Experience and Productivity in Wage Formation in Finnish Industries
Service Skills Australia - Productivity in the Service Industries (2010)
Transcript of Service Skills Australia - Productivity in the Service Industries (2010)
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LABOUR AND SKILLS FORECASTING FOR THE SERVICE INDUSTRIES:
PRODUCTIVITY IN THE SERVICE INDUSTRIES
REPORT PREPARED FOR SERVICES SKILLS AUSTRALIA BY
MICHAEL LONG AND CHANDRA SHAH
Research Report
October 2010
CENTRE FOR THE ECONOMICS OFEDUCATION AND TRAINING
Prepared by:
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CONTENTS
1. THE 3P FRAMEWORK ........................................................................................................... 11.1 Population ...................................................................................................................... 11.2 Participation ................................................................................................................... 31.3 Productivity growth ........................................................................................................ 4
Types of measures ....................................................................................................... 6Cautions ....................................................................................................................... 8Australias productivity growth.................................................................................... 9
2. EDUCATION & TRAINING AND PRODUCTIVITY .................................................................. 123. SERVICES INDUSTRIES AND PRODUCTIVITY .................................................................... 13
3.1 By type of productivity ................................................................................................. 17Labour productivity .................................................................................................... 17Capital productivity .................................................................................................... 18Multifactor productivity - value-added (MFPVA) ....................................................... 18Multifactor productivity - gross output (MFPGO) ...................................................... 21
3.2 By industry .................................................................................................................... 22Wholesale trade ......................................................................................................... 22Retail trade ................................................................................................................. 23Accommodation & food services .............................................................................. 26Arts & recreation services ......................................................................................... 27
APPENDIX A: ANZSIC, PRODUCTIVITY AND SERVICE SKILLS AUSTRALIA ............................ 30ANZSIC ........................................................................................................................ 30Industry-level productivity estimates ........................................................................ 31Service Skills Australia, ANZSIC & productivity estimates ...................................... 32Wholesale trade ......................................................................................................... 34Retail trade ................................................................................................................. 34Accommodation and food services .......................................................................... 34Arts and recreation services ..................................................................................... 34Administrative support services................................................................................ 35Other services ............................................................................................................ 35SSA Industry sectors, ANZSIC and productivity estimates ...................................... 36
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TABLES and FIGURES
Tables
1. Net overseas migration, Australia 1985-89 to 2000 2
2. Population growth projections, 2010 to 2020 2
3. Trends in labour productivity by industry, Australia 1998-99 to 2008-09 17
4. Trends in capital productivity by industry, Australia, 1998-99 to 2008-09 19
5. Trends in value-added multifactor (labour and capital) productivity by industry, Australia, 1998-
99 to 2008-0920
6. Trends in gross output multifactor (labour and capital) productivity by industry, Australia 1997-98
to 2007-0821
7. Trends in gross output multifactor (labour and capital) productivity by industry, Australia 1997-98
to 2007-0824
A. ANZSIC divisions by market status and availability of productivity growth estimates 37B. ANZSIC sub-divisions, groups and classes within the Wholesale Trade division and percent of
persons employed in each group as a percent of persons employed overall and in the division
39
C. ANZSIC sub-divisions, groups and classes within the Retail Trade division and percent of persons
employed in each group as a percent of persons employed overall and in the division40
D. ANZSIC sub-divisions, groups and classes within the Accommodation and Food Services division
and percent of persons employed in each group as a percent of persons employed overall and in
the division
41
E. ANZSIC sub-divisions, groups and classes within the Arts and Recreation Services division and
percent of persons employed in each group as a percent of persons employed overall and in the
division
42
F. ANZSIC sub-divisions, groups and classes within the Administrative Support Services division and
percent of persons employed in each group as a percent of persons employed overall and in the
division
43
G. ANZSIC sub-divisions, groups and classes within the Other Services division and percent of
persons employed in each group as a percent of persons employed overall and in the division44
Figures
1. Average labour productivity growth by selected OECD countries, 2004 to 2008 8
2. Annual change in selected measures of productivity growth, 12 selected market industries,
Australia, 1973/74 to 2008/0910
3. Annual change in selected measures of productivity growth, 5-year moving averages, 12 market
industries, Australia, 1973/74 to 2008/0911
4. Labour productivity growth in OECD by industry, 1981-2007 13
5. Trends in labour productivity by industry, Australia 1998-99 to 2008-09 14
6. Trends in capital productivity by industry, Australia 1998-99 to 2008-09 17
7. Trends in multifactor (labour and capital) productivity by industry, Australia,
1998-99 to 2008-09 20
8. Trends in gross output multifactor (labour and capital) productivity by industry, Australia, 1997-
98 to 2007-0822
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Foreword
I am pleased to be able to present the report, Productivity in the Service Industries,which
the board of Service Skills Australia commissioned from the Centre of Economics inEducation and Training (CEET) at Monash University.
The report is released together with its sister work, Forecasts of Labour and Skills
Requirements in the Service Industry 2010-2015.
This report has been commissioned to encourage debate among stakeholders on the
nature of productivity measures and their application to industry. Whileon the surface
it may appear strange for a Skills Council to ask an economist to consider productivity
measures, the intent behind the work is to raise the question what do we actually mean
by productivity? This question is particularly pertinent when one considers the broader
ramifications of how the effectiveness of our national skilling system is harnessed, if it is
to contribute to a broader increase in national productivity.
The reportfor which we gratefully thank Michael Long and Dr Chandra Shahseeks to
explore a range of productivity measures as they apply to the service industries and
broader Australian industry. While it might be considered short-sighted to draw
conclusion of it depends which measures you use, Long and Shah do illustrate the
issues surrounding productivity by describing different measures and their application to
the service industries. They also provide a brief case study on a modern service industry
business and highlight how changes in this business may not be reflected in productivity
measures.
Service Skills Australia commends this report for consideration and we look forward to its
contribution to the broader debate and workforce development agenda.
Kit McMahon
General Manager
November 2010
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SUMMARY
This paper discusses aspects of productivity growth in selected service industries in
Australia. It is part of a larger projectLabour and skills forecasting for the services
industriescommissioned by Service Skills Australia (SSA). The focus is on the four
industry categories that overlap approximately with the coverage of the SSA:
Wholesale services
Retail services
Accommodation & food services
Arts & recreation services.
Productivity growth underlies improved living standards. Various measures of productivity
(labour, multifactorial, among others) are available, but productivity growth is essentially
the change in output at constant prices given some constant economic inputs such as
labour and capital.
The analyses in this paper are based on Australian Bureau of Statistics (ABS) estimates
of industry-level productivity growth, which are provided for selected broad categories of
the Australian and New Zealand Standard Industry Classification (ANZSIC). Careful
qualification of these estimates is required because of the sometimes poor
correspondence between ANZSIC categories and SSA industry sectors. Productivity
growth estimates are not available for some categories that contain part or all of SSA
industry sectors and the four most relevant ANZSIC categories for which productivity
growth estimates are available contain varying mixes of SSA sectors as well as sectors
that are not within the scope of the SSA.
Recent experience of productivity growth in Australia has not been encouraging with
lower growth over the last decade than during the 1990s.1 Value-added multifactor
productivity growth was negative in 2008-09.2 Productivity estimates over the short term,
however, can be affected by extraneous factors such as the business cycle and droughts.
In a future where workforce participation is expected to decline due to population ageing,
productivity growth is the major potential source of higher living standards. International
comparisons, however, suggest that recent growth in labour productivity has been low
Australia ranks fourth lowest out of 33 OECD countries.3
Service industries are frequently viewed as having inherently low levels of productivity
growth, partly because they are mostly labour-intensiveand the shift of employment
towards services industries is therefore viewed as a brake on overall productivity andeconomic growth. The term service industries, however, covers a broad spectrum of
market and non-market based industries whose productivity growth varies widely.
Productivity measures also typically do not reflect all of any improvements in the quality
of outputs and can therefore underestimate productivity growth especially in the service
industries.
1 See House of Representatives Standing Committee on Economics, 2010 Inquiry into raising the
productivity growth rate in the Australian economy. The Parliament of the Commonwealth of Australia,
Canberra. pp 31-57.2 ABS, Experimental estimates of industry multifactor productivity, Australia: detailed productivity estimates.
1985-86 to 2008-09. 5260.0.55.0023 OECD, OECD.Stat: DatasetLabour productivity growth, extracted 24 May 2010. Average 2004-08.www.oecd.org/statistics/productivity.
