Comparing supply-side specifications in models of global agriculture and the food system
2 December 2013
Robinson, S., van Meijl, H., Willenbockel, D., Valin, H., Fujimori, S., Masui, T., Sands, R., Wise, M., Calvin, K., Havlik, P., Mason d’Croz, D., Tabeau, A., Kavallari, A., Schmitz, C., Dietrich, J. P. and von Lampe, M. (2014), Comparing supply-side specifications in models of global agriculture and the food system. Agricultural Economics, 45: 21–35. doi:10.1111/agec.12087
This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scope—partial versus economy-wide—and in how they represent technology and the behavior of supply and demand in markets. The CGE models are “deep” structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) “shallow” structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) “deep” structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specification—comparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.