Estimates of Industry Multifactor Productivity

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Updates estimates of multifactor productivity (MFP) for industries and market sector aggregates.

Reference period
2019-20 financial year

Analysis of results

On an hours worked basis, market sector multifactor productivity (MFP) fell 0.7% in 2019-20. Market sector gross value added (GVA) declined 1.2%, the first decline recorded for the market sector since the series commenced in 1994-95. By comparison, combined labour and capital inputs declined 0.5%, reflecting capital services growth of 1.0% and hours worked fall of 1.7%. Labour productivity grew 0.6% in 2019-20, resulting from a greater fall in hours worked than GVA. 

On a quality adjusted labour input (QALI) basis, MFP fell 1.0% and labour productivity fell 0.1%. The weaker growth on this basis reflects a positive contribution from changes to labour composition, due to educational attainment and work experience.

Key figures market sector productivity, 2019-20
 Hours worked basisQuality adjusted hours worked basis
 % change% change
Multifactor Productivity-0.7-1.0
Gross Value Added-1.2-1.2
Labour Input-1.7-1.1
Capital Input1.01.0
Labour Productivity0.6-0.1


Changes to hours worked

Historically, labour input for productivity compilation has been sourced from the hours worked series of the Labour Force Survey (LFS). For the 2019-20 reference year, the national accounts moved to hours worked movement from the Australian Labour Account for industries and the market sector aggregates. This more accurately captured the fall in hours worked due to COVID-19 related restrictions which occurred after the LFS reference period (for further information see Assessing the impact of COVID-19 on the Labour Account). The change will affect the hours worked series for the current year.

Estimates of industry productivity

In 2019-20, weakness in MFP was broad-based with ten out of 16 market sector industries recording a fall in MFP. The largest falls in MFP were in Agriculture, forestry and fishing (8.3%), and Administrative and support services (7.8%). The largest MFP gains were in Mining (3.7%) and Retail trade (3.6%).

Agriculture, forestry and fishing records the third consecutive fall in MFP

MFP fell 8.3% in 2019-20, recording its third consecutive fall. The fall was driven by:

  • A large fall in GVA (8.0%) reflects declines in grain crop and other agricultural production due to ongoing drought conditions. 
  • Combined inputs grew 0.4%, reflecting a 2.8% rise in hours worked and a 0.7% decline in capital services. The fall in GVA, coupled with an increase in hours worked, resulted in a large fall (10.4%) in labour productivity. 

a. Natural log growth x 100

Mining records the strongest MFP growth

Mining MFP rose 3.7% in 2019–20, recording the seventh consecutive rise in MFP. Mining productivity growth reflects:

  • Solid growth in GVA (4.9%), supported by continued strength in oil and gas extraction and increased demand in iron ore. 
  • Combined inputs grew at a slower rate than GVA. The moderate growth in combined input was mainly driven by subdued capital services growth (1.0%) as Mining transitions from investment to production.
  • Labour productivity rose 3.2% as GVA outpaced hours worked growth (1.7%). 

Solid MFP growth in Retail trade driven by a fall in hours worked

Retail trade MFP grew 3.6% in 2019-20, the largest growth since 2009-10. This was driven by:

  • A small decline in GVA (0.5%), driven mainly by a large fall in Motor Vehicle and Part Retailing as COVID-19 negatively impacted the industry. The fall was partially offset by a rise in Food Retailing and Other Store Based Retailing reflecting consumers' stockpiling non-perishable products and alcoholic beverages at the early stage of COVID-19.
  • Combined inputs saw a larger fall (3.9%), driven by a fall in hours worked of 5.3% and a marginal fall in capital services of 0.4%. The large fall in hours worked (5.3%) is likely indicative of a shift to online retailing and shorter trading hours due to COVID-19. 