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Industry-specific estimates provide a more positive view of productivity growth in some
services industries over the last decade compared with average annual growth of 1.5% in
labour productivity and 0.2% in value-added multifactor productivity across 12 market
industries:
Wholesale services. Labour productivity growth (2.4% pa) and value-added
multifactor productivity growth (0.7% pa) were greater than the market average. Retail services. Labour productivity growth (2.2% pa) and value-added multifactor
productivity growth (1.1% pa) were greater than the market average.
Accommodation & food services. Labour productivity growth (1.4% pa) and value-
added multifactor productivity growth (0.3% pa) were about the market average.
Arts & recreation services. Labour productivity growth (0.8% pa) was less than the
market average while value-added multifactor productivity growth (0.6% pa) was
greater than the market average
Another measure, gross output multifactor productivity, covering a slightly different
period, shows that productivity in the Wholesale, Retail and Accommodation & food
service industries grew at, or slightly above the national average, while Arts & recreationservices grew below the market average.
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1. THE 3P FRAMEWORK
This paper discusses aspects of productivity growth in the Australian service industries. It
is part of a larger projectLabour and skills forecasting for the services industries
commissioned by Service Skills Australia (SSA).
It reviews the 3P framework for economic growthpopulation, participation and
productivity. The contribution of education and training to productivity growth is
considered, followed by a discussion of ABS industry-level productivity estimates and
their relationship to SSA industry sectors.
Productivity is part of the 3P framework frequently used to examine economic growth.
The three Ps are:
Population growth;
Participation in the workforce; and
Productivity.
The latter twoparticipation and productivityare arguably more important because they
directly relate to economic growth per person and hence to growth in living standards.
Population growth, however, arguably contributes to participation through its effect on
aggregate demand (and hence employment levels) and age structure and to productivity
through effects on economies of scale both in the public and private sector.
1.1 Population
Population growth potentially influences economic growth as both a source of demand for
goods and as a source of supply of labour. Australias population has been growing
recently at historically high levelsbetween 1996 and 2001 annual growth was 1.18%,
between 2001 and 2006 growth was 1.29% and between 2008 and 2009 population
grew by 2.07%. The main drivers of population growth in Australia have been immigration,
fertility and longevity.
After many years of decline, fertility rates during the last decade increased strongly from
1.73 in 2001 to 1.97 in 2008, levels that have not been reached since 19774. While in
the longer term higher fertility rates will contribute to increased labour supply, in the
short-term they may have the opposite effect as childcare makes participation in theworkforce more difficult. Current levels of fertility remain below those required for long-
term population replacement.
Table 1 shows the substantial increase in net overseas migration (the balance of
immigrants over emigrants) in recent years.
4 ABS, Births Australia, 2008 33010D010_2008. Table 1, Age-specific fertility and total fertility rates.
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Table 1 Net overseas migration, Australia 1985-89 to 2000
Year 1985-89 1990-94 1995-99 2000-04 2005 2006 2007 2008 2009
Net oseas migration 127,740 64,160 93,920 114,920 137,000 182,100 244,100 301,200 277,700
% of population 0.8 0.4 0.5 0.6 0.7 0.9 1.2 1.4 1.3
ABS, Australian demographic statistics 3101.0, average per year
The increasing life expectancy of Australians is also contributing to population growth,
although the ageing of the population profile also reflects past patterns of fertility and
migration.
There are several projections of future population growth. The ABS considered three
scenarios (Series A, B and C) for population growth that for 2010 to 2020. These
projections date from 2006 and even the highest has underestimated recent population
growth because of the high levels of net migration. The results and key assumptions are
shown in Table 2.
Table 2 Population growth projections, 2010 to 2020
Series Population
(000s)
Growth rate pa
%
Growth 2010-20
%
Net oseas
migration
Fertility rate
Series A 26,098,4 1.68 18.3 220,000 2.0
Series B 25,993.3 1.64 17.8 180,000 1.8
Series C 25,948.8 1.62 17.6 140,00 1.6
ABS, Population Projections, Australia, 3222.0.
By comparison, the assumed levels of migration underlying the three scenarios used by
Skills Australia in their modelling of demand for skillsOpen Doors, Low-trust
Globalisation and Flagshave a much broader spread250,000, 200,000 and 100,000
respectively5. All three scenarios assume a fertility level of 1.8, which acts to moderate
some of the differences between the ABS and Skills Australia estimates. Nevertheless,
the population projections of the Open Doors scenario are higher than the highest ABS
projections, while the Flags scenario population growth projections are lower than the
lowest ABS scenarios.
Treasurys Intergenerational Report 2010is underpinned by projections of Australias
future population growth.6 It assumes a fertility rate of 1.9 with net overseas migration ofaround 244,000 for the years 2007-09 falling to a sustained 180,000 from 2012
onwards. Net overseas migration is then assumed to continue at about 0.6% of the total
population--similar to levels that have prevailed historically. These assumptions resulted
in the widely discussed estimates of an Australian population of 35.9 million by 2050an
annual growth rate of 1.2% per annum, or somewhat lower than the historical average
1.4%. The growth is higher in the next decade than in subsequent years.
5 Access Economics, 2009. Economic modelling of skills demand. Report for Skills Australia.
www.skillsaustralia.gov.au/PDFs_RTFs/AE_Skills_Demand.pdf6 Circulated byThe Hon. Wayne Swan MP, 2010. Intergenerational report 2010. Australia to 2050: future
challenges. Treasury, Canberra
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A recent report by BIS Shrapnel notes a rapid decline in net overseas migration already
and expects it to fall to 145,000 persons per year as early as 2011/12, with population
growth declining to 1.3% in the near term.7
Comparison among the various sets of population projections is not as straightforward is
might be expected because of the differing combinations of assumptions that are used
and the ways in which these are expressed. Net overseas migration levels are the most
volatile and difficult to predict element of population growthand in Australia, migration
is an important contributor to total population growth.
Comparison among the various sets of population projections is not as straightforward is
might be expected because of the differing combinations of assumptions that are used
and the ways in which these are expressed. Net overseas migration levels are the most
volatile and difficult to predict element of population growthand in Australia, migration
is an important contributor to total population growth.
The Skills Australia population projections are those most relevant to education and
training policy. The projections of population growth underlying the Open Doors scenario
the scenario that has been the major focus of policy developmentmay be too high
because they assume that historically high level of net overseas migration that prevailed
between 2006 and 2008 will continue. Even the more conservative assumptions
underlying the Low-trust Globalisation scenario may prove to be too high. The impact on
both estimates of demand for skills and supply of skills is direct, but it is less clear what
any impact might be on the balance between supply and demand.
1.2 Participation
Participation refers to the proportion of the population participating in the labour force
that is, either working or looking for work. It is usually defined in terms of an age profile
persons aged 15 to 64 years or persons 15 years or older. With the ageing of the
population, interest has focused on the broader age defined participation rate that
includes older people.
Changes in the level of employment of the population can directly affect the level of
economic growth. All else equal, the greater the proportion of the population that is
employed, the higher will be the level of economic growth. Participation, however, is a
catch-all phrase for employment levels and includes several aspects:
Participation overall;
Unemployment; and
Hours of work.
Projected participation rates are usually predicated on the assumption that
unemployment rates and average hours of work (or the mix of full- and part-time work)
are unchanged or change in some known manner.
Assumptions underlying estimates of population growthparticularly the interaction
between fertility, migration and mortalitycan affect estimates of future participation in
7www.bis.com.au/verve/_resources/Rel_PopulationGrowth_FINAL_file.pdf
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the labour force. Higher population growth rates depend on assumptions of higher rates
of net overseas migration which implies that a higher proportion of the population will be
in the prime working ages of 15 to 64 years. Higher population growth, all else equal, is
also likely to be associated with lower levels of unemployment.
These issues are explored extensively in The Intergenerational Report 2010. The reportprojects that the labour force participation rate for people aged 15 years and over will to
fall from current levels of about 65% to less than 61% by 204950a decline that will
reduce economic growth per capita. The overall trend, however, is not uniform across the
40-year period covered by the projections. In particular, over the next five years or so,
participation rates are expected to increase slightly.
The expected increase over the next five years or so continues a longer-term trend of
increasing participation rates underpinned by the age profile of the population, higher
participation by women and, in the last decade or so, higher participation by older males.
Changes to child care arrangements, the retirement age and arrangements for access to
superannuation are part of the policy response to increase (or at least minimise any
decline) in participation in the longer term.
