Staple food prices rose sharply in 2007/2008, dropped slightly after July 2008, and rose again in 2010/2011. Since 2008, food prices have remained high, indicating a structural upward adjustment in food prices amidst excessive price volatility. The 2008 food price increases led to considerable media coverage and alarm among governments who implemented a variety of responses to protect their populations from food insecurity. At the start of the high food price crisis in May 2008, the African Union and New Partnership for Africa’s Development (AU/NEPAD) invited 16 African countries to a workshop in South Africa. The aim of the workshop was to assist selected African countries identify and formulate appropriate plans to mitigate food insecurity and manage rising food prices. This study set out to investigate whether the strategies implemented by national governments at the start of the crisis mitigated high food prices through improved risk management strategies in five African countries (Ethiopia, Kenya, Malawi, Rwanda and Uganda) and evaluated these strategies to see if they were included in the national agriculture and food security investment plans. To achieve this, the study set out to explore four sub-problems, namely: What was the impact of high food prices on populations in the five selected countries (Ethiopia, Kenya, Malawi, Rwanda and Uganda)? How did the five countries respond to the 2008 food price crisis with regard to providing for immediate needs and protecting vulnerable groups from food insecurity? How many early actions were included in country compacts and agriculture and food investment programmes? Do country investment plans include household risk management programmes that will protect vulnerable groups against high food prices in future? The involvement of the researcher in the AU/NEPAD workshop and his subsequent engagement with national government representatives provided a unique opportunity to analyse the iterative process of Country Investment Plan (CIP) development. This innovative and largely qualitative study integrated comparative, content and thematic analysis approaches, using the four elements of the Comprehensive Africa Agricultural Development Programme’s (CAADP) Framework for African Food Security (FAFS) to analyse the national plans. The study drew on available data from a wide variety of national, regional and international documents. Additional data were collected through a survey questionnaire completed by CAADP country focal persons. Data sourced from documents included Food Price Indices, country policy responses to high food prices, poverty and malnutrition indicators and the types of risk management strategies designed under CAADP. The study found that food prices increased across all five countries between 2007 and 2008, although the effects of the increases varied, being influenced by, among other factors, the proportion of national stocks purchased on the international market (i.e. net importers of staple crops), the availability of substitute staples on the domestic market and the magnitude of the difference between international and domestic market prices. The 2008 food price increases forced populations to spend a higher proportion of their income on food and eroded their purchasing power, impacting on the food security of these populations. Poor people adopted eroding consumption strategies that increased food insecurity. The impact of the high food prices on populations was determined by whether they were net food buyers or producers, the mix of staple commodities in their food basket and the proportion of income spent on food. As poor net food importing countries, imported staple foods became too costly, except in Uganda - a net exporter of food staples consumed in the surrounding countries. High food prices also provoked social unrest in Ethiopia and exacerbated political and economic instability in Kenya. Countries’ early responses to the food price crisis were varied and included responses that can be classified into three main categories, namely: Trade-oriented responses protected domestic stocks, reduced tariffs, restricted exports to reduce prices for consumers or increased domestic supply Consumer-oriented responses provided direct support to consumers and vulnerable groups in the form of, among others, food subsidies, social safety nets, tax reductions and price controls Producer-oriented responses provided incentives for farmers to increase production - using measures such as input subsidies and producer price support. Most responses were aimed at managing prices, suggesting that governments tried to protect citizens from price increases and buffer consumption reduction. Safety net programmes mitigated risks through the provision of food for immediate consumption. As a result, malnutrition levels unexpectedly decreased or remained static in these five countries, despite expectations and media claims that the number of hungry people would increase significantly. The early actions from the food price workshop plans were generally systematically translated into long-term programmes in the Compacts and Country Investment Plans. In Ethiopia, seven of eight early action plans were translated into the CIP, Kenya included three of eight, Malawi’s CIP included four of ten, and Rwanda included six of its ten early actions in their CIP programme, while Uganda included only six of thirteen early actions in their CIP. The study found that CIPs included risk management strategies, but these focused predominantly on improving early warning systems and crisis prevention. The risk management options largely included options for improving crisis prevention, followed by improving emergency responses and strengthening risk management policies and institutions. Only Kenya’s CIP included more risk management options for improving emergency responses – four of six risk management programmes. Despite expectations that programmes developed under CAADP FAFS would include all FAFS elements, CIPs lacked programmes to improve dietary quality. Only Rwanda’s CIP included nutrition programmes - three of six programmes in their