added in 2017. The monthly estimates are benchmarked to annually chained Fisher volume indexes of GDP obtained from the constant-price supply and use tables. For the period starting with January 2023, the estimates are derived by chaining a Laspeyres volume index at 2022 prices to the prior period. This makes the monthly GDP by industry estimates more comparable with the expenditure-based GDP data, which are chained quarterly.

Quality evaluation

Data at the detailed industry level are analyzed and verified for outliers, source data issues, time series consistency, links to current economic events, and coherence with related economic indicators not directly used in the derivation of the GDP estimates.

Every quarter, the MGDP estimates are confronted with estimates of expenditure-based GDP, which is compiled using different sources and methods. Each compilation approach has its strengths and weaknesses. Thus, the robustness and quality of macroeconomic statistics are improved through the combination and comparison of different data sources and different measurement methods.

Disclosure control

Statistics Canada does not release collected information 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.

MGDP estimates are derived from the SUTs, which contain no suppressions for confidentiality. It has been determined that the distance between respondent information obtained from business surveys and administrative data and the aggregating structure and the conceptual and statistical measurement framework underlying the compilation of the SUTs is sufficiently large such that they mask the information provided by respondents and negate the need for data suppressions.

Revisions and seasonal adjustment

Revisions arise from the incorporation of new benchmark data and updates to indicators, methodologies, and seasonal adjustment factors. The revision policy for the January to August reference months is to revise back to January of the previous year; for the September reference month, back to January of the fourth previous year; and for the October to December reference months, back to January of the current year. Comprehensive revisions are carried out occasionally. More information on revisions can be found in Revisions to Canada's GDP.

MGDP uses the X-12-ARIMA seasonal adjustment method to seasonally adjust its time series. Monthly data are adjusted to reflect variation in the number of trading days within each month, and seasonal adjustment factors are applied to derive the seasonally adjusted data. Any trading day adjustments generated by the X-12-ARIMA method 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

MGDP monthly estimates are anchored to the annual SUTs, which are only available almost three years after the end of a reference year.

MGDP estimates are the timeliest measure of Canadian GDP and include an advance (flash) estimate in addition to the regular estimate of real GDP on a monthly basis. The flash estimate is published one month after the reference month, whereas the regular estimate is published through the regular monthly release 60 days after the end of the reference month. The MGDP program uses projectors based on data that are collected from monthly surveys and administrative sources to develop production indicators to estimate value added by industry. Due to time constraints, such monthly surveys by their nature have a smaller sample size than their annual counterparts. They also collect fewer key variables such as sales or labour inputs, whose growth rates may be correlated but not necessarily equal to those of value added.
There is therefore a trade-off between timeliness and accuracy. Monthly indicators are timely, but do not have the same level of accuracy as the data sources used to compile the SUTs. As more data becomes available, MGDP estimates are updated and become more accurate. The data are deemed most robust when the SUTs are available, almost three years after the first estimates of MGDP.

Source data accuracy is periodically assessed through regression analysis and other means to ensure the indicators remain reasonable estimators of their target variables.

It is not possible to calculate a direct measure of the margin of error in the GDP estimates due to the integrative nature of GDP estimation, which depends on various data sources and methods. The reliability of data sources used to estimate MGDP varies and depends on factors such as sample size, response rates, and collection method, resulting in different coefficients of variation. All such information is taken into consideration when evaluating data quality while making subject matter based expert judgment for MGDP projections. Furthermore, in general, the higher the level of aggregation, the more reliable are the estimates.

In addition, as the MGDP estimates are benchmarked to the volumes derived from the latest SUTs, the quality of these volume estimates has a direct influence on the quality of the MGDP estimates.

Documentation

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