The Skills Australia scenarios imply different levels of labour force participation by 2025
Open Doors (67%), Low trust globalisation (64%) and Flags (63%). These estimates are
not directly comparable with the longer-term Treasury forecasts of less than 61% by
2049-50 because of the initial improvement in participation rates during the period, but
the forecasts for the Open Doors scenario in particular appear to be higher than Treasury
estimates.
The implications for economic growth of the different levels of participation in the three
Skills Australia scenarios are amplified by differences in the implied unemployment rates
which are inversely related to participation. The size of the workforce under the three
scenarios reflects mutually reinforcing levels of population, participation and
unemployment.
1.3 Productivity growth
Productivity measures relate real physical output to real input and measures of
productivity growth relate changes in physical output given constant real inputs. The most
common way of thinking about improvements in productivity is in terms of technology or
techniqueperforming a task more efficiently. There are, however, many possible
contributors to changes in productivity. In addition to innovation in technology or
technique productivity can be influenced by:
The quality of the workforcea more skilled workforce in many circumstances can
produce more than a less skilled workforce allowing for the costs of training and
possibly higher salaries. Similarly a healthy population and workforce can be moreproductive.
Workforce strategiespolicies designed to motivate, better deploy and retain staff
can improve productivity.
Capacity utilisationif plant can be used for three shifts a day instead of two, the
same semi-fixed capital and land can be used to produce more output.
Economies of scaleapplying the same production processes and approaches can
often be more effectively implemented on a larger scale.
Natural disastersdrought, for instance, can reduce agricultural output given the
same inputs of labour, capital and intermediate goods.
Government regulationtoo little or too much regulation can reduce economicproductivity.
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The Coffee ShopCoffee shops have a particular fascination for financial writerspossibly because they are an
enterprise with which many of their readers are familiar. Tim Harford, in the Undercover
Economist uses the coffee shop as a basis for discussion of the economic theories of pricing,
scarcity, competition, free trade and economic rent.8 More recently Buttonwood, writing in The
Economist, used coffee shops as an example of market forces.9 Buttonwood is interested in the
organisation of coffee shops, their efficiency and its relationship to competition. In an informal
observational study he notes the efficiency of the division of labour used in his local Starbucks
one person taking the orders, another the cash and a third making the drinksreminiscent of
Adam Smiths classical discussion of a pin factory. And it is in large part the organisation of
resources that drives productivitymore or better output given constant inputs.
Coffee shops display several other aspects of productivity growth apart from front-of-shop
organisation. A feature of the coffee shop market has been the rise of the large national and
international chains of coffee shopsStarbucks, Gloria Jeans, the Coffee Club, Michels and
Hudson Coffee, among others, in Australia. This tendency parallels the rise of other large chains
in retailing including supermarkets, department stores, clothing, hardware, and fast food. Apartfrom market power, greater size creates economies of scale with potential advantages in many
areas including branding, purchasing of product and coffee-making machines, management
and training. To the extent that retail chains are efficient and there is competition, larger chains
are likely to continue to expand at the expense of smaller firms and with that expansion,
productivity in the industry should increase. Improved productivity, however, is not limited to the
larger chains. Competition will also stimulate smaller firms to improve their productivity.
The use of larger, faster espresso machines can improve labour productivitymore coffee per
barista hourbut its effect on capital or multifactor productivity may be moot. Nor does
improved productivity necessarily translate into improved profitability. Given competition, the
rewards of improved productivity are often only continued survival. Although circumstances may
vary across locations, in London at least the profitability of coffee shops seems to be lowan
artefact of the level of competition and the economic rents paid by coffee shops for preferable
locations.10
The coffee shop highlights a problem encountered in the measurement of productivity,
particularly in service industrieschanges in the quality of the product and service. The output
might be measured in terms of annual mega litres of coffee, but that coffee can be of varying
quality. Measurement of productivity may not reflect a shift in the mix of output towards better
quality coffee. On the other hand, however, if the better quality coffee results from the
employment of better trained baristas, possibly at higher wages, measurements of labour input
in terms of simply hours of work will also be unchanged (although if the coffee shop pays for the
training, it will be recorded as an input). Similarly, if the quality increases through the purchase
of better quality coffee beans, increased inputs costs may also not be measured. Changes in
the strictly service component of the transactionmore prompt filling of orders, a greater varietyof product or more congenial surroundingsis not likely to be reflected in productivity
measures.
8 Harford T, 2006. The undercover economist, Little Brown, London.
9 Buttonwood (pseud), Productivity and coffee shops, Buttonwoods Notebook, The Economist, 5 Apr 2010http://www.economist.com/blogs/buttonwood/2010/04/consumers_and_queues
10 Harford T, 2006. ibid. p. 8
http://www.economist.com/blogs/buttonwood/2010/04/consumers_and_queueshttp://www.economist.com/blogs/buttonwood/2010/04/consumers_and_queueshttp://www.economist.com/blogs/buttonwood/2010/04/consumers_and_queues -
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Types of measures
Measures of productivity can vary in the extent to which they seek to include or exclude
the different ways in which fixed inputs can provide more output. Additionally there are
different types of productivity measures. Since this report draws extensively on the ABSs
Experimental estimates of multifactor productivity, the following discussion focuses on
the four measures provided from that exercise:11
Labour productivity(LP) estimated by dividing an index of the volume of value added
(VA) for an industry by an index of labour input (L), that is,
LP = VA / L or LP = (GO - I) / L.
Capital productivity(KP), estimated by dividing an index of the volume of value added
(VA) for an industry by an index of capital inputs (K), that is,
KP = VA / K orKP = (GO-I) / K.
Multifactor productivity-value added, (MFPVA) is estimated by dividing an index of the
volume of value added by a combined index of labour (L) and capital (K) inputs, that
is,
MFPVA = VA / (KL) or MFPVA = (GO-I) / (KL)
Multifactor productivity-gross output, (MFPGO), estimated by dividing an index of the
volume of gross output (GO) by a combined index of labour (L), capital (K) and
intermediate (I) inputs (IKL), that is,
MFPGO = GO / (IKL)
The industry-level measures of MFP mostly use the methodology and data that underlie
national estimates of market sector productivity published in association with the
national accounts. A difference is that net taxes on products (sales tax, excise tax and
GST less any subsidies) are excluded from the industry-level estimates but are included in
the published aggregate. Hence analyses are conducted in basic prices rather than
purchaser prices.
These measures are constructed from a series of indexes based on data drawn from the
ABSs statistical survey program as well as government administrative collections.
Inputs and outputsindexes based on the industry value added, gross output and
intermediate inputs indexes.
Price indexesindexes that are intended to facilitate comparison of the value of
inputs and outputs over time and are used in the construction of all four measures of
productivity.
Labour inputsan index based on hours worked in an industry from the ABS Labour
force survey. Hours worked includes the labour of employees, the self-employed and
proprietors of business. It does not include voluntary labour. The measure is used in
estimates of labour productivity and as part of a combined measure in estimates ofMFP.
Capital inputsthe industry capital services index is based on weighted changes in
the estimated productive capital value of assets.
11 See ABS, Experimental estimates of industry multifactor productivity Australia, 2007. Information paper,
5260.0.55.001; ABS, Estimating industry-level multifactor productivity for the market-sector industries inAustralia: Methods and experimental results. Research paper, 1351.0.55.004; and ABS, Experimental
estimates of industry multifactor productivity, Australia: Detailed productivity estimates, 5260.0.55.002.
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Combined capital and labour inputs (value added)an index that combines the
labour and capital indexes using the respective income shares of capital and labour
within the industry and used in estimates of value added MFP.
Combined capital and labour inputs (gross output)an index that weights the labour,
capital and intermediate input indexes by their respective cost shares and is used inestimates of gross output MFP.
Income share indexan index that reflects the division of income between capital and
labour within industries and is used to weight capital and labour inputs for MFPVA and
as a proxy for costs in MFPGO.
Labour productivity and (the far less used) capital productivity are partial measures of
productivity growth. They measure changes in output associated with changes in the
input of either labour or capital respectively. The main limitation of partial productivity
measures is that they attribute to only one factor of productionlabour or capital
changes in output that can be more properly attributed to all factors of production or to
changes in the inputs of another factor.
Nevertheless labour productivity is possibly the most widely used productivity measure,
partly because it is relatively easily measured (hours of work is a fairly straightforward
metric) and possibly because it is the form most closely related to changes in living
standards. Increases in labour productivity, given constant workforce participation and
some other caveats, usually translates into increased GDP per capita.