CIP. The study concluded that while the proposed risk management strategies could mitigate risks associated with high food prices and offer some buffer for populations from food insecurity, the programmes are not comprehensive. The plans were generally weak regarding improving dietary quality through diversification of food consumption and production. Although the CIPs included risk management strategies, these strategies would not address risks in a comprehensive manner. More effective and coherent actions are still required to help the most food insecure populations cope with increasing high food prices and future price shocks; help developing country farmers respond to the opportunities offered by the rising demand for their products; and bring more stability in prices. The early food price response workshop seems to have influenced the development of programmes in the CAADP compact and CIPs, despite the fact that the workshop did not intend to assist countries with the development of comprehensive national investment plans. The large funding gaps in the CIPs constrain implementation of essential mitigation and development strategies and could leave countries vulnerable to the negative impacts of higher prices for consumers and threaten future household food security. The study recommends that countries invest in agriculture-led growth to boost domestic production and strengthen institutional capacities regarding national food stock reserves to reduce their dependency on imports and ensure food insecurity. National monitoring and evaluation systems need to be strengthened to evaluate and monitor the implementation of CIPs and to warn about future high food prices. Empirical estimation of the impact of price increases on households across all CAADP countries is needed to understand and monitor the impact of price changes and interventions. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.

In this study, a household resilience score was developed as a measure of rural household resilience to identify households with low resilience and to measure progress towards improved household resilience. Resilience is the ability of households to cope with risk. The motivation for the study originated from the first objective of the Framework of African Food Security (FAFS) of improved household risk management, and the indicator of progress towards this objective – proposed by the FAFS - a resilience score. A review of the literature indicated that the assets owned by a household could be used as a proxy for resilience. The household component of the Demographic and Health Surveys for six African countries was used to develop and apply the resilience score. The score was estimated using an index of assets owned by the household and information regarding household access to certain services and characteristics of the dwelling. There is disagreement in the literature concerning the best method of constructing an asset index in terms of how to weight the variables included in the index. As a result, four methods of constructing an index of socio-economic status (SES) were selected for comparison in this study: two linear principal component analysis (PCA) techniques; a non-linear or categorical principal component analysis (CATPCA) method; and a simple sum of assets technique. The results from the application of each of the four indices to the country data and the resulting classification of households into quintiles of SES were compared across several assessment criteria. No single method out-performed the others across all the assessment criteria. However, the CATPCA method performed better in terms of the proportion of variance explained by the first principal component and the stability of the solution. The results showed that for all methods, SES was not evenly distributed across the sample populations for the countries analysed. This violates the assumption of uniformity implied when using quintiles as classification cut-off points. As an alternate to the quintile split cluster analysis was applied to the SES scores derived for each country. The classification of households into SES groups was repeated using k-means cluster analysis of the household SES scores estimated by the CATPCA method for each country. The results showed that a greater proportion of households fell into relatively lower levels of SES, which is in contrast to the assumption of uniformity of SES made when using the quintile cut-off approach. Cluster analysis better reflected the clustered nature of the household data analysed in this study, compared to the quintile cut-off method. In a final analysis, the index of SES along with k-means cluster analysis was applied to household data from two different time periods for five African countries to determine whether the resilience measure was able to detect changes in household SES between the two periods and, therefore, whether the tool could be used to monitor changes in household resilience over time. The results showed evidence of adjustments in SES over time: there were differences in the per cent of households allocated to the clusters of SES between the two periods. Using the CATPCA index and k-means cluster analysis, Egypt, Uganda and Mali showed an increase in the per cent of 'poor' households, while for Kenya and Tanzania there was a reduction in the per cent of households allocated to the first cluster between time periods: the decrease for Kenya from 2003 to 2008 was as much as 13 percentage points. The observed changes in SES were then compared to changes in national poverty estimates reported in the literature. The resilience score developed in the study displayed an ability to track changes in household SES over time and could be used as a measure of progress towards improved household resilience. As such, the resilience measure could be valuable to policy-makers for monitoring the impacts of policies aimed at improving household resilience. Future research is recommended before the reliability of the resilience measure developed here can be fully ascertained. / Thesis (M.Sc.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.