Information technology's contribution to labour productivity growth
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Information technology’s
contribution to
labour productivity growthC
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Cita
ation
atistics New Zealand
Sta Z (20113). Informattion technolo
ogy’s contrib
bution to labbour
pro owth. Availab
oductivity gro ble from wwww.stats.govt.nz.
BN: 978-0-47
ISB 78-40853-9 (o
online)
Pubblished in October
O 2013
3 by
Sta
atistics New Zealand
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ww
ww.stats.govt.nzContents
List of table
es and figu
ures..................................................................................................... 4
1 Purpose
e and summ
mary.................................................................................................... 6
Purpose ............................................................................................................................. 6
Summarry ........................................................................................................................... 6
2 Introduc
ction ..................................................................................................................... 7
Previouss research and context .......................................................................................... 7
Overview
w of approac
ch ....................................................................................................... 7
Outline of
o this paperr .......................................................................................................... 8
3 Methodo
ology .................................................................................................................... 9
The grow
wth accountiing framewo
ork ................................................................................... 9
Output ............................................................................................................................. 10
nput .................................................................................................................... 10
Labour in
IT capita
al services in
ndex .................................................................................................. 10
Factor in
nput weights
s ........................................................................................................ 13
Industry coverage ............................................................................................................ 14
4 Results ........................................................................................................................... 15
IT’s conttribution to measured-se
m ector labour productivity
y growth ................................... 15
Estimate
es for broad industry gro
oups and ind
dustries ...................................................... 17
Industrie
es in detail ........................................................................................................... 22
5 Explainiing IT capital’s contrib
bution ............................................................................ 27
User cossts ....................................................................................................................... 27
Productivve capital sttocks ................................................................................................. 30
6 Comparring estimattes of IT’s c
contribution
n to labour productivitty .......................... 31
Defining IT ....................................................................................................................... 31
Defining capital................................................................................................................ 31
Deflatorss .......................................................................................................................... 32
Specifyin
ng the user-cost formula
a .................................................................................... 33
7 Summarry ........................................................................................................................ 36
Future work
w ..................................................................................................................... 36
References
s.......................................................................................................................... 37
Appendix............................................................................................................................. 38
3List of ttables and fig
gures
List of tab
bles
4 Results ........................................................................................................................... 15
1 Growthh accounting
g for labour productivity, measured sector, and former mea asured
sector, 1978–2012 .......................................................................................................... 16
2 Growth h accounting g for labour productivity using qualitty-adjusted llabour inputs, 1999–
2012 ................................................................................................................................ 17
3 Growth g for labour productivity, by broad in
h accounting ndustry grouup and indus stry,
average annual grow
wth rates, 19978–2011 ...................................................................... 18
h accounting
4 Growth g for labour productivity, by broad in ndustry grouup and indus stry,
average annual grow
wth rates, 19996–2011 ...................................................................... 19
5 Income
e shares and
d input grow
wth, by broad
d industry grroup and inddustry, 1996
6–201121
6 Outputts and inputs
s, selected i ndustries, average
a annual growth rrates, by cyc
cle ..... 24
5 Explainiing IT capital’s contrib
bution ............................................................................ 27
7 Deprecciation rates
s for selected
d assets, 19
978–2011 ................................................... 29
6 Comparring estimattes of IT’s c
contribution
n to labour productivitty .......................... 31
8 Sensitiivity of the contribution
c o
of IT to labour productiv vity under altternative user-cost
formula specification
s ns, by broad d industry gro oup and industry, averaage annual growth, g
2008–11 .......................................................................................................................... 34
List of figures
4 Results ........................................................................................................................... 15
1 Measu
ured-sector contributions
c s to labour productivity
p growth,
g annuual percenta age
change ............................................................................................................................ 15
ation, media
2 Informa a, and teleco
ommunicatio
ons contributions to laboour productiv vity
growth, average
a annnual percenttage change
e ................................................................. 22
3 Financce and insura
ance contrib butions to labour produc ctivity growthh, average annual a
percentaage change ......................................................................................................... 23
4 Professional, scien
ntific, and te
echnical serv
vices contrib butions to labbour produc ctivity
growth, average
a annnual percenttage change e ................................................................. 23
5 IT capiital income shares,
s sele
ected industrries ............................................................. 25
6 Ratio of
o IT capital income to n
non-IT capita
al income, se
elected induustries ................... 26
5 Explainiing IT capital’s contrib
bution ............................................................................ 27
7 Compu
uter rental price per doll ar of capitall services, selected induustries ................... 28
8 Softwa
are rental price per dolla
ar of capital services,
s selected indusstries .................... 28
9 Asset price
p indexe
es, selected assets .......................................................................... 29
10 IT pro
oportion of to
otal product ive capital stock,
s selected industriees .......................... 30
6 Comparring estimattes of IT’s c n to labour productivitty .......................... 31
contribution
11 IT cap
pital measurres, annual percentage change for finance andd insurance............ 32
412 Economy-wide capital services, OECD estimates using different deflators............ 33
7 Summary .................................................................................................................... 36
13 Information media, and telecommunications contributions to labour productivity
growth, including communications equipment, average annual growth rates.............. 38
51 Purpose an
nd sum
mmary
Purpose
Growth in in
nformation teechnology (IIT) is considdered a key driver for proroductivity grrowth in
many counttries. Howevver, New Zea aland has litttle information on the eextent to which IT
has benefite
ed labour prroductivity, e
either at the measured sector
s or inddustry level.
Information technology’s contributio
on to labourr productivityy growth asssesses the role
r of IT
pening grow
capital deep wth on labourr productivityy and fills an
n informationn gap in
understandiing New Zeaaland’s prodductivity perfformance.
Summa
ary
Contribution
ns of IT capital deepenin
ng to labourr productivity
y growth aree presented for New
Zealand’s in
ndustries and the measu ured sector for 1978–20 011. Figuress are derived
d using
the standard
d growth acccounting fra
amework.
Most industtries showedd double-diggit growth in IT capital se
ervices. Howwever, only a
handful of in
ndustries be
enefited from
m this growthh, in terms of
o labour prooductivity.
We found sttrong contrib butions of IT
T capital dee
epening to thhe labour pro
roductivity grrowth of
the informattion, media, and telecom mmunication ns; finance and
a insurancce services; and
professiona
al, scientific, and techniccal services industries.
