Digitisation of Australian Industry is Narrow and Shallow

 Changes in software capital expenditure and the capital stock

 

Industry investment in physical and intellectual assets is essential for building capacity and upgrading technology, and one reason for the low rate of productivity growth of Australian industry is the lack of business investment in the capital stock, which is the accumulated amount of machinery, equipment, buildings, structures, software and R&D in the economy. With investment the capital stock is upgraded and grows, and a low level of investment means slower growth in output, increasing economic inefficiency, less economic dynamism, and lower productivity.

 

Productivity is determined by the amount and quality of capital per worker, their skills and experience, and the rate of adoption of new technology. This post looks at the 2023-24 data from the Australian Bureau of Statistics for productivity, capital stock [1], and gross fixed capital formation (GFCF, i.e. capital expenditure or capex) on computer software. Because the ABS data on machinery and equipment (M&E) capital stock and GFCF includes investment in computers and information technology with all other M&E, the software data is one way of tracking the digitisation of Australian industry. 

 

Software and Labour Productivity

 

In 1987 Robert Solow made his well-known observation ‘You can see the computer age everywhere but in the productivity statistics‘, often referred to as the Solow paradox. Explanations for the paradox included measurement issues, the relatively small share of information technology (IT) in total investment, the time needed for industry to reorganise around IT, a substitution effect as computers made other capital like machinery and transport equipment more efficient, localised gains in IT manufacturing, that hard to measure service industries like finance and professional services were major adopters of IT, and the alignment of computers with bureaucracy as they created more but not always more useful work (like email chains, online forms and time wasted browsing the internet). 

 

Figure 1 shows Australia’s software net capital stock chain volume measure for All Industries (the capital stock adjusted for depreciation  and changes in prices), and the hours worked labour productivity measure for the 16 market sector industries. Up to 2021 they had similar paths as both increased at about the same rate, but over the last three years the software capital stock has grown rapidly, and much more than labour productivity, which returned to trend after the spike during COVID. There is an echo here of the late 1990s, when software capex and the capital stock increased during the early stages of the IT revolution and the internet but the rate of growth of productivity did not increase, and in fact fell in the years around 2000. 

 

Figure 1. Software capital stock and productivity

 
Source: ABS 5204 and 5260

Note: All Industries net capital stock chain volume measure, and hours worked labour productivity. 

 

There is no suggestion of causality here, with the post-2021 increase in software capital stock not reflected (yet) in the productivity index. This is different to the M&E relationship with labour productivity in Figure 2 below (from the previous post), where productivity rose with a two year lag after the increase in the M&E capital stock that began in 2006, then flattened out after M&E stopped rising in 2015, and rose again a couple of years after M&E increased in 2021. There are several reasons why the M&E capital stock has a more direct relationship with productivity: new M&E typically replaces older but similar M&E, so does not require a lot of training or reorganisation, and is unlikely to be underutilised; new M&E will usually be smarter and more automated, so increases output but requires less labour; small firms have access to the same new M&E as large firms; and diagnostic software in new M&E makes maintenance easier with less downtime. 

 

Figure 2. Machinery and equipment capital stock and productivity

 

Source: ABS 5204 and 5260

Note: All Industries net capital stock chain volume measure, and hours worked labour productivity. 

 

The differences between software and M&E are important, and explain why there is a weaker relationship between the software capital stock and productivity. First is the training and learning required with new software, particularly for large complex systems, and the time it takes to become familiar with a new system or major update. Second, underutilisation is an issue because there are often features in a software system that are not used, but have to be paid for. Third is the implementation challenge, because software and IT investments will often be disruptive and many have been expensive failures. Finally, to take full advantage of new systems will typically require reorganisation, with redesigned processes and restructured roles. Small firms find all these factors more challenging than large firms with more resources and deeper skill sets, and the weak relationship between software capex and productivity growth may be because of the large number of small firms. As an aside, these were the explanations given for the productivity slowdown around 2000, and now they will apply again in the adoption of AI by businesses [2]. 

 

The lack of a relationship between the software capital stock and labour productivity becomes more apparent when comparing their growth for different industries over 2020 to 2024. As Table 1 shows, a couple high productivity growth industries like Agriculture and Accommodation also had large software capital stock increases, but then so did negative productivity growth industries like Manufacturing and Retail trade. In a group of five industries with capital stock increases between 80% and 90%, the labour productivity growth varied from -20% for Mining to +5% for both Wholesale trade and Administrative and support services. For both productivity and capital stock changes, the aggregate outcome balances out a wide range of outcomes across industries. 

