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Concepts

Australian System of National Accounts: Concepts, Sources and Methods
Reference period
2020-21 financial year

Labour productivity

19.11    Labour productivity is defined as a ratio of some measure of output to labour input; that is, output per unit of labour. Labour productivity is usually expressed in terms of growth rate.

19.12    Labour productivity is widely used for making historical, inter-industry and inter-country growth comparisons. Furthermore, labour productivity is often regarded as an indicator of improvements in living standards as growth in labour productivity has a close long-term relationship with growth in labour earnings.

19.13    Labour productivity has a close relationship to multifactor productivity. In the growth accounting framework, growth in labour productivity can be decomposed into growth in capital deepening (the ratio of capital to labour), growth in labour quality and growth in MFP. More detail is provided in Annex 19B.

Capital productivity and capital deepening

19.14    Capital productivity is defined as a ratio of some measure of output to capital input; that is, output per unit of capital. Obviously, changes in this ratio can also reflect technological changes, and changes in other factor inputs (such as labour).

19.15    The measure of capital input used by the ABS in its estimates of capital productivity is the flow of capital services coming from the stock of capital and most assets are estimated using the Perpetual Inventory Method (PIM). They are calculated by weighting chain volume measures of the productive capital stock of different asset types together using their rental prices in the weights. Rental prices can be regarded as the 'wages' of capital.

19.16    Capital deepening (or capital intensity) refers to changes in the capital to labour ratio. Increased capital deepening means that, on average, each unit of labour has more capital to work with to produce output, so is an indicator of ability to augment labour. Labour saving practices, such as automation of production, will result in increased capital deepening, which is often associated with a decline in capital productivity. Thus, growth in capital deepening is an important driver (alongside MFP) of labour productivity growth. It may not be very useful to interpret declines in capital productivity in isolation since declines in capital productivity can be more than offset by labour productivity (resulting in MFP growth).

Multifactor productivity

19.17    MFP is defined as a ratio of some measure of output to a combined input of multiple factors, such as labour and capital. In empirical analyses, it is expressed in terms of growth rate; that is, growth rate of output minus the growth rate of inputs. 

19.18    At the aggregate and industry level, MFP is defined as the ratio of real value added to the combined inputs of capital and labour. At an industry level, MFP is also measured as the ratio of gross output to the combined inputs of capital, labour, and intermediate inputs.

19.19    In the productivity measurement literature, gross output based MFP is a preferred measure at a disaggregated level, as it requires less restrictive assumptions (see Jorgenson et al., 2005 and Diewert, 2008).⁷⁴ Ideally, MFP measures disembodied technical change attributable to improved use of factor inputs. In the case of gross output, this efficiency can be attributed to improvements in not only the use of primary inputs, capital and labour, but also in the use of intermediate inputs.

The KLEMS growth accounting framework

19.20    The KLEMS growth accounting framework is a useful tool in addressing the challenge of developing more detailed industry performance indicators for the formulation and evaluation of policies involving long–term growth, efficiency and competitiveness. It provides, through a more detailed statistical decomposition, more information on the inputs contributing to output growth, and production efficiency. This helps policy makers and economists to identify factors associated with economic growth, such as structural changes in industry’s input mix, particularly with regards to the relative contribution from the intermediate inputs. This also facilitates a more disaggregated analysis of the industry origins of aggregate productivity growth, such as changes in the relative importance of input components over time.

19.21    Within intermediate inputs, the classification into energy (E), materials (M) and services (S) is beneficial in that they have distinctively different roles in the production process. This helps in evaluating trends in the way industries interact. One key interaction is that the intermediate input components reflect renting, hiring and out-sourcing between industries. An industry’s reliance on primary inputs relative to intermediate inputs may change due to changes in leasing and hiring arrangements rather than the productive process itself. When capital is rented under an operational lease arrangement from a firm in another industry, the use of the capital is classified as an intermediate input of the lessee. For example, a construction company may lease a crane from the rental and hiring industry, which is recorded as a service component in the intermediate inputs of the lessee and as capital services by the lessor in the rental and hiring industry.

19.22    The intermediate inputs indices for energy, materials and services and their respective shares are sourced from the Supply Use tables (SUT) compiled by the ABS. The main advantage of deriving the indices and shares for energy, materials and services using this method is to control for heterogeneity in both the prices and volumes of the components and to recognise more explicitly that the way in which each of these components contributes to production differs. A key development in the SUT has been the wider application of the double deflation method, that is, real output and real intermediate inputs are derived separately for most industries. By sourcing more specific price deflators, the approach enables improved volume estimation, particularly for intermediate inputs.

