“Market power is like the wind. You can feel it but you cannot see it”
During 2002 and 2003 retail food prices in South Africa increased dramatically. These increases put the spotlight on the concentration and market power of food manufacturing firms and retailers in the food supply chain. The proprietary nature of information on processes within the supply chain makes it difficult to identify uncompetitive behaviour. This paper reports on the application of a series of econometric analyses to test for asymmetric price transmission in the South African agro‐food sector. The paper specifically seeks to show how market concentration increases the degree of asymmetry by comparing different levels of asymmetry between commodity and retail prices in the South African Economy. The results show that in South Africa industries that are considered to be concentrated at some level show a high degree of asymmetric price transmission, which, however, decreases when the retail product is perishable.
Commodity prices in general are known to have a high volatility. This is in fact what attracts speculators. The South African futures exchange (SAFEX) is not immune to this volatility. Volatility increases the risk of paying higher prices for a specific commodity, and it also makes the use of derivative instruments to hedge against price risk more expensive. Given the importance of South Africa as a regional supplier of maize and price discovery mechanism, investigations into the volatility of the maize price are not only important, but also indispensable if all parties involved are to manage this risk. The question therefore is whether the SAFEX maize price volatility can be explained by using fundamental factors or whether this volatility is unexplainably high.
Econometric demand and supply models of agricultural commodities and crops have been around for a long time with extensive research and adaptations being made in the grain and livestock sectors. This much attention has, however, not been afforded to long term commodities. This paper presents a partial equilibrium framework for modeling long term commodities using the South African wine industry as an example. The model structure is presented and two different approaches to closing the model are compared. The usefulness of the model is tested in the form of baseline projections and the analysis of a typical “what if” question. (JEL Classification: D5, L66, Q11)
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