 

Table 1. Software net capital stock and productivity by industry 2020-2024

 

Software Capital Stock and Capex 

 

The top two industries in Figure 3 are Professional, scientific and technical services, and Finance and insurance services, and they accounted for 43% of total software net capital stock in 2024, showing how concentrated it is in Australia, and those two industries are 7.6% and 7.8% of industry gross value added respectively. These are service industries that have output measurement issues because they are not goods producing, which is part of the reason for the weak IT/productivity relationship. Adding Information, media and telecommunications, and Public administration and safety make up the top four industries with 51% total software net capital stock and 23.4% of industry gross value added. Also service industries. 

 

 

Figure 3. Software capital stock by industry

 

Source: ABS 5204. 

 

Software capex is also concentrated in the same four industries, and they accounted for 49% of the total in 2024. Professional, scientific and technical services, and Finance and insurance services were again by far the largest. They are followed by Information, media and telecommunications and Public administration and safety. The next four industries had between $2 and $2.5 billion software capex and accounted for another 22% of total software capex. These were Electricity, gas, water and waste, Health care and social assistance, Retail trade, and Transport, postal and warehousing. Those eight industries did 71% of software capex and are 43.7% of industry gross value added. 

 

The middle group of five industries of Construction, Education and training, Administrative and support services, Manufacturing, and Wholesale trade had 19% of capex and 18% of software capital stock in 2023-24. These industries are 25.5% of industry gross value added. 

 

The bottom five industries are Agriculture, forestry and fishing, Accommodation and food, Mining, Arts and recreation, Rental, hiring and real estate services, had 7% of software capex and capital stock in 2023-24. These industries make up 19.3% of industry gross value added, of which Mining is 10.4%. 

 

Figure 4. Software capital expenditure by industry

 

Source: ABS 5204. 

 

Tracking Digitisation with the Software Capital Stock

 

The ABS does not separate capex for computers and IT from the M&E total, so the digitisation of Australian industry cannot be tracked through the M&E data. However, there is the data for computer software that was used above, and that provides an alternative method of tracking digitisation, because investment in computing equipment will also require expenditure on software to make it run. 

 

Figures 5 and 6 have the percent change in the annual chain volume measure of the software net capital stock for each industry over five year intervals since 2000. This shows how annual capex, which varies considerably from year-to-year, accumulates over time into capital stock, and comparing the change in the capital stock in the five periods is indicative of the digitisation of Australian industry in three ways.

 

 First, twelve of the 18 industries had their biggest increase in their software capital stock in the most recent 2019-2024 period, and for those industries this was the biggest percentage change in any of the five periods. Three other industries were close to their previous peak change, that was in the 2000-2004 period. The substantial  increase in the software capital stock between 2000 and 2024 suggests an increase in the digitisation of industry. 

 

Second, for nine industries the change in their software capital stock in 2015-2019 was lower than the previous 2010-2014 period, and in another five was similar. This suggests there had been a trend of falling software capex in many industries that was reversed in the most recent period of 2020-2024.

 

Third, between 2020 and 2024 seven industries increased their capital stock by over 100%, and seven between 75 and 99%. This level of software investment across so many industries is unprecedented in Australia.  For example, in 2000-2004 Mining and Professional services both increased their software capital stock by over 100%, and in 2010-2014 Retail trade by 95%, but there has not been a software investment surge in the past comparable to the one in 2020-2024. 

 

Figure 5. Software capital stock increase by industry over five year periods

 

Source: ABS 5204. Annual chain volume measure of net capital stock.

 

Figure 6. Software capital stock increase by industry over five year periods

 

Source: ABS 5204. Annual chain volume measure of net capital stock.

 

Out of the four software-intensive industries, Professional, scientific and technical services, Finance and insurance services, and Public administration and safety all had larger capital stock increases in 2020-2024 over 2015-2019, but for Information, media and telecommunications the increase fell to half the earlier rate of change. The 150% increase for Professional services was the second largest out of all industries, behind Retail trade (where increased online shopping will have been a driver of software capex).  

