R&D policy instrument mix sequencing: evaluating the impact of receiving R&D grants and R&D tax credits over time on firm-level R&D
The R&D policy instrument mix concept has become increasingly important for understanding how public R&D support drives firm-level R&D. To-date, empirical studies have conceptualised the R&D policy instrument mix as a static unit, whereby firms receive different R&D policy instruments at one point in time. However, firms can also receive different instruments in a sequence, over time. While potential sequencing effects are well rehearsed theoretically, this issue remains a major gap in the empirical literature. Our study evaluates, for the first time, how R&D policy instrument mix sequencing impacts firm-level R&D. We construct a unique dataset, comprising 8, 556 unique firms, and 36, 136 firm-year observations, over a 17-year period for Ireland. Our analysis focuses on two different R&D policy instruments (R&D grants and R&D tax credits) pursuing the same policy objective. We develop a novel approach to measure R&D policy instrument mix sequencing, focusing on the R&D policy instruments firms receive over a four-year time window. We implement this approach using a multi-treatment panel-data matching approach, which addresses issues of selection bias. Our results suggest that R&D policy instrument mix sequencing is highly effective at driving firm-level R&D, and that some sequences are more effective than others. These findings highlight opportunities to realise superior policy outcomes through targeted sequencing.
Authors
- Kevin Mulligan (ORCID: https://orcid.org/0000-0001-7870-2430)
- Mauricio Perez-Alaniz (ORCID: https://orcid.org/0000-0001-8859-6969)
- Christian Rammer (ORCID: https://orcid.org/0000-0002-1173-9471)
- Helena Lenihan (ORCID: https://orcid.org/0000-0001-6038-0904)
Institutions
- Queen's University Belfast (GB)
- Centre for European Economic Research (DE)
- University of Limerick (IE)
Publication Details
- Journal
- Industry and Innovation
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1080/13662716.2024.2388650
- Citations
- 12
- Primary Topic
- Innovation Policy and R&D
- Type
- article
- Field-Weighted Citation Impact
- 13.55
Funders
- Science Foundation Ireland