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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.
Lenihan et al. (Wed,) studied this question.