 

Conclusion

 

Australian industry has greatly increased investment in computer software in recent years. Fifteen out of eighteen industries had or were close to record levels of capital expenditure on software for the five years 2020-2024, and seven of those industries increased their software capital stock by over 100%. This is a useful indicator of the increasing digitisation of industry, because the previous period of peak capex was 2000-2004, and that was followed by a decade and a half of lower capex  for most industries.

 

However, software capex and capital stock is highly concentrated in Australia. Two industries, Professional, scientific and technical services, and Finance and insurance services, accounted for 43% of total software net capital stock in 2024, and 34% of capex. Those two industries are 7.6% and 7.8% of industry gross value added respectively. With Information, media and telecommunications, and Public administration and safety, the top four industries have 51% total software net capital stock, 49% of capex, and 23.4% of industry gross value added. However, of those four industries, only Professional services with 150% had a large increase in capital stock in 2000-2024, Information, media and telecommunications increased by only 24% and the other two by around 60%. 

 

The next four industries were Electricity, gas, water and waste, Health care and social assistance, Retail trade, and Transport, postal and warehousing. Those accounted for another 22% of total software capex, 21% of capital stock, and almost 20% of industry gross value added. The largest increase in 2020-2024 capital stock was 190% by Retail trade, as increased online shopping drove software capex, and Health care had a 140% increase. 

 

A group of five industries of Construction, Education and training, Administrative and support services, Manufacturing, and Wholesale trade, had 19% of capex and 18% of software capital stock in 2023-24. These industries are 25.5% of industry gross value added. 

 

The bottom five industries of Agriculture, forestry and fishing, Accommodation and food, Mining, Arts and recreation, Rental, hiring and real estate services, had 7% of software capex and capital stock in 2023-24. These industries make up 19.3% of industry gross value added, of which Mining is 10.4%. 

 

The software intensive industries are all services, and it is notable that the goods producing industries of Agriculture, Construction, Manufacturing and Mining are in the bottom half of industries for the value of their capital stock. With the exception of Agriculture, which has the lowest capital stock but high productivity growth, the other three are among the productivity laggards in Australia, and have had little or negative labour productivity growth over the last few years. 

 

The link between productivity and software capex and capital stock is, however, a weak one. Training and learning is required for new software, there are often features in a software system that are not used, software and IT investments will often be disruptive and taking advantage of new systems needs reorganisation, redesigned processes and restructured roles. Small firms find all these factors more challenging than large firms with more resources and deeper skill sets, and one part of the explanations for the weak relationship between software capex and productivity growth may be the large number of small firms. 

 

Digitisation of Australian industry is narrow and shallow. It is narrow because two industries worth 15.4% of industry gross value have 43% of total software net capital stock, and do 34% of software capex. It is shallow because adding the next two industries gives the top four industries 51% of software capital stock, 49% of capex, and 23.4% of industry gross value added. The top eight industries account for 73% of software capital stock, 71% of software capex, and 44.7% of industry gross value. The other 12 industries that make up 45% of industry gross value (the balance is in ownership of dwellings) only account for 26% of software capex and 25% of software capital stock. 

 

An important point is  that the service industries that make up the top eight have output measurement issues because they are not goods producing, and this is another part of the explanation of the weak IT/productivity relationship. A related factor may be an increase in the number of employees working with computers due to increased use of IT, but there is no way to identify and measure any change in the quantity or quality of output due to efficiency gains. 

 

Increasing capex on software would have a marginal effect on aggregate capex. In 2023-24 total GFCF was $649 billion, with $245 billion on Non-dwelling construction the largest component, followed by $142 billion on Dwellings, $129 billion on M&E, $41 billion on Software and $27 billion on R&D. Nevertheless, raising capex on software will be a necessary element in improving Australia’s productivity growth rate because it is an important enabler of increased efficiency and leads to reorganisation of processes and organisations. Incentives to increase software capex like accelerated depreciation or tax write-offs would be effective, and could be supported with other policies to increase training and skills development. Targeting small and medium sized firms would greatly increase the effectiveness of such policies.

 

                                                                        *

[1] Capital stock in the current year is last year’s stock minus depreciation plus new investment. The volume measure of Net capital stock is adjusted for depreciation due to wear and tear from use and changes in prices. 

 

[2] On 5^th August the Productivity Commission released their report on Harnessing Data and Digital Technology. 

