Linking micro data for the analysis of ICT effects

1. Linking micro data for the analysis of ICT effects Mika Maliranta, ETLA Istat – Stat Fin Workshop, June 26th and 27th, Rome

2. 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

3. 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: • Building the ICT micro panel data for the Research Lab of Statistics Finland • Establishing research links • 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)

4. 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 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 1998- Linkable comprehensive registers and other survey data  needed for analyzing productivity effects and controlling background factors (e.g. education) Motivation of the study

5. 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 • How intensive is the use of ICT (ICT diffusion), e.g. what is the proportion of workers that use ICT in their work? • How productively ICT is used, on average, by the workers?

6. 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)

7. Statistics Finland Data compiled @ Statistics Finland Statistics Finland's Internet use and Industrial Employment e-commerce in Statistics Statistics enterprises -surveys are the primary ICT (individual) (plant) data source ('98, '99, '00, '01, '02) Manufacturing & ICT selected services aggregation Survey Samples range from 1300 to 2700 (leaving a few hundred obs. for analysis panel analysis) Financial Statements A 4-page questionnaire Statistics collects a wealth of information (but ICT investment & staff not covered) The Confederation of Industrial Innovation R&D Employers has its own e-business & Survey Survey IT investment surveys

8. 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

9. 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:

10. Productivity effects of computers

11. 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

12. 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

13. Graph 1. Catching up potential has run dry in Finnish manufacturing, USA=100 Source: Maliranta (1996), ICOP database, Groningen University Back

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