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RR02 2002/06 „RTD Evaluation Toolbox (abridged version)“

Beteiligte Autoren der JOANNEUM RESEARCH:
Mag. Wolfgang Johannes Polt
S. Arvanitis (ETH Zürich) ; M. Boden (PREST); S. Bührer (FhG-ISI); H. Capron (Université Libre de Bruxelles); M. Cincera (Université Libre de Bruxelles); R. Cowan (MERIT); J. Eaton (Boston University and NBER); L. Georghiou (PREST); G. Fahrenkrog (IPTS); M. Keilbach (ZEW); E. Kinsella (CIRCA Group); S. Kuhlmann (FhG-ISI); G. Licht (ZEW); P. Patel (SPRU); W. Polt; J. Rigby (PREST); J. Rojo (Joanneum Research); G. Sirilli (ISRDS-CNR); E. Stern (Tavistock Institute); A. Tübke (IPTS); B. Woitech; L. Zinöcker (Joanneum Research)
This survey is an effort to compile contemporary models on measuring the leverage effects of public R&D funding. As our starting point we take the consensus amongst economists that leaving R&D performance only to private firms without government intervention will result in an under-investment in R&D in terms of desired social returns (cf. Martin and Scott [2000:439]). Various studies on the R&D spending behavior of firms raise the question whether government R&D funding has a complementary or substitution effect on private R&D investment. Does government funding crowd out private R&D funding completely, partially, or not at all? Are there in fact positive leverage effects observable? Many economists, based on the pioneer work of Blank and Stigler (1957) as well as Griliches (1958), have evaluated the firm behavior on different R&D funding policies. Hence, at the beginning it is necessary to point out our interest in this field. The ‘OECD Working Group on Innovation and Technology Policy’ focuses on the new patterns of private and public financing of R&D. In recent publications they indicate considerable evidence of significantly changing business strategies for R&D:“The growing levels of business R&D compared to publicly funded R&D imply that the private sector exerts greater influence over national innovation systems and that governments must better leverage their more limited resources to improve national innovative performance. The changing patterns of business R&D suggest that governments will need to adapt S&T policies to better complement private sector activities and address emergent market failures while avoiding government failures.”         
 (OECD [2001:2]) The consequences of the changing environment are our main motivation in surveying analytical models and performing new studies on the efficiency of current public R&D policies. Two fields of research have been identified to analyze the linkage between private and public R&D investment. First, there are qualitative analyses, namely case studies, surveys, and peer reviews, which are very expensive if done on a large scale and not well suited for generalization. Furthermore the results are often exposed to critique over the expert’s objectivity. Second, the group of quantitative research studies, which is organized by the degree of data aggregation. The structuring in line of business, firm level, industry level, and macroeconomic models are the commonly used classification of quantitative research studies (cf. David et al. [2000]). Macroeconometric models on measuring leverage effects consider aggregate private and public R&D spending variables with limited possibilities to adjust for heterogeneities and asymmetries among firms or interdependence of enterprise behavior in imperfectly competitive markets (cf. David et al. [2000:525-26]). Thus we decided to focus mainly on the evaluation of microeconometric (line of business, firm level, and industry level) models where we can observe the more disaggregated effects, which are vital for adjusting public R&D funding policies. To cope with the different approaches of recent models a brief outline of various public subsidy instruments and the anticipated firm behavior is given in part 2. In part 3 of this literature survey we are going to present and compare a number of different methods to estimate leverage effects of public R&D spending as well as the key results of these studies.
RR02 2002/06 „RTD Evaluation Toolbox (abridged version)“


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