IT capital de
eepening co
ontributions w e measured sector, acco
were also prresent in the ounting
for 0.5 percent growth a year in labbour producttivity for 1996–2012 eveen though IT
T
comprises a small sharre of total inccome.
62 Introd
duction
n
This chapteer outlines prrevious rese
earch about information technology’’s (IT) role in
n
productivity and introdu
uces the frammework for the
t research h reported heere.
T is considered a key drriver for prod
Growth in IT ductivity grow
wth in counttries. Interna ational
studies have shown larg ge effects in n the United States, with
h smaller (buut still signifiicant)
contribution
ns to producttivity in Canaada (Khan & Santos, 20 002) and Euurope (Van Ark,A
Inklaar, & McGuckan,
M 2003).
2 Wei a
and Zhao (20 012) found IT contributeed approxim mately
0.65 percennt a year to Australia’s
A la
abour productivity growtth for 1996––2010.
Previou
us resea
arch and
d conte
ext
There has been
b little research into the role of IT
T on producctivity in New
w Zealand, with
w the
exception of Engelbrecht and Xaya avong (2006 6, 2007). Enggelbrecht annd Xayavong g (2007)
use a growtth accounting frameworkk on industrry-level data from 1988––2003. They y focus
on informatiion and com mmunicationss technology y (ICT), whic
ch covers booth IT and
communications techno ology.
ICT intensitty is based on
o the propo ortion of inte
ermediate inputs that aree ICT-relateed. ICT-
intensive ind
dustries werre found to h have higher multifactor productivity growth, and d distinct
patterns in the
t growth contributions
c s, relative to non-ICT inttensive induustries. Compared
with other countries,
c En
ngelbrecht a and Xayavon ng (2007) suuggest that ““NZ seems tot be
one of the fe
ew countries s so far to s how positive e productivitty impacts frrom ICT whe
en
industry leve
el data are employed”
e ( 2007, p22).
The study reeported here e draws on iimprovemen nts to service-industry ooutput
measureme ent, capital-s
services meaasurement for
f IT and no on-IT assetss, industry-le
evel
labour inputts estimatess, and metho
ods for allocating entreppreneurial inccome to labour and
capital deve
eloped since e Engelbrechht and Xayaavong’s (200 07) study.
This paper assesses
a IT
T’s contributiion to labourr productivity
y growth in N
New Zealan nd, by
industry, forr 1978–20111. 1 This perio
0F od covers significant changes in IT,, in relation to
software, ne etworking ca
apabilities, m
media, storage, and proc cessing. Maainframes saat
alongside mini-compute
m ers during thhe 1970s. Th he Apple II (1977),
( IBM personal co omputer
running MS-DOS (1981 1), and Apple e Macintosh h (1984) marked the advvent of perso onal
computers. Software ca apabilities w
were enhance ed following the releasee of Microsoft
Windows (1985, and ve ersion 3.0 in 1990). The World Wide e Web’s devvelopment in n 1990
heralded ye et another ne
ew era for ap pplying IT.
Overvie
ew of ap
pproach
h
This paper’ss approach is based on the growth accounting framework. This is the same
s
approach th
he Australian
n Bureau of Statistics (A
ABS) uses to
o determine the contribu
ution of
1
Communica ations capital is
s not available e as a separatte asset class but is part of oother asset classes, the
extent to whicch varies acros ss industries. For the inform mation, media, and telecomm munications inndustry it
is part of the electronic
e equipment asset class, as well as other cons struction. Whille other industtries may
have commun nications capittal, it is likely tto be a very sm
mall part of the
e total electronnic equipmentt asset
class (which covers
c medicaal and surgicall equipment, broadcasters,
b transmitters, rreceivers, and
d other
telecommuniccation equipment, optical an nd photograph hic equipment, and photocoppiers). Given the t
challenges in identifying comparable com mmunications capital across s industries, thhis paper focus
ses on IT
rather than ICCT.
7Information technology’s contribution to labour productivity growth
IT capital deepening (Wei and Zhao, 2012), and is consistent with the underlying
methodology in New Zealand’s official productivity statistics series. 2 1F
The focus is on the use of IT capital rather than the production of IT services. Official
productivity statistics show the role of capital inputs on labour productivity, with the role of
IT subsumed within capital input’s contribution. The analysis reported in this paper
extends the official framework to determine the contribution of IT and non-IT capital on
labour productivity.
Capital inputs are measured as the flow of capital services from the productive capital
stock. This accounts for both the volume of IT capital and the associated capital costs
that are used to weight the IT assets. This is important for understanding the contribution
of IT to labour productivity given the sharp price decline in IT capital and its high rate of
depreciation, which are reflected in capital costs. 3 2F
IT covers computers and software for all industries. The Internet’s role is not assessed.
Internet usage may contribute to gross output, for example by providing a new
mechanism for selling goods and services, but will also form part of intermediate
consumption. Therefore, the benefits of the Internet may form part of value added and
multifactor productivity but cannot be readily identified.
Outline of this paper
This paper presents:
the methodology for deriving contributions of IT to labour productivity growth
estimates from the growth accounting approach
an analysis of underlying capital volume and user cost data, to gain further insight
into the estimated contributions
commentary on comparing estimates across countries, to aid interpretation.
The paper concludes that in a number of industries labour productivity has strongly
benefited from IT capital growth, with these effects also reflected in measured-sector
labour productivity growth.
2
The methodology employed in this paper could be readily applied to determine the contributions of
other types of capital to labour productivity (eg natural resources or research and development).
3
The capital services approach is also preferable to using raw IT investment data, which may overstate
the effect on labour productivity, given the need to replace IT on a more-frequent basis than other fixed
assets.
83 Meth
hodolog
gy
This section
n presents th
he methodollogy used to
o determine the contribuution of IT to
o labour
productivity growth amoong New Ze
ealand’s induustries.
The gro
owth accountin
ng frame
ework
The growth accounting framework is used to assess the efffect of IT onn labour
productivity.
h the industrry-level prod
Starting with duction function, which exhibits
e connstant returns to
scale, growtth in output volumes (defined as value added d, which is ggross outputt less
intermediatee consumptiion) can be decompose ed into the coontributions of IT (compputers
and softwarre) ,, , no
on-IT capital ,, , labo
our , , and multifactor productivity (MFP)
:
∆lln , ∆ ln , , ∆ ln ,, ,, ∆ ln ,, ,, ∆ ln ,
utions of IT, non-IT capiital, and labo
The contribu our to outpu
ut depend onn weights ,, ,
,, , and
d ,, , as well
w as volum
mes ,, , ,, , and , respective
vely.
