Productivity Effects of Inventor Mobility in Agglomerations and Teams

• Applicants: Dr. Fabian Gäßler; Dr. Joerg Heining; Professorin Dr. Karin Hoisl
• Subject Area: Accounting and Finance ; Statistics and Econometrics
• Term: from 2016 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 329144242

The main goal of the proposed project is to contribute to the understanding of knowledge production by inventors in either teams or (industrial) agglomerations. Towards this objective, our main focus will be on the role of inventor mobility via the labor market. According to the literature, the latter is a prominent mechanism to transfer knowledge and a contributor to successful knowledge generation. In the first part of the project we analyse the effects of spatial mobility on inventive productivity in the context of agglomerations. The results will provide micro level evidence how knowledge production of inventors benefits from an environment of agglomeration. In the second part, we address the dynamics of inventor teams in form of individual mobility or the co mobility of inventor teams. By using changes in team composition, we want to explain the role of team specific capital for inventive performance. In our research we aim at identifying the causal effects of mobility on knowledge production, as measured by patent applications. Our project is also the first to study these research questions in the context of the German labor market and innovation system. So far, contributions to research on the proposed topics have been hardly possible due to the lack of adequate inventor micro data. Therefore, the generation of a novel linked inventor biography dataset on German inventors, combining patent register data with social security data by means of record linkage, form the initial part of our project. The generation of this data will be based on and exploit prior experience and methodological skills of the applicants and the project partners with respect to patent register and social security data. The resulting linked employer-employee dataset includes detailed information from patent registers as well as labor market biographies originating from social security data. This database enables us to apply state-of-the-art micro econometric methods and to implement alternative strategies to identify the causal relationships of interest. With the conclusion of our research we commit to contribute our research data to the scientific community by supplying the dataset via the research data centre of the Federal Employment Agency at IAB.

• DFG Programme: Research Grants
• Cooperation Partner: Professor Dr. Dietmar Harhoff