 

 

Australian Productivity and Performance

  National and industry statistics from the ABS 

 

Australia is fortunate in having high quality data from the Australian Bureau of Statistics, one of the world’s leading national statistical agencies. The ABS regularly publishes a range of productivity measures for tracking and understanding economic performance. The ABS notes productivity measures should be used for analysis of long-term growth, and short-term fluctuations are not reliable indicators of performance: ‘Caution needs to be exercised in interpreting productivity measures, which are derived as a 'residual', and are therefore subject to any errors in the output and input measures.’

 

Productivity is a measure of the efficiency of production, how much output is delivered from the inputs used. That ratio between output and inputs is affected by economy-wide factors, such as innovation, research and development, education and training, technology and investment, management and industrial relations. There are also specific factors that affect worker productivity, such as the quality and age of the capital stock (of machinery, plant and equipment, and buildings and structures), the rate of technological change and adoption of new technologies [1]. 

 

Although productivity growth many countries in Europe and Asia has been low over the last decade, for the last two years Australian productivity growth has been very low and was negative in 2022-23. Nevertheless, Australia’s productivity performance has not been as poor as some commentators make out (see here and here). As Figure 1 shows, using Purchasing Power Parity (PPP) estimates rather than converting to US dollars, in 2019 Australian productivity was in the middle of the range for developed economies, and the growth rate between 1990 and 2019 was better than some countries (e.g. Canada, Italy) but worse than others (e.g. Denmark, Germany). Estimates using PPPs for 2022 are similar. 

 

Figure 1. Productivity compared

Source: Our World in data. Based on Purchasing Power Parity not currencies. 

 

The Treasurer Jim Chalmers has said that productivity will be a focus of the newly re-elected government. Late last year he started five Productivity Commission inquiries, on economic dynamism and resilience, workforce issues, data and digital technology, a more efficient care economy, and investment in the clean energy transformation. The recommendations from those inquiries will join, and probably be very similar to, the 29 reform directives based on 71 recommendations in the Productivity Commission’s 9 volume 2023 report Advancing Prosperity.

 

This highlights the problem: there is a shopping list of solutions to low productivity, and a basket of recommendations from industry associations, unions, think tanks and commentators with their favoured reforms. While most are worthy, like improving education and training or more R&D and innovation, some are self-serving, like tax reform and regulations. Another problem is that productivity is a long-run measure, and many of these recommended policies or actions would take a long time to implement or have an effect. What is needed is a more focused agenda with one or two measurable targets that can be achieved in the short to medium term, say five to ten years. 

 

Productivity Statistics

 

The ABS publishes productivity measures for the whole economy, the market sector, and for each of the 16 industries in the market sector. The number and variety of these measures can make it difficult to identify and find the most appropriate or relevant measure. This overview explains the different measures and provides data on each for comparison, with some comments on characteristics and performance.   

 

The most widely used productivity measure is labour productivity, which is gross domestic product per hour worked for the whole economy or gross value added per hour worked for the market sector. This measure is relatively straightforward and does not require assumptions to be made about the inputs and outputs, although there can be issues in the measurement of their quantities. 

 

As well as labour, production requires intellectual and physical capital, like R&D, tools, equipment and buildings. The ratio of a unit of output produced by a unit of the combination of labour and capital is multi-factor productivity (MFP). This is a more complex measure because estimating the stock of capital requires an estimate of annual capital investment and a depreciation rate to account for the declining efficiency due to use and age of the existing stock. Capital productivity has been the weak point in Australia, due to the low level of industry investment, particularly in IT capital equipment and software. 

 

There are also quality adjusted labour input indexes, which take into account characteristics of the workforce like years of education, levels of training, industry of employment, age and sex. These quality adjusted measures can be used for both labour productivity and MFP, and reflect changes in the composition and skills of the workforce.

 

Finally, there is the KLEMS productivity measure, the most comprehensive but also the most complex of the measures available. This measure has five input categories for capital (K), labour (L), energy (E), materials (M), and services (S), for market sector industries. The KLEMS measure identifies industry cost structures and the contribution to output growth of each of those inputs.

 

In this post these productivity statistics are reviewed and the most recent data presented. Economic and industry performance are discussed, starting with the high level whole economy data and then moving to the industry level measures for labour productivity, multi-factor productivity and the KLEMS measures. Construction industry productivity is discussed and the performance of the industry assessed. The importance of investment in the capital stock is emphasised. 

