Productivity accounts

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

An increase in the economic participation of women has been identified as a major driver of economic growth, leading to increased interest in supporting the entrepreneurial activities of women. This paper uses newly developed data on the gender of business owners to investigate differences in labour productivity between men-owned, women-owned and equally owned enterprises. This paper uses the Canadian Employer–Employee Dynamics Database (CEEDD).

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The Multifactor Productivity application is an analytical tool that provides custom aggregation and custom tabulation of productivity statistics based on the series in CODR table 36-10-0211. The application permits custom aggregation across industries for all published variables, data transformations such as growth rate calculations, log-transformations and index re-basing, correlation and density analysis and visualization of retrieved outputs. The output values from calculations are available as .csv files. Visualizations can be downloaded as .png files. The data in the application are annual values beginning in 1961 and ending with the most recent data available.

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The COVID-19 pandemic has changed how production occurs in the economy in two ways. One is the full or partial closure of non-essential activities such as travel, hospitality, arts and entertainment, personal services, airlines, etc. The other is the widespread shift from in-office work to working from home. This Insights article depicts labour productivity growth in Canada and its sources by industry during the COVID-19 pandemic in order to examine the implications these changes may have had on the productivity performance of the economy.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

Understanding intangible investments is essential for providing accurate measures of gross fixed capital formation (GFCF), gross domestic product (GDP) and productivity growth, and for understanding the innovation system. Statistical agencies need measures of intangible investment to produce economic statistics on aggregate activity that accurately measure concepts such as GDP, GFCF or savings. The levels of GDP, GFCF and savings will be underestimated to the extent that expenditures are incorrectly classified as intermediate inputs that are fully consumed during the period being measured—and not as investments that are not fully consumed during the period when the expenditures are incurred. Estimates for GDP and productivity growth rates may be similarly underestimated. This paper updates and expands upon the intangible capital estimates presented by Baldwin et al. (2009), who extended already measured intangibles (i.e., research and development [R&D], software, mineral exploration) to include additional asset classes consistent with international research on intangible capital measurement (see Corrado, Hulten and Sichel 2009).

Description: Release published in The Daily – Statistics Canada’s official release bulletin

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Multifactor productivity (MFP) declined in Canada from 2000 to 2009 and then recovered after. The movements in productivity since 2000 have attracted great attention from researchers and policy makers because productivity is important both for economic growth and for improvements in living standards. This paper applies the stochastic frontier framework to decompose each firm’s MFP into two parts: its technological frontier and its technical efficiency. Change in the aggregate technological frontier refers to improvements in the productivity potential of an economy, i.e., the maximum productivity of an economy if all firms are fully efficient. Aggregate technical efficiency reflects the economy’s capacity to achieve that potential. The results of this decomposition can show whether the movements in productivity after 2000 in Canada were mainly the result of changes in the technological frontier and productivity potential or of changes in the technical efficiency.

Description: This table contains 1404 series, with data for years 1961 - 1997 (not all combinations necessarily have data for all years), and was last released on 2009-01-22. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Multifactor productivity and related variables (27 items: Multifactor productivity based on gross output; Multifactor productivity based on value-added; Labour productivity based on value-added; Labour productivity based on gross output ...), Standard Industrial Classification (SIC) (52 items: Agricultural and related services industries; Mining (including milling); quarrying and oil well industries; Fishing and trapping industries; Logging and forestry industries ...).

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The Canadian Productivity Accounts: Data is an electronic publication that contains a series of tables on productivity growth and related variables for the business sector and its 51 major sub-sectors based on the North American Industry Classification System. These tables allow users to have a broader perspective on Canadian economic performance. They complement the information available on CANSIM which offers more detail, particularly at the industry level.

