Abstract
The article assesses the effect of Aid for Trade (AfT) inflows on trademarks applications submitted by AfT recipient-countries’ residents. Based on a set of 59 AfT recipient-countries over the period 2002–2014, and using the negative binomial regressions approach, results show that total AfT flows exert a positive and significant effect on trademark applications. However, this positive effect is primarily driven by that of AfT for productive capacity building on trademark applications. The policy implication of these findings is that higher AfT inflows, in particular AfT flows for productive capacity building to recipient-countries would help trading firms submit a high number of trademarks applications, which would in turn contribute to promoting international trade in these countries.
Acknowledgements
This article represents the personal opinions of individual staff members and is not meant to represent the position or opinions of the WTO or its Members, nor the official position of any staff members. The author would like to express his sincere gratitude to the anonymous Reviewers for their useful comments on an earlier version the article. Any errors or omissions are the fault of the author.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1 According to the United Nations, the Group of LDCs constitutes the poorest and most vulnerable countries to natural and external shocks (for further details, see http://unohrlls.org/about-ldcs/)
2 The WTO Agreement on TRIPS covers seven main areas of intellectual property: copyrights, trademarks, patents, geographical indications, industrial designs, layout designs of integrated circuits, and undisclosed information including trade secrets.
3 Intellectual property rights (IPRs) are key features of the Trade-related Intellectual Property Rights (TRIPs) Agreement, signed by WTO Members in 1994. This Agreement was one of the founding Agreements of the WTO (successor of the General Agreement on Tariffs and Trade - GATT-).
4 A good literature review on this subject matter could be found in Schautschick and Greenhalgh (Citation2016).
5 Details on the components of these categories of AfT are provided in Appendix 1.
6 The Negative Binomial model lifts the assumption of independence of observations by adding a parameter – the unobserved specific effects – reflecting unobserved (between-subject) heterogeneity, which might explain overdispersion.
Additional information
Notes on contributors
Sèna Kimm Gnangnon
Sèna Kimm Gnangnon is Economist at the Secretariat of the World Trade Organization (WTO). He holds a PhD degree in Development Economics, at CERDI (Centre d'Etudes et de Recherches sur le Développement International) – University of Clermont-Ferrand, in France. Before joining the WTO, he was Economist at the Organization Internationale de la Francophonie, and Consultant at the French Agency for Development (in Paris), as well as at the WTO Secretariat (in Geneva). He also held Research Assistant and Teaching Assistant positions in CERDI (Centre d'Etudes et de Recherches sur le Développement International) – University of Clermont-Ferrand, France.