Breaking the ‘big data’ barrier when selecting agricultural export markets: An innovative approach

South Africa - 21 November 2017

A country’s comparative advantage is not only dependent on factor endowments. History, random events (wars, oil crises, sanctions, etc.) and past government policies are important factors shaping a country’s trade patterns. Such factors are recognised in both traditional and new trade theory. Therefore, the formulation (and implementation) of industrial and agricultural export policy needs to take cognisance of these factors. In the search for new markets or new product opportunities in existing markets – which in turn aids both trade policy making and business decision making ‒ a major challenge is making sense of the huge volumes of available product and market information, which is one of the manifestations of ‘big data’. Using an example from the South African fruit industry, this paper illustrates how the big data challenge can be tackled using the TRADE-Decision Support Model (DSM) methodology. Having applied this methodology, an initial 1 221 realistic export opportunities were identified in 107 markets. Of the overall 54 products in the fruit and nuts HS chapter 08 category, 22 had ‘major potential’, representing about US$3.5 billion across 102 countries. Most of the potential for ‘mature’ products lay in ‘new’ markets from a South African agricultural exports perspective. Of this potential, 80 per cent were found in 10 products (including grapes, apples, mandarins, lemons and limes). Some non-traditional products were also identified, such as bananas, cashew nuts, kiwifruit and guavas. Europe still represents approximately half of the total realistic export potential in the short term, estimated at US$6 billion, followed by North America (22 per cent) and Asia (21 per cent).

Available from: http://www.tandfonline.com/doi/full/10.1080/03031853.2017.1298456

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