This study examines the comparative impact of multilateral trade agreements on intra-regional trade in the Southern African Development Community (SADC) and the Economic Community of West African States (ECOWAS) regions in Africa. Annual data was gathered from 2000 to 2018 and dynamic panel data and econometric techniques were used to control for individual country characteristics, endogeneity, serial correlation, heteroscedasticity and interdependencies between the countries in each region. Two estimations were done, one using the tariff measures of multilateral agreements, the second using non-tariff measures of multilateral agreement. The results of the empirical analysis show that the SADC region has a slight edge over ECOWAS in terms of technological progress and investment, especially in trade infrastructure. However, the ECOWAS levels of employment and economic growth are higher than those in the SADC region. These differences further translate into differences that drive intra-African trade in these regions, and how they relate to the role of multilateral agreements in intra-African trade in each of these regions. While technology and investment are key drivers and enhancers of intra-African trade in SADC countries, economic growth and employment stand out as key enhancers of intra-African trade in ECOWAS, especially where multilateral agreement is represented by tariff measures. This study reports that when non-tariff measures are used to represent multilateral agreements, export trade costs, in addition to investment and technology, are the key drivers of intra-African trade in SADC countries. For ECOWAS, under non-tariff measures of multilateral agreements, only economic growth drives intra-African trade. / Business Management / D. Phil. (Business Management)
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/27227 |
Date | 02 1900 |
Creators | Osarumwense, Uwakata Yvonne |
Contributors | Aregbeshola, Rafiu Adewale |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | 1 online resource (x, 146 leaves), application/pdf |
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