Research Collaborations Research Collaborations

These reports have been prepared for the European Commission - Joint Research Centre under subcontracting arrangements.

A reappraisal of the impact of corporate R&D and innovation on employment

Marco Vivarelli
August 2016

The aim of this report is to provide updated quantitative and qualitative analyses of the impact of corporate R&D and innovation on employment in industries and firms in the European Union member states. Over the last decades, the paradigm based on ICT and automation has led to a dramatic adjustment of the employment structure raising again a widespread fear of an upcoming "technological employment". After a critical survey of the more updated empirical evidence on the topic, new econometric analyses (longitudinal data), based on a dynamic labour demand, are provided. The first one is at the sectoral-level and uses OECD STAN-ANBERD data; the second one is at firm-level and uses European R&D top-performers Scoreboard data. In addition, two microeconometric studies, based, respectively, on Italian and Spanish firm-level data, are provided. Finally, in order to offer evidence of the "qualitative" impact of innovation, a tentative study matching, at the sectoral-level, OECD STAN-ANBERD and EU-SILC data, has been provided. Overall, R&D seems to have a positive and significant impact on employment, especially in high-tech industries. Moreover, R&D positively affects the categories of tertiary educated workers, high-skilled white-collars and the employees handling non-routinized tasks.

Study on tools for causal inference from cross-sectional innovation surveys with continuous or discrete variables

Dominik Janzing
June 2016

Dominik Janzing, from the Max Planck Institute for Intelligent Systems, recently finished a subcontracted report entitled "Tools for causal inference from cross-sectional innovation surveys with continuous or discrete variables." The machine learning community has recently developed some exciting new techniques for causal inference from observational data, which work even for discrete variables. In this project, Dominik applied these techniques to analyse Scoreboard data (on the world's largest R&D investors) as well as Community Innovation Survey data. The report contains a large number of results, and also makes the software available for future research.