Productivity Measures and Related Variables - National and Provincial (Annual) (MFP)
Detailed information for 2017
The annual multifactor productivity program breaks down the growth in labour productivity into its key determinants: capital intensity (or changes in the amount of capital per hour worked), investment in human capital, and multifactor productivity which includes technological change, organizational innovation and economies of scale.
Data release - March 8, 2019
Productivity measures the efficiency with which resources are employed in economic activity. Annual productivities series are widely watched by analysts, government policymakers and researchers to quantify the extent to which productivity contributes to economic growth and the standards of living over the long-run.
The Canadian Productivity Accounts (CPA) are responsible for producing, analyzing and disseminating Statistics Canada's official data on productivity and for the production and integration of data on employment, hours worked and capital services consistent with the System of National Economic Accounts. To this end, the CPA comprises three programs. The quarterly program provides current estimates on labour productivity and labour costs at the aggregate level for 15 industry groups (see record number 5042). The annual multifactor productivity program provides yearly estimates on multifactor productivity and related measures (output, capital input, labour input and intermediate inputs) as they apply to the major sectors of the economy and to the industry level at the national and provincial levels (see record number 1402). Lastly, the annual provincial program, as an integral part of the provincial and territorial economic accounts, provides estimates on employment, hours worked, labour productivity and labour costs at the industry level for each province and territory (In this issue: record number 5103).
Reference period: Calendar year
Collection period: One year after the reference period
- Economic accounts
- Productivity accounts
Data sources and methodology
Most estimates are only available for the business sector and its constituent subsectors and industries. However, estimates for employment and hours are also available for the non-business sector.
This methodology does not apply.
This methodology does not apply.
Data collection for this reference period: 2018-11-01 to 2018-12-31
Data are collected from other Statistics Canada surveys and/or other sources.
The output of the total business sector in the annual program of the CPA is measured as value-added at basic prices. The value-added at basic prices has been calculated using the 'bottom-up' approach-by aggregating all industries in the business sector. This differs from the output measure of the total business sector in the quarterly program of the CPA (see record number 5042). The output of the total business sector in the quarterly program is based on GDP at market prices. The GDP at market prices has been calculated using the 'top-down' approach-by subtracting several non-business sector components from final demand. These two approaches give slightly different growth rates in the short run but are the same over longer periods of time.
The difference in the output of the total business sector in the annual program and quarterly program of the CPA can be attributed to a number of factors. First, the value-added output of the total business sector in the annual program is valued at basic prices, while the value-added output in the quarterly program is valued at market prices. The difference between value-added at market prices and value-added at basic prices is taxes on products less subsidies on products.
Second, the real value-added calculated using the bottom-up and top-down approach involves the chained-Fisher aggregation of different components. The real value-added based on the bottom-up approach is calculated from the aggregation of industry value-added estimates, while the real value-added based on the top-down approach involves the aggregation of individual components of the final demand. As a result, the two estimates are not identical.
Third, the revision cycle differs for the two estimates of output of the total business sector. The output estimates of the total business sector are preliminary and subject to revision for the period from the most recent year of input-output tables to the reference year for which annual estimates are possible. The output and productivity estimates based on the top-down approach are revised in May of each year, while the output and productivity estimates based on the bottom-up approach are revised in November of each year.
At the industry level, various output measures-gross output, value added and sectoral output, each of which responds to a different analytical need, are employed by the annual program of the CPA. Gross output and value added are produced by the Industry Accounts Division, while sectoral outputs are produced by the CPA for comparability with the United States.
The annual multifactor productivity program is responsible for constructing labour input and capital input data that accord with the CSNA production framework, using various data sources available at Statistics Canada. Other sources on labour and capital input data, available within Statistics Canada, do not completely satisfy this requirement. For more details see the Economic Analysis Methodology Paper Series: National Accounts, available from the online catalogue (no. 11F0026MIE, free).
This methodology type does not apply to this survey.
Unlike labour income data on paid jobs, data on the income of self-employed workers are not available from the Income and Expenditure Accounts Division. The income of self-employed workers is therefore established by imputation. The imputation is based on the assumption that the value of an hour worked by a self-employed worker is equal to a fraction of the value of an hour worked by a paid worker (paid at the average rate) in the same industry. The relative value of an hour worked between self-employed and paid workers is calculated using information in the Census of Population.
The annual multifactor productivity program of the CPA provides data on chained-Fisher volume indices and nominal values of output, capital input, labour input, and intermediate inputs for the total business sector as well as for individual industries. The chained-Fisher index of value-added, gross output, sectoral output and intermediate inputs is estimated from the make and use tables in the input-output accounts of Statistics Canada. It starts with the make and use tables in current and constant dollars, derives implicit price indices for commodity outputs and inputs, and then applies the Fisher aggregation to estimate the chained-Fisher index.
