Africa is a continent of great diversity, perhaps more so than any other of the continents. It is a continent richly endowed with resources and these endowments have long formed the basis of trade between Africa and the rest of the world. The export specialisation of a country has a lot of bearing on its import patterns – if it exports mostly primary goods it is likely to import mostly secondary and tertiary goods. In fact, these complementary patterns are seen to drive trade between nations and have been termed reciprocal comparative advantage in the economic literature.

This reciprocity is based on a national industrial profile that is determined both by natural resource endowments and deliberate industrial and trade policy. In the case of the latter, experience has shown that the most effective policy is crafted with full cognisance of the national comparative advantage. The dynamic of trade and the power of the markets will then see trade relations develop organically among complementary economies, whether geographically close or distant.

The nations of Africa, although geographically proximate, only conduct around 12% of their total trade with one another (‘intra-African trade’), whereas in the case of a regional economic community (REC) such as the European Union (EU), the figure is closer to 70%[1]. This historical bias away from intra-African trade is now being addressed via the introduction of a free trade area (FTA) for Africa. The African Continental Free Trade Area (AfCFTA), which entered into force on the 30th May 2019, aims to create a single free trade area among the members of the African Union – both the continental and the island states.

The backdrop of the AfCFTA and its stated intention to increase intra-African trade forms the context for a forthcoming tralac trade brief which assesses the extent of economic similarity (or difference) among the exporting economies of Africa[2]. The most important area of investigation of this research is the extent to which the economies of Africa are complementary or competitive.

It is well known that African exporters are overwhelmingly focused on primary products; however, this in itself does not preclude greater trade integration. Within the aggregate category of primary products there are many sub-categories and an exporter of one type of primary good, for example fuels, may still need to import other primary goods such as mineral ores. It is these types of complementarities that this forthcoming trade brief investigates, using an unsupervised statistical learning methodology known as clustering. The approach taken is to assess differences at a bilateral level, i.e., with respect to each African nation vis a vis every other African nation. This approach, although more painstaking, can provide far greater insights than by simply looking at gross measures of divergence, such as for example, deviation from the mean.

Several novel visualisation techniques are introduced in order to present the clustered data. The heat map, network diagram and cluster histograms are all chart types not typically used in supervised economic analysis but which can add much value when using an unsupervised technique such as clustering. Rather than a single form of chart or visualisation, clustered data requires a collection of tools in order to represent the many relational dimensions within the data.

Given the geographic size of Africa, trade gravity prerogatives alone will dictate that regional partners will be more likely to trade with each other, especially among the small and medium economic-sized nations. Therefore, regional factors and especially REC memberships will be important in determining new or enhanced trade flows. In light of this, the clustering analysis was applied to Africa’s four main RECs and may be summarised as follows:

• The EAC has its members evenly distributed across five export clusters, which is an ideal outcome for a trade bloc. Each member would be expected to be able to find markets among its REC partners and reciprocally, to be able to offer markets to its partners.
• Not many members of ECOWAS have diversified economies. However, there is a good distribution across the main primary goods categories of agricultural, minerals and fuels and their associated clusters. New intra-trade could build on these complementarities.
• SADC has a large representation in the diversified/manufacturing cluster and has three members in a tobacco specialist cluster. It also has a member in the ‘extreme specialist’ category – Namibia. On balance, it looks less well configured for increasing intra-trade, but since the members of the diversified/manufacturing cluster are relatively diverse (no cluster is a monolith, or tracks directly to one export product category), trade within the categories of this cluster would be possible.
• COMESA is a large and geographically diverse REC, without the underlying logic of the other three RECs. It follows the Africa aggregate more closely than the other RECs, which is understandable given its spatial diversity and size. If logistic issues can be overcome, trade could grow on the back of the complementarities and representation in all six clusters.

What of the potential for increased intra-African trade at a continental level? The analysis does reveal a high level of dependence by African exporters on primary and crude goods. A superficial analysis would conclude that given this focus on primary goods production and export, the nations of Africa are not sufficiently complementary to facilitate growing intra-trade. However, there is diversity within the categories of primary production and export, and each African nation differs in its pattern of revealed comparative advantage – its actual sector export performance relative to the world pattern. Some differ more than others, and certainly, there are some economies that are perhaps too similar at this stage for there to be the prospect of increased intra-trade.

However, the analysis produces seven clusters of economies, including extreme specialists, which are sufficiently different as groups for trade to be viable between groups. At a REC level, each REC, as representing west, east and southern Africa, presents a different pattern and the EAC REC looks best poised at this point for higher levels of intra-trade. ECOWAS has diverse primary goods exporters and this is where new trade opportunities could be found. SADC is less diverse across clusters than either of the other two RECs or even COMESA and the residual group, but it has more diversified economies represented and also more manufacturing exporters. SADC’s intra-trade should therefore focus on finding complementarities within the third cluster, and between its manufacturing exporters and the manufactures importers in the rest of Africa.

As Africa positions itself for greater intra-trade and closer economic integration, increasing scrutiny will be placed on the complementarities, or not, of its economies. Reciprocal comparative advantage is an old and simple, yet powerful idea in trade economics. It holds the key to unlocking the benefits of regional markets and economies of scale and scope as countries bring down trade barriers and open markets to the exports of their neighbours.

The AfCFTA is a trade bloc founded not specifically on complementary comparative advantage, but rather on nationalistic and pan-African prerogatives. However, for it to succeed the nations of Africa will have to find and develop complementarities between their economies. At this stage, a good proportion of Africa’s economies are similar and therefore ‘competitive’ in principle, but a more nuanced investigation does reveal the potential for developing complementary trade patterns.

By John Stuart

John Stuart is an economist and policy analyst with special interests in trade, economic integration, data visualisation and economic modelling. He began his career in academia at Rhodes University and later the University of Cape Town, after which he entered private consulting first with AFReC (Pty) Ltd and subsequently with PBS (Pty) Ltd. Besides economics research and teaching, he has experience in project management, general management, public sector performance management, systems analysis and entrepreneurship. He holds an M. Com degree in Economics from the University of Natal (Durban).

Courtesy:  The Trade Law Centre (Tralac)

References

[1] Data sourced from Trade Map (http://www.trademap.org)

[2] Stuart, J. 2019. Patterns of Comparative Advantage in Africa: Assessing Similarities and Differences. Trade Brief (forthcoming). Stellenbosch: tralac

AfCFTAData analysis and statisticsIndustrial policyTrade policy