Reverse causality in the R&D-patents relationship: an interpretation of the innovation persistence

Anna Laura Baraldi (), Claudia Cantabene and Giulio Perani

Economics of Innovation and New Technology, 2014, vol. 23, issue 3, 304-326

Abstract: Starting from the failure of the R&D-patents traditional relationship, when time-series and/or within-industry dimensions are included in the empirical analysis, the present work tries to contribute to the empirical literature from two directions. First, it performs a Granger causality test based on the theoretical presumption of a reverse patents→R&D link as an explanation for the failure of the traditional relationship. Second, assuming the reverse patents-R&D causality, we test and interpret the lag structure of such a relationship which shows the effective patent life that firms can expect within the two Schumpeterian patterns of innovations they belong to. In the light of the effective patent life , we offer a further explanation of innovation persistence which overturns the findings of the existing literature on persistence.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/10438599.2013.848059 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Reverse causality in the R&D – patents relationship: an interpretation of the innovation persistence (2013)
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:23:y:2014:i:3:p:304-326

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

DOI: 10.1080/10438599.2013.848059

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 ().