Abstract
Understanding causal relationships among key economic variables is crucial for policy makers, who wish to e.g. stimulate private R&D growth. To this end, we applied a technique recently imported from the Machine Learning community (Structural Vector Autoregressions (SVARs) identified using Independent Components Analysis (ICA)) to a data-set of the world’s largest R&D investors. Our analysis highlights the key role of firm growth in the areas of employment and sales, rather than growth of profits or market capitalization, in stimulating R&D growth. R&D growth appears toward the end of the causal ordering of the growth process. Our results suggest that policies to increase private R&D would do better to target growth of sales and employment rather than market capitalization or profits.
Original language | English |
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Pages (from-to) | 508-533 |
Number of pages | 26 |
Journal | Industry and Innovation |
Volume | 26 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2019 May 28 |
Externally published | Yes |
Keywords
- R&D investment
- SVAR
- firm growth
- market capitalization
- sales growth
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Management of Technology and Innovation