This approa ach acknowledges that IIT possesse es separate characterist
c tics to non-IT
T capital,
as it feeds into the prod
duction functtion as a dis
stinct factor input. In otheer words, th
he
heterogeneity between IT and non--IT capital is s allowed forr. MFP is speecified as
disembodied technological change .
on can be re
This equatio earranged to s labour prooductivity could be
o show that an industry’s
determined by growth in
n the (weigh
hted) amounnt of IT and non-IT
n capita
tal available per
hour (capita
al deepening
g) and MFP::
,, ,.
∆ln , ∆ ln ,, ∆ln ,, ∆ln
, ,
The contribuution to labo
our productivvity depends s on volume es of IT and non-IT capittal, as
well as weig
ghts that refllect the relattive importance of thesee assets in tthe productio
on
process. Thhis approach h allows the contribution n of IT capita
al deepeningg to be calcu
ulated
for each ind
dustry in eacch year, but does not ne ecessarily shhow that IT ccapital deep
pening is,
on average,, associated d with higherr labour prod ductivity acro
oss industriees.
IT growth may
m also ben nefit MFP, byy enabling new
n business models orr complemen ntarities
between IT and non-IT capital or la
abour, but th
his is not identified in thee growth acc
counting
framework.
This approaach follows the same meethod used in official pro
oductivity sta
tatistics for
measuring the
t contributtions to labo
our productiv
vity, except for having sseparate cap pital
services ind
dexes for IT and non-IT capital and associated weights.
9Information technology’s contribution to labour productivity growth
Growth accounting assumptions
The growth accounting approach relies on certain assumptions to determine MFP growth.
The OECD (2011) outlines the key issues:
Growth accounting estimates show correlation, not causation (eg labour
productivity growth could lead to growth in IT capital deepening).
Assumptions of perfect competition in all markets, constant returns to scale, and full
mobility of labour and capital are strong and not well tested. Increasing returns-to-
scale are more than a possibility when assessing the role of IT, but the extent to
which this occurs is not known.
Firms are assumed to be price takers and to maximise profits. There are no
adjustment costs or temporary fluctuations in output during the period in which new
inputs are integrated into the production process.
Variable capacity utilisation of capital is not accounted for (see the capacity
utilisation section for more discussion).
All measurement errors are subsumed within the MFP residual.
Any externalities related to factors of production are also included in MFP, and any
such externalities will lead to underestimating the production factor’s contribution.
There is also the assumption of complete asset coverage. If there are non-IT assets that
are not measured then the proportion of capital cost attributable to IT will be overstated,
and the contribution of IT to labour productivity will also be overstated.
The next sections define output and labour input, and describe how the IT capital
services index and factor weights are derived.
Output
Output is defined as chain-volume value added, sourced from the national accounts.
Aggregate and industry value-added data are chained Laspeyres volume indexes, re-
expressed as indexes with a base value of 1000. The base year is the March 1978 year
for most industries and the March 1996 year for the measured sector and some service
industries.
Labour input
At the industry level, labour input is measured as the sum of industry hours paid. This is a
composite series that uses data from the Linked-Employee-Employer Dataset (LEED),
Household Labour Force Survey, Quarterly Employment Survey, and the Business
Demography Database. Hours worked are often preferred to hours paid, in order to better
reflect the actual amount of time spent contributing to production. However, hours paid
data are more robust at the industry level. Industry-level hours-paid data are unadjusted
for workforce composition, which means that hours paid for each worker are treated
equally regardless of skill level. A composition-adjusted labour input series is available for
the measured sector.
IT capital services index
The starting point for measuring IT capital services is to construct productive capital
stocks using the perpetual inventory method (PIM). Assumptions are required for the rate
10Information technology’s contribution to labour productivity growth
of efficiency reduction and for asset lives when using the PIM. 4 Software and computers
3F
have an efficiency reduction parameter value of 1 (which assumes no decline in efficiency
over time) and a mean asset life of four years (which is the lowest of all assets and leads
to high depreciation rates). These assumptions are applied uniformly across industries for
computers and software. 5 4F
The efficiency units of assets with different lives are aggregated to determine the
weighted average of the age-efficiency units, which is multiplied with gross fixed capital
formation to derive the productive capital stock. 6 5F
The IT capital services index is a Törnqvist aggregate index of computers and software
for all industries. The computers asset class covers all computing equipment, including
personal computers, networking systems, scanners, printers, receivers, and word
processors. Computer software includes computer programs, program descriptions, and
supporting materials for both systems and applications software. Purchased software and
software developed on own account are included, if the expenditure is large. 7 Additional 6F
IT capital may be embodied in other capital-asset classes, but this cannot be readily
identified nor is the extent of this known.
Capital is allocated to industries by ownership. Some industries may benefit from using IT
or non-IT capital owned by other industries if it is hired out. If an industry sells an asset to
another and rents it back, the output of the renting industry stays the same, but its
intermediate consumption leads to a fall in its value added. However, capital inputs have
also fallen, so capital productivity is potentially unchanged. The opposite effect may arise
for the industry that now owns the asset, so aggregate capital productivity might remain
unchanged. However, the contribution of IT capital deepening to labour productivity
growth may be understated for an industry that rents its IT (because some effects will be
subsumed within intermediate consumption).
4
In this analysis, productive capital stock was sourced directly from the national accounts; sensitivity
analysis on the parameters underlying the PIM was not done.
5
The Australian Bureau of Statistics assumes a value of 0.5 for each of these assets, and an asset life of
2.5 years for computer software. A value of 0.5 reflects an assumption of an even distribution of
efficiency decline over time. The efficiency reduction parameter forms part of the hyperbolic age-
efficiency equation:
M A
E
M bA
where
E = the efficiency of the asset at period t
M = the asset life as for an assumed retirement distribution
A = the age of the asset of the given vintage at period t
b = the efficiency reduction parameter.
6
For the years in which the demand and supply estimates have yet to be reconciled through supply-use
balancing, economy-wide GFKF data by asset type and sector are obtained from quarterly GDP
estimates. Where specific information is not yet available, industry and market group allocations are
made according to the proportions from the latest balanced year. Source: Statistics NZ (2013a)
Productivity Statistics: Sources and Methods.
7
Major expenditure on the purchase, development, or extension of computer databases that are
expected to be used for more than one year, whether marketed or not, are also included in principle.
