The Reality of Food Losses: A New Measurement Methodology

Measuring food loss, identifying where in the food system it occurs, and developing effective policies along every stage of the value chain are essential first steps in addressing the problem of food loss in developing countries. Food loss has been defined in many ways, and disagreement remains regarding proper terminology and measurement methodology. Although the terms “post-harvest loss,” “food loss,” and “food loss and waste” are frequently used interchangeably, they do not refer consistently to the same aspects of the problem. In addition, none of these classifications includes pre-harvest losses. Figures regarding food loss remain highly inconsistent, precise causes of food loss remain undetected, and success stories of decreasing food loss remain few. We improve over this measurement gap on food losses by developing and testing the methodology traditionally used with three new methodologies that aim to reduce the measurement error in assessing the magnitude of food loss. The methods account for losses from the pre-harvest stage through product distribution and include both quantity loss and quality deterioration. We apply the instrument to producers, middlemen, and processors in seven staple food value chains in five developing countries. Throughout the different estimation methodologies, losses at the producer level represent between 60 and 80 percent of total value chain losses, while the average loss at the middleman and processor level lies around 7 and 19 percent, respectively. Differences across methodologies are salient, especially at the producer level. While the estimation results from the three new methods implemented are close and the differences are mostly not statistically significant, the aggregate self-reported method reports systematically lower loss figures. Finally, our results show the major reasons behind the losses identified for each commodity and country. Specifically, we find that they included pests and diseases and lack of rainfall. W(This abstract was borrowed from another version of this item.)