Canadian Productivity Accounts (CPA) are responsible for producing, analyzing and disseminating Statistics Canada's official data on productivity and for producing and integrating data on employment, hours worked and capital services consistent with the Canadian System of National Accounts. To this end, the CPA comprise three programs. The quarterly program provides current estimates on labour productivity and labour costs at the aggregate level for 15 industry groups. The annual national program provides yearly estimates on labour productivity, multifactor productivity and several indicators of sources of growth and competitiveness as they apply to the major sectors of the economy and to the industry level. Lastly, the annual provincial program, as an integral part of the Provincial Economic Accounts, provides estimates on employment, hours worked, labour productivity and labour costs at the industry level for each province and territory.

The Canadian Productivity Accounts: Data covers four series of statistical tables:

Table 1: Output, labour compensation, capital cost and cost of intermediate inputs in current dollars

Table 2: Productivity and related measures

Table 3: Productivity and related measures for the business sector, Canada and United States

Table 4: Productivity and related measures for the manufacturing sector, Canada and United States

Productivity measures the efficiency with which inputs (labour and capital in particular) are utilized in production. Productivity measures can be applied to a single input, such as labour productivity (output per hour worked), as well as to multifactor productivity (output per unit of combined labour and capital inputs). Statistics Canada produces these two main measures of productivity, but other productivity ratios can also be measured (e.g., output per unit of capital services).

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This table contains 2886 series, with data for years 1961 - 2001 (not all combinations necessarily have data for all years), and was last released on 2007-03-06. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Labour productivity measures and related measures (13 items: Real value added; Hours worked for all jobs; Total number of jobs; Annual average number of hours worked for all jobs ...), Industries, by aggregation (222 items: Total economy; special aggregation; Business sector - goods; special aggregation; Business sector - services; special aggregation; Business sector; special aggregation

Description: This table contains 138 series, with data for years 1961 - 2001 (not all combinations necessarily have data for all years), and was last released on 2007-03-06. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Employment measures (2 items: Number of employee jobs; Hours worked for employee jobs ...), Non-business sector industries, by aggregation (69 items: Non-commercial sector industries; special aggregate; Non-commercial sector - goods; special aggregate; Non-commercial sector - services; special aggregate; Agricultural and related service industries; S-level aggregation ...).

Description: This table contains 1998 series, with data for years 1946 - 2001 (not all combinations necessarily have data for all years), and was last released on 2007-03-06. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Labour productivity measures and related measures (9 items: Real value added; Total number of jobs; Annual average number of hours worked for all jobs; Hours worked for all jobs ...), Industries, by aggregation (222 items: Total economy; special aggregation; Business sector - goods; special aggregation; Business sector - services; special aggregation; Business sector; special aggregation ...).

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This paper examines some of the reasons behind the slowdown of output growth relative to employment during 2006. It finds the two have converged frequently in recent years, including most of 2002 and 2003. After reviewing the sources of last year's productivity slowdown by industry, it looks at the negative impact of labour shortages on the quality of labour, especially in western Canada.

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The statistical data of this section are in five subsections. They contain data on national income and expenditure and related aggregates from 1926 to 1976 in series F1-152; on income produced, by industry, from 1919 to 1926 and on gross capital formation from 1901 to 1930 in series F153-182; on the stock of tangible capital from 1926 onwards in series F183-220 and on inventory book values in series F221-224; on real gross domestic product by industry in series F225-240; and on indexes of labour productivity in series F241-294.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Canada and the United States share a deep economic relationship that contributes to most measures of their economic performances having a tight common trend over the long term. However, a notable exception is the increasing disparity in labour productivity growth between the two nations. This article summarizes recent research by Statistics Canada, focusing on the information and cultural services industry and how its competitive intensity relative to the United States has influenced the Canada-U.S. labour productivity growth gap since 2001.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: The COVID-19 pandemic affected the Canadian economy in numerous ways, one of which was changing the relationship between growth in production, and changes in real consumption and real gross fixed capital formation (GFCF). Typically, real consumption and real GFCF are expected to progress similarly to real gross domestic product (GDP), however during the period covered by the COVID-19 pandemic, real consumption and real GFCF grew at a stronger pace than real GDP. This article illustrates how examining real income rather than real production can address this paradox. Specifically, the roles of changes in production (the use of capital, labour and multifactor productivity used to produce real GDP) and changes in non-production sources of real income growth (the trading gain and net income from abroad) are examined.

