Theme 1: Contract Farming
Project: Contracting Out of Poverty

We develop contracts designed to improve small farmers’ welfare and test them both in the laboratory and in the field in Peru, Tanzania and Vietnam through impact evaluations. Our innovation is that we implement these contract structures in a field setting in these countries, which is ideal because of the diverse geography, potential for contract farming with agricultural products and on-site technical support given to implement the contract structures. The contracts are applied in several rural communities selected through a typology of micro-regions where the findings and recommendations can be scaled up.

  • Saenger, Christoph; Torero, Maximo; and Qaim, Matin, 2014. “Impact of Third-party Contract Enforcement in Agricultural Markets-A Field Experiment in Vietnam,” American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(4), pages 1220-1238.
Countries: Peru, Tanzania, Vietnam
Funding: BMZ, USDA

Theme 2: Input Markets
Project: Improving the Effectiveness of Policies and Strategic Investments in the Fertilizer Supply Chain for Some African Countries Taking into Account the Global and Country-Level Market Structure and Constraints

The fertilizer industry is a global market with high levels of concentration and increasing trade from production in regions with low‐cost raw materials. A few countries control most of the production capacity of the main nitrogen, phosphate and potash fertilizers. There are considerable differences across regions when it comes to fertilizer use intensity. The fertilizer-use intensity in Asia, which has the highest use intensity, is 20 times higher than that of sub‐Saharan Africa, the region with the lowest use intensity. Latin America — and even South Asia — relies heavily on imported fertilizer, becoming more dependent on foreign suppliers. International fertilizer prices have shown an upward trend over time and high fluctuations, especially with nitrogen- and phosphate-based fertilizers.

It is important to take into account the potential behavior of major producers at the global and regional level to better understand the industry supply chain in low-income regions. The project aims to improve the fertilizer markets and increase input use in developing regions, particularly in sub-Saharan Africa, by providing an in-depth analysis of the fertilizer supply chain in key countries and identifying the main constraints at the global, regional and local levels.

Countries: Brundi, Ethiopia, Kenya, Mozambique, Nigeria, Senegal, Tanzania, Zambia 
Funding: European Commission

Theme 3: Food Losses Across the Value Chain
Project 1: The Reality of Food Losses: A New Measurement Methodology

Population growth, rising incomes and limited availability of land and other natural resources endanger global food security. A promising strategy to mitigate these problems is to reduce losses and waste from food production to human consumption: across the food value chain, there are considerable losses of agricultural production that could have fed vulnerable populations. The United Nations has recognized the importance of this approach in the Sustainable Development Goal target 12.3, aiming to “halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains, including post-harvest losses” by 2030.

While food losses have a detrimental role on food security, there is little information about the extent and nature of the issue, the stages of the value chain in which food losses occur, and the cost-effectiveness of any particular policies to resolve the problem.

The implementation of a strategy to reduce food losses faces three important challenges. First, there is no accurate information about the extent of the problem, especially in developing countries. The available estimates suggest that food losses are alarmingly high and may account for at least one third of total production. For the most part, calculations of food losses hinge upon accounting exercises that use aggregate data from food balance sheets provided by national or local authorities. These “macro” estimations are subject to considerable measurement error, rely on poor-quality data, or are not based on representative samples. Moreover, they quantify the volume of food that is lost, but do not take into account potential deterioration of quality or reductions of economic value that also affect producers and consumers.

Second, there is scarce evidence regarding the source of food losses. Food losses are associated with a wide array of factors (examples: poor agricultural management skills and techniques, inadequate storage, deficient infrastructure, inefficient processing, lack of coordination in marketing systems) and can occur in different stages of the value chain: production, harvesting, post-production, processing, distribution, or consumption. Because of the aggregate nature of their data, macro studies are unable to capture the critical stages where food losses are. Arguably due to the cost of primary data collection, most of micro studies have not incorporated detailed information about sources of food losses in their survey instruments. Most of them aim to capture total food losses based on producers’ self-reported estimates but do not aim to disentangle the relevant production phases in which losses are generated.

Third, there is little evidence of how to reduce food losses across the value chain. There have been efforts to introduce particular technologies along specific stages of the value chain, including silos for grain storage, triple bagging for cowpea storage or mechanized harvesting and cleaning equipment for wheat and maize. However, adoption rates or the economic sustainability of these efforts are not known. In particular, there is a need to better understand how to introduce economic incentives for actors from farm-to-fork, taking into account the upstream and downstream linkages across the value chain.

The project aims to quantify and characterize the nature of post-harvest losses across the value chain for different commodities in a wide array of countries. For this purpose, we designed a set of surveys to measure the extent of food losses. While the surveys were tailored to specific countries, commodities and commodity varieties — for example, maize in China has different attributes to Maize in Guatemala — they provide a consistent measurement of food losses across different agents in the value chain (farmers, middlemen, and processors).

