Working Paper
Möglichkeiten und Grenzen der Evaluation von staatlichen Forschungs- und Innovationsmaßnahmen in Bezug auf ihren Beitrag zur Klimaneutralität
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Climate
Innovation and Structural Change
Sustainable Development
Industrial Policy
Public funding for research and innovation is an important building block for achieving climate neutrality in Germany and other countries. At the same time, there is a considerable need to evaluate the impact of such measures in order to optimise their design.
This paper shows the possibilities and limitations of an evaluation and addresses the specificities of R&I processes. The focus is not only on the evaluation of R&I measures in terms of emission reductions, but also on other contributions of R&I measures to the overarching objective of climate neutrality. In addition, the paper presents the steps and approaches for an impact analysis and different methods used for this purpose are and discusses their opportunities and challenges.
This shows that a systematic analysis of the impacts of governmental R&I measures is possible in principle, but that the quantitative methods in particular are complex on the one hand, and on the other hand very quickly reach their limits in the case of R&I measures that are characterised by a long time lag between funding and impact and a large number of indirect effects and uncertainties. Accordingly, the potential for quantifying emission savings from R&I projects and R&I measures is also limited. This applies in particular to R&I measures targeting intangible activities. The contributions of government R&I measures may also be in the form of cost reductions or system effects. The methods available for cost reductions and their limitations are similar to those for emission reductions. System effects are even more difficult to evaluate. Given this complexity, an overall assessment of the impact of R&I funding on greenhouse gas emission reductions, and more generally on climate neutrality, is often not possible in quantitative terms. Therefore, in cases of doubt, indicator-based or purely qualitative methods may have to be used.
