Firm-level contributions to the R&D intensity distribution: evidence and policy implications

Sebastiano Cattaruzzo, Agustí Segarra-Blasco and Mercedes Teruel

Economics of Innovation and New Technology, 2024, vol. 33, issue 1, 45-65

Abstract: This paper decomposes the Spanish aggregate R&D distribution to disentangle the contributions of R&D public financing, gazelle firms, and financial constraints. Applying the Chernozhukov, Fernández-Val and Melly (2013) distribution regression approach, we estimate the contributions of these components at each point of the distribution. The analysis is carried out for two periods, pre-crisis 2004–2008 and post-crisis 2009–2014. We thereby introduce a comparative perspective that allows us to consider possible business cycle effects. Our findings show that the main explanatory factors of the significant post-crisis drop in Spanish aggregate R&D are changes in the public financing scheme and the decreased contribution of gazelles. Our results provide a rigorous analysis of Spanish R&D, hint at a possible transmission channel for reduced business dynamism, and offer interesting insights for policymaking.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10438599.2022.2140658 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:ecinnt:v:33:y:2024:i:1:p:45-65

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GEIN20

DOI: 10.1080/10438599.2022.2140658

Access Statistics for this article

Economics of Innovation and New Technology is currently edited by Professor Cristiano Antonelli

More articles in Economics of Innovation and New Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().