Conceptually changes in labour productivity can be disaggregated into:12
capital deepeningthe relative increase in capital per worker employed. For instance,
if the amount of labour is held constant but the equipment is improved, output per
worker can improve.
MFPmeasures the ratio of growth in output to growth in two or more factor inputsand reflects that part of the change in output that cannot be explained by changes in
the combined inputs. For instance, if a firm makes no changes to its labour, capital or
other inputs, but is able to increase its output, its multifactor productivity has
increased.
An important difference among the measures of productivity is whether they are based on
value added output orgross output. The first three (labour, capital and MFPVA) are value
added measures while the last (MFPGO) is based on gross output. The difference between
these two approaches depends on the way in which intermediate goods and services
(that is, goods and services that are inputs to the production process) are treated. In the
value-added measures, intermediate goods are subtracted from gross output to calculate
the value added by the production process. The value added is therefore the differencebetween final outputs and initial (non-labour, non-capital) inputs13. For gross output
measures, however, intermediate inputs are included separately among the inputs.
Although this may appear only a subtle difference, it has implications for the size and
meaning of the two MFP measures, which suggests that MFPGO may be a technically
superior measure.
12 Access Economics, 2009. Economic modelling of skills demand. Report for Skills Australia.
13 More formally, value added is the weighted difference between growth in constant price gross output andintermediate inputs, with the current price shares of value added and intermediate inputs in gross output
as weights.
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Figure 1 Average labour productivity growth by selected OECD countries, 2004 to2008
OECD.Stat 24 May 2010.
Value-added and gross output measures of productivity mostly show similar trends,
although the nature of their calculation means that the absolute changes in the MFPGO
are less than for the MFPVA. Because value-added based MFP measures do not
separately identify changes in intermediate goods they are more sensitive to changes
that affect the proportion of inputs to production contributed by intermediate goods and
services such as outsourcing.
On the other hand, industry-level value-added based MFP measures are more closely
aligned with, and easier to calculate from, national accounts. And the method of
calculation means that estimates of MFPVA for a given year are usually available nearly
12 months earlier than the corresponding MFPGO estimate.
Cautions
The descriptor experimental is a caveat on ABS estimates of industry level productivity
growth. In the context of the efforts in other countries, however, the caution may be
somewhat overstated. Conceptual and data difficulties are inherent in the task of
measuringproductivity and awareness of some of these problems may contribute to viewof the results as more indicative than definitive. Some of the problems are:
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Changes in quality. Some changes in the quality of production (which should be reflected
in any changes in measured output) are captured in the price data used to deflate the
current price estimates but the final output measures may not adequately capture all
quality changes. It is particularly difficult to perform accurate quality adjustment for
service industries, as change in the quality of service is very difficult to measure
objectively because of the intangible nature of the product and the data required. If
the extent of quality change is not completely captured in the data, output growth and
MFP may be understated.
Effects of the business cycle. To the extent that productivity measures reflect the effects
of the scale of production, capacity utilisation, substitution between labour and capital
and changes in resource allocation more generally, they may be sensitive to the
business cycle. ABS commentary on the measures, therefore, refers to productivity
cycles and the need to compare productivity from peak to peak when economic
conditions are assumed to more similar. The timing of these peaks, however, may not
be consistent across industries. As with any time series data, and perhaps more so
with productivity measures, conclusions can vary according to the choice of start andend years.
Intra-industry transfers. Estimates of gross output for industry-level productivity should be
limited to the value of goods and services produced for use outside the industry
output created by firms within an industry for use by other firms within an industry
should be removed. Estimates of productivitygrowth, however, will only be affected if
the relative size of intra-industry transfers changes. The consequent uncertainty in
estimates of productivity growth is greatest in industries with higher levels of within-
industry trade such as Manufacturing and Construction and least in service industries
where much of production is for the end user. ABS estimates of industry-level
productivity do not exclude these transfers because there is no reliable Australian
data.
Australias productivity growth
With the projected longer-term decline in labour force participation due to the ageing of
the population profile, improvements in labour productivity will be the major contributor
to future growth in GDP per capita. Australias growth in value-added labour productivity
has not been strong by international standards and recent growth has been low by
historical standards. Figure 1 shows comparisons of average labour productivity among
OECD countries over a recent five-year period. Australia ranked fourth lowest out of the
33 countries for which data is available.
The measure of labour productivity underlying this figure differs from that used elsewhere
in this report. The estimates are drawn directly from the respective National Accounts of
member countries. They are expressed in purchase prices because they include taxes
and subsidies and they are for the entire market economy rather than the 12 core
industries that underlie the Australian experimental estimates. While there are the usual
caveats on OECD-derived international comparisons because of the potential for
differences in methodology among countries as well as further caveats because of the
inherent difficulties in the measurement of labour productivity, the message is not
encouraging for growth in living standards.
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Figure 2 Annual change in selected measures of productivity growth, 12 selected
market industries, Australia, 1973/74 to 2008/09
ABS, Experimental Estimates of Industry Multifactor Productivity, Australia: Detailed
Productivity Estimates. 5260.0.55.002.
Figures 2 and 3 are based on the same set of experimental estimates for 12 core market
industries in Australia. Both figures show results for value-added labour, capital and MFP
productivity growth and for gross output MFP. The gross output MFP estimates are
available only from the 1990s and were not available for 2008-09 at the time of writing.
Figure 2 shows the results for each year separately, while Figure 3 presents a five-year
moving average of the same estimates.
Figure 2 shows the often-substantial year-to-year variation of estimates and underlines
the care required in the selection of start and end points when examining trends in
productivity over time. To some extent, and without a great deal of precision, the
relationship between productivity growth and the business cycle can also be seen in the
changes in productivity growthwith quite severe troughs corresponding to the economic
contractions of the mid 1970s, the early 1980s and 1990s and most recently in 2008-
09.
Figure 3 shows the same values expressed as a five-year moving average. The moving
average removes much of the year-to-year variation and allows longer-term trends to
appearalthough the change in the scale of the vertical axes between the two figuresdoes not make the full impact of the smoothing immediately apparent. The somewhat
cyclical movements in productivity growth are possibly clearer as is the consistent
location of MFPVA growth approximately halfway between labour and capital productivity
growth (MFPVA is not a simple average of labour and capital, but involves a weighting by
income share).
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Figure 3 Annual change in selected measures of productivity growth, 5-year moving
averages, 12 market industries, Australia, 1973/74 to 2008/09
ABS, Experimental Estimates of Industry Multifactor Productivity, Australia: Detailed
Productivity Estimates. 5260.0.55.002.
The series for MFPGO is now even shorter because of the five-year moving average. For
the years for which comparisons are available, however, MFPGO growth is less than MFPVA
growth, a feature that partly results from the arithmetic of their calculation. The pattern of
growth of MFPGO is also similar to that of MFPVA, but, as expected, is flatter.
In recent years all four productivity growth measures have been declining, although three
measures (excluding capital productivity) have remained positive. Definitive interpretation
is not possible. Recent decline may be repeating earlier patterns of an initial substantial
increase following a decline in economic activity with gradual decline in productivity until
the next recession. On the other hand, the period in the mid and late 1990s witnessed a
period of gradually increasing productivity growth after the recession of the early 1990s
until it peaked before declining through much of the 2000s. Whether the relatively high
productivity growth during that period will be recovered after the global economic crisis is
difficult to forecast.
The Intergeneration report observes that labour productivity grew by 1.6% per year overthe last three decades but has averaged only 1.4% in the past decade compared with
2.1% in the 1990s. The measures used in this and other reports are derived directly from
Australias National Accounts and are higher than the Experimental estimates for
methodological reasons outlined above.
The three Skills Australia scenarios assume labour productivity growth to 2025 of 1.75%,
1.50% and 1.35% respectively, with productivity for the high growth Open Doors scenario
driven by policies that encourage trade, population movements and skills formation. In
the context of productivity growth in the 1990s of 2.1%, the higher end assumption of
1.75% is within reasonable bounds, although optimistic, while the latter two estimates
are closer to recent experience.
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2. EDUCATION & TRAINING AND PRODUCTIVITY
The trend in economic theory and research over the last several decades has been to
highlight the importance of investment in human capital (the skills, knowledge and ideas
of workers) as the basis for sustained economic growth rather than investment in
machines and buildings.