Measured productivity and technical progress

19.23    It is useful to distinguish between measured productivity and technical progress in productivity analysis. Productivity statistics aim to measure technical progress or the efficiency of production. In practice, productivity changes are measured by the difference between the growth in the volume of output and the growth in the volume of inputs, reflecting more than just technical progress. Year-to-year changes also contain 'noise' that is distinct from the notion of technical progress; it is therefore advisable to examine productivity changes over an extended period to look through some of the short-term volatility.

19.24    Although, from a conceptual standpoint, MFP can be interpreted in various ways, a key interpretation of MFP is as disembodied technological change attributable to improved use of factor inputs. Embodied technological change represents advances in the design and quality of new capital and intermediate inputs. Disembodied technological change is generally interpreted as representing costless improvements or knowledge, for example, network effects or spillovers from diffusion of publicly available R&D, and benefits to factor inputs from organisational change or better management. These spillovers and other benefits to factor inputs are generally not quantifiable within the KLEMS growth accounting framework.

19.25    At the industry level, ABS publishes both gross output-based MFP and value added-based MFP – they are complementary. One advantage of the gross output-based MFP approach is that it is a natural output concept⁷⁵ and consistent with the traditional production theory linking output to primary as well as intermediate inputs. By comparison, the value added-based MFP approach assumes that the components of value added are separable from that of intermediate inputs.⁷⁶ ⁷⁷

19.26    For a given industry, the relationship between changes in gross output-based MFP and value added-based MFP can be approximated by:

    \(\large \Delta \ln GO\;MFP_i^{} \approx \frac{{V{A_i}}}{{G{O_i}}}\Delta \ln VA\;MFP_i^{}\)                                                                                                         

where \(\small{\frac{{V{A_i}}}{{G{O_i}}} , \Delta \ln GO\;MFP , \Delta \ln VA\;MFP}\) are the two period average of the ratio of nominal industry value added to nominal industry gross output, rate of change in gross output-based MFP, and rate of change in value added-based MFP, respectively.⁷⁸ Since this ratio is always less than unity, gross output-based MFP will always have less amplitude than value added-based MFP, i.e. rise less and fall less. However, the degree to which they differ varies from industry to industry, due to both the variation in each industry’s relative value-added proportion, as well as the degree to which the ratio changes over time.  At an aggregate level, the value-added concept is more appropriate as it removes inter–industry transfers.

19.27    In interpreting MFP, it should be noted that measured productivity growth could include factors other than technological change, for example adjustment costs, cyclical effects and measurement errors.⁷⁹ A limitation of MFP theory is that the assumptions of the neoclassical models do not necessarily hold in practice, which can affect the interpretation of the resulting estimates. For example, imperfect competition can result in gains from increasing market dominance being reflected as productivity gains. Additionally, in static models of production, such as the one used in estimating KLEMS MFP, capital is an exogenous input, which ignores dynamic feedback between MFP and capital. For example, if technological change increases output per person, the additional output per person may lead to further savings and investment and thus a rise in the capital–labour ratio. While traditional growth accounting identifies this induced effect as the contribution of capital growth, the effect can be attributed to an initial shift in technology. Therefore, MFP measures may understate the importance of productivity growth in contributing to output growth.

19.28    The methodology used in compiling the estimates implicitly assumes that the proportion of capital stock used in production (capital utilisation) does not change; therefore any real world change in the extent to which capital is utilised in production will be recorded as a change in productivity. Another assumption of the methodology is each hour of labour input is fully utilised in production. Further, improvements in output due to a firm’s ability to produce more output because of their size, that is, economies of scale, will also appear as a measured productivity improvement.

Endnotes

  1. Jorgenson, D.W., Mun S. Ho, and K.J. Stiroh (2005) Information Technology and the American Growth Resurgence. Cambridge, MA: MIT Press; and Diewert, Erwin (2008) 'OECD Workshops on Productivity Measurement and Analysis: Conclusions and Future Directions', in Productivity Measurement and Analysis: Proceedings from OECD Workshops. Paris:  Organisation for Economic Co-operation and Development (OECD).
  2. Balk, Bert M. (2010) 'An Assumption-free Framework for Measuring Productivity Change', The Review of Income and Wealth, Vol. 56, Issue 1 (June), pp.224-256.
  3. Bosworth, B.P. and J.E. Triplett (2003) Services Productivity in the United States: Griliches' Services Volume Revisited, Washington, DC: Brookings Institute.
  4. Changes in value added-based MFP can also be driven by changes in the efficiencies of intermediate inputs, for example, due to the use of more refined oil or more refined metal ore.
  5. The ratio was first described in Bruno (1978). For a more precise reconciliation, see Diewert (2014).
  6. OECD (2001) OECD Productivity Manual: A Guide to the Measurement of Industry Level and Aggregate Productivity Growth. Paris:  Organisation for Economic Co-operation and Development (OECD)