Modeling Economic Systems as Locally-Constructive Sequential Games: Abstract: Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these properties imply real-world economies are locally constructive sequential games. This paper discusses a modeling approach, agent-based computational economics (ACE), that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing.
A bit more:
This working paper discusses how agent-based computational economics (ACE) permits the modeling and implementation of economic systems as locally constructive sequential games. Section 2 of the paper characterizes seven specific ACE modeling principles in order to distinguish ACE more carefully from other modeling approaches, such as general equilibrium modeling and game theory within economics, and standard usages of state-space modeling by economists, engineers, and physicists.
Sections 3-6 cover ACE research objectives, the ACE enabling of comprehensive empirical validation, and the growing use of ACE computational platforms to cross the "valley of death" between policy conceptualization and real-world policy implementation.
Edgier ACE explorations are cited and summarized in Sections 7-8. These include:
(i) the study of labor markets as evolutionary sequential games with endogenous hiring, firing, and quits (Section 7.1);
(ii) the study of macroeconomies with anticipatory learning by locally-constructive consumers and firms attempting to achieve intertemporal objectives (Section 7.2);
(iii) the study of risk management by strategically interacting rural and urban decision-makers residing within a watershed affected by climate and hydrological processes (Section 7.3);
(iv) the study of new market design features for U.S. electric power systems (Section 7.4;
(v) the use of ACE modeling principles as design principles guiding the development of decentralized "transactive energy" architectures for U.S. transmission and distribution systems (Section 7.5);
(vi) a spectrum of experiment-based models ranging from 100% human subject to 100% computer agent (Section 8).
This paper is an invited paper for the Journal of Economic Methodology