Large MFP decline in Administrative and support services, reversing growing trend in previous years

MFP fell 7.8% in 2019-20, reversing an upward trend in the previous three years. The fall reflects:

  • GVA fell 4.9%, with weakness shown across all subdivisions. The divisions' GVA has been negatively impacted by COVID-19 and natural disasters. This saw reduced demand for employment and administrative services as well as travel related services.
  • Combined inputs grew 3.1%. The growth was primarily driven by strength in hours worked (3.4%) since the division is very labour intensive. A fall in GVA, together with an increase in measured hours worked, translated to a large decline (8.0%) in labour productivity. 

Productivity growth cycles

Growth cycle analysis can minimise the effects of some temporary influences (such as variation in capital utilisation) by averaging productivity measures over a cycle. For more information about the productivity growth cycle, please see the Feature Article: Experimental Estimates of Industry Value Added Growth Cycles in the 2015–16 issue of Estimates of Industry Multifactor Productivity (cat. no. 5260.0.55.002).

MFP contributed an average of 0.8 percentage points (ppts) to GVA growth per year for the latest growth cycle (2011-12 to 2017-18). This shows an increased MFP contribution from the previous cycle (2003–04 to 2011–12), in which MFP was flat. Relative to earlier growth cycles, GVA growth in the latest cycle was more subdued, averaging 2.6%. Capital services contributed 1.2 ppts to GVA growth in the latest cycle, compared to 2.2 ppts in the previous cycle.

Contribution to output growth, by growth cycle, average percentage points
     Growth cycles 
 1998–99 to 2003–042003–04 to 2011–122011–12 to 2017–18
Output (GVA) growth (b)
Contribution to output growth
(hours worked basis)
Capital services1.72.21.2
Hours worked0.70.90.5
Multifactor productivity1.20.00.8

b. Natural log growth x 100

Experimental productivity measures – Direct Aggregation Across Industries (DAAI) approach

Experimental productivity measures (Tables 20-23) present the estimated industry contributions to market sector labour productivity (LP) growth under an alternative decomposition framework, the direct aggregation across industries (DAAI) approach (see Experimental productivity growth accounts). This approach enables the separation of direct productivity and hour reallocation effects. In addition, it allows tracking industry origins of the market sector’s LP growth.

Contribution to market sector LP growth – by industry, 2019-20, percentage points
 Direct productivityHour reallocation
A Agriculture, Forestry and Fishing-0.30.0
B Mining0.50.2
C Manufacturing-0.3-0.1
D Electricity, Gas, Water and Waste Services-0.10.0
E Construction-0.30.1
F Wholesale Trade0.00.0
G Retail Trade0.30.3
H Accommodation and Food Services0.00.5
I Transport, Postal and Warehousing0.00.1
J Information, Media and Telecommunications0.2-0.1
K Financial and Insurance Services-0.10.2
L Rental, Hiring and Real Estate Services-0.20.0
M Professional, Scientific and Technical Services-0.1-0.1
N Administrative and Support Services-0.40.0
R Arts and Recreation Services0.10.2
S Other Services0.10.3
Total contribution-0.61.6

The direct productivity effect is measured as the sum of direct LP industry contributions. In 2019-20, the direct productivity effect detracted 0.6 ppts from the market sector’s LP growth. This reflects broad-based weakness in LP performance, with ten of the sixteen market sector industries recording a fall in LP.  The most significant detractors to aggregate growth were from Administrative and support services, Manufacturing, and Agriculture, forestry and fishing, reflecting large declines in LP in these divisions. Conversely, strength in LP in Mining and Retail trade made a positive contribution to market sector LP growth. 

The hour reallocation effect which captures compositional changes to hours worked across industries, was the key contributor (1.6 ppts) to market sector LP growth. The positive reallocation effect was largely resulted from lower LP industries seeing the largest falls in hours worked due to stricter containment measures in these industries. The most significant reallocation effects were found in Accommodation and food services, and Retail trade, which both saw large declines in hours worked in 2019-20. 

Experimental state productivity estimates

Experimental estimates of market sector aggregates for state and territory are in Tables 27 to 42, and more information is detailed in Feature Article: Experimental Estimates of State Productivity.

