Using and Improving Modeling Efforts to Inform Energy and Climate Policy
(Natural Resource Security, Energy and Environmental Policy)
Saturday, November 14, 2015: 8:30 AM-10:00 AM
Board Room (Hyatt Regency Miami)
*Names in bold indicate Presenter
Panel Organizers: Evan E. Johnson, University of North Carolina at Chapel Hill
Panel Chairs: Kenneth R. Richards, Indiana University
Discussants: Carol Lenox, U.S. Environmental Protection Agency
The U.S. energy system represents a complex and multi-dimensional policy landscape in which patterns of behavior and policy outcomes at higher levels actually result from decentralized interactions among diverse groups of actors at state and local levels. Further, individual consumers demonstrate tremendous heterogeneity in their behavior and responses to different policy options. Both sets of conditions frustrate attempts to devise uniform and centralized policy solutions. In the context of this uncertainty and diversity, policy analysts and researchers have increasingly turned to computational models as an invaluable tool for studying the behavior of complex social systems. Research that improves and expands these models is thus an indispensable component of evidence-based efforts to design and evaluate policies. In addition, such research affords new opportunities to exploit an increasingly rich array of social and economic data.
Evidence-based social science can enhance modeling platforms for policy design and evaluation in three primary ways. First, it leverages available empirical information to inform model inputs. Second, it helps researchers and modelers parameterize those inputs in ways that unpack some of the heterogeneity and uncertainty surrounding interactions among system actors. Third, the process of model-based analysis, itself, leads to model improvement. Exploring model simulations that are aligned with empirical data can illuminate extraneous model parameters and identify opportunities to incorporate new variables. The proposed panel will encompass empirical projects that represent each of these dimensions of model improvement. It combines scholarship in policy analysis, economics and systems modeling to explore promising methodological approaches to strengthening systems models to improve the accuracy of policy research.
This session will bring together researchers whose work sheds light on the key methodological considerations involved in systems models improvement for policy analysis. One group employs state-level data to build an integrated energy-economy model that informs efforts to simulate regional energy outcomes by accounting for variation in policy at the levels of states and municipalities. Another focuses on diversity across individual consumers, disaggregating trends in purchasing behavior and willingness to pay in order to provide behavioral constraints for energy systems models. A third applies stochastic optimization techniques to an open source energy systems model to explicitly account for future uncertainty.
This panel represents one half of a two-part series on the improvement of modeling platforms to inform the evaluation and design of public policies. While the second panel will focus explicitly on the application of systems models as a source of evidence-based policy research, this panel will focus exclusively on methodological approaches to building and enhancing the models themselves. The two sessions will complement one another as parts of a larger sequence on the improvement of systems models for policy design. However, either panel will, by itself, provide attendees with a diverse array of perspectives and findings that will clarify the relevance and usefulness of systems modeling approaches. Both panels will engage perspectives from multiple academic disciplines as well as those of practitioners with direct experience in the use and development of computational models to inform public policy.