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Rising wages and prices have characterized 2021 and 2022. Soaring unit labour costs have raised competitiveness concerns. This article examines the relationship between real wages and productivity to see whether real wage growth (growth in real total compensation per hour worked) has lagged behind labour productivity growth in recent years. It examines whether the result is sensitive to differences in the definition of real wages.

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This presentation focuses on labour productivity, a measure of efficiency widely used in conjunction with data on labour costs and profitability to gauge the competitiveness of Canadian businesses.

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The COVID-19 Pandemic has been affecting Canadians’ daily lives since the second quarter of 2020. Production and employment were cut back largely at the beginning in order to slow the spread of this contagious disease, leading to a sharp decline in income and a rise in the unemployment rate. GDP per capita of a country is often used for assessing the standard of living and its cross-country comparisons. Since 2020, Canada’s per capita GDP has averaged -1.3% per year, down from its long-term annual average of 1.2% from 1981 to 2019 and from 1.0% per year from 2010 to 2019. For a better understanding of the sources of Canada’s per capita GDP growth, this article decomposes GDP per capita into labour productivity, work intensity, employment rate, participation rate, and the share of working population. The contributions of these 5 ratios to Canada’s per capita GDP growth are examined.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

An increase in the economic participation of women has been identified as a major driver of economic growth, leading to increased interest in supporting the entrepreneurial activities of women. This paper uses newly developed data on the gender of business owners to investigate differences in labour productivity between men-owned, women-owned and equally owned enterprises. This paper uses the Canadian Employer–Employee Dynamics Database (CEEDD).

Description:

The COVID-19 pandemic has changed how production occurs in the economy in two ways. One is the full or partial closure of non-essential activities such as travel, hospitality, arts and entertainment, personal services, airlines, etc. The other is the widespread shift from in-office work to working from home. This Insights article depicts labour productivity growth in Canada and its sources by industry during the COVID-19 pandemic in order to examine the implications these changes may have had on the productivity performance of the economy.

Description: This product contains articles related to the latest methodological, conceptual developments in the Canadian System of Macroeconomic Accounts as well as the analysis of the Canadian economy. It includes articles detailing new methods, concepts and statistical techniques used to compile the Canadian System of Macroeconomic Accounts. It also includes information related to new or expanded data products, provides updates and supplements to information found in various guides and analytical articles touching upon a broad range of topics related to the Canadian economy.

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This paper describes the evolution of the Multifactor Productivity Program launched at Statistics Canada in 1987 and the improvements made in multifactor productivity measurement since then. The improvements were made in response to developments in the economic literature, better data sources, and the needs of the user community. The paper also summarizes research that uses alternate data and methodologies to assess the accuracy of the Multifactor Productivity Program and to provide insights into areas that traditional international multifactor productivity programs omit. Finally, the paper outlines future directions that are being contemplated to further improve the measurement of productivity at Statistics Canada.

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This report highlights the revisions to the quarterly estimates of labour productivity and associated variables in the business sector resulting from the historical revision of the national gross domestic product by income and by expenditure accounts (NIEA) released on October 1st, 2012.

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Measures of productivity are derived by comparing outputs and inputs. The System of National Accounts (SNA) in Canada provides a useful framework for organizing the information required for comparisons of this type. Integrated systems of economic accounts provide coherent, consistent alternate estimates of the various concepts that can be used to measure productivity.

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Official data from statistical agencies are not always ideal for cross-country comparisons because of differences in data sources and methodology. Analysts who engage in cross-country comparisons need to carefully choose among alternatives and sometimes adapt data especially for their purposes. This paper develops comparable capital stock estimates to examine the relative capital intensity of Canada and the United States.