Due to hours worked falling faster than falls in output, LP growth across the states and territories was positive, except for Queensland.

The four large states (New South Wales (NSW), Victoria (VIC), Queensland (QLD) and South Australia (SA)) recorded negative MFP growth, whereas the remaining states and territories recorded positive MFP growth. 

  • The Northern Territory (NT) recorded the strongest MFP (11.9%) and LP (15.7%) growth, mainly due to the strength in Mining, following some recently completed LNG projects.   
  • QLD experienced declines in MFP (2.4%) and LP (1.8%), as natural disasters and COVID-19 containment measures resulted in a large contraction in output in 2019-20 as seen in most states. The state, however, saw a smaller fall in hours worked than most other states which drove additional weakness in MFP and LP. 

Caution is required when interpreting the 2019-20 positive LP growth seen in all states except QLD. Broadly this is due to hours worked contracting faster than output.  This result, in part, reflects the impact of natural disasters and COVID-19 containment measures. For more information see productivity measurement in the time of a pandemic.

MFP growth 2019-20, percentage change (c)

MFP growth 2019-20, percentage change
Mutifactor Productivity Growth New South Wales (NSW) : -0.9% Victoria (VIC): -1.2% Queensland (QLD): -2.4% South Australia (SA): -0.6% Western Australia (WA): 0.9% Tasmania (TAS): 0.7% Northern Territory (NT): 11.9% Australian Capital Territory (ACT): 1.0%

Labour productivity growth 2019-20, percentage change (c)

Labour productivity growth 2019-20, percentage change
Labour Productivity Growth New South Wales (NSW) : 0.5% Victoria (VIC): 0.2% Queensland (QLD): -1.8% South Australia (SA): 0.8% Western Australia (WA): 1.6% Tasmania (TAS): 3.2% Northern Territory (NT): 15.7% Australian Capital Territory (ACT): 1.7%

c. Natural log growth x 100

New South Wales – MFP contracted in 2019-2020

  • NSW market sector MFP detracted 0.9% from GVA growth which fell 1.8% in the year. This is the first fall in output growth for this state in time series. COVID-19 containment measures, in addition to other natural disasters, adversely impacted output growth in 2019-20. 
  • Capital services continued to grow steadily, contributing 0.5 ppts to output growth in the year. Hours worked saw the largest fall since 1995-96, detracting 1.4 ppts from GVA growth. 

Victoria – records negative MFP growth in 2019-20

  • In 2019-20, market sector MFP in VIC fell 1.2% contributing to the fall in GVA of 1.6%, the first fall since 1995-96. The weakness in output growth reflected the adverse impact of COVID-19 containment measures.  
  • Capital services contributed 0.7 ppts to output growth while hours worked detracted 1.1 ppts.

Queensland – continued fall in MFP growth in 2019-20

  • Market sector MFP fell 2.4% for QLD in 2019-20 while COVID-19 containment measures resulted in a large decline in GVA (2.3%). QLD saw a smaller fall in hours worked than most other states which drove additional weakness in MFP and LP.
  • Capital services contributed 0.4 ppts to GVA growth which was partially offset by a negative contribution from hours worked (-0.3 ppts). 

South Australia – records the second year of contraction in MFP

  • In 2019-20, market sector MFP in SA fell (0.6%) on the back of a larger fall (1.9%) in 2018-19. COVID-19 pandemic related restrictions and containment measures resulted in a 2.5% fall in GVA. 
  • The largest detractor to output growth was hours worked which detracted 1.8 ppts from GVA growth. Capital services also recorded weakness, falling 0.1%, which was the first fall in the timeseries.

Western Australia – records the third consecutive MFP growth

  • Market sector MFP in WA recorded a growth of 0.9% in 2019-20, the third consecutive growth. 
  • Market sector GVA grew 1.4% driven by Iron Ore Mining and Oil and Gas Extraction, which were largely unaffected by COVID-19 related restrictions.
  • Capital services contributed 0.7 ppts to growth in GVA while hours worked recorded a small fall, detracting 0.1 ppts from output growth.

