service skills australia - productivity in the service industries (2010)

7/29/2019 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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Productivity in the service industries

1

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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Service Skills Australia

2

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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11

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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14

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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15

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%




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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%




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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


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%


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

service skills australia - productivity in the service industries (2010)

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