Government commitment to higher levels of education and training is expressed in the
Council of Australian Governments (COAGs) and other educational attainment targets for
the Australian population and the financial commitments made in order to achieve those
targets. The targets span the school, VET and higher education sectors. Those most
relevant to the VET sector are:
To halve the proportion of Australians ages 20-64 without qualifications at
Certificate 3 level and above between 2009 and 2020; and
To double the number of higher [VET] qualification completions (diploma and
advanced diploma) between 2009 and 2020
The link between education and training and participation, productivity and economic
growth is in the first instance indicated by the simple observation of the association
between higher levels of educational qualifications, higher earnings (wages are deemed
to reflect the labour productivity of individuals) and labour force participation (again a
reflection of the productivity of individuals). The link is further supported by more detailed
statistical analyses that attempt to isolate the separate effect of an individuals education
on their earnings and likelihood of employment. Beyond these are the often more than
satisfactory levels of estimates of rates of return to education and training treated as an
investment.14
Analyses of the links between education and training and productivity extend beyond the
individual to the influences of workforce development and workforce qualification on
competitiveness and productivity of firms and to analyses of education and productivity
growth between-countries and over time. The links between education and economic
growth extend to a web of positive individual effects on health, investment decisions and
consumer behaviour among others to more society and economy-wide effects on reduced
crime and social welfare expenditure and expansion of general and institutional trust and
civic co-operation.
Education attainment has characteristics that suggest that it can have effects beyond the
individual that lead to on-going, sustainable economic growth.15 Once produced,
knowledge, ideas and techniques can be used by many people at the same time fordifferent purposesand ideas can be combined to produce new ideas. To the extent that
knowledge, ideas and techniques build on each other, they provide the basis for self-
sustaining and on-going improvements in productivity and economic growthand to the
extent that education contributes to the production and adoption of new knowledge,
ideas and techniques, increased levels of education contribute to increased rates of
productivity and economic growth.
14
See Long M & Shah C, 2008. Private returns to vocational education and training qualifications. NCVER,Adelaide.
15 See Keeley B, 2007. Human capital: How what you know shapes your life, OECD, Paris.
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3. SERVICES INDUSTRIES AND PRODUCTIVITY16
Historically productivity improvements in the service industries have been assumed to be
low, partly because service industries are mostly labour intensive and partly because the
delivery of the service is presumed to be relatively immutable. The archetypal example is
a performance of Mozarts string quintet in G Minorit took five musicians to perform it in1787 when it was composed and it takes five musicians today. If it is performed properly,
it should take just as long to be performed now as it did then, and there will be little if any
consistent improvement in quality. All that changes is cost.17
A broader theory of long-term decline in productivity growth in advanced economies was
built on this claimthe shift of production away from higher productivity growth
manufacturing and related industries to low productivity growth service industries implied
a decline in average productivity growth.
The typical scenario is summarised in Figure 4, which shows labour productivity growth
for the manufacturing and service sectors averaged across 15 OECD countries for 1981
to 2007. The contrast is starkaverage growth in manufacturing has been 4.5% per year
compared with only 1.6% per year in the services sector.
Figure 4 Labour productivity growth in OECD by industry, 1981-200718
The service sector is often very broadly defined and may include the major industry
groupings of wholesale and retail trade, finance, insurance, communications, public
utilities, transportation, and government, as well as business and personal services.
Sometimes the scope can be even broader. A recent review of productivity in Australia
seemed to exclude only Agriculture, Forestry and Fishing, Mining and Manufacture as well
16 This section draws heavily on ABS, Experimental estimates of industry multifactor productivity Australia,
2007. Information paper, 5260.0.55.001; ABS, Estimating industry-level multifactor productivity for the
market-sector industries in Australia: Methods and experimental results. Research paper, 1351.0.55.004;
ABS, Experimental estimates of industry multifactor productivity, Australia: Detailed productivity estimates,
5260.0.55.002 and ABS, Australian system of national accounts, 5204.0.
17Baumol WJ, 1967. Macroeconomics of unbalanced growth: the anatomy of urban crisis, American
Economic Review, 57 (3), 415-426. The argument is known as Baumols cost disease. 18 Adapted from OECD, OECD science, technology and industry scoreboard 2009, OECD, Paris. Figure 2.1.2,
from STAN database, 21-Sep-2009.
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as Ownership of Dwellings from the services sector.19Giving the services sector such a
wide scope may deprive the term of any meaning and combine industries with differing
rates of productivity growth. A narrower definition that restricts the scope to mostly labour
intensive industries and that draws a distinction between market and non-market (that is,
mostly government) sectors seems more useful.
To return to the previously cited example of the string quintet, there may be greater scopefor productivity growth than appearances suggest. The activities of a string quintet are
part of the Arts and Recreation Services Division. The output might be measured simply
as the number of hours of public performances the quintet plays in a given year.
Compared with a string quintet playing the same music in some previous period, this
measure might be increased by better transport (they spend literally less time on the
road). If, however, their output is measured by the number of people hearing them play by
the number of hours they play, their output could also be improved by performing in
larger venues. Their productivity can be vastly extended if digital recordings are made of
their performances and soldmany more people can listen to and watch their
performances even when they are not playing. It might be argued, however, that to
achieve this last increase in productivity the string quartet is now providing a commodity
rather than a service. 20
Figure 5 Trends in labour productivity by industry, Australia 1998-99 to 2008-09.
See Table 3
Productivity growth has varied among service industries and within service industries
across countries.21 For the years 1995-2000, for instance, the OECD reports strong
increases in annual labour productivity growth (3% or higher) for selected OECD countriesin Wholesale and retail (Norway, Sweden, USA, Canada), Transport and storage (Germany
and Sweden), Post and communications (many countries), Financial services (many
countries). There was, however, little growth in Community, personal and social services.
19 See House of Representatives Standing Committee on Economics, 2010 Inquiry into raising the
productivity growth rate in the Australian economy. The Parliament of the Commonwealth of Australia,
Canberra. p. 73. Ownership of dwellings is a source of GDP recognised in National Accounts, but is not an
industry within ANZSIC.
20 Making digital recordings and sales might shift their main activity from the Arts & recreation services
industry to the Information, media and telecommunications industry, as discussed later and in Appendix A.
21 Wlfl A, 2003. Productivity growth in service industries: An assessment of recent patterns and the role ofmeasurement. STI Working Paper 2003/7, Economic Analysis and Statistics Division, OECD. Results for
Australia were not included in the analyses.
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Measurement of productivity growth is difficult and in the service industries is particularly
difficult. Some commentators have suggested that it is close to impossible.22 Others have
suggested that estimates of long-term decline in productivity, often associated with some
service industries, simply do not make sense23.
While productivity growth may vary and even be negative for understandable reasons for
particular industries and even countries in the short-term, estimates of longer-term
negative growth suggest that there are problems with the measurement of productivity.
The first recommendation of the 2010 parliamentary inquiry into raising productivity
growth in Australia was:24
That the Australian Bureau of Statistics (ABS) investigate alternative ways of
measuring the optimal available use of economic resources used in services
industries in the economy, either by:
o Excluding those services sectors which do not have straight-forward
quantifiable input and output data from the aggregate MFP estimates and
instead developing a separate services sector index which is not necessarily
based on traditional productivity constructs; or
o Investigating ways to develop robust services sector MFP estimates for all
services industry categories for inclusion in the aggregate MFP estimates. The
government should ensure that the ABS is funded appropriately to conduct the
study.
The immediate basis of the recommendation was the recognition that changes in theservice sector are more likely to be in quality rather than quantity and it is difficult to
measure qualityhence standard measures of productivity will understate productivity
growth in the services sectors.
The broad scope of the use of the term service industries, however, also means that
part of the motivation is that a substantial part of the service industries are not market-
based and hence their productivity is unmeasured by standard National Accounts
approaches.25
It is difficult to estimate productivity growth for the non-market sector (mostly
government-provided services such as education, health and social services) because
there are no market prices with which to value output. Instead, input costs are often
used. On this basis there is frequently little measurable productivity growth in the non-
market service sector.
22 Grilches Z, 1994. Productivity, R&D and the Data Constraint,American Economic Review84 (1994): 1-23,
claims that productivity numbers are half reasonable for about a third of the US economy, mostly, but not
entirely, due to the non-market services economy.
23 Wlfl A, 2003. Op cit.
24
Op. cit. p.xix25 Although this difficulty is widely recognised, some (but not all) improvements in quality are captured in
price movements and other industries also deliver increased productivity as improved quality of output.
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The difficulties in estimating productivity growth, however, are somewhat reduced when
the service industries are mostly in the market sector and market prices are available for
inputs and outputs. Concerns remain about the ability to capture adequately changes in
quality of services providedbut this can also be a problem in estimating productivity
growth for the manufacturing sector.
