EXPERIMENTAL PRODUCTIVITY GROWTH ACCOUNTS
This release includes four experimental tables (Tables 20 to 23) that present the estimated industry contributions to market sector labour productivity growth under an alternative decomposition framework.
The framework explains aggregate labour productivity growth in terms of the direct (within industry) effect and the reallocation (between industry) effects. The components are derived using industry productivity measures weighted by the relative industry shares and summed across all industries. This approach is considered a “bottom-up” approach and traces the aggregate productivity performance to its industry origins. The decomposition framework utilised by the ABS is described in Chapter 19 of the Australian System of National Accounts: Concepts, Sources and Methods, 2013 (cat. no. 5216.0).
Table 20 presents an overview of the decomposition of market sector labour productivity growth.
Table 21 provides the industry contributions to market sector labour productivity growth on a gross output basis, decomposed into the following three components:
- Sum of gross output based industry labour productivity growth. Also known as the 'direct productivity effect' and is equal to the weighted sum of industry gross output labour productivity growth rates, using the industry shares in total value added as weights.
- Intermediate inputs reallocation. This component represents the intermediate input intensity factor. As value added is defined as gross output minus intermediate input, the relative growth of intermediate inputs over gross output must be accounted for in aggregating industry gross output to reach aggregate output. For example, if growth of intermediate input usage is faster than that of gross output, the growth of value added is reduced and hence the growth rate of aggregate labour productivity declines. If less intermediate inputs are used for a given level of gross output, then more value added is created and hence aggregate labour productivity improves. The intermediate input intensity factor is useful for capturing the impact of company outsourcing or specialisation on productivity growth at an aggregate level. Suppose specialised services companies are more efficient in producing the same services that are currently produced within other companies. If those other companies contract out that part of services to these external specialised companies, the overall productivity will increase.
- Labour reallocation effect. This component captures the impact on aggregate output of the shift of labour between low-productivity-level industries and high-productivity-level industries. Market sector labour productivity growth depends not only on the rates of productivity within industries but also on changes in the composition of industries. For example, it was found that the shift of labour from a low-productivity-level industry to a high-productivity-level industry would raise aggregate productivity growth even if these two industries experienced zero growth in productivity. Faster employment growth in high-productivity-level industries contributes to improvements in the market sector labour productivity growth by increasing the size of aggregate output given the same quantity of hours worked.
Gross output based decomposition can be further simplified by combining gross output and intermediate inputs. Table 22 provides industry contributions to market sector labour productivity growth on a value added basis, decomposed by the following two components:
- Sum of value added based industry labour productivity growth. Also known as the 'direct productivity effect' and is equal to the weighted sum of industry value added labour productivity growth rates, using the industry shares in total value added as weights. As industry labour productivity rises, aggregate labour productivity also increases in proportion to industries’ shares in aggregate output.
- Labour reallocation effect, as presented in Table 21.
Table 23 provides the contributions to market sector value added labour productivity or the 'direct productivity effect' for:
- IT capital deepening. This captures the contribution from growth in capital services from computers and software per hour worked.
- Non-IT capital deepening. This captures the contribution from growth in all other capital services per hour worked from non-dwelling construction, machinery and equipment (excluding computers), intellectual property products (excluding software), and livestock.
- Labour composition. This captures the contribution to market sector labour productivity growth from changes in the composition of the workforce due to changes in educational attainment and work experience.
- MFP growth.
The two capital deepening components (IT and non-IT) add to total capital deepening. Separating capital deepening into IT and non-IT is useful because replacement of IT capital is at a much faster rate, relative to non-IT capital, due to its shorter asset life span.
This release also presents experimental estimates of mining multifactor productivity (MFP) which accounts for changes in
mineral and energy resources inputs (Table 24).
Improvements in the valuation of mineral and energy resources have recently been incorporated in the Australian System of National Accounts (ASNA) (cat. no. 5204.0). These improvements enable the ABS to include a measure of natural resources in the inputs for the Mining industry (Division B). Productivity statistics aim to measure technical progress or the efficiency of production. In practice, they measure the difference between the growth in the volume of output and the growth in the volume of inputs, which reflects more than just technical progress. In particular, changes in unmeasured inputs are captured in the measure of productivity. The ABS regularly engages with key users to improve the estimates and bring productivity closer to its conceptual definition. There is a growing consensus among analysts that inclusion of mineral and energy resources will improve the interpretability and overall fitness for purpose of productivity measures in the Mining industry.
The mining MFP estimates based on natural resource inputs will be experimental for a number of reasons. There is no clear international standard on how to include mineral and energy resources into productivity statistics, and few countries have attempted its inclusion. The ABS method described in
Information paper: Introduction of Mining Natural Resources into Australia’s Productivity Measures, 2012-13 (cat. no. 5204.0.55.010) is put forward as one possible solution.
Productivity measures which do not measure mineral and energy resources will continue to be maintained in the core productivity tables (Tables 1 to 19), so that the influence of natural resource inputs can be separated. Similarly, productivity measures for the market sector published in the ASNA did not include mineral and energy resources.
The ABS welcomes feedback on the new experimental tables. For more information, please contact Derek Burnell on 02 6252 6427.
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