Tasmania – moderate MFP growth recorded in 2019-20

  • Tasmania MFP grew 0.7% in 2019-20 following strong MFP growth of 4.3% in the previous year. Market sector GVA fell 1.0% on the back of solid growth over the previous three years. 
  • Capital services grew in the year, contributing 0.5 ppts to GVA growth, while a large fall in hours worked detracted 2.2 ppts from output growth.

Northern territory – records the strongest MFP growth of all states and territories in 2019-20

  • NT market sector GVA recorded strong growth in 2019-20 (8.2%), reflecting the transition from mining related construction to production. GVA growth in the territory was faster than other states and territories. The main contributor to market sector GVA growth was MFP growth (11.9%), outpacing the growth in other states and territories in 2019-20. 
  • The marked rise in MFP growth in the territory was due to strong growth in GVA accompanied by sizeable detraction in hours worked (3.2 ppts) and capital services (0.4 ppts).

Australian Capital Territory – MFP grew in 2019-20

  • In 2019-20, the ACT recorded softer growth in market sector GVA (1.5%) on the back of strong growth over the past five years. COVID-19 related restrictions and natural disasters have adversely impacted GVA growth in some industries. 
  • MFP growth contributed 1.0 ppt to GVA growth, while capital services contributed 0.6 ppts.
  • Hours worked fell slightly on the back of a large fall in 2018-19, detracting 0.1 ppts from GVA growth. 


This publication incorporates revisions implemented in 2019–20 as follows:

  • The 2019–20 edition of the Australian System of National Accounts, which incorporates revisions in the 2018–19 annual supply and use tables. For specific details of the revisions, including changes to estimates, and the range of improvements incorporated, please see Australian System of National Accounts, 2019–20 (cat. no. 5204.0).
  • Revisions to hours worked as published in the Labour Force, Australia (cat. no. 6202.0). 

Frequently asked questions

About productivity statistics

Q. What is productivity?

A. Productivity is broadly defined as the ratio of a volume measure of output to a volume measure of input; that is, output per unit of input. Productivity can be defined for an individual entity, an industry, sector, or the economy as a whole. Growth in productivity can occur from an increase in output, a decrease in inputs or a combination of both. Productivity growth is the gap between output growth that is not accounted for by growth in inputs.

Q. What is labour productivity?

A. Labour productivity is defined as a ratio of output to labour input, that is, the amount of output produced for an hour of work. Changes in this ratio can also reflect changes in other factor inputs (such as capital). An increase in labour productivity means that more output is being produced per hour of work.

Q. What is capital productivity and capital deepening?

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

Capital deepening 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. 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 gains in labour productivity (resulting in MFP growth).

Q. What is multifactor productivity?

A. Multifactor productivity (MFP) is defined as a ratio of a measure of output to a combined input of labour and capital. In empirical analysis, it is expressed in terms of growth rate, that is, growth rate of output minus the growth rate of inputs. At the aggregate and industry level, gross value added-based MFP is defined as the ratio of gross value added to the combined inputs of capital and labour. At an industry level, gross output-based MFP is also measured as the ratio of gross output to the combined inputs of capital, labour, and intermediate inputs.

Q. What measures are available?

A. The ABS has been producing MFP statistics since 1985. There are different measures of productivity and the choice between them usually depends on the purpose of use and the availability of data. Broadly, productivity measures can be either partial productivity measures, which relate a measure of output to a single measure of input, or multifactor productivity measures, which relate a measure of output to a combination of inputs.

The ABS produces annual indexes of labour, capital and multifactor productivity for the market sector as well as for each industry division within the market sector.

