Industry productivity database

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• Background
• Improvements to labour input estimates
• Improvements to capital services estimates
• Output and intermediate inputs
• Comparison of the business sector output in the annual and quarterly programs of the Canadian Productivity Accounts
• Multifactor productivity
• Available on CANSIM: tables 383-0021 to 383-0022

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Background

Statistics Canada released a new experimental industry database that, for the first time, provides a series for multifactor productivity (MFP), output and inputs that include capital (K), labour (L), energy (E), materials (M) and purchased services (S) in the new North American Industry Classification system back to 1961. The Canadian Productivity Accounts has developed this KLEMS database using similar methods to backcast each series so that they would be consistent with the methods used by the System of National Accounts.

Previously, the KLEMS database was constructed up to 1997 using the Standard Industrial Classification (SIC) System and since then using the North American Industry Classification System (NAICS). For the purposes of time series continuity, new estimates using the NAICS have been backcast to 1961. In order to do this, industries that had been originally defined using the old SIC system had to be split into parts to reflect the NAICS. This was relatively easy to do in 1997 because most of the source data had been double coded to both classification systems in that year. This allows splitting ratios to be developed for the sources in that year—gross domestic product (GDP) and its components, labour and investment. These splitting factors could also have been used for previous years.  But errors would have been introduced in doing so, unless the components remained relatively similar over time. Unfortunately, the changing importance of industries makes this unlikely. Therefore, the Canadian System of National Accounts decided to use the commodity data that are available in its system of input/output tables to develop changing splitting ratios for output, intermediate inputs, capital income (or gross operating surplus) and labour income over time. These were used to develop GDP estimates, labour and investment that were compatible over time.

The SIC-based investment data for the period 1961 to 1997 have been converted to the NAICS industries with a detailed SIC-NAICS capital income split in the input/output tables developed for the period 1961 to 1997. The capital income split between NAICS and SIC is too volatile for the following four industries: textile and textile products; wood; publishing; and paper and allied products. As such, we have chosen the gross domestic product split for those four industries when converting investment data from SIC to NAICS.

The above procedure for estimating NAICS-based investment series is also adopted for converting labour estimates from SIC to NAICS. The wage/salaries split between SIC and NAICS in the input/output tables is used to convert hours and jobs estimates of paid workers from SIC to NAICS. The mixed income split between SIC and NAICS is used to convert hours and jobs estimates of self-employed workers from SIC to NAICS.

Additional improvements have been made to both the labour and capital estimates in the productivity accounts.

Improvements to labour input estimates

Labour input for multifactor productivity (MFP) measures reflects the compositional shifts of workers by education, experience and class of workers (paid vs. self-employed). The growth of labour input (labour services) is an aggregate of the growth of hours worked by different classes of workers, weighted by the hourly wages of each class.

The assumptions about the share of labour going to the self-employed have been modified to reflect changes that occurred during the 1990s. In the past, it was assumed that the self-employed essentially earned incomes similar to the employed. While the census of population up to 1990 showed this was a reasonable assumption, during the 1990s, self-employed income fell behind that of production workers. The new measure of self-employed for calculating labour input assumes that that the hourly earning of self-employed workers is proportional to that of paid workers with the same level of education and experience. The proportional or scaling factor for each level of education and experience is based on the relative hourly earnings of paid versus self-employed workers derived from the census of population.

Hours worked is also revised to reflect new information on jobs and hours per jobs of the business and non-business sectors. Data on labour input for the non-business sector have been revised to make them more compatible with the GDP estimates for this sector. Non-business gross domestic product (GDP) is estimated primarily from the wages and salaries of this sector—along with a small amount of returns to capital that are measured using estimates of depreciation. In this world, labour productivity estimates should be essentially zero. Previous estimates have used the Labour Force Survey (LFS) to calculate jobs and hours worked in the non-business sector. However, non-business sector GDP is calculated using the Public Institutions Division's (PID) estimate of the public sector employment. The new estimates of the public sector hours worked make use of the Public Institutions Division's estimates along with data from the Labour Force Survey on hours worked per person in the public sector to estimate hours worked in the non-business sector.

With the development of provincial labour productivity accounts, new benchmarks for the level of labour inputs have been developed that were introduced into the KLEMS data base. These benchmarks include changes in the source data (with an increased use of the Survey of Employment, Payrolls and Hours for industry estimates) and changes in the number of holidays built into the hours-worked estimates.

Improvements to capital services estimates

Capital input is measured by the services that flow from the stock of capital.  This differs from the stock of capital sometimes used in productivity measurement because not all forms of capital provide services at the same rate just as not all hours worked provides labour services at the same rate. Short lived assets such as a car or computer must provide all of their services in just the few years before they completely depreciate.  Office buildings provide their services over decades. So in a year, a dollar's worth of a car provides relatively more services than a dollar's worth of a building. Because of differences in capital services between assets, capital input can increase not only because investment increases the amount of the capital stocks, but also if investment shifts toward assets (such as equipment) that provide relatively more services per dollar of capital stock.

