Deep regional trade agreement as a driver for global value chains in Africa: the case of ECOWAS region

Essotanam Mamba () and Afi Balaki ()
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Essotanam Mamba: University of Kara
Afi Balaki: University of Kara

Economic Change and Restructuring, 2023, vol. 56, issue 3, No 24, 2037-2068

Abstract: Abstract Deep regional trade agreement (RTA) is likely to enhance global value chains (GVCs) by increasing coordination of trade policies. Economic Community of West African States (ECOWAS), established on 28 May 1975, aims to promote integration of members into regional and global trade, especially trade in GVCs. Thus, a trade liberalization programme called ECOWAS Trade Liberalization Scheme (ETLS) is instituted in 1979. The ETLS covers protocols and conventions which go beyond tariff reduction and must be signed and then ratified. The paper investigates the effects of deep RTA on GVCs for 11 countries from the ECOWAS region during 1996‒2018 by applying the fractional logit regression technique. GVCs are calculated as shares of foreign value-added (FVA), domestic value-added (DVA), and DVA exports (DVX) in gross exports. Unlike previous works that often use the binary variable, RTA is measured by a new continuous indicator relating the ETLS protocols and conventions ratified. Second, the paper analyses control of corruption as a channel through which RTA influences GVCs. The findings reveal that deepening RTA significantly increases FVA, while it reduces DVA, but only at the 10% level. Furthermore, our findings indicate the existence of a complementarity relationship between deep RTA and control of corruption in DVX model. ECOWAS governments should pursue the ratification of the ETLS protocols and conventions in order to increase their chances of integration into GVCs (FVA). Furthermore, governments should remember that RTA should not be seen in isolation, and control of corruption is needed to enhance its effect on DVX.

Keywords: Deep regional trade agreement; Control of corruption; Global value chains; ECOWAS; Fractional logit regression; Panel data; C26; F1 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10644-023-09503-x

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