1. EXPLORING TRADE LINKAGES AMONGST AFRICAN ECONOMIES: EVIDENCE FROM A GLOBAL VECTOR AUTOREGRESSIVE (GVAR) ANALYSIS E.C Kinfack and Dr A. Pholo 2 nd International Conference on Sustainable Development in Africa 26-27 november 20015, Dakar

2. OUTLINE OF THE STUDY Motivation Objective(s) and contribution Methodology Results and interpretation Conclusion

3. Motivation  African countries considered regional integration as a key strategy in order to improve intra-African trade and to stimulate economic growth.  Despite the large number of RECs in Africa the region still trade heavily with countries outside the continent (ECA, 2012).  The trade linkage is an important feature of any economic integration.  The synchronisation of business cycles among members within a REC is considered to be an important criterion for countries to form a successful union and trade linkage is an important channel of transmission for such synchronisation (Marcus, 2010).  Intra-regional trade, together with geographically diversified trade linkages, can strengthen the capacity of African countries to absorb global shocks (Ncube et al, 2014).

4. Objective(s) and contribution Main objective To explore the trade linkages among members within some selected RECs in Africa Contribution First study to explore the trade linkages in Africa Among the few studies that implemented the GVAR models in Africa and perhaps the first that actually focuses on RECs in Africa.

5. Methodology  GVAR was proposed by Pesaran et al (2004), and developed by Dees et al (2007)  The importance of GVAR: 1.The model is suitable for large data sample. GVAR was developed to handle large-scale variables and quantify global interdependencies that exist between countries. 2.The Global Impulse Response Functions (GIRFs) obtained from the GVAR model are invariant to the order of the variables (Pesaran et al. 2004; Cesa-Bianchi et al. 2011). 3.The model has the ability to combine individual country- specific model into a global framework and allows for the analysis of the interaction amongst them while avoiding any dimensionality problems.

6. Methodology cont….. The model consist of three main steps: 1.each country is modelled individually. 2. Building the GVAR model From equation (1), if we assume

7. Methodology cont…..

8. Methodology cont... 3. Estimation of the model, data and data sources

9. GIRF’s results of positive shock on CEMAC trade’s variables Export shock from Cameroon Import shock from Cameroon Export shock from Gabon Import shock from Gabon

10. GIRF’s results of positive shock on CEMAC trade’s variables Export shock from Equatorial guinea Import shock from Equatorial guinea Export shock from CongoImport shock from CAR

11. GIRF’s results of positive shock on EAC’s trade variables Import shock from Kenya Export shock from Rwanda Export shock from Tanzania

12. GIRF’s results of positive shock on SADC’s trade variables Export shock from Botswana

13. GIRF’s results of positive shock on SADC’s trade variables Import shock from Lesotho Export shock from Mozambique

14. GIRF’s results of positive shock on SADC’s trade variables Export shock from Namibia Import shock from South Africa

15. GIRF’s results of positive shock on SADC’s trade variables Export shock from Zimbabwe

16. Conclusion  There is evidence of trade linkages amongst members within RECs in Africa and the magnitude varies from one country to another and from one region to another.  There are very few countries that share bilateral trade with RECs in Africa. Trade relationships are mostly unilateral in Africa  Based on The GIRFs, trade linkages are still low within RECs in Africa  African countries should diversified their trade.

17. Thank you