The following discussion focuses on productivity growth in four ANZSIC-defined industriesin the market sector of the service industries that overlap with the scope of SSA:
Wholesale trade industry
Retail trade industry
Accommodation & food services industry
Arts & recreation services industries.
The correspondence between these ANZSIC-based categories and the industry sectors
identified by SSA is mixed.
The discrepancies are:
The four ANZSIC categories do not include several SSA industry sectors.
o Beauty, Hairdressing and Funeral services are located in ANZSICs Other
Services division for which productivity growth estimates are not available.
o Travel agents and tour booking agencies are located in ANZSICs AdministrativeSupport Services division for which productivity growth estimates are not
available.
The four ANZSIC categories contain industry sub-divisions, groups and classes that
are not within the scope of the SSA:o Parts of the Wholesale trade divisionmainly agricultural products (wholesale
nursery, meat wholesaling and seafood wholesaling and timber), electricity and
gas and automotive vehiclesare not within the scope of SSA.
o Parts of the Retail trade division motor vehicles and motor vehicle parts, plant
nurseries, fresh meat, fish, poultry, fish and vegetables, pets, electricity and
gas, timber merchandising and retail bakeriesare not within the scope of SSA.
o The Arts and Recreational Services division includes horseracing which is not
within the scope of SSA.
One ANZSIC division can incorporate several SSA industry sectors. For instance, the
Retail, Community Pharmacy and Floristry sectors fall within ANZSICs Retail Trade
division and hence separate productivity growth estimates are not available.
An industry such as tourism, defined on the basis of different services delivered to
a common client, is not easily identified within ANZSIC, where the industry
categories are defined on the basis of similarity of process and output.
Further details are provided in Appendix A.
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3.1 By type of productivity
This section discusses productivity growth in the services and other industries by the four
measures of productivity in the ABS estimates:
Value-added labour productivity
Value-added capital productivity
Value-added multifactor productivity
Gross output multifactor productivity.
Table 3 Trends in labour productivity by industry, Australia 1998-99 to 2008-09
1998-09
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
Annualchange
Comp.growth
Agriculture 100.0 100.7 109.0 110.4 102.9 132.2 142.4 153.8 123.8 132.1 149.4 4.8% 4.1%
Mining 100.0 111.2 123.2 123.8 112.6 100.2 96.8 81.9 83.6 81.0 71.8 -2.9% -3.3%Manufacturing 100.0 101.0 106.5 112.0 111.9 117.8 114.8 118.4 121.6 122.5 120.5 1.9% 1.9%
Utilities 100.0 101.6 100.4 96.7 93.0 90.0 86.5 80.7 79.9 74.0 68.8 -3.6% -3.7%
Construction 100.0 95.8 87.1 95.8 106.0 103.4 102.4 105.3 103.0 107.2 103.8 0.5% 0.4%
Wholesale 100.0 99.7 104.1 107.7 110.7 114.6 119.7 124.2 117.6 126.9 126.9 2.5% 2.4%
Retail 100.0 98.2 101.4 105.8 104.1 110.2 110.4 111.1 114.6 117.6 123.8 2.2% 2.2%
Accom & food 100.0 99.7 100.2 102.3 105.9 106.4 108.9 113.9 117.6 113.0 115.3 1.5% 1.4%
T'port & store 100.0 102.5 102.9 110.6 116.8 114.9 118.1 121.6 126.1 124.2 117.3 1.7% 1.6%
Communication 100.0 91.0 90.4 101.7 99.6 108.6 103.9 106.3 110.0 124.4 126.5 2.6% 2.4%
Financial 100.0 104.9 105.4 106.9 108.7 114.5 115.5 116.7 121.3 126.3 126.3 2.4% 2.4%
Arts & Recn 100.0 104.4 111.5 103.6 106.5 114.0 114.2 107.3 111.7 105.3 108.0 0.9% 0.8%
Market 100.0 99.7 101.8 106.0 107.7 111.2 111.3 113.7 114.9 116.6 116.3 1.5% 1.5%
Adapted from ABS, Experimental Estimates of Industry Multifactor Productivity, Australia, Detailed
Productivity Estimates, 5260.0.55.002
Labour productivity
Labour productivity in Australias market economy grew 16.3% between 1998-99 and
2008-09 with a compound growth rate of 1.5% per annum over the period (Table 3). The
compound yearly growth measure suggests that labour productivity in (especially) the
Wholesale (2.4%) and Retail industries (2.2%) grew faster than average while labour
productivity growth in the Accommodation & food (1.4%) was well about average and was
well below average in the Arts & recreation industry (0.8%).
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Figure 6 Trends in capital productivity by industry, Australia 1998-99 to 2008-09
See Table 4.
Among other industries, labour productivity grew most strongly Agriculture (4.1%) and in
Communication (2.4%) and Financial services (2.4%) and least strongly in the Mining (-
3.3%) and Utilities (-3.7%) industries.
Capital productivity
Value-added capital productivity in Australias market economy declined by 12.7%
between 1998-99 and 2007-08an annual compound decline of -1.3% over the period
(Table 4). The compound annual growth measure of capital productivity shows that the
decline was least in Arts & recreation (0.1%) and well below average for the Wholesale
industry (-2.5%) and the Retail (-1.8%) and Accommodation & food service (-1.8%)
industries.
Among other industries, capital productivity declined most strongly in the Utilities (-2.8%),Mining (-2.7%) and Manufacturing (-2.2%) industries while Agriculture (1.9%) experienced
well above average growth.
Multifactor productivity - value-added (MFPVA)
Value-added multifactor productivity in Australias market economy grew by just 1.7%
from 1998-99 to 2008-09a compound rate of 0.2% per annum over the period (Table
5). All four service industry groupings grew more rapidly than average. The compound
annual growth measure shows that MFPVA grew most quickly for the Retail industry (1.1%
per year) and the Wholesale industry (0.7% per year), followed by Arts & recreation (0.6%
per year) and by Accommodation & food services (0.3% per year).
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Table 4 Trends in capital productivity by industry, Australia, 1998-99 to 2008-09
1998-09
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
Annualchange
Comp.growth
Agriculture 100.0 106.6 110.8 113.9 90.7 112.9 116.2 117.6 99.1 104.9 120.3 2.6% 1.9%
Mining 100.0 102.6 110.1 108.0 104.8 97.0 97.7 91.6 90.2 82.8 75.9 -2.6% -2.7%
Manufacturing 100.0 98.3 99.0 99.9 101.7 99.0 94.0 89.4 87.9 87.9 79.8 -2.2% -2.2%
Utilities 100.0 97.7 96.8 95.3 93.9 90.7 87.4 85.1 81.4 76.2 75.2 -2.8% -2.8%
Construction 100.0 103.6 86.1 93.7 105.2 108.0 107.4 110.7 111.3 110.1 101.4 0.5% 0.1%
Wholesale 100.0 100.2 97.1 97.3 97.4 93.4 89.3 85.8 83.4 79.9 77.5 -2.5% -2.5%
Retail 100.0 99.0 94.2 98.4 97.1 96.5 93.8 88.9 88.5 86.5 83.1 -1.8% -1.8%
Accom & food 100.0 100.4 101.1 97.8 96.7 95.4 94.8 92.6 90.2 86.3 83.0 -1.8% -1.8%
T'port & store 100.0 101.6 103.9 105.4 109.5 109.4 112.0 111.5 113.6 114.0 106.9 0.7% 0.7%
Communication 100.0 95.1 91.9 89.7 91.2 91.5 89.1 88.5 88.5 88.9 83.5 -1.8% -1.8%
Financial 100.0 100.7 97.1 96.8 94.2 96.1 95.2 97.8 104.3 106.4 102.7 0.3% 0.3%
Arts & Recn 100.0 97.6 97.3 93.8 94.3 96.9 98.4 97.2 100.1 98.4 101.1 0.1% 0.1%
Market 100.0 100.0 97.7 98.8 98.7 98.8 97.2 95.1 94.1 92.2 87.3 -1.3% -1.3%
Adapted from ABS, Experimental Estimates of Industry Multifactor Productivity, Australia, Detailed
Productivity Estimates, 5260.0.55.002
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Figure 7 Trends in multifactor (labour and capital) productivity by industry, Australia
1998-99 to 2008-09. See Table 5
Among other industries, MFPVA grew most quickly in Agriculture (2.6% per year) and the
Financial & insurance services (1.4%) and Transport, post & storage (1.2%). Growth was
slowest for the Utilities (-3.1%) and Mining (-2.8%) industries.