The asset detail for capital services estimates in the MFP programs consists of 15 types of equipment, and 13 types of structures, and land and inventories for a total of 30 types of assets.

The capital services measure for the MFP programs of Statistics Canada is based on the bottom-up approach. This bottom-up approach involves the estimation of capital stock by asset, the aggregation of capital stock of various asset types within each industry to estimate industry capital services, and the aggregation of capital services across industries to derive capital services in the business sector and in the aggregate industry sectors.

Improvements have also been made on the capital stock side. Investment is now benchmarked on the estimates of investment included in the input-output tables. New estimates of depreciation have been incorporated into estimates of capital services. A revised methodology is used to measure the stock of land that is included in the capital stock.

Recent studies by Statistics Canada provided new empirical evidence on the rate of depreciations for various types of assets. As a result, we have incorporated those new estimates of depreciation rates in the capital service estimates.

We have revised the procedure for estimating land stock in the capital services. We have adopted the U.S. Bureau of Labor Statistics methodology for estimating land in Canadian industries. The existing procedure essentially assumes that there is no change in the real value of land in the business sector and it then estimates the real value of land at the industry level based on the industry distribution of property taxes. A brief description of the new procedure is presented here.

The nominal value of land in the agriculture and non-farm business sectors is taken from the balance sheet for the sectors (Statistics Canada, CANSIM tables 002-0020 and 378-0004). The real value of land in those two sectors is set to equal an estimate of total area of the dependable agriculture land for cultivation and total area of urban land.

The data on the value of land at the industry level is scarce. In order to estimate the nominal value of land stock of individual industries, we multiply structure capital stock by land-structure ratios. The land-structure ratios are derived from the corporate balance sheets by sectors which provided data on book values of land and structures by industry for the period 1972 to 1987 (CANSIM table 180-0002).

The real value of land at the industry level is estimated by deflating the nominal value of land using the structure capital's deflators. The final estimates of land values at the industry level are benchmarked to the aggregate land stock in the total non-farm business sector.

Output and intermediate inputs

The industry productivity database provides data on chained-Fisher quantity indices and nominal values of output and intermediate inputs for the total business sector as well as for individual industries. Output is valued at basic prices while intermediate inputs are valued at purchaser prices. The output of the total business sector is measured as value-added, while the output at the industry level is measured as gross domestic product (GDP) or value-added, sectoral output and gross output. The previous measure of MFP in the aggregate business sector was based on real GDP at market prices. The real gross domestic product measure at market prices was estimated from final demand side of the Canadian system of national accounts.

The chained-Fisher index of value-added, gross 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.

Comparison of the business sector output in the annual and quarterly programs of the Canadian Productivity Accounts

The output of the total business sector in the annual program of the Canadian Productivity Accounts 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 Canadian Productivity Accounts (see Statistical Program 5042). The output of the total business sector in the quarterly program is based on gross domestic product (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 Canadian Productivity Accounts 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.

Fourth, the imputed rent of owner-occupied dwellings is treated differently in the two estimates of output of the business sector. The imputed rent in the top-down approach does not exclude all of the intermediate inputs, while it does in the bottom-up approach.

Multifactor productivity

The multifactor productivity measures at Statistics Canada are derived from a growth accounting framework that allows us to isolate the effects on labour productivity growth of increases in capital intensity, skills upgrading and intermediate inputs deepening. The residual portion of labour productivity growth that is not accounted for by increased capital intensity, skills upgrading and intermediate input deepening is called multifactor productivity growth. Growth in this area is often associated with technological change, organizational change or economies of scale.

Multifactor productivity in the business sector is based on value-added. It measures the efficiency with which capital and labour inputs are used to generate value-added. It is the ratio of output to combined labour and capital inputs. Multifactor productivity at the industry level is measured using either value-added, sectoral output or gross output. Multifactor productivity based on gross output or sectoral output measures the efficiency with which all inputs including capital, labour and intermediate inputs are used in production. It is the ratio of output to combined units of all inputs.

Available on CANSIM: tables 383-0021 to 383-0022

Table 383-0021 provides a series for multifactor productivity, value-added, capital input and labour input in the aggregate business sector and major sub-sectors, by North American Industry Classification System (NAICS). The table provides the series for the period from 1961 to the most recent year for which annual estimates are possible. Table 383-0022 provides series on multifactor productivity, gross output, value-added, capital, labour and intermediate inputs at a detailed industry level, by North American Industry Classification System (NAICS). The table provides data for period from 1961 to the most recent year of the input-output tables.

With the release of those new tables, the previous tables 383-0013, 383-0014, 383-0015, 383-0016, 383-0017, 383-0018, and 383-0019 on multifactor productivity will be deleted.