Using Linguistic Networks to Explain Strength of Intellectual Property Rights

Thomas Cook and Amy H. Liu

World Development, 2016, vol. 87, issue C, 128-138

Abstract: What explains the strength of intellectual property rights (IPR)? While extant research would suggest democratic governments are better constrained to protect property rights, we are agnostic about this mechanism with respect to IPR. We argue IPR—distinct from physical property by their lack of geographical boundaries—are stronger in states not because property owners have a democratic voice, but because they can exit the state as an alternative. We test this argument using a newly constructed network variable that measures the degree of linguistic compatibility between states based on languages of education. We contend that the cost of exit is lower when the language of the intellectual property owner is widely used globally; and vice versa. This linguistic network variable improves on traditional common-language measures in that it considers the same language can be spoken in more than just a pair of dyads and that the education sector is an important arena for disseminating languages that need not be official. We find that (1) democracy has a weak and usually non-significant effect but (2) high linguistic compatibility has a strong and robust effect. The results call attention to the conceptual heterogeneity of property rights and the limited theoretical linkage between regime type and these bundles of rights.

Keywords: intellectual property rights; languages; networks (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305750X15302679
Full text for ScienceDirect subscribers only

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:eee:wdevel:v:87:y:2016:i:c:p:128-138

DOI: 10.1016/j.worlddev.2016.06.008

Access Statistics for this article

World Development is currently edited by O. T. Coomes

More articles in World Development from Elsevier
Bibliographic data for series maintained by Catherine Liu ().