Table 5 Trends in value-added multifactor (labour and capital) productivity by industry,
Australia, 1998-99 to 2008-09
1998
-09
1999
-00
2000
-01
2001
-02
2002
-03
2003
-04
2004
-05
2005
-06
2006
-07
2007
-08
2008
-09
Annual
change
Comp.
growth
Agriculture 100.0 104.1 110.0 112.5 94.6 119.0 124.4 128.8 106.7 113.3 129.2 3.3% 2.6%
Mining 100.0 104.8 113.3 111.8 106.9 98.0 97.7 89.8 89.1 82.5 75.2 -2.7% -2.8%
Manufacturing 100.0 99.7 103.0 106.3 107.1 108.6 104.5 103.6 104.3 104.7 99.1 -0.1% -0.1%
Utilities 100.0 98.9 97.9 95.7 93.5 90.4 87.1 83.4 80.8 75.4 72.9 -3.1% -3.1%
Construction 100.0 98.2 86.8 95.1 105.7 105.1 104.1 107.2 105.7 108.4 103.5 0.5% 0.3%
Wholesale 100.0 99.9 101.8 104.3 106.1 106.8 107.9 108.9 104.1 108.0 106.9 0.7% 0.7%
Retail 100.0 98.4 99.7 104.0 102.5 106.8 106.2 105.2 107.6 109.0 111.7 1.1% 1.1%
Accom & food 100.0 99.8 100.4 100.7 102.7 102.6 104.0 106.1 107.2 102.9 102.7 0.3% 0.3%
T'port & store 100.0 102.2 103.3 108.6 113.9 112.7 115.7 117.5 121.0 120.1 113.0 1.3% 1.2%
Communication 100.0 93.5 91.4 94.3 94.6 97.6 94.4 94.8 96.1 101.2 98.1 -0.1% -0.2%
Financial 100.0 103.2 101.9 102.6 102.2 106.1 106.0 108.0 113.8 117.1 115.0 1.4% 1.4%
Arts & Recn 100.0 102.0 106.2 100.1 102.0 107.4 108.2 103.7 107.5 103.1 105.9 0.6% 0.6%
Market 100.0 99.8 99.9 102.7 103.5 105.4 104.6 104.7 104.7 104.6 101.7 0.2% 0.2%
Adapted from ABS, Experimental Estimates of Industry Multifactor Productivity, Australia, Detailed
Productivity Estimates, 5260.0.55.002
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Figure 8 Trends in gross output multifactor (labour and capital) productivity by
industry,Australia, 1997-98 to 2007-08. See Table 6
Table 6 Trends in gross output multifactor (labour and capital) productivity by
industry,
Australia 1997-98 to 2007-08
1997-08
1998-09
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
Annualchange
Comp.growth
Agriculture 100.0 104.6 106.4 108.9 110.1 101.4 112.3 114.7 116.4 107.7 110.4 1.0% 1.0%
Mining 100.0 98.0 100.5 105.0 104.1 101.4 96.5 96.5 92.0 91.5 87.5 -0.9% -1.3%
Manufacturing 100.0 101.1 101.1 102.3 103.6 103.9 104.8 103.5 103.2 103.4 103.3 0.4% 0.3%
Utilities 100.0 98.9 98.4 97.8 96.7 95.7 94.0 92.3 90.4 89.0 86.0 -1.3% -1.5%
Construction 100.0 101.3 100.8 96.9 99.9 103.6 103.4 103.1 104.0 103.7 104.5 0.4% 0.4%
Wholesale 100.0 100.5 100.5 101.3 102.3 103.2 103.4 103.9 104.4 102.3 104.1 0.3% 0.4%
Retail 100.0 100.8 100.0 100.5 102.6 101.9 104.0 103.7 103.3 104.6 105.3 0.5% 0.5%
Accom & food 100.0 102.7 102.6 102.8 102.9 104.0 104.0 104.5 105.6 106.4 104.4 0.7% 0.4%
T'port & store 100.0 100.5 101.4 101.7 103.8 106.0 105.4 106.5 107.2 108.5 108.1 0.9% 0.8%
Communication 100.0 101.9 98.7 97.6 99.2 99.3 100.9 99.4 99.7 100.3 102.8 0.0% 0.3%
Financial 100.0 103.5 105.7 105.1 105.6 105.3 108.0 108.2 109.5 113.4 115.8 1.4% 1.5%
Arts & Recn 100.0 99.9 100.7 102.1 99.5 99.8 101.9 101.7 99.5 100.9 99.0 0.1% -0.1%
Market 100.0 101.3 101.3 101.5 102.7 103.0 104.1 103.9 104.1 104.3 104.5 0.5% 0.4%
Adapted from ABS, Experimental estimates of industry multifactor productivity, Australia, Detailed
productivity estimates, 5260.0.55.002. Period differs from Tables 3 to 5 because values for
2008-09 were not available at the time of writing.
Multifactor productivity - gross output (MFPGO)
Gross output multifactor productivity (MFPGO) in Australias market economy grew 4.5%
between 1997-98 and 2007-08the compound rate of growth was just 0.4% per year
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(Table 6). The period reported for this measure differs from that of other measures
because of unavailability of estimates.
The compound annual growth measure shows that MFPGO grew a little faster than
average in the Retail industry (0.5%) and at just on the average for the market economy
of 0.4% and at somewhat below average (-0.1%) for the Arts & recreation industry. Among
other industries, MFPGO grew most quickly in the Finance & insurance (1.5%) andTransport, postal and storage (0.8%) industries and least in the Mining (-1.3%) and
Utilities (-1.5%) industries.
3.2 By industry
Wholesale trade
Wholesale trade contributes around 5% to the sum of gross value added by the Australian
economy.26 It includes:
Basic material wholesaling;
Machinery and motor vehicle wholesaling (including computer wholesaling); and
Personal and household good wholesaling.27
Wholesale trade is a labour intensive industry, which is reflected in the 66% income
share for value added MFP in 2008-09 compared with 52% for the market sector overall.
During the last decade, Wholesale Trade has been characterised by average GVA growth,
markedly lower growth in labour inputs with some capital deepening.
Growth in multifactor productivity (MFP) in the Wholesale trade industry has been
relatively strong for most of the last two decades, particularly the second half of the
1990s when it averaged about 3.3% per yearone of the highest growth rates of any of
industry sector (Table 7). MFP growth subsequently declined during the next decade and
has been volatile but on average slightly negative over the last few years. The earlier
increase resulted from both strong growth in outputs and slower growth in inputs, whichresulted from substantial rationalisation within the industry, a wider uptake of technology
among firms, and the increased use of new inventory management techniques, such as
'just-in-time' processing.
The decline in MFP growth in the Wholesale trade industry in recent years has mirrored
the overall decline in Australias market sector.28 Despite the absolute decline, MFP
growth in the Wholesale trade industry has been mostly above the national average for
the market sector and in recent years growth has still been better than average for the
market sector.
Labour productivity in the Wholesale trade industry also grew strongly in the second half
of the 1990s (4.3% per year) and this growth persisted into the first five years of the
2000s (3.7%) before declining more recently to only 1.6% (Table 7). Nevertheless, labourproductivity growth in the Wholesale trade industry has generally exceeded that of the
average for the market economy in recent years and over the last 15 years or so.
Capital productivity in Wholesale trade has mostly declined over the last two decades
apart from the second half of the 1990s. This pattern partly reflects a broader trend of
little or negative growth in capital productivity in the market sector of the Australian
26 Gross Value Added (GVA) across all industry sectors sums to GDP, allowing for Property, taxes and
subsidies. See Table A in Appendix A.
27 Motor vehicle and motor vehicle parts wholesaling is not within the scope of SSA. It is the largest industry
subdivision in terms of GVA, but not employment, see Table B in Appendix A.28 Values here and elsewhere in this section are drawn from ABS, Experimental Estimates of Industry
Multifactor Productivity, Australia, Detailed Productivity Estimates, 5260.0.55.002.
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economy. Even so, capital productivity in the Wholesale trade industry has been below
even this low average for the last two decades apart from a brief period in the second
half of the 1990s.