 

Labour Productivity

 

Labour productivity is the most straightforward measure, and is output per unit of labour input as persons employed or hours worked. The ABS publishes estimates of labour productivity as gross domestic product (GDP) per hour worked for the economy as a whole and for the 16 industries in the market sector as gross value added (GVA) per hour worked in the annual System of National Accounts. The long run data from 1995-96 shows growth in the 1990s that slowed down in the 2000s, and has been flat for the last five years. Figure 2 shows GDP per hour worked for the whole economy. The index has increased from 70 in 1995-96 to 100 in 2023-24, or 44%. 

 

Figure 2. Labour productivity, whole economy

Source: ABS 5204

 

Market sector productivity does not include estimates for three industries considered to be non-market because they lack meaningful prices and it is impossible to calculate volume measures of output (a cost-of-service delivery method is used, i.e. wages and salaries). The industries are Public Administration and Safety, Education and Training, and Health Care and Social Assistance.  Because productivity cannot be accurately measured in the non-market sector, comparisons should be made using market sector statistics. Also, although efficiency and productivity in the non-market sector should be improved as much as possible, the cost-of-service measure used means that will have little effect on labour productivity growth for the whole economy. 

 

Figure 3 shows gross value added (GVA) per hour worked for the 16 industries in the market sector. In 2022-23 market sector labour productivity fell 3.5%, the largest fall since the series began, due to an increase in hours worked of 6.9% compared to GVA growth of 3.8%. The index for GVA per hour worked has increased from 63 in 1995-06 to 101 in 2023=24, or 61%. The difference between the two measures is significant, for the whole economy as GDP per hour worked the growth in productivity has been less than for the market sector. Unsurprisingly, the public sector has lower productivity growth than the market sector, and as its share of the economy has grown in the last few years productivity growth for the whole economy has slowed. 

 

Figure 3. Labour productivity, market sector

 

Source: ABS 5204

 

 

Quarterly indexes of GDP and GVA per hour worked are published in Australian National Accounts: National Income, Expenditure and Product. The annual estimates smooth the quarterly labour productivity measures, which are revised for up to three years as more data becomes available. In the revisions June is often revised down and September often revised up, larger estimates have larger revisions, positive estimates are more likely to be revised down, while negative estimates are more likely to be revised up. Revisions are largest in the September quarter, when the ABS benchmarks their estimates. 

 

Figure 4. Labour productivity, whole economy, quarterly

Source: ABS 5204

 

The quarterly labour productivity measures very considerably from quarter to quarter, and clearly show the whole economy estimates do not vary as much from quarter to quarter as the market sector estimates. Market sector productivity growth has been stronger but more volatile. These quarterly estimates should be regarded as indicative of trends but not definitive.

 

Figure 5. Labour productivity, market sector, quarterly

Source: ABS 5204

 

Construction Industry

 

Construction labour productivity has barely changed over the last 20 years. However, during the mining boom 2011-2016 labour productivity rose and then fell, following the increase and decrease in the volume of work done. As Figure 6 shows, since 2020 productivity has been around the same level as it was before the boom [2].

 

Figure 6. Construction labour productivity

Source: ABS 5206

 

Multi-factor Productivity

 

Labour and capital can be combined into multi-factor productivity (MFP), measured as GDP per unit of combined labour and capital. The ABS publishes annual indexes of industry level MFP estimates for the market sector, in Estimates of Industry Multifactor Productivity.

 

Figure 7. Multi-factor productivity

Source: ABS 5206

 

Construction MFP also rose and fell with the mining boom, and has followed a similar path as labour productivity with somewhat lower fluctuations in the year-to-year changes. What Figure 8 shows is that in many years up to  2014-15 there has been little or no increase in Construction MFP, except for years such as 2001-02 and 2011-12, when it jumped by 10% or more, and for the last decade has fallen in every year except two. 

 

Figure 8. Construction MFP

Source: ABS 5206

Industry Comparisons

 

Over the last five years there have been significant differences between industries in productivity growth. Table 1 has the 16 industries in the market sector, and shows between 2019 and 2024 three industries had high growth in output per hour worked of over 10%, but overall performance has been affected by five industries with negative growth, low growth in another seven industries, and no growth in construction. For most industries, MFP growth was worse than for labour productivity as hours worked. The highest performing industries were Agriculture, Forestry and Fishing and Information, Media and Telecommunications, the worst performing industries were Mining and Electricity, Gas, Water and Waste. 

