Innovation, productivity and learning induced by export across European manufacturing firms

Agustí Segarra-Blasco, Mercedes Teruel and Sebastiano Cattaruzzo

Economics of Innovation and New Technology, 2022, vol. 31, issue 5, 387-415

Abstract: This paper analyses the links between R&D, innovation, productivity and exports for European manufacturing firms between 2001 and 2014. In comparison with previous studies, we consider the temporal and spatial dimension of learning-by-exporting. By applying a Heckman equation and GSEM methodology, we find a robust self-selection process from productivity to export and export-induced learning effects in terms of length of time and number of markets. Our results show that firms in leader countries are more sensitive to temporal learning, while spatial learning has more influence for firms in less advanced countries. Our results indicate that the export learning has a different impact depending on the innovation position of each country.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1080/10438599.2020.1823673 (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:31:y:2022:i:5:p:387-415

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

DOI: 10.1080/10438599.2020.1823673

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 ().