Modeling for insights, not numbers: the experiences of the energy modeling forum

It has often been contended that the primary goal of policy modeling should be the insights quantitative models can provide, not the precise-looking projections--i.e. numbers--they can produce for any given scenario. Students of the energy policy process, in particular, have noted that preoccupation with the plethora of detailed quantitative results produced by large-scale computer models has substantially impeded their influence on key policy decisions. The creation of the Energy Modeling Forum (EMF) at Stanford University in 1976 represents one potential remedy for that situation. The EMF was formed to foster better communication between the builders and users of energy models in energy planning and policy analysis. The EMF operates through ad hoc working groups, composed of national and, more recently, international energy modeling and policy experts. These working groups conduct studies concentrating on a single energy topic. The diversity of backgrounds of the working group members ensures that the language of the EMF studies is English, not computer. Each working group identifies existing models relevant to the study's focus. A series of tests is then designed by the group to illuminate the models' basic structure and behavior. A comparison of results is published in a widely distributed report that identifies the models' strengths and weaknesses in the context of the study's topic. Seven EMF studies have been initiated to date: (1) Energy and the economy, (2) Coal in transition, (3) Electric load forecasting, (4) Aggregate elasticity of energy demand, (5) US oil and gas supply, (6) World oil and (7) Macroeconomic impacts of energy shocks. Each EMF study has broadened the understanding of the nature of the relevant policy issues and the models that have been, are, or could be used to address them. The present paper describes how each study's key insights were developed in the context of a simplified analytical framework that provided the proper perspective for understanding the model results.