 

 

Quality Adjusted Labour Input Measures 

 

Measuring labour input as hours worked assumes that the workforce is homogeneous. An alternative approach to human capital is quality adjusted labour inputs (QALI). These classify workfers by industry of employment, sex, educational attainment, and age group [3}. QALI indexes are published for the market sector in the Australian System of National Accounts, and for each market-sector industry in Estimates of Industry Multifactor Productivity. The difference between hours worked and quality adjusted labour input is a measure of composition change in the workforce due to a shift in the skill mix of labour input.

 

Figure 9. Quality adjusted labour input productivity

Source: ABS 5204

 

Figure 10. Quality adjusted labour input multi-factor productivity

Source: ABS 5204

 

Growth Cycles

 

Labour productivity growth in Australia could be better, recently averaging less than 1% a year growth for the market sector. The 20 year average growth rate was 1.7% in 2015-16, but by 2022-23 it had fallen to 0.9%. There is a strong relationship between economic conditions and productivity, because the rate of growth in GDP affects the rate of growth of productivity. The ABS uses peak-to-peak growth cycles in MFP to adjust for the effect of changes in GDP growth, and publishes growth cycles for the different productivity measures for the market sector, in Table 2. These show a slowdown in labour productivity growth in the recent cycle from 2017-18 to 2021-22, but a small increase in MFP growth.  

 

 

 

Industry Comparisons

 

Table 2 compares labour productivity across the 16 market sector industries for the long run 1995-06 to 2023-24 and the last five years 2019-2024, as GVA per hours worked and GVA with QUALI. There are wide differences in industry performance over both periods. The increase in the QUALI indexes for the long-run were generally 10 to 20% below the unadjusted labour productivity, but for the five years 2018-19 to 2023-24 changes in the QUALI indexes are typically close to the hours worked. 

 

Construction was the only industry where the QUALI indexes had a greater increase than the hours worked indexes. Several industries had worse productivity performance than Construction, such as Mining, Electricity, Gas, Water and Waste, and Administrative and Support services. Despite the common claim that there has been no growth in Construction productivity, over the five years to 2024 Construction was one of the best performing industries in quality adjusted labour productivity as hours worked. 

 

 

Table 4 compares MFP across the 16 market sector industries for the long run 1995-06 to 2023-24 and the five years 2019-2024. MFP increased by a lot less than labour productivity in both periods, and again the QUALI indexes increase less. In the 5 years to 2024 there was little difference between the two measure for many industries. Construction MFP had a 1% rise in the hours worked measure in the long run, but declined in the other periods. 

 

 

 

Capital Productivity

 

The two major inputs to productivity are labour and capital, and these have the two characteristics of quantity and quality. Labour is adjusted for years of education and experience in the QUALI measures above, while capital is adjusted for age through a depreciation rate that reflects wear and tear from use. This is not a straightforward calculation because of assumptions about the effect of age and use on the performance of plant, equipment and machinery and the durability of building and structures [4]. This makes estimates of the capital stock (the quantity of those assets) and capital productivity sensitive to the rate used. 

 

Capital productivity has fallen, particularly in the decade after 2004. This decline in capital productivity is the reason Australia’s productivity growth has been so low. Although the workforce is increasingly trained and skilled, the capital stock has not been replaced and updated due to the low level of business investment. As Figure 11 shows, in the majority of years since 1995-96, capital productivity has decreased. 

 

Figure 11. Capital productivity

Source: ABS 5204

 

Figure 12 shows Total private gross fixed capital formation (GFCF), which is private sector investment in the capital stock, and capital productivity. The increases during the fiscal response to the 2008-09 global financial crisis and the expenditure on plant and equipment during the mining boom from 2012 is apparent. What is significant is the decline in expenditure on software, which is a separate item in the capital expenditure statistics, which will have contributed to the already established decline in capital productivity (so not the only causal factor), and between 2018 and 2021 capital productivity and the shares of GDP of both total private GFCF and private software GFCF were all flat, before an increase in GFCF in 2023 and 2024 lifted capital productivity. Australian productivity overall can be improved by increased investment in the capital stock, and in particular in IT and software capital [5]. 