The growth in gross valued added for the Wholesale trade industry over the last decade
(3.0% per year) and over the last five years (2.8% per year) was the same as for themarket sector as a whole. This was despite substantially lower than average growth in
labour inputs over the last 10 years (0.6% compared with 1.5% per year) and over the
last five years (0.7% compared with 1.9% per year). Growth in capital services, however,
was substantially higher5.7% per year for Wholesale trade compared with 4.0% per year
for the market sector over the last 10 years and 6.7% per year for Wholesale trade
compared with 5.4% per year for the market sector over the last 5 years. The fastest
growing categories of capital stock were Computers (just under 30% per year for the last
decade) and Electrical and electronic equipment (just over 10% per year for the last
decade). The ABS suggests that the increase in capital services could be associated with
industry investment in the centralisation of distribution centres. It could also be
associated with increasing mechanisation and automation of handling as well as
computerisation of dispatch and inventory control. Despite the relative increase in capital
inputs, the share of income of capital has not increased.
Retail trade
Retail trade contributes around 5% to the sum of Gross Value Added by the Australian
economy. It is a labour intensive industry, which is reflected in the 71% income share for
value added MFP in 2008-09 compared with 52% for the market sector overall. Retail
trade has been characterised by more rapid than average growth in gross value added
over the last decade and similarly more rapid than average growth in its inputs of labour
and capital.
The main component of the measured output of Retail trade is gross marginsthe
difference between sales and cost of goods sold current price terms. The change in thevolume of Retail industry output is based on the quantity of goods sold.
The industry includes:
Food retailing;
Personal and household goods retailing; and
Motor vehicle retailing and services.29
Growth in MFP has averaged between 1% and 2% per year over the last two decades and
has usually been a little above the average for other market sector industries. Relative
performance has been strongest in the last four years during which growth averaged two
percentage points above the market sector average.
Significant changes in the industry since the late 1980s have contributed to increases in
measured productivity, especially the deregulation of shopping hours and the
consolidation of the industry, including the creation of large specialist retail stores in
areas such as hardware (eg Bunnings), toys (eg Toys-R-Us) and sporting goods (eg Rebel
Sport). Some benefits from these changes are not necessarily reflected in the changes in
measured productivity. For instance, deregulation of trading hours may have improved
convenience for shoppers, which is not necessarily captured by volume measures based
on goods traded. Similarly the measures for capital services do not incorporate the
29 Motor vehicle and motor vehicle parts retailing is not within the scope of SSA. See Table C, Appendix A.
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probable effect of extended trading hours on the industrys better utilisation of its existing
stock of assets.
Table 7 Average growth in multifactor, labour and capital productivity by industry,
Australia, selected periods, 1985-86 to 2008-09 (%)
1985/86-89/90 1990/91-94/95 1995/96-99/00 2000/01-04/05 2005/06-08/09% % % % %
Labour productivity
Agriculture 3.6 0.2 7.8 7.8 2.1
Mining 4.6 6.7 5.7 -2.4 -6.9
Manufacturing 1.4 1.6 2.8 2.7 1.2
Utilities 9.3 5.3 5.4 -3.2 -5.5
Construction -1.6 0.4 2.3 1.6 0.4
Wholesale 0.1 2.1 4.3 3.7 1.6
Retail -0.9 2.4 2.4 2.4 2.9
Accom & food -0.4 -1.3 2.6 1.8 1.5
T'port & store 1.7 2.4 2.5 2.9 -0.1
Communication 7.9 8.6 5.0 2.9 5.2
Financial 5.3 6.3 4.0 2.0 2.3
Arts & recreation -2.6 -0.5 1.3 1.9 -1.3
Market sector 1.5 2.1 3.1 2.2 1.1
Capital productivity
Agriculture 2.2 -0.6 8.7 2.8 1.5
Mining 3.1 1.5 -1.5 -0.9 -6.1
Manufacturing -0.4 -1.4 -1.5 -0.8 -4.0
Utilities 2.3 0.9 -0.9 -2.2 -3.7
Construction -5.4 -1.0 3.4 1.3 -1.3
Wholesale -1.3 -0.3 1.8 -2.3 -3.5
Retail -4.6 0.7 -0.1 -1.0 -3.0
Accom & food -1.9 1.3 0.0 -1.1 -3.3
T'port & store -4.1 1.9 2.2 2.0 -1.1
Communication 0.8 4.1 -0.5 -1.3 -1.6
Financial -4.6 0.4 0.5 -1.1 2.0
Arts & recreation -4.4 -1.6 -3.8 0.2 0.7
Market sector 0.0 -0.3 0.2 -0.6 -2.6
Adapted from ABS, Experimental Estimates of Industry Multifactor Productivity, Australia, Detailed
Productivity Estimates, 5260.0.55.002.
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Table 7 Average growth in labour, capital and multifactor productivity by industry,
Australia, selected periods, 1985-86 to 2008-09 (%)continued
1985/86-89/90 1990/91-94/95 1995/96-99/00 2000/01-04/05 2005/06-08/09
% % % % %
Value-added multifactor productivity (MFPVA)
Agriculture 2.5 -0.3 8.4 4.5 1.7
Mining 3.6 3.1 0.6 -1.3 -6.3
Manufacturing 0.9 0.3 0.7 1.0 -1.3
Utilities 5.8 2.6 1.2 -2.5 -4.3
Construction -2.5 0.0 2.6 1.5 -0.1
Wholesale 0.1 1.3 3.3 1.6 -0.2
Retail -1.4 2.0 1.8 1.6 1.3
Accom & food -0.6 -0.6 1.9 0.8 -0.3
T'port & store -0.8 2.2 2.4 2.5 -0.5
Communication 3.9 5.8 1.6 0.2 1.0
Financial 3.5 4.2 2.7 0.6 2.1
Arts & Recreation -3.0 -1.0 -0.4 1.2 -0.5
Market sector 0.9 1.1 1.8 0.9 -0.7
Gross output multifactor productivity (MFPGO)
Agriculture -- -- 3.1% 1.7% -1.1%
Mining -- -- 0.3% -0.8% -3.2%
Manufacturing -- -- 0.4% 0.5% 0.0%
Utilities -- -- 0.6% -1.3% -2.3%
Construction -- -- 0.8% 0.5% 0.5%
Wholesale -- -- 1.7% 0.7% 0.1%
Retail -- -- 0.9% 0.7% 0.5%
Accom & food -- -- 0.9% 0.4% 0.0%
T'port & store -- -- 1.0% 1.0% 0.5%
Communication -- -- 0.5% 0.2% 1.1%
Financial -- -- 1.9% 0.5% 2.3%
Arts & recreation -- -- 0.0% 0.2% -0.9%
Market sector -- -- 0.7% 0.5% 0.2%
Adapted from ABS, Experimental Estimates of Industry Multifactor Productivity, Australia, Detailed
Productivity Estimates, 5260.0.55.002. MFP-GO values unavailable for 1985/86-89/90 and
1990/91-94/95 and 2008/09. Market sector is the weighted average productivity growth for the
12 industries shown in the table.
Growth in labour productivity in the Retail trade industry has averaged between 2.4% and
2.9% per year over the last two decades or so. It has been one of the few industries (withInformation and media) in which labour productivity has increased in recent years. The
growth in labour productivity in Retail trade has been mostly a little above the average of
the market sector except in recent years when it has been well above average.
Capital productivity has declined in the Retail trade industry over the last 15 years after a
period of growth in the first half of the 1990s.
Labour is the major input in the Retail trade industry and the hours worked has been
increasing by an average of 2.0% per year in the last decadewell above the market
sector average of 1.5% per year. At the same time, the relative contribution of capital as
reflected in income share has also been increasing over the last decadefrom 23% in
1999-00 to 29% in 2008-09. While current levels of capital income share are historically
high, they had reached 27% earlier in the 1990s. Over the last decade, capital services (ameasure of capital inputs) grew strongly by an average of 6.1% per yearmore than in
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any other industry. This increase was driven by the rapid growth in gross fixed capital
formation (GFCF) that has occurred since the mid 1990s. Growth in computer hardware
(scanning technology, EFTPOS facilities and computerised inventory management) of just
under 30% per year underpins some of the increase in capital inputs.
Accommodation & food services
The Accommodation & food services industry consists of enterprises mainly engaged in
the provision of hospitality serviceshotels, motels, clubs, pubs, taverns and bars, cafes
and restaurants.30 The industry is relatively small in terms of gross value added to the
economy, contributing just 3% to aggregate GDP in 2008-09.31
The industrys contribution to the economy over the last 5 years, 2004/5-2008/9,
measured by value added (1.7% per year), has grown significantly more slowly than the
total economy (2.9% per year). This is part of a longer-term trend of slower than average
growth over the last 10 years. Slower growth of gross value add is not inherent in the
industryin earlier periods its growth has been slightly above average. Among the market
sectors of the economy