Table 8. Differences in the measurement of technological activities
Assumptions on the nature of technological activities
Formal and informal R&D including software technology
The distribution of technological activities
Mainly in large firms, manufacturing, and electronics/chemicals/transportation
Also in smaller firms in nonelectrical machinery and large and small firms in services
within 1 year. (Some observers have been reluctant to make the reverse offer.)
These competencies are located not only in firms, but also in financial, educational, and management institutions. Institutional practices that lead to under- or misinvestment in technological and related competencies are not improved automatically through the workings of the market. Indeed, they may well be self-reinforcing (Table 7).
Software Technology. Although R&D statistics have been an invaluable source of information for policy debate, implementation, and analysis, they have always had a bias toward the technological activities of large firms compared with small ones and toward electrical and chemical technologies compared with mechanical engineering. The bias is now becoming even greater with the increasing development of software technology in the service sector, while R&D surveys concentrate on manufacturing (Table 8).
As a consequence, statistical and econometric analysis will increasingly be based on incomplete and potentially misleading data. Perhaps more worrying, some important locations of rapid technological change will be missed or ignored. While we are bedazzled by the “high-tech” activities of Seattle and Silicon Valley, the major technological revolution may well be happening among the distribution systems of the oldest and most venal of the capitalists: the money lenders (banks and other financial services), the grocers (supermarket chains), and the traders (textiles, clothing, and other consumer goods).
To conclude, if economic analysis is to continue to inform science and technology policy making, it must play greater attention to the empirical evidence on the nature and locus of technology and the activities that generate it and spend more time collecting new and necessary statistics in addition to exploiting those that are already available. That the prevailing norms and incentive structures in the economics profession do not lend themselves easily to these requirements is a pity, just as much for the economists as for the policy makers, who will seek their advice and insights elsewhere.
This paper has benefited from comments on an earlier draft by Prof. Robert Evenson. It draws on the results of research undertaken in the ESRC (Economic and Social Research Council)-funded Centre for Science, Technology, Energy and the Environment Policy (STEEP) at the Science Policy Research Unit (SPRU), University of Sussex.
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