However, given the present data sources, it is not possible to distinguish between software and
databases developed on contract or on own account, so it is not known to what extent databases are
included. The costs of collecting and capturing the information stored in databases are excluded.
Source: Statistics NZ (2013b) Measuring Capital Stock Manual.
11Information technology’s contribution to labour productivity growth
Movements in the productive capital stock for both computers and software are each
weighted by their respective two-period shares of capital income to derive the IT capital
services index:
,,
,, ,,
,, ,,
1 ,, ,, ,, ,,
,,
2 ∑ ,, ,, ∑ ,, ,,
where
= volume measure of the flow of IT capital services from IT capital stock in industry i
,,
in period t
, , = volume measure of the productive capital stock j for each type of IT asset in
industry i in period t
, , = two-period share of capital cost of using IT asset j in industry i in period t. Note: the
two-period shares of capital costs for all IT assets sum to unity in a given period
, , = user cost (rental price) per dollar of capital services from capital stock j for each
type of IT capital in industry i in period t
The user cost, the price at which the owners of capital are considered to charge
themselves, is unobservable and is imputed as:
,, ,, ,, ,, ,
where
,, = the asset price index of asset j in industry i in period t
,, = the rate of economic depreciation of asset j in industry i in period t
= the real exogenous rate of return (set at 4 percent)
,, = the average non-income tax rate on production for industry i in period t
The non-IT productive capital-stock and capital-services series are constructed in the
same manner as that for IT capital (but with different assumptions in applying the PIM,
such as asset lives and efficiency reduction parameters). They are aggregated over all
other remaining assets derived through the PIM, along with land and inventories.
Capacity utilisation
The level and growth rate of capacity utilisation is implicitly assumed to be the same for
IT and non-IT assets. Variations in capacity utilisation can have marked effects on capital
services, and to a lesser extent on MFP (Tipper & Warmke, 2012). Adjusting for variable
12Information technology’s contribution to labour productivity growth
capacity utilisation involves applying a rate of capacity utilisation to productive capital-
stock data. Level differences in capacity utilisation across IT and non-IT assets will affect
capital services through productive capital stocks. Factor input weights (which are based
on proportions of user costs) will also be affected.
In the long term, capital services growth is likely to be similar whether adjusted for
capacity utilisation or not, but there will be persistent differences in the income share
weights. This is because the IT and non-IT income shares depend on the level of
productive capital stock. The income share effect is not mitigated by presenting
productivity estimates over growth cycles, but the capital service growth effect is.
The New Zealand Institute of Economic Research’s capacity utilisation series, which is
the most appropriate data source available for capacity utilisation adjustment, does not
contain an appropriate asset dimension. Consequently, this measurement issue cannot
be assessed. Data are presented over growth cycles (defined as ‘peak-to-peak’) in order
to account for fluctuations in capacity utilisation.
Factor input weights
In the standard approach to measuring MFP, the factor weight for capital (used to
combine labour and capital to derive total inputs) does not have an asset dimension.
Capital income needs to be apportioned between IT and non-IT capital in order to
aggregate the two capital-services indexes along with labour, and to determine the
contributions of IT and non-IT capital to labour productivity. This is achieved by using
capital-cost shares, which can be used under the assumption of perfect competition –
where capital costs exhaust capital income. Factor input weights represent the marginal
effect of a percentage increase in an input on value added (ie are interpreted as output
elasticities).
Total capital income , and labour income , in each industry i for each
period t are derived as:
, , , ,
, , , ,
where
, = gross operating surplus in industry i in period t
, = working proprietors' income in industry i allocated to capital in period t
, = net taxes on production and imports allocated to capital in industry i in period t
= compensation of employees in industry i in period t
, = working proprietors' income in industry i in period t allocated to labour
, = net taxes on production and imports allocated to labour in industry i in period t
Total industry capital income is then proportionately allocated to IT and non-IT, using IT
and non-IT capital-cost shares in industry total income from flows of capital services as
weights:
13Information technology’s contribution to labour productivity growth
∑ ,, ,,
,, ,
∑ ,, ,, ∑ ,, ,,
∑ ,, ,,
,, ,
∑ ,, ,, ∑ ,, ,,
Factor input weights are then calculated as:
,,
,,
,
,,
,,
,
,
,,
,
Where , ,, ,, , .
The factor weights (labour , , , IT , , , and non-IT , , ) sum to unity, whether for
calculating industry or aggregate combined-inputs indexes, because the identity
, , holds. Also, the sum of the IT and non-IT weights
equals the capital weight in the standard productivity framework. The weights are
calculated as two-period shares, and are applied exponentially to the relevant input index
to calculate a Törnqvist index of total inputs.
Industry coverage
Productivity statistics are available for 25 ‘market-based’ industries that cover the
measured sector, and for the health care and social assistance, and education and
training industries. Productivity data are available from 1978 for 20 industries, and from
1996 for a further five market-based industries.
This paper reports on analysis for each industry in the measured sector, the three broad
industry groups within the measured sector, and for the measured sector.
IT contributions to labour productivity growth in the health and education industries are
likely to be minimal, as non-residential buildings dominate the productive capital stocks
for these industries and the total capital weights are among the lowest of all industries.
144 Resu
ults
This section
n presents thhe contributiions of IT to labour prod
ductivity; firsst for the measured
sector, then
n by broad in
ndustry grou up and indus stry, and then focuses oon the IT
contribution
ns for selecte
ed industriess.
IT’s con
ntributio
on to me
easured
d-sectorr labourr produc
ctivity
growth
Under the growth
g accouunting frameework, labou
ur productivity growth caan be decom
mposed
into contribu
utions from IT capital de
eepening, no
on-IT capital deepening , and MFP.