To do so, the paper applies common depreciation rates to Canadian and U.S. assets to come up with comparable capital stock estimates by assets and by industry between the two countries. Based on common depreciation rates, it finds that capital intensity is higher in the Canadian business sector than in the U.S. business sector. This is the net result of quite different ratios at the individual asset level. Canada has as higher intensity of engineering infrastructure assets per dollar of gross domestic product produced. Canada has a lower intensity of information and communications technology (ICT) machinery and equipment (M&E). Non-ICT M&E and building assets intensities are more alike in the two countries.

However, these results do not control for the fact that different asset-specific capital intensities between Canada and the United States may be the result of a different industrial structure. When both assets and industry structure are taken into account, the overall picture changes somewhat. Canada's business sector continues to have a higher intensity of engineering infrastructure and about the same intensity of building assets; however, it has a deficit in M&E that goes beyond ICT assets.

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This paper provides an overview of the productivity program at Statistics Canada and a brief description of Canada's productivity performance. The paper defines productivity and the various measures that are used to investigate different aspects of productivity growth. It describes the difference between partial productivity measures (such as labour productivity) and a more complete measure (multifactor productivity) and the advantages and disadvantages of each. The paper explains why productivity is important. It outlines how productivity growth fits into the growth accounting framework and how this framework is used to examine the various sources of economic growth. The paper briefly discusses the challenges that face statisticians in measuring productivity growth. It also provides an overview of Canada's long-term productivity performance and compares Canada to the United States - both in terms of productivity levels and productivity growth rates.

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The Canadian Productivity Accounts (CPA) of Statistics Canada maintain two multifactor productivity (MFP) programs.

The Major Sector Multifactor Productivity Program develops the indexes of MFP for the total business sector and major industry groups in the business sector.

The Industry Multifactor Productivity Program or the Industry KLEMS Productivity Program develops the industry productivity database that includes MFP indexes, output, capital (K), labour (L), energy (E), materials (M) and services (S) inputs for the individual industries of the business sector at various levels of industry aggregation. This paper describes the methodologies and data sources that are used to construct the major sector MFP indexes and the industry productivity database (or the KLEMS database). More specifically, this paper is meant to:provide a background of the major sector MFP program and the industry KLEMS productivity program;present the methodology for measuring MFP;describe the data sources and data available from the MFP programs;present a quality rating of the industry KLEMS productivity data; anddescribe the research agenda related to the MFP program.

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This paper examines the various products associated with the quarterly labour productivity program. It outlines the nature of the volatility in the very short-run estimates and examines properties of the revisions made to the estimates of Canadian labour productivity and its components (gross domestic product and hours worked) since the inception of the program in 2001.

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This paper examines the effects of alternative specifications of the user costs of capital on the estimated price and volume indices of capital services. It asks how sensitive the results are to the use of exogenous versus endogenous rates of return, to alternate ways of including capital gains, and to whether corrections are made for tax rates. The paper also examines the effect of the various user cost formulae on the measured multifactor productivity growth.

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This paper generates depreciation profiles for a diverse set of assets based on patterns of resale prices and retirements. In doing so, it explores the sensitivity of estimates of the growth in capital stock and capital services to alternate estimates of depreciation.

In the first instance, survival analysis techniques are used to estimate changes in valuation of assets over the course of their service life. In the second instance, a two-step procedure is utilized that first estimates the discard function for used assets (assets discarded at zero prices) and then uses the resulting estimates to correct for selection bias that arises when just positive used-asset prices are employed to estimate age-price profiles to produce depreciation rates. For the third method, a discard function and an asset efficiency function are jointly specified and estimated.

These three different methods produce depreciation profiles that follow convex patterns. Accelerated profiles are apparent for many individual assets in the machinery and equipment and structures classes.

We also compare the ex post estimates of length of life that are based on outcomes to ex ante expected lives and find they are much the same. We therefore choose ex ante lives along with information from the ex post rates on the rate of decline in an asset's value to generate a set of depreciation rates for use in the productivity accounts.

We then use our depreciation model to produce estimates of the growth in capital stock and capital services over the 1961 to 1996 period. We find that the resulting estimates of capital stock and capital services are quite similar to those previously produced.