In order to generate a more reliable value chain actors’ data, we use stratified random sampling in each of the value chain segments to the extent possible. The data come from 3,253 interviews of economic actors from 6 sets of surveys, using comparable questionnaires covering all the segments of the dairy and potato value chains in Brazil, China, and India. The initial set of questionnaires for all segments including farmers, wholesale/logistics, processors, and retailers were developed in English and then adapted and translated into Chinese, Portugal and Hindi. Detailed information on input use and technologies, output, logistical interface, energy costs, procurement systems, and institutional arrangements of each actors were collected.Rational. Three existing knowledge gaps motivate this study. First, there has been little research on linking energy, transformation, and poverty reduction in the developing countries. Second, there has been little research analyzing energy costs in the various segments of the food supply chains, differentiating over products, tracing both patterns in energy intensity by segment as well as the impacts of these costs on net incomes of actors. Third, there has been little empirical research empirically linking energy policy and public energy system investments with energy costs and performance in food supply chains in developing countries. Objectives. 1) to develop an integrated conceptual framework for modeling the relations among three interrelated factors, transformed versus traditional food supply chains; energy costs from electricity and fuel; and net incomes of supply chain participants and food prices; 2) to apply the framework to analyze horticulture and dairy supply chains in China, India, and Brazil, to assess how energy costs are generated and affect behavior in the segments of the supply chain and what the implications of these are for food costs to consumers and incomes to producers; and 3) to formulate policy pathways for moving towards more optimal energy use practices that contribute to supply chain development and reduction of poverty.

Inventory per country the energy policies and public and private-sector investments related to energy costs and access for all segments of the value chains studied. Inventory and “map” the different value chains for the two products, in two study provinces/states. Collect detailed data in “stacked surveys”, with a representative sample survey in each segment of the value chains, as well as supplemental case studies, as discussed above. Analyze the data from all the segments of the value chain surveys. Use the findings from step four, arrayed as parameters in simulations at different levels to model the impacts of energy policies and investments on energy costs, intensity, efficiency, and energy cost burdens of the poor.