The research project aimed to design and create a panel dataset that can be used for impact analyses of research and innovation funding measures (input, output, outcome, behavioral additionality) targeting companies, and to analyze the properties of this dataset with regard to the applicability of different econometric evaluation methods as well as the possibilities for conducting differentiated impact analyses by funding area, firm characteristics, or impact dimensions.

The project improved the conditions for quantitative impact analyses of R&D and innovation funding in Germany, thereby expanding the possibilities for analyzing the economic efficiency of public support measures. To this end, information from administrative data on R&D and innovation funding for companies in Germany was linked with data on R&D and innovation activities, as well as other company indicators relevant for evaluations, from existing panel surveys (the R&D survey of the Wissenschaftsstatistik and the ZEW Innovation Survey) to create a panel data basis. For the dataset thus generated, an assessment was conducted to determine the extent to which it is suitable for applying various econometric evaluation methods, given that these methods place different requirements on data structures (e.g., the need for continuous time-series data over a longer period). In addition, the project examined which differentiation options for impact analyses are possible and which measures in the area of data generation and linkage would be necessary to expand these options.