Figure 1 shoows that IT contribution s were refle
ected in meaasured-sectoor labour
productivity. For 1996–22012, meassured-sectorr labour prod ductivity incrreased 1.5 percent
p
T capital dee
annually. IT epening was the largest driver (contributing 0.5 percent a year),
along with MFP
M ercent a yearr), followed by non-IT ca
(0.5 pe apital deepeening (0.4 peercent a
year). The IT contributio
ons were driiven by growwth in the vo
olume of IT ccapital services (up
15.0 percennt annually) while
w the IT capital inco
ome weight averaged
a 4.88 percent off total
income. 8 7F
Figure 1
1 Measured-sector contributions to labour productivity growth, annual percentage change
IT capital de
eepening alsso contribute ed strongly to
t labour pro oductivity grrowth among g the
former measured-secto or industries from 1978 to t 1996. Con ntributions ro
rose from 0.1
percent in 1981 to 0.9 percent
p in 19987 but fell back
b to 0.1 percent by 11996. As witth the
measured sector,
s contrributions of I T capital de
eepening inc creased, to re
reach 0.6 pe ercent in
2000 and re emain relativ
vely stable thhereafter. Average
A conttributions weere 0.5 percent a
year for 20000–11. Tablee 1 presentss the contrib butions to lab
bour product ctivity growth
h for the
measured sector
s and foormer measu ured sector across grow wth cycles.
8
Labour incom
me averaged 57.4 percent a
and non-IT ca
apital income 37.7
3 percent.
15Information technology’s contribution to labour productivity growth
Table 1
1 Growth accounting for labour productivity, measured sector and former measured sector, 1978–2012
Growth accounting for labour productivity, measured sector, and former measured
sector
1978–2012
Contribution
Contribution
Labour of non-IT
of IT capital MFP
productivity capital
deepening
deepening
Sector Cycle(1) Percent
Measured 1997–00 2.8 0.5 0.5 1.7
(2)
sector 2000–08 1.3 0.5 0.3 0.5
2008–12 0.7 0.5 0.6 -0.4
1996–2012 1.5 0.5 0.4 0.5
Former 1978–82 2.1 0.1 0.4 1.6
measured 1982–85 1.3 0.4 1.3 -0.3
(3)
sector 1985–90 2.7 0.7 1.7 0.3
1990–97 2.6 0.3 0.3 2.0
1997–00 3.3 0.5 0.6 2.1
2000–08 1.3 0.5 0.3 0.5
2008–12 1.2 0.5 0.9 -0.3
1996–2012 1.8 0.5 0.6 0.7
1978–2012 2.0 0.4 0.7 0.9
1. 1978–82 and 2008–12 are incomplete cycles.
2. Measured sector includes: agriculture, forestry, and fishing; mining; manufacturing; electricity, gas,
water, and waste services; wholesale trade; retail trade; accommodation and food services; transport,
postal, and warehousing; information, media, and telecommunications; finance and insurance; rental,
hiring, and real estate services; professional, scientific, and technical services; administrative and
support services; arts and recreation services; and other services. Series available from 1996.
3. Former measured sector includes: agriculture, forestry, and fishing; mining; manufacturing;
electricity, gas, water, and waste services; wholesale trade; retail trade; accommodation and food
services; transport, postal, and warehousing; information media and telecommunications; finance and
insurance; and arts and recreation. Series available from 1978.
Accounting for workforce composition
IT can be related to skills in two distinct ways. First, IT may be skills-replacing; lower-
skilled workers can do the same job as higher-skilled workers, thereby reducing the
returns for higher skills. An example is an automated stock control system in a
warehouse. Second, IT may also be skills-complementing and increase the returns for
higher skills. This might happen in a research setting, where IT enables a highly-skilled
worker to access and integrate more information into their work.
Estimates of IT’s contribution may therefore be affected by the industry labour-input
measures not reflecting workforce composition. Omitting changes in labour quality will
lead to an upwards bias in IT’s contribution if highly skilled workers are required to
effectively utilise IT.
The strong contributions from IT capital deepening hold after adjusting for workforce
composition. Estimates of the contribution of IT capital deepening, using quality-adjusted
labour inputs, are similar to those presented in figure 1. 9 But contributions from non-IT 8F
9
This finding is similar to O’Mahony and Vecchi (2005) who find that accounting for labour quality had
little impact on estimates of IT’s contribution to MFP.
16Information technology’s contribution to labour productivity growth
capital deepening are more sensitive to the labour input measure, due to the higher
income share weight for non-IT capital services.
Table 2 presents the contributions to labour productivity growth using quality-adjusted
labour inputs. Figures in parentheses represent the difference in percentage points from
the main estimates which are unadjusted for workforce composition.
Table 2
2 Growth accounting for labour productivity using quality-adjusted labour inputs, 1999–2012
Growth accounting for labour productivity using quality-adjusted labour inputs,
measured sector
1999–2012
Labour productivity
Contribution of IT Contribution of non-IT
(composition- MFP
capital deepening capital deepening
Year adjusted)
1999 0.1 (-1.0) 0.5 (0.0) 0.3 (-0.4) -0.8 (-0.6)
2000 4.2 (-1.0) 0.6 (0.0) -0.2 (-0.4) 3.8 (-0.6)
2001 0.5 (-0.7) 0.5 (0.0) -0.1 (-0.3) 0.0 (-0.4)
2002 1.0 (-0.1) 0.6 (0.0) -0.1 (0.0) 0.5 (0.0)
2003 1.3 (-0.2) 0.4 (0.0) -0.5 (-0.1) 1.4 (-0.1)
2004 0.5 (-0.5) 0.6 (0.0) 0.1 (-0.2) -0.2 (-0.3)
2005 1.6 (0.4) 0.5 (0.0) 0.5 (0.1) 0.6 (0.2)
2006 2.0 (0.1) 0.7 (0.0) 0.7 (0.0) 0.6 (0.0)
2007 1.3 (0.4) 0.5 (0.0) 0.5 (0.2) 0.3 (0.2)
2008 0.9 (-0.7) 0.4 (0.0) 0.4 (-0.3) 0.1 (-0.4)
2009 -1.8 (0.4) 0.4 (0.0) 1.4 (0.1) -3.5 (0.2)
2010 2.7 (-1.0) 0.6 (0.0) 1.1 (-0.4) 1.0 (-0.5)
2011 0.2 (-0.3) 0.5 (0.0) -0.2 (-0.1) -0.1 (-0.2)
2012 1.0 (0.1) 0.5 (0.0) -0.2 (0.0) 0.7 (0.1)
Note: Data are available from 1998 as workforce composition data is sourced from the New Zealand
Income Survey (NZIS). The composition-adjusted series is only available for the measured sector as the
NZIS is not stratified by industry.
Estimates for broad industry groups and industries
Contributions of IT capital deepening to labour productivity growth were strongest for
service industries, followed by goods-producing industries, and finally primary industries.
