Implementing Rural-Urban Disaggregated Food Demand in a Partial Equilibrium Model

Global general and partial equilibrium models focused on the agricultural sector can help policy makers do ex-ante analysis by providing a variety of macro-level outcomes, such as changes in flows of international trade, and changes in the supply, demand, and prices of globally traded commodities. IFPRI’s IMPACT model (International Model for Policy Analysis of Agricultural Commodities and Trade) model is one such model. Since its inception nearly 20 years ago the model has evolved to inform increasingly complex and nuanced policy issues, such as the explicit modeling of water use and the productive response of agriculture to climate change. However, on the demand side it has remained a fairly blunt instrument. One oft mentioned shortcoming of global food policy models such as IMPACT model is that they treat national populations as a single composite consumer. As (relatively) wealthier urban and poorer rural populations exhibit different demand characteristics, have different base levels of food consumption, and have different levels of wealth, assigning a single representative consumer for an entire country could result in misleading results regarding both global prices and consumption and the food security of the poorer segments of the population. In this poster we present a global partial equilibrium food security model with disaggregated demand. Working from the IMPACT model, we divided national populations into their urban and rural components. Studies have shown that rural and urban consumers, as well as poor and rich consumers, have structurally different food demands. Accordingly, we assign different demand elasticities (price and income), different base consumption (at the commodity level), and different incomes to sub-populations populations within each country. We have completed an extensive study of the food demand literature, using the findings to develop parameters to represent the structural differences in urban and rural food demand (see right for explanation of this process). We use rural/urban population and income data and projections from the UN to complete the disaggregation.