Annual productivity measures for the market sectorAustralian System of National Accounts (cat. no. 5204.0)
Annual industry level gross value added-based MFP indexesEstimates of Industry Multifactor Productivity (cat. no. 5260.0.55.002)
Annual industry level gross output-based MFP indexesEstimates of Industry Level KLEMS Multifactor Productivity (cat. no. 5260.0.55.004)
Quarterly estimates of labour productivity (i.e. GDP per hour worked) for the market sector and for the whole economyAustralian National Accounts: National Income, Expenditure and Product (cat. no. 5206.0)
Quarterly and annual GDP per capitaAustralian National Accounts: National Income, Expenditure and Product (cat. no. 5206.0)


Q. What are the different measures of labour input?

A. The three common methods of measuring labour input are number of employed persons, hours worked and quality adjusted hours worked. The ABS publishes productivity statistics on both an hours worked basis and quality adjusted hours worked basis. These statistics are derived from estimates of hours actually worked, obtained from the Labour Force Survey. Indexes of hours worked are preferred to employment numbers because hours worked captures changes in overtime, standard weekly hours, leave, and part-time work. Quality adjusted hours worked further captures changes in the education and experience of the workforce.

A quality adjusted labour input (QALI) measures both changes in hours worked and changes in quality (that is, changes in educational achievement and experience). Aggregate QALI indexes have grown faster than the corresponding unadjusted hours worked indexes, implying that labour quality has been increasing. Assuming that higher wages reflect a higher marginal product of labour, labour quality will increase when the high wage rate groups of workers increase their hours worked faster than the low wage rate groups. Aggregate QALI indexes for the market sector and twelve selected industries are compiled using Australian Census data. Inter-census periods are interpolated so care should be taken interpreting year on year changes in labour composition.

Q. What is KLEMS?

A. The ABS published experimental estimates of industry level KLEMS MFP in March 2016 and removed the experimental label from KLEMS MFP with  the release in 2019-20. The term KLEMS represents the five inputs categories - capital (K), labour (L), energy (E), materials (M), and services (S). KLEMS provides, through a more detailed statistical decomposition, more information on the contributions to output growth, and production efficiency. KLEMS also provides a suitable tool for evaluating the effects of changes in the input mix, such as the role of labour hours and composition relative to capital services or intermediate inputs in accounting for industry output growth. For more information see Estimates of Industry Level KLEMS Multifactor Productivity (cat. no. 5260.0.55.003 and cat. no. 5260.0.55.004).

Q. Are productivity statistics revised?

A. Yes. Revisions are an inevitable consequence of the compilation process, reflecting both the complexity of economic measurement and the need to provide economic policy advisers and other users with initial estimates that are timely in order to maximise their use in analysis of current economic conditions. Revisions arise from the progressive incorporation of more up to date data, re-weighting of chain volume series and from time-to-time the introduction of new economic concepts, data analysis and improved data sources and methods.

Q. What is a growth cycle?

A. A useful method of examining changes in productivity over an extended period involves identifying and dividing the data into productivity growth cycles. Productivity growth cycle peaks are determined by comparing the annual MFP estimates with their corresponding long-term trend estimates. The peak deviations between these two series are the primary indicators of a growth cycle peak, although general economic conditions at the time are also considered. The purpose is to minimise the effects of cyclical factors that may cause the year-to-year changes in MFP to deviate from its conceptual definition. In this way, most of the effects of variations in capacity utilisation and much of the random error are removed. By averaging between peaks, it is assumed that these peaks represent similar levels of capacity utilisation, allowing more like-for-like comparisons of MFP between different growth cycles.

