Research objectives and content
Technological regimes can be distinguished from technological trajectories in terms of complexity: a higher-order regime is expected to perform a longer cycle because it incorporates both the technical and the market dynamics as subdynamics. Data sets are available from previous research consisting of time series of both technical and service characteristics of four technologies (aircrafts, cars, helicopters and computers). Using recent elaborations on entropy measures for the analysis of multivariate data, we analyze the data on path-dependent transitions in trajectories and the emergence of regimes.
The datasets can be decomposed in terms of major producers. Effects of market power on technological strategies can then be analyzed. Additionally, the data allows us to disaggregate in terms of national systems, and in terms of supranational systems (EC and North America). These units of analysis are especially relevant with regard to the military technologies (aircraft and helicopters).
The objectives are threefold. Theoretically, results can be made relevant to theoretical hypotheses in the economics of technical change. Secondly, from a policy perspective, steering effects differ with respect to trajectories in comparison with regimes. A more cornplex regime is expected to generate large
. Furthermore, countries differ in terms of their knowledge bases and policies which constitute the national systems of Comparative analysis allows us to highlight their national competencies. Thirdly, computational routines will be developed to handle multivariate datasets systematically, by which future research is facilitated.
Training content (objective, benefit and expected impact) The INRA / SERD will provide post-graduate courses on economics, econometrics a related areas. Prof. Saviotti will supervise the project.