Measuring Postharvest Losses At The Farm Level In Malawi

Reducing food loss and waste are important policy objectives prominently featured in the United Nation’s Sustainable Development Goals. To optimally design interventions targeted at reducing losses, it is important to know where losses are concentrated between the farm and fork. This paper measures farmlevel postharvest losses for three main crops—maize, soy, and groundnuts—among 1,200 households in Malawi. Farmers answered a detailed questionnaire designed to learn about losses during harvest and transport, processing, and storage and which measures both total losses and reductions in crop quality. The findings indicate that fewer than half of households report suffering losses conditional on growing each crop. In addition, conditional on losses occurring, the loss averages between 5 and 12 percent of the farmer’s total harvest. Compared to nationally representative data that measure losses using a single survey question, this study documents a far greater percentage of farmers experiencing losses, though the unconditional proportion lost is similar. We find that losses are concentrated in harvest and processing activities for groundnuts and maize; for soy, they are highest during processing. Existing interventions have primarily targeted storage activities; however, these results suggest that targeting other activities may be worthwhile.

In Mozambique, food security remains a key issue and the country suffers perennial food shortages, especially in the provinces of Manica,Tete, Sofala, Zambezia, Maputo and Gaza. Weaknesses in post-harvest systems, which contribute to both a lower supply and higher food prices (due to post-harvest losses) are key reasons behind these food shortages. Currently, none of the post-harvest losses programmes conducted in Mozambique provides loss estimates along the entire value chain for a given commodity. In this report, we quantify losses across the value chain in maize, which is a key staple food in Mozambique, in the provinces of Manica and Zambezia. The study, carried out by the International Food Policy Research Institute (IFPRI) in collaboration with the Agrifood Economics Division (ESA) at FAO, sheds light on understanding the magnitude, nature and consequences of food losses across the maize value chain in selected regions in Mozambique. In particular, the methodology used in this report allows to accurately measure food losses and identify in which segment of the value chain these food losses occur and the causes of the losses.

Although the Malawian food supply is shaped largely by trends in smallholder food crop production, Ma­lawi’s decades-long focus on improving smallholder productivity has only moderately improved food secu­rity and nutrition outcomes. Country statistics indicate an estimated 36.7 percent of rural Malawian house­holds failed to access sufficient calories between 2010 and 2011. During the same period, 47 percent of children under the age of five years were esti­mated to be stunted in their growth. These indicators imply that some Malawian diets are lacking in terms of quantity (total calories consumed), and most are lacking in terms of quality (sufficient calories derived from nutrient-dense foods, such as meat, fish, eggs, dairy, legumes, fruits, and vegetables). Good nutrition requires both enough total calories (quantity) and enough vitamins and minerals per calorie (quality). How can Malawi better leverage its smallholder agriculture sector to improve nutrition? This report provides a series of primary and secondary data anal­yses that examine different aspects of this question.

This book provides a thorough introduction to and examination of agricultural value chains in Sub-Saharan Africa. First, the authors introduce the economic theory of agri-food value chains and value chain governance, focusing on domestic and regional trade in (and consumption of) food crops in a low-income country context. In addition to mainstream and heterodox thinking about value chain development, the book pays attention to political economy considerations. The book also reviews the empirical evidence on value chain development and performance in Africa. It adopts multiple lenses to examine agricultural value chains, zooming out from the micro level (e.g., relational contracting in a context of market imperfections) to the meso level (e.g., distributional implications of various value chain interventions, inclusion of specific social groups) and the macro level (underlying income, population and urbanization trends, volumes and prices, etc.).Furthermore, this book places value chain development in the context of a process the authors refer to as structural transformation 2.0, which refers to a process where production factors (labor, land and capital) move from low-productivity agriculture to high-productivity agriculture. Finally, throughout the book the authors interpret the evidence in light of three important debates: (i) how competitive are rural factor and product markets, and what does this imply for distribution and innovation? (ii) what role do foreign investment and factor proportions play in the development of agri-food value chains in Africa? (iii) what complementary government policies can help facilitate a process of agricultural value chain transformation, towards high-productive activities and enhancing the capacity of value chains to generate employment opportunities and food security for a growing population.

Recall biases in retrospective survey data are widely considered to be pervasive and have important implications for effective agricultural research. In this paper, we leverage the survey design literature and test three strategies to attenuate mental anchoring in retrospective data collection: question order effects, retrieval cues, and aggregate (community) anchoring. We embed a survey design experiment in a longitudinal survey of smallholder farmers in Malawi and focus on anchoring bias in maize production and happiness exploiting differences between recalled and concurrent responses. We find that asking for retrospective data before concurrent data reduces recall bias by approximately 34% for maize production, a meaningful improvement with no increase in survey data collection costs. Retrieval cues are less successful in reducing the bias for maize reports and involve more data collection time, while community anchors can exacerbate the bias. Reversing the order of questions and retrieval cues do not help to ease the bias for happiness reports.

Agribusiness has a major role to play in the transformation of the agricultural sector in Africa. With the demand for high-value food products increasing around the world, the production and export of these goods represents an opportunity to achieve increases in income and employment. To capture the benefits of this trend and capitalize on this opportunity for long-term agricultural growth, agribusiness in Africa must become more competitive. In addition to improving competitiveness, increasing agricultural productivity and food security are also major challenges in African agricultural development. In this paper, we compare the agribusiness competitiveness of African countries and develop typologies connected with their food security and agricultural productivity status. The typologies reveal various stylized facts on the competitiveness of agribusiness to help nations prioritize issues for agricultural development and growth. We develop the measures of agribusiness competitiveness and apply them to African countries. Additionally, we present policy implications and lessons for increasing the competitiveness of agribusiness in African countries.