As table 3 shows, within these broad groups IT capital deepening contributions to labour
productivity growth varied across industries. For 1978–2011, the strongest contributions
were in the information, media, and telecommunications industry and finance and
insurance. Sizeable IT capital deepening contributions were observed for printing; and
transport equipment, machinery, and equipment manufacturing; and for both wholesale
trade and retail trade. Labour productivity in electricity, gas, water, and waste services
benefited from IT capital deepening in the 1990s, leading to a contribution of 0.3
percentage points a year for 1978–2011.
In the latest incomplete cycle (2008–11), printing; transport equipment, machinery, and
equipment manufacturing; retail trade; and administrative and support services showed
contributions of IT capital deepening to labour productivity of 0.5 percent a year or above.
17Information technology’s contribution to labour productivity growth
Primary industries showed the lowest contribution of IT capital deepening for 1978–2011.
MFP provided the main contributions for the agricultural industries and non-IT capital for
mining. This result is perhaps not surprising given the nature of these industries and the
dominance of other assets in their capital stocks (eg land and inventories for agriculture).
Industries with higher contributions from IT capital deepening for 1978–2011 also tended
to have higher contributions for 1996–2011 (see tables 3 and 4). Table 4 also includes
growth accounting estimates for the additional service industries that are measured from
1996. Information, media, and telecommunications, finance and insurance, and
professional, scientific, and technical services were the industries with the highest
contributions to labour productivity growth from IT capital deepening for 1996–2011. IT
capital deepening was the highest contributor to labour productivity for administrative and
support services, and arts and recreation, for 1996–2011. IT capital deepening provided
higher contributions than non-IT capital deepening for other services during this time.
Table 3
3 Growth accounting for labour productivity, by broad industry group and industry, average annual growth rates, 1978–2011
Growth accounting for labour productivity, by broad industry group and industry,
average annual growth rates
1978–2011
Contribution
Contribution
Labour of non-IT
of IT capital MFP
productivity capital
deepening
deepening
Industry Percent
Primary industries 3.3 0.1 1.3 1.9
Agriculture, forestry, and fishing 3.2 0.1 0.8 2.3
Agriculture 3.0 0.0 0.5 2.5
Forestry and fishing, and services to
2.9 0.1 1.1 1.7
agriculture, forestry, and fishing
Mining 2.1 0.1 2.7 -0.7
Goods-producing industries 1.4 0.2 0.9 0.3
Manufacturing 1.6 0.3 1.0 0.3
Food, beverage, and tobacco 1.8 0.2 1.0 0.6
product manufacturing
Textile, leather, clothing, and
2.4 0.2 0.6 1.6
footwear manufacturing
Wood and paper products
2.1 0.3 0.8 1.0
manufacturing
Printing 0.6 0.4 0.2 0.0
Petroleum, chemical, polymer, and
2.1 0.3 1.6 0.2
rubber product manufacturing
Non-metallic mineral product
1.8 0.2 1.1 0.6
manufacturing
Metal product manufacturing 0.6 0.2 0.7 -0.3
Transport equipment, machinery,
1.2 0.5 0.3 0.4
and equipment manufacturing
Furniture and other manufacturing 0.1 0.2 0.1 -0.2
Electricity, gas, water, and waste
2.2 0.3 1.7 0.2
services
18Information technology’s contribution to labour productivity growth
Contribution
Contribution
Labour of non-IT
of IT capital MFP
productivity capital
deepening
deepening
Industry Percent
Construction 0.6 0.1 0.3 0.2
(1)
Service industries 2.2 0.7 0.4 1.1
Wholesale trade 1.0 0.4 0.0 0.6
Retail trade 1.1 0.5 0.3 0.3
Accommodation and food services -1.2 0.1 0.2 -1.5
Transport, postal, and warehousing 3.5 0.2 0.2 3.1
Information, media, and
5.6 1.4 1.8 2.2
telecommunications
Finance and insurance 2.8 1.5 0.2 1.1
1. Service industries include: wholesale trade; retail trade; accommodation and food services;
transport, postal, and warehousing; information media and telecommunications; finance and insurance;
and arts and recreation.
Table 4
4 Growth accounting for labour productivity, by broad industry group and industry, average annual growth rates, 1996–2011
Growth accounting for labour productivity, by broad industry group and industry,
average annual growth rates
1996–2011
Contribution
Contribution
Labour of non-IT
of IT capital MFP
productivity capital
deepening
deepening
Industry Percent
Primary industries 1.9 0.1 1.4 0.4
Agriculture, forestry, and fishing 1.8 0.1 0.9 0.8
Agriculture 1.9 0.1 0.7 1.1
Forestry and fishing, and services to
-0.4 0.1 0.3 -0.7
agriculture, forestry, and fishing
Mining -0.3 0.1 1.5 -1.8
Goods-producing industries 1.3 0.2 0.6 0.4
Manufacturing 1.7 0.3 0.5 0.8
Food, beverage, and tobacco
1.0 0.1 0.6 0.3
product manufacturing
Textile, leather, clothing, and
2.9 0.3 0.5 2.1
footwear manufacturing
Wood and paper products
2.7 0.3 0.8 1.6
manufacturing
Printing 0.3 0.6 0.5 -0.8
Petroleum, chemical, polymer, and
3.0 0.2 0.6 2.2
rubber product manufacturing
Non-metallic mineral product
1.6 0.2 1.4 -0.1
manufacturing
19Information technology’s contribution to labour productivity growth
Contribution
Contribution
Labour of non-IT
of IT capital MFP
productivity capital
deepening
deepening
Industry Percent
Metal product manufacturing 0.6 0.2 -0.1 0.5
Transport equipment, machinery,
1.9 0.7 0.2 1.0
and equipment manufacturing
Furniture and other manufacturing 1.4 0.3 0.2 0.8
Electricity, gas, water, and waste
-0.4 0.3 1.7 -2.4
services
Construction 0.8 0.2 0.0 0.6
Service industries (measured
(1) 1.6 0.6 0.2 0.7
sector)
Service industries (former measured
(2) 2.2 0.8 0.5 1.0
sector)
Wholesale trade 2.0 0.6 -0.2 1.7
Retail trade 1.8 0.5 0.2 1.1
Accommodation and food services -0.5 0.1 0.4 -1.0
Transport, postal, and warehousing 1.3 0.2 0.7 0.4
Information, media, and
5.1 1.4 1.9 1.7
telecommunications
Finance and insurance 3.7 1.8 0.2 1.6
Rental, hiring, and real estate
2.4 0.1 1.1 1.2
services
Professional, scientific, and
0.2 0.9 0.0 -0.7
technical services
Administrative and support services -2.2 0.4 -0.1 -2.5
Arts and recreation services -0.6 0.3 0.2 -1.1
Other services 2.6 0.3 0.2 2.1
1. Service industries (measured sector) include: wholesale trade; retail trade; accommodation and food
services; transport, postal, and warehousing; information, media, and telecommunications; finance and
insurance; rental, hiring, and real estate services; professional, scientific, and technical services;
administrative and support services; arts and recreation services; and other services.
