COMPUTATIONAL SOCIAL SCIENCE

Department of Computational Social Science Seminar Abstract

Friday, November 4 - 3:00 p.m.
Center for Social Complexity Suite
Third Floor, Research Hall

Title: A Complex Adaptive Systems Approach to Economic Impact Analysis

Holly Russo
CSS PhD Candidate
George Mason University

Abstract: Economic impact analysis is the study of the implications of a proposed policy or potential shock to an economy. The tool generally employed in this type of analysis is computable general equilibrium (CGE) modeling. A CGE model consists of a system of equations representing an entire economy, solved simultaneously such that a specific set of equilibrium conditions are held.

This approach has several characteristics that limit its ability to realistically represent the changes to an economy that could result from shocks or deliberately introduced policies. First, the parameters in the model are derived from historical data and remain fixed throughout the simulation of the shock. Second, CGE models are limited to only one or a few homogenous agents. Also, since the model equations are solved simultaneously, there is no way to represent behaviors such as panic or herding, imperfect information or lags between cause and effect; nor is there the ability to model expectations that may influence consumption and investment behavior. Finally, the fact that there must be a specific number of endogenous variables corresponding to the number of equations in the model forces unrealistic decisions such as the requirement to hold wages fixed if one is to represent unemployment in the model.

In this talk I will discuss CGE modeling and its limitations in more detail, and then present an approach for designing an agent-based modeling alternative. I will describe the specific CGE model chosen for this study, and the experiments that will compare the output of the two models, including the deviations from equilibrium that are demonstrated by the ABM.