This article presents a comparative analysis of the evolution of national research policies during the past three decades in six European countries (Austria, Italy, France, Netherlands, Norway and Switzerland), with a special focus on the changes of public project funding schemes. It systematically uses indicators on the volume of funding attributed by each instrument and agency, which have been developed in a project of the European network of excellence PRIME. A common model is identified in these countries, where project funding is the second main channel of public funding of research, but also there are considerable variations among them in the share of instruments and agencies, and in beneficiaries. There are three interesting commonalities: a strong increase of project funding volumes; a differentiation of instruments; and a general shift towards instruments oriented to thematic priorities. They also show that individual countries appear to follow quite distinct paths in the organisation setting of funding agencies, and that national differences in funding portfolios persist through time.
This paper investigates the impact of firm R&D policies supporting R&D investment and collaboration on company innovation performance. Individual and cooperative R&D investments are considered as intermediate outcomes (input and behavioural additionality, respectively) contributing to the final outcome (probability of product innovation). We use a treatment random coefficient model to estimate the policy additionality on a panel dataset merging the third and the fourth wave of the Italian Community Innovation Survey. Results show a significant and positive policy impact on company propensity to product innovation only for the input additionality and for the interaction between the input and the cooperative additionality. This occurs when company cooperation scores overcome a given threshold, in accordance with the assumption that cooperation entails benefits but also coordination costs.
This paper applies different econometric methods to evaluate the effect of public subsidies on firms' R&D activity. For the sake of robustness, results from the Heckman selection model (Heckit), Control-function regression, Difference-in-differences, and various Matching methods are compared by using the third and fourth wave of the Italian Community Innovation Survey (CIS3, years 1998 and CIS4, years 2002. We predict the absence of a full crowding-out of private R&D performance, both for the whole sample and for some subsets of firms. Nevertheless, we conclude that while for variables expressed as ratio (R&D intensity and R&D per employee) the difference in results is negligible, R&D expenditure presents a strong variability among the approaches, even for those relying on similar identification assumptions. Given the utmost importance of this target-variable, future works should go beyond the use of single methods, especially when they are thought of to steer future policymaking.
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