Linking micro data for the analysis of ICT effects

Mika Maliranta, ETLA

Istat – Stat Fin Workshop, June 26th and 27th, Rome

Structure of presentation

• The importance of ICT analysis

• Methodological approaches

• Some findings about diffusion and productivity effects of ICT (computers, Internet and LAN) in Finnish business

• Some consideration of the data needs

The economic effects of ICT research project

• Initiated by The Ministry of Trade and Industry to promote micro-level ICT research

• Conducted by Maliranta, Mika (Statistics Finland/ETLA) & Rouvinen, Petri (Etlatieto Oy.)

• The purpose of the project:1. Building the ICT micro panel data for the

Research Lab of Statistics Finland 2. Establishing research links3. First-round analysis of the productivity effects

of ICT:Maliranta, Mika – Rouvinen, Petri (2003), ‘Productivity Effects of

ICT in Finnish Business’, ETLA Discussion Papers 852 (see www.etla.fi)

Motivation of the study• The Finnish economy (manufacturing) has benefited from the

catching up potential– Catching up potential has run dry by the early 90s (see Graph 1)Finnish economy needs a new source of productivity growth– Are the “new economy” tools (i.e. computers, networks, etc.) the

solution?• Services account for an increasing proportion of labor, output

and ICT useDiffusion of ICT to services is an important element of economic growthProductive use of ICT in services is crucialAnalysis should cover service sector (the problems of ‘manucentrism‘)

• The Finnish statistical system provides us with a great opportunity for comprehensive economic analysis– Relatively good quality data from the Finnish ICT surveys conducted for

years 1998-– Linkable comprehensive registers and other survey data needed for analyzing productivity effects and controlling background

factors (e.g. education)

The research question

• The research question of our ultimate interest: The effect of ICT on aggregate (labor) productivity• Some simple algebra:

• The effect is composed of two elements

1. How intensive is the use of ICT (ICT diffusion), e.g. what is the proportion of workers that use ICT in their work?

2. How productively ICT is used, on average, by the workers?

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i ii XPX

X

YYGDP

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i PwX

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XP

Research approaches

• Macro: the use of aggregate data– Industry and/or country data (OECD studies etc.)– Growth accounting (strong assumptions about the

behavior of the firms)

• Micro: the use of micro data– Firm/plant data (difficulties in getting representative,

comprehensive and reliable data)

• Micro-micro: – case studies (difficulties in getting general conclusion)

Data compiled @ Statistics FinlandStatistics FinlandStatistics Finland's Internet use and e-commerce in enterprises -surveys are the primary ICT data source ('98, '99, '00, '01, '02)

Manufacturing & selected services

Samples range from 1300 to 2700 (leaving a few hundred obs. for panel analysis)

A 4-page questionnaire collects a wealth of information (butICT investment & staff notcovered)

The Confederation of Industrial Employershas its own e-business &IT investment surveys

Employment Statistics(individual)

Industrial Statistics

(plant)

aggregationICT

Survey

Financial Statements

Statistics

R&D Survey

Innovation Survey

analysis

Diffusion of ICT use

• ICT is a recent phenomenon, some chilling in the diffusion in the very recent years (see Graph 2)

• The proportion of workers equipped with a computer has increased– 10 percentage points in manufacturing and– 6 percentage points in services in a few year’s

time

• Internet usage has increased more rapidly

Measuring ICT’s productivity effects

• Hypothesis:– A worker equipped with ICT (computer, internet or LAN)

is more productive, on average, than a worker without ICT, measured by

• Other firm and worker characteristics need to be controlled carefully!

• Measurement– Labour: – In ‘efficiency’ units:– Production function:

Productivity effects of computers

Table. Productivity effects of ICT in Finnish businesses

Model ICT-variable sample 1

,

output elasticity of ICT

1 COMPUTER all 0,095 0,126 0,856 0,018 0,111 0,053

2 COMPUTER all 0,099 0,129 0,871 0,000 0,114 0,056

3 LAN all 0,148 0,122 0,870 0,008 0,170 0,081

4 LAN all 0,153 0,123 0,877 0,000 0,175 0,083

5a COMPUTER young 0,277 0,122 0,858 0,020 0,323 0,139

5b COMPUTER middle 0,096 0,125 0,856 0,020 0,113 0,054

5c COMPUTER old 0,042 0,133 0,848 0,020 0,049 0,024

6a LAN young 0,234 0,084 0,908 0,008 0,258 0,122

6b LAN middle 0,148 0,121 0,871 0,008 0,169 0,080

6c LAN old 0,117 0,156 0,836 0,008 0,140 0,065

Findings• Computers improve a worker’s productivity by 10-20 %

consistent with the economic theory and earlier estimates roughly a half %-points of annual output growth can be attributed to

ICT: (10%/3 years)*15%=0.5% per year.Output elasticity of ICT capital is around 5 - 8 %.

• Significant differences between different ‘technologies’, sectors and firms– Young firms use ICT more productively than older ones– Internet (external communication) very productive in the young service

firms and very unproductive in the old manufacturing firms– LAN ( internal communication) quite productive in manufacturing firms

• Important to control labor characteristics and other relevant factors; – dropping the controls for educational levels and fields doubles the

estimates of ICT effects

Some consideration of the data needs• Careful analysis of productivity effects of ICT calls for

good panel micro data– Large and representative samples to obtain “degrees of

freedom” for the analysis– Linkability with registers and other surveys

A need for co-ordination between surveys (and consideration for respondence burden)

• Avoidance of asking the same question twice (or three times)• A lot of various information from the same firms (in the same year)

– The needs of the panel analysis• The same information from the same firms from the different years• Conflict with the need sharing respondence burden through rotation• The ‘long differences’ are more useful than the ‘short differences’ A firm may be included in the sample, say, every second or three

years, not necessarily in the successive years

Graph 1. Catching up potential has run dry in Finnish manufacturing, USA=100

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Belgium

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BackSource: Maliranta (1996), ICOP database, Groningen University

Graph 2. Diffusion of ICT use among the workers

Manufacturing

-2 %

0 %

2 %

4 %

6 %

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10 %

per

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The proportion ofcomputer users

4,5 % 3,3 % 2,1 %

The proportion ofInternet users

6,5 % 8,8 % 4,1 %

1998-99 1999-00 2000-01

Services

-2 %

0 %

2 %

4 %

6 %

8 %

10 %

per

cen

tag

e p

oin

tsThe proportion ofcomputer users

2,0 % 5,8 % -1,7 %

The proportion ofInternet users

3,6 % 6,4 % 2,0 %

1998-99 1999-00 2000-01

The increase of the proportion of workers using ICT (computers or internet)

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