2. Service industries (former measured sector) include: wholesale trade; retail trade; accommodation
and food services; transport, postal, and warehousing; information, media, and telecommunications;
finance and insurance; and arts and recreation services.
Contributions of IT capital deepening were driven by growth in capital services as income
shares were relatively low. Although similar growth in capital services was observed
across industries, income shares were remarkably low (or even non-existent) for some
industries (see table 5).
20Information technology’s contribution to labour productivity growth
Table 5
5 Income shares and input growth, by broad industry group and industry, 1996–2011
Income shares and input growth, by broad industry group and industry
1996–2011
Average income
Average annual input growth
share
IT Non-IT IT Non-IT Labour
Industry Proportion Percent
Primary industries 0.01 0.53 14.7 2.1 -0.6
Agriculture, forestry, and fishing 0.01 0.56 13.1 2.5 1.7
Agriculture 0.00 0.47 14.8 1.1 -0.8
Forestry and fishing, and services to
0.00 0.43 17.3 0.2 -1.3
agriculture, forestry, and fishing
Mining 0.01 0.81 15.6 3.7 1.9
Goods-producing industries 0.02 0.40 13.0 1.7 0.1
Manufacturing 0.02 0.39 12.4 0.4 -1.0
Food, beverage, and tobacco product
0.01 0.41 12.9 2.0 0.7
manufacturing
Textile, leather, clothing, and footwear
0.02 0.27 9.9 -3.8 -5.3
manufacturing
Wood and paper products
0.02 0.37 12.4 0.2 -1.7
manufacturing
Printing 0.04 0.32 15.1 -0.5 -2.1
Petroleum, chemical, polymer, and
0.02 0.50 8.1 -1.0 -2.4
rubber product manufacturing
Non-metallic mineral product
0.02 0.48 15.7 2.5 -0.5
manufacturing
Metal product manufacturing 0.02 0.36 13.6 -0.9 -0.5
Transport equipment, machinery, and
0.05 0.26 15.3 0.0 -0.9
equipment manufacturing
Furniture and other manufacturing 0.02 0.24 12.5 -1.5 -2.7
Electricity, gas, water, and waste
0.03 0.79 13.3 4.0 1.7
services
Construction 0.01 0.22 20.7 2.7 2.6
(1)
Service industries (measured sector) 0.05 0.35 15.0 2.4 1.7
Service industries (former measured
(1) 0.06 0.34 14.3 2.4 1.0
sector)
Wholesale trade 0.04 0.33 14.0 -0.3 0.4
Retail trade 0.04 0.28 15.9 1.7 1.2
Accommodation and food services 0.01 0.24 16.1 3.8 2.3
Transport, postal, and warehousing 0.02 0.38 14.0 2.9 1.1
Information, media, and
0.14 0.47 10.4 4.6 0.3
telecommunications
Finance and insurance 0.12 0.28 16.8 1.1 0.3
21In
nformation technology’s con
ntribution to labbour productiv
vity growth
Averag
ge income
Averaage annual in
nput growth
share
s
IT Non-IT IT Non-IT Labourr
Industry Pro
oportion Percentt
Rental, hiring
g, and real estate services 0.00 0.78 17.9 2.1 0.7
Professional, scientific, an
nd technical
0.07 0.15 17.3 3.5 3.5
services
Administrativve and supporrt services 0.05 0.15 15.7 4.2 5.3
Arts and recreation service
es 0.02 0.43 19.4 4.4 3.9
es
Other service 0.01 0.14 22.7 2.3 0.8
1. Service in
ndustries (mea asured sector) include: whollesale trade; retail trade; acc
ccommodation and food
services; transport, postal, and warehou using; informa
ation, media, and
a telecommuunications; finance and
insurance; reental, hiring, and
a real estatee services; pro
ofessional, scieentific, and tecchnical service
es;
administrativve and supporrt services; artts and recreatiion services; and
a other servvices.
2. Service in
ndustries (form
mer measured sector) includ de: wholesale trade;
t retail traade; accommoodation and
food servicess; transport, postal,
p and wa
arehousing; infformation, med
dia, and telecoommunication ns; finance and
d
insurance; and arts and re ecreation serv ices.
Industriies in de
etail
This section
n focuses on n IT’s contrib
bution to lab
bour productivity for the tthree industtries
where the strongest
s conntributions wwere found: information,, media, andd
telecommun nications; fin
nance and in nsurance; an onal, scientiffic, and technical
nd professio
services.
As figure 2 shows,
s IT caapital deepe
ening made positive con ntributions too labour prod
ductivity
in the inform
mation media a and teleco
ommunicatio ons industry from 1978. For 1978–2 2011, IT
capital deeppening accounted for ap pproximately y one-quarteer of total labbour productivity
growth (con ntributing 1.4
4 percent of the 5.6 perccent annual growth). Avverage annual
contributionns from MFP P and non-IT T capital deeepening were e 2.2 percennt and 1.8 peercent,
respectivelyy. IT provide
ed greater co ontributions to labour productivity grrowth than non-IT
n
capital until 1985, contrrasting with S
Solow’s (1987) view tha at IT had minnimal effect on
productivity. IT’s contrib
butions to la bour producctivity growth
h were stronngest for this
s
industry durring the 1990 0s.
Figure 2
2 Information, media, and telecommunications contributions to labour productivity growth, average annual percentage cha
ange
Figure 3 sho
ows that lab
bour producttivity in the finance and insurance inndustry bene efited
most strong
gly from grow
wth in IT cap
pital deepening. The con ntributions oof IT capital
22In
nformation technology’s con
ntribution to labbour productiv
vity growth
deepening were
w greatest during the
e 1980s and d the 2000s, with the strrong perform
mance of
the 1990s driven
d by MF
FP. For 1978 8–2011, app proximately half the laboour productiv
vity
growth could be explain
ned by IT ca apital deepen
ning. Non-ITT capital deeepening
contribution
ns were minimal over thee long term and in all co
omplete cyclles.
