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 links 3.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

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)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 use  Diffusion of ICT to services is an important element of economic growth  Productive use of ICT in services is crucial  Analysis 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 –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?

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 Statistics Finland Statistics 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 (but ICT investment & staffnotcovered) The Confederation of Industrial Employershas its own e-business & IT investment surveys Employment Statistics (individual) Industrial Statistics (plant) aggregation ICT 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)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

Findings Computers improve a worker’s productivity by %  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 %. 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 Back Source: Maliranta (1996), ICOP database, Groningen University

Graph 2. Diffusion of ICT use among the workers The increase of the proportion of workers using ICT (computers or internet) Back