The surveys capture information about the different processes of each of these agents and quantify food losses in each production stage with four methodologies:

  1. Disaggregated self-reported measures of losses: We collect self-reported measures of volumes and values of food losses incurred during different processes (harvesting, threshing, milling, shelling, winnowing, drying, packaging, transporting, sorting, picking, transforming, etc.).
  2. Losses based on commodity damage: We collect detailed data from farmers, middlemen, and processors on the quality (based on damage coefficients) of agricultural commodities that they use as inputs and outputs. This allows us to quantify food losses in terms of quality attributable to each agent across the value chain.
  3. Losses based on commodity attributes: We capture information about different types of commodity attributes, including size, impurities, broken grain, and ascertain the price penalty that each of these types of crop damage entails.
  4. Losses based on inefficiencies: In this last methodology, we estimate the highest potential production level based on a stochastic production possibility frontier, which assumes an optimal use of inputs and technologies. Then, we compare this potential level with the realized production to determine food losses. Therefore, this methodology, allows us to contrast how much food could have been produced in the absence of inefficiencies in the agricultural sector.

The coverage of the project spans across Africa, Asia, and Latin America, and encompasses some of the most important crops in developing countries. The surveys to estimate food losses across the four proposed methodologies have been collected in eleven countries for ten agricultural commodities.

These surveys allow us to quantify the extent of food losses across the value chain using consistent approaches that are comparable across commodities and regions. They also enable us to characterize the nature of food losses. In particular, we will be able to ascertain the production stages across of the value chain and the particular processes in which losses are incurred. The results of these studies will inform about the particular areas that require investments to reduce food losses.

  • Luciana, Delgado; Schuster, Monica; and Torero, Maximo, 2021. “On the Origins of Food Loss.” Applied Economic Perspectives and Policy, 2021; 1– 31.
At the Global Entrepreneurship Summit 2019, Torero discusses the impact of food loss and waste on the availability of increasingly scarce resources and how it can be tackled.

Torero explains measuring food loss across value chains
(Video: Courtesy of University of New England)
Countries: China, Ecuador, Ethiopia, Ghana, Guatemala, Honduras, Peru
Funding: CGIAR - PIM

Theme 3: Food Losses Across the Value Chain
Project 2: Innovations to Reduce Losses Across the Value Chain in Guatemala and Honduras (field work in progress)

In this project, we implement solutions to address quality-related losses among maize and bean farmers in Guatemala and Honduras. In particular, we propose to test two interventions.

First, provide farmers with information about cost-effective technologies to improve their crop management skills during their production. In coordination with local institutions and based on our results from Phase 1, we design information packages that tackle the most important pests and diseases that affect maize and beans in the project regions. In our baseline surveys we collect GPS location of the farmers as well as their cellular phones which will allow us to provide in different ways this information in coordination with our local partners.

Second, provide farmers with quality certification mechanisms. Without certification mechanisms, farmers might not be rewarded for any investments or efforts to increase the quality of their harvests. In this line, we plan to implement a certification mechanism for farmers’ maize and beans production through a third-party independent contractor. This mechanism will introduce economic incentives for farmers and promote self-efficacy to reduce quality-related food losses. We will also coordinate to see how if the results are positive how we can scale up this through the government.

To assess the impact of these innovations in the reduction of food losses, we will invite farmers in the Phase 1 baseline (1,155 in Honduras and 1,209 in Guatemala) to participate in a field experiment. Farmers will be randomly assigned to three experimental groups. The first group will receive information about cost-effective technologies to curb quality losses. This information will be conveyed through personal visits and mobile phones. The second group will receive vouchers to test their maize and bean harvests in a third-party independent lab and get appropriate certifications of the quality of their production. The third group will receive neither information nor vouchers, and will act as a control group. This control group will provide a counterfactual of food losses in the absence on any of these innovations.

This experimental impact evaluation will allow us to provide causal evidence about the potential of information and certification interventions to reduce the extent to food losses in Guatemala and Honduras. While based on particular commodities (maize and beans) and locations (Guatemala and Honduras), we address types of interventions that are general enough to scaled-up be and expanded to other regions and crops.

Countries: Guatemala, Honduras
Funding: CGIAR - PIM

Theme 4: Innovations in Inclusive Value Chains
Project: Innovations in Inclusive Value Chains

The increasing use of innovation-system and value-chain approaches to contribute to rural poverty reduction, income growth, poverty reduction, and greater gender equity notwithstanding, there is little systematic knowledge about how to operationalize these approaches in different contexts and how to use evaluation of such interventions to support learning, management, and accountability.

This research program brings together results on innovations on inclusive value chains and the existing gaps on impact evaluation and scaling up. They assess the opportunities emerging from new markets for agricultural produce and identify challenges to smallholder participation in these markets and the resulting benefits. They illustrate how interventions have fostered agricultural innovation and inclusive value-chain development, and the extent of their impacts. Methods for evaluating complex interventions that involve innovation and value-chain development are presented, along with empirical results of evaluation studies. This research program formulates several implications for agricultural policymakers and programmers, and identify knowledge gaps and priorities for future research.

  • Tool: Inclusive and Efficient Value Chains addresses the changing international, regional, and local contexts for agricultural markets, and investigates how smallholders, both men and women, can be integrated into the complex and demanding modern marketing arrangements. Here are featured contents added to the site recently.
IFAD learning video: Supporting pro-poor value chain development
Region: Global
Funding: CGIAR - PIM