Q. Which industries are covered?

A. Ideally, MFP measures should cover all economic activities, but this is only possible if all of the necessary data are available. The market sector comprises sixteen industries under the Australian and New Zealand Standard Industrial Classification, 2006 (ANZSIC06); that is, from ANZSIC06 Divisions A to N, plus Divisions R and S. The detailed industries included in the market sector are as follows:

AAgriculture, Forestry and Fishing
DElectricity, Gas, Water and Waste Services
FWholesale Trade
GRetail Trade
HAccommodation and Food Services
ITransport, Postal and Warehousing
JInformation, Media and Telecommunications
KFinancial and Insurance Services
LRental, Hiring and Real Estate Services
MProfessional, Scientific and Technical Services
NAdministrative and Support Services
RArts and Recreation
SOther Services


Until 2009-10, the market sector consisted of twelve industries (Divisions A to K and P of Australian and New Zealand Standard Industrial Classification 1993). The current market sector definition improves relevance in two key respects: it reflects the growing contribution of services industries in the economy; and improves economic coverage. The current estimates are not directly comparable to those published prior to the adoption of ANZSIC06 due to significant changes in coverage.

Q. Why do some industries not have productivity statistics?

A. While measures of labour productivity are published for the non-market sector (cat. no. 5206.0), non-market industries (ie. Divisions O, P and Q) are currently excluded from ABS MFP productivity estimates. The industries included in the non-market sector are:

OPublic Administration and Safety
PEducation and Training
QHealth Care and Social Assistance


Non-market industries are those industries in which the majority of output is provided free of charge or at prices which are not economically significant (in that there is only a weak relationship between price and the supply and demand for the good or service). Output measures for the non-market industries are typically derived using input costs and so by definition there is no productivity growth. Ownership of dwellings is also excluded from the market sector because no employment is associated with it.

Q. What is growth accounting?

A. Growth accounting involves decomposing gross output growth into contributions from growth in labour, capital and intermediate inputs and MFP. This framework provides an analytical tool to identify the underlying drivers of growth. ABS MFP statistics are compiled on the basis of the standard growth accounting framework, which is widely adopted by leading statistical agencies and recommended by the OECD. Growth accounting allows us to better understand the contribution of productivity growth to output growth, as well as the other drivers of output growth. 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.

Interpreting productivity results

Q. How is productivity data used?

A. Productivity statistics are useful performance indicators for the formulation and evaluation of policies involving long-term growth, efficiency and competitiveness. 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.

Q. How do I interpret productivity results?

A. The interpretation of productivity indexes depends on how output and inputs are measured. Ideally, the output indexes will measure all output produced from the input which is measured by the input indexes. Caution is required when interpreting productivity statistics due to the various inputs and output measurement issues and the complexity of the production processes. The ABS measures of productivity growth reflect a mix of factors, including:

  • technical change;
  • changes in processes, structures, knowledge or management practices;
  • reallocation of inputs between firms and industries;
  • changes in capacity utilisation or economies of scale;
  • investment and natural resources;
  • government policies and external shocks such as weather conditions and;
  • measurement error and revisions.

In practice, both output and inputs can be difficult to measure and, because productivity is estimated as a residual, the timing of output and input affects productivity indexes. For example, when production takes longer than a year, inputs will be measured before the corresponding output leading to a decline in measured productivity. For the Australian economy, examining MFP movements over growth cycles is a common approach for interpreting productivity performance over time, due to the short-term volatility of annual estimates.

Q. What are some limitations of productivity analysis?

A. Productivity estimates are subject to limitations in measurement, as not all inputs and outputs to a production process can be measured accurately. This may be due to inherent measurement difficulties, or because including that input or output is out of scope of the analysis. In either case, changes in an unmeasured input or output will affect productivity measurement and how it is interpreted. Examples of difficult to measure and usually unmeasured inputs include the weather, water, natural resources, intangibles such as organisational and social capital, and public capital, such as government provided infrastructure. They can have a significant bearing on how inputs are transformed into outputs, but are outside the current scope of ABS models.

Q. How can I get more information on productivity?

A. Free access to all published productivity data is available on the ABS website ( If you require more detailed information, or would like to speak to someone about productivity estimates, please email

We also recommend the following products for further information:

Data downloads

Tables 1 to 19: Estimates of industry multifactor productivity

Tables 20 to 26: Experimental estimates of industry multifactor productivity

Tables 27 to 42: Experimental estimates of state productivity

Previous catalogue number

This release previously used catalogue number 5260.0.55.002.

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