 

Figure 12. Capital productivity and private gross fixed capital formation

Source: ABS 5206. Total private GFCF and Private GFCF on Software as percent of GDP in current dollars. 

 

Industry KLEMS MFP

 

KLEMS MFP is only available for individual market sector industries, the ABS does not publish aggregate KLEMS indexes for the market sector. The KLEMS framework has five input categories: capital (K), labour (L), energy (E), materials (M), and services (S), with the contributions to output growth of each of those inputs, which allows analysis of changes in the input mix, such as labour hours worked, capital services or intermediate inputs. The intermediate inputs are energy (E), materials (M) and services (S), which includes hiring, renting and out-sourcing between industries. For example, if a construction company leases a crane from the rental and hiring industry, it 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. 

 

Industry cost structures are diverse and vary from industry to industry and over time. The variation from year to year in the contribution of each input to output growth reflects factors like wage and price changes, interest rates, and fluctuating demand. Therefore, averages are conventionally used, and Figures 13 A and B show the long-run averages for each industry for the period data is available, from 1995-06 to 2022-23.. 

 

Clearly, for most Australian industries the main contributor to growth has been services provided by other industries, including Construction. Non-IT capital intensive industries are Mining, Electricity, Gas, Water and Waste Services, Transport, Postal and Warehousing Services, and Rental, Hiring and Real Estate Services. Agriculture, Forestry and Fishing, Manufacturing and Construction have a high level of materials as inputs.

 

 Financial and Insurance Services is the only industry with a high level of IT capital services. The low level of IT capital services in many industries is a major problem at a time when IT related innovations like generative artificial intelligence, cloud computing and reality capture are advancing rapidly, and points to the most important challenge for Australian industry, which is increasing the level of investment in new physical and intellectual capital, and IT and software in particular.

 

Figure 13A. Industry averages, market sector

Source: ABS 5206

Figure 13B. Industry averages, market sector

Source: ABS 5206

 

 

The main features of these averages for each industry are:

 

Agriculture, Forestry and Fishing – hours worked and non-IT capital services detracted from growth, services and materials were the major contributors

Mining – non-IT capital services was the main contributor (reflecting the use of heavy machinery and equipment), and in 2022-23 were 59% of input costs. 

Manufacturing – hours worked and energy detracted from growth, hours worked and materials were the main contributors, and in 2022-23 materials were 48%) of total input costs.

Electricity, Gas, Water and Waste Services - hours worked and non-IT capital services were the main contributors. In 2022-23 the services cost share was 58%.

Construction - services, hours worked and materials were the main contributors

Wholesale Trade – services and hours worked were the main contributors

Retail Trade - services, hours worked and both IT and non-IT capital services were the main contributors

Accommodation and Food Services - services and hours worked were the main contributors

Transport, Postal and Warehousing Services – services and non-IT capital services were the main contributors

Information, Media and Telecommunication Services – services, IT and non-IT capital services were the main contributors. In 2022-23 the services cost share was 54%.

Financial and Insurance Services – services and IT capital services were the main contributors

Rental, Hiring and Real Estate Services – services and non-IT capital services were the main contributors

Professional, Scientific and Technical Services – services and hours worked were the main contributors

Administrative and Support Services - hours worked was the main contributor. As a labour-intensive industry labour services accounted for 59% of total input costs in 2022-23.

Arts and Recreation Services - services and non-IT capital services were the main contributors

Other Services – services, materials and non-IT capital services were major contributors

 

Conclusion

 

The ABS publishes productivity measures for the whole economy, the market sector, and each of the 16 industries in the market sector. This post reviews these measures and provides their data, discusses their purpose and application, and recent economic and industry performance. 

 

The most widely used productivity measure is labour productivity as gross domestic product per hour worked. This is the measure commonly used for international comparisons, which are often done by converting countries’ currencies to US dollars but should be done using purchasing power parity to adjust for costs. Using PPPs, the level of Australian labour productivity is in the middle of other OECD countries. The index has increased from 70 in 1995-96 to 100 in 2023-24, or 44%.