Figure 3
3 Finance and insurance contributions to labour productivity growth, average annual percentage change
As figure 4 shows,
s the professional
p l, scientific, and technical services iindustry had
d
minimal laboour productiivity growth for 1996–20 011. IT capittal deepeninng was by fa
ar the
greatest conntributor to labour produuctivity, but declining
d MFFP all but coompletely offfset this
contribution
n. IT capital contributions
c s to labour productivity
p growth
g exceeeded non-IT T
contribution
ns in all perio
ods.
Figure 4
4 Professional, scientific, and technical services contributions to labour productivity growth, average annual percentage ch
hange
Outputs and inputs
For 1978–2011, growth h in IT capita
al services was
w strong in n finance annd insurance e
(increasing 25.6 percen nt a year) an
nd informatio
on, media, and
a telecomm munications s (up
20.4 percen nt a year). Fo
or 1996–201 11, IT capita
al-services growth
g sloweed to 16.8 percent a
year in finan
nce and insu urance and tto 10.4 perccent a year in informatioon, media, an nd
telecommun nications. Buut it grew 17
7.3 percent a year in pro
ofessional, sscientific, and
technical seervices durin
ng this periodd.
The growth in IT capital services coonsistently surpassed
s growth in laboour input forr each of
es that bene
the industrie efited strong ly from IT ca
apital deepe
ening. With ssuch strong growth
23Information technology’s contribution to labour productivity growth
in IT capital services, ‘IT capital per hour paid’ closely reflected the growth in IT capital
services as changes in labour input were relatively minor.
Table 6 summarises output and input growth over growth cycles for the three main
industries benefiting from IT capital deepening. All three industries showed declining
capital productivity in all cycles. This is the result of consistently high growth in IT capital
services in all cycles. IT capital input slowed across cycles for each industry, but still grew
faster than non-IT assets and labour inputs – resulting in strong growth in IT capital
deepening. Relatively low weights for IT capital mediated the strong growth IT input had
on total inputs.
Table 6
6 Outputs and inputs, selected industries, average annual growth rates, by cycle
Outputs and inputs, selected industries, average annual growth rates, by cycle
1978–2011
IT Non-IT
IT Non-IT capital- capital- Total
Output Labour
capital capital labour labour inputs
ratio ratio
Industry Cycle(1) Percent
Information, 1978–82 3.5 0.5 35.9 -0.7 35.3 -1.2 0.6
media, and 1982–85 5.5 0.6 40.9 3.5 40.1 2.9 2.9
telecom-
1985–90 5.7 -0.4 29.6 7.6 30.1 8.1 4.5
munications
1990–97 6.0 -1.3 22.0 4.5 23.6 5.9 3.2
1997–2000 8.7 -1.6 16.3 7.2 18.2 8.9 4.9
2000–08 5.8 1.7 8.0 3.9 6.2 2.2 3.7
2008–11 0.9 -3.2 3.8 2.4 7.3 5.8 0.2
1978–2011 5.3 -0.3 20.4 4.2 20.7 4.4 3.0
1996–2011 5.4 0.3 10.4 4.6 10.1 4.2 3.6
Finance and 1978–82 5.6 2.3 62.8 1.6 59.2 -0.7 2.6
insurance 1982–85 5.0 2.6 72.1 6.0 67.8 3.3 5.9
1985–90 2.6 3.7 29.1 5.2 24.6 1.5 6.1
1990–97 2.5 -1.0 5.8 -0.9 6.8 0.0 -0.4
1997–2000 3.9 -3.7 24.5 -3.1 29.4 0.6 -1.8
2000–08 5.1 2.0 15.4 1.5 13.1 -0.6 3.6
2008–11 1.7 -0.9 16.6 4.6 17.7 5.6 3.2
1978–2011 3.8 0.9 25.6 1.8 24.4 0.9 2.7
1996–2011 4.0 0.3 16.8 1.1 16.4 0.8 2.4
Professional, 1997–2000 4.1 3.4 22.1 5.7 18.0 2.1 5.1
scientific,
2000–08 4.2 3.7 18.5 4.8 14.3 1.0 4.8
and technical
services 2008–11 0.2 0.9 10.6 -3.2 9.6 -4.0 1.1
1996–2011 3.8 3.5 17.3 3.5 13.3 -0.1 4.5
1. 1978–82 and 2008–11 are incomplete cycles.
Output growth can be decomposed into contributions from IT capital deepening, non-IT
capital deepening, labour input, and MFP.
24In
nformation technology’s con
ntribution to labbour productiv
vity growth
For the information, me edia, and tele
ecommunica ations indus
stry, IT capitaal provided strong
ns to output growth
contribution g (con tributing 1.4
4 percent annually for 19978–2011) – but
non-IT capittal (which includes com munications s capital) and MFP weree generally thet main
contributorss (providing 2.2
2 percent and 1.8 perrcent to annu ual output g rowth, respeectively).
For finance and insuran nce, MFP wa as the main contributor to output grrowth during g the
1990s whilee IT contributed the mosst in the 1980s and 2000 0s. Labour pprovided thee highest
contribution
ns to output growth
g in the nal, scientific
e profession c, and technnical services
industry unttil 2008, whe
en IT input g
growth became the main n contributorr.
IT capital income shares
IT capital co
omprises a relatively
r low
w share of to
otal industry income, eveven for those
e
industries where
w IT cap
pital servicess make a strrong contribuution to laboour productiv
vity (see
figure 5).
Finance and d insurance had the hig hest share of o income atttributable too IT capital by
b 2011,
but still lesss than one-fiffth of its tota
al industry in
ncome. Growwth in IT cappital income was
strong durin ng the 1980ss for informa ation, media, and telecommunicatioons, and for finance
f
and insuran nce. Capital income grow wth accelera ated again fo
or 1996–20001 for inform mation,
media, and telecommun nications, an nd from 199 97–2005 for finance andd insurance.
Figure 5
5 IT capital income shares, selected industries
Figure 6 shoows that, wh hen compariing IT capita al income with non-IT caapital income (ie
removing thhe degree off labour inten nsity), IT capital incomee has becom me more imp portant in
the capital mix
m over time. While the e IT income share for professional, sscientific, annd
technical seervices is the
e lowest of tthe three inddustries, it ha
as more incoome attributtable
from IT capital relative to
t its non-IT
T capital than n the other industries coonsidered he
ere.
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