This study aims to test the performance of agricultural markets in the Democratic Republic of Congo (DRC). Although the DRC is classified as the fifth biggest producer of cassava, nearly 70 percent of its population living mainly in urban areas is suffering from food shortages. Since the markets are poorly integrated, food prices are very volatile. Small agricultural producers obtain low prices for their products, while vulnerable household’s consumers experience high prices. Over the last few years, the price of cassava has increased considerably, from US$ 72 per ton in 2007 to US$ 123 per ton in 2009. This dramatic increase in the price of a basic foodstuff has significantly affected poor people in both urban and rural areas. The increase in cassava market prices and the food insecurity level in DRC are an indication that markets have not efficiently performed their fundamental role of connecting producers and consumers. Therefore, understanding the status of value chain development and the degree of market integration is important to improve food security, as well as people’s livelihood in rural areas. Several techniques were identified in the literature for testing agricultural market performance, including: market integration, parity bound analysis, causality, symmetry, error correction mechanisms and value chain analysis. Some studies used mathematical models including deterministic analytical models and stochastic analytical models. For the purpose of this study and because of data limitations, value chain analysis and market integration techniques were applied. The value chain analysis was performed to identify critical issues and constraints that undermine value chain development, as well as to identify business and technological opportunities that can enhance the performance and competitiveness of the sub-sector. The prices of cassava products in the DRC were found to be high, due to the high costs of production, processing and marketing of cassava at different levels of the market chain. Poor market linkages lead to low utilisation of value addition technologies, and this contributes directly to poor market opportunities. This results in a wide range of negative aspects for the sector, such as decreasing incentives for the production and consumption of cassava products and lack of sufficient competitiveness to make cassava a significant commercial commodity. Investment in the sector is considered risky by different chain actors, and is limited as a result of the overall non-competitiveness of the sector. The cassava market in the DRC is organised around Kinshasa in Western Congo, and around Lubumbashi in the South-eastern part of the country. In view of the strategic importance of the two marketplaces, a market integration analysis was conducted to consider whether food policy focusing on those two reference marketplaces would be sufficient to stabilise the cassava supply nationwide, since most of the marketplaces seem to have a strong relationships with these two reference markets. Using co-integration techniques, an error correction mechanism and an index of market connection, the findings established that among the 11 pairs of trading markets, 6 of them were segmented, meaning that price changes in the reference markets were not fully transmitted to the regional markets. Four key factors, including macroeconomic environment, transportation infrastructure, market information flow and distance, played a significant role in price differentials, and caused potential and existing markets to cease to function as efficient generators of wealth and distributors of food. This is apparently one of the most important reasons for increased food insecurity and poverty among food producers and consumers alike. The results confirm the poor value chain status of cassava, which leads to the stagnation of this crop as a semi-commercial crop, and restrains its absorption into the mainstream market chain in local, national and regional markets. The market integration results showed segmented and moderated integrated markets arising from the 11 pairs of trading markets, of which 6 were identified as segmented. The results from the error correction mechanism (ECM) suggest that on average about 30% of past deviations from the long run are corrected each month. Among the 11 paired markets, the highest coefficient of price adjustment in the long run was indicated by the paired markets Bukavu–Goma (43%), Mbujimayi–Kananga (38%) and Matadi-Kinshasa (36%); and the lowest was given by the paired market Kisangani–Kinshasa (15%). In the short run, the IMC of 0.85 suggests a strong market connection between Matadi and Kinshasa, which then suggests that price shocks that occur in the market of Kinshasa affect immediately, and partially, the Matadi markets supplying it. This high IMC coefficient was also found between Bukavu and Goma (0.86), and Kananga and Mbujimay (0.81). None of the other markets trading with Kinshasa and Lubumbashi respond in the short run to price changes in these reference markets. This implies that only 3 market pairs out of 11 hav strong intgration which therefore presents clear evidence of weak market integration between production and deficient areas in the DRC as awhole. This weak linear relationship between markets can be postulated as one of major causes of food insercurity in the country. This understanding of cause of food insecurity and various issues surrounding market integration would futher help policy makers to improve efficiency of cassava marketing system, lower farm to retail price spread and consolidate food security accross the country. Copyright / Dissertation (MSc(Agric))--University of Pretoria, 2012. / Agricultural Economics, Extension and Rural Development / unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/26621 |
| Date | 24 July 2012 |
| Creators | Mumbeya, Njingulula Paulin |
| Contributors | Kirsten, Johann F., pnjingulula@yahoo.fr |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Dissertation |
| Rights | © 2011, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
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