 

Labour productivity is also available as gross value added per hour worked for the 16 industries in the market sector. Market sector productivity does not include estimates for three industries that lack meaningful prices and volume measures of output. The industries are Public Administration and Safety, Education and Training, and Health Care and Social Assistance.  Because productivity cannot be accurately measured in the non-market sector, comparisons should be made using market sector statistics, and improvement in non-market productivity will have little effect on labour productivity growth for the whole economy.

 

The index for GVA per hour worked in the market sector has increased from 63 in 1995-06 to 101 in 2023=24, or 61%. The difference between the two measures is significant, for the whole economy as GDP per hour worked the growth in productivity has been less than for the market sector because the non-market sector has lower productivity growth than the market sector, and as its share of the economy has grown in the last few years productivity growth for the whole economy has slowed. Construction labour productivity has barely changed over the last 20 years. However, during the mining boom 2011-2016 labour productivity rose and then fell, following the increase and decrease in the volume of work done.

 

As well as labour, production requires capital, for example tools, equipment and buildings, and the combined labour and capital measure is known as multi-factor productivity (MFP). This is a more complex measure because it uses a depreciation rate to account for use and age of the existing stock of capital. There has been a slowdown in labour productivity growth between 2017-18 to 2021-22, but a small increase in MFP growth over that period.  

Capital productivity has been falling, in the majority of years since 1995-96 capital productivity decreased, and declining capital productivity is the fundamental reason Australia’s productivity growth has been so low. The capital stock has not been replaced and updated due to the low level of business investment, particularly in IT and software. 

 

Quality adjusted labour input indexes take into account years of education, levels of training, industry of employment, age and sex. These quality adjusted measures are provided for the 16 market sector industries, and for both labour productivity and MFP. In the five years 2018-19 to 2023-24, changes in the QUALI indexes were close to the hours worked index. Despite the common claim that there has been no growth in Construction productivity, over the five years to 2024 Construction was one of the best performing industries in quality adjusted labour productivity as hours worked.

 

Finally, there is the KLEMS productivity measure for market sector industries, with five input categories for capital (K), labour (L), energy (E), materials (M), and services (S). The KLEMS measure identifies the cost structure and the contribution of each input to an industry’s output growth. For most Australian industries the main contributor to growth has been services provided by other industries. Non-IT capital intensive industries are Mining, Electricity, Gas, Water and Waste Services, Transport, Postal and Warehousing Services, and Rental, Hiring and Real Estate Services. Agriculture, Forestry and Fishing, Manufacturing and Construction are industries with a high level of materials as inputs.  Financial and Insurance Services is the only industry with a high level of IT capital services. 

 

The low level of IT capital services in Australian industry is the major problem at a time of IT related innovations like artificial intelligence, cloud computing and reality capture. To improve the productivity of Australian industry, the single most important requirement is increasing the level of investment in new physical and intellectual capital, and IT and software in particular. Industry policies should be targeting a significant increase in capital investment in the short-term, while policies targeting longer-term issues like innovation and R&D are developed. 

 

 

 

[1] The ABS methodology is in Chapter 19 of the Australian System of National Accounts: Concepts, Sources and Methods is on productivity measurement. 

 

[2] A 2023 post analysed construction productivity during the mining boom here https://gerarddevalence.substack.com/p/the-long-cycle-in-australianhtml?r=wtchb

 

[3] The ABS interpolates workforce compositional changes from the five yearly census data. Workers are grouped by education, age, and sex. For education there are four categories: Unqualified, Skilled Labour, Bachelor Degree, and Higher Degree. For age there are five categories: 15 to 24 years, 25 to 34 years, 35 to 44 years, 45 to 54 years, and 55 to 64 years. For sex there are two categories: Male and Female. The skills and education of the Construction workforce were detailed in

https://gerarddevalence.substack.com/p/the-changing-composition-of-construction?r=wtchb 

[4] Measuring the capital stock and estimating capital productivity is complex. It relies on a ‘rental price’ for capital, a long-term discount rate used to estimate capital services as an input to production by weighing different types of productive capital stock adjusted for efficiency loss and retirement. The ABS uses a discount rate of 4% based on long-term bond rates adjusted for CPI. Estimates of capital services growth and MFP are very sensitive to the rate of return used.

 

[5] The intellectual and physical capital stock of Australian industry in 2022-23 was analysed in https://gerarddevalence.substack.com/p/investment-in-physical-and-intellectual?r=wtchb