The methodology for the measurement of capital and labour inputs employed by the CPA recognizes that different categories of capital assets and types of workers have different productive characteristics. In the case of capital input, this means that tangible assets have different service lives, depreciation rates, tax treatments and, ultimately, different marginal products. The growth rates of the various capital assets are Fisher-chain-weighted by their corresponding rental prices to derive capital input estimates. The capital assets in the national multifactor productivity measures include machinery and equipment, construction, land and inventories while the capital assets in the provincial measures only include machinery and equipment and construction.
Much like the estimates of capital input, which capture substitution across asset classes, the estimates of labour input used to measure the multifactor productivity incorporate substitution between various types of heterogeneous labour (e.g., workers cross-classified by age, education and experience). The growth rates of the different types of labour are Fisher-chain-weighted by their corresponding wages.
Capital input and labour input are estimated by industry and aggregated at different levels of aggregation using, respectively, capital income and labour compensation share of GDP.
Productivity measures at the industry level are derived from a set of industry accounts. Under this approach, a variety of productivity series at the industry level are constructed using alternate measures of output valued at basic price-value added, gross output and sectoral output-along with their corresponding inputs. Industry data on outputs and inputs permit the construction of bottom-up multifactor productivity measures for major sectors (e.g. services and goods-producing industries) as a weighted average of industry productivity growth rates, where the weights are defined in terms of the ratio of industry current dollar 'output' to the current dollar GDP of the sector considered.
Three criteria are used to evaluate the quality of the estimates:
A. The quality of the data sources including deflators;
B. The nature of breaks (if any) in the series; and
C. The volatility of the series.
The combination of these criteria should be considered as a necessary condition for quality; however, no criterion on its own can be a sufficient condition for quality. Based on these criteria, variables are assigned a quality rating using a three-point scale: 1 - reliable, 2 - fairly reliable, and 3 - unreliable.
A) Quality of data sources and deflators
A variable cannot receive rating 1 (reliable) if:
1) the series in current prices are unreliable (no surveys or administrative sources) because they are based on imputed data; and/or
2) The variable has no appropriate deflator for constructing a reliable series in constant prices.
If the series look "reasonable" despite weaknesses i) and ii) above, it would be given a 2 (fairly reliable) rating. Otherwise, it would be considered unreliable (3) by default.
B) Breaks in the series
A few examples are: macroeconomic or industry-specific shocks whose impact is temporary or permanent; changes associated with the environment within which the industry operates (regulation, etc.); and changes associated with the statistical infrastructure (classification; sources, concepts and methods).
If breaks that affect the series are explicable--in other words, if they are covered by one of the above examples--then the series could receive rating 1 (provided the other quality criteria are satisfied).
If the breaks are not explicable, the series cannot obtain rating 1.
C) Volatility in the series
Does the change in the volatility of series over time suggest a change in cyclical fluctuations or a change in data estimation methods? Economists seem to have reached a consensus: the cyclical fluctuations have been greater since 1973. We therefore expect that the series will show more volatility during the period from 1973 to the present compared with the pre-1973 period but not the reverse.
We should also expect that, in general, estimates of capital would be less volatile than labour estimates. Capital is conceptually a stock, therefore, it changes sluggishly. However, there are times where investment shows discrete changes and, as a result, we might expect to see substantial changes in capital stock.
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.
The CPA use the confidentiality model developed by the Industry Accounts Division. This model uses a method which suppresses sensitive cells.
Data are also suppressed if they have been assigned an unacceptable quality rating.
Revisions and seasonal adjustment
Data for these estimates are revised for the last four years, following the CSNA procedures. Data of the four most recent years are always considered preliminary.
Data for the aggregate business sector and sub-sectors at the national level are deemed to be reliable based on the quality evaluation principles laid out above in the "Quality evaluation" section. For more information see the publication The Statistics Canada Productivity Program: Methodology 2000, which is part of the Canadian Productivity Accounts: Methods and Concepts series (Catalogue no. 15-002-MIE2001001). At the moment, there are no data reliability ratings for the labour productivity measures at the provincial level.
- User Guide for Statistics Canada's Annual Multifactor Productivity Program
A description of the method used to derive productivity measures can be found in the "User Guide for Statistics Canada's Annual Multifactor Productivity Program," as part of The Canadian Productivity Review series (15-206-X) available on our website.
Last review : December 06, 2007.
- User Guide: Canadian System of Macroeconomic Accounts
This guide provides a detailed explanation of the structure, concepts and history of Canada's System of Macroeconomic Accounts.
Last review : June 22, 2018.
- Revisions to the Multifactor Productivity Accounts
The documentation about the revisions to multifactor productivity growth estimates can be found in "Revisions to the Multifactor Productivity Accounts," as part of The Canadian Productivity Review series (15-206-X) available from our website.
- Date modified: