Assessing the returns to collaborative research: Firm-level evidence from Italy

Giuseppe Medda, Claudio Piga () and Donald Siegel

Economics of Innovation and New Technology, 2006, vol. 15, issue 1, 37-50

Abstract: We use firm-level data from Italian manufacturing firms to assess the relationship between various types of R&D and total factor productivity growth, including collaborative research with other firms and universities. A novel twist to our empirical analysis is that we estimate a sample selection model, which allows us to treat the decision to conduct R&D as endogenous. We find strong evidence of positive returns to collaborative research with other companies, whereas collaborative research with universities does not appear to enhance productivity. This result implies that firms may conduct R&D with universities when appropriability conditions are weak and the outcomes of such research projects do not yield direct strategic benefits.

Keywords: R&D; Collaborative research; Total factor productivity; Sample selection bias (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25) Track citations by RSS feed

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/1043859042000332213 (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:15:y:2006:i:1:p:37-50

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

DOI: 10.1080/1043859042000332213

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 ().