Uncertainty, Rationality and Complexity in a Multi Sectoral Dynamic Model: The Dynamic Stochastic Generalized Aggregation Approach

48 Pages Posted: 10 Apr 2016

See all articles by Michele Catalano

Michele Catalano

Prometeia Association

Corrado Di Guilmi

University of Technology Sydney (UTS) - UTS Business School

Date Written: March 29, 2016

Abstract

The paper proposes an innovative approach for the analytical solution of agent-based models. The approach is termed Dynamic Stochastic Generalized Aggregation (DSG-A) and is tested on a macroeconomic model articulated in a job and in a goods markets with a large number of heterogeneous and interacting agents (namely firms and workers). The agents heuristically adapt their expectations by interpreting the signals from the market and give rise to macroeconomic regularities. The model is analytically solved in two different scenarios. In the first, the emergent proper- ties of the system are determined uniquely by the myopic behavior of the agents while, in the second, a social planner quantifies the optimal number of agents adopting a particular strategy. The integration of the DSG-A approach with intertemporal optimal control allows the identification of multiple equilibria and their qualitative classification.

Keywords: aggregation, uncertainty, opinion dynamics, master equation, optimal control

JEL Classification: C61, E03, E32

Suggested Citation

Catalano, Michele and Di Guilmi, Corrado, Uncertainty, Rationality and Complexity in a Multi Sectoral Dynamic Model: The Dynamic Stochastic Generalized Aggregation Approach (March 29, 2016). CAMA Working Paper No. 16/2016 , Available at SSRN: https://ssrn.com/abstract=2760136 or http://dx.doi.org/10.2139/ssrn.2760136

Michele Catalano

Prometeia Association ( email )

Italy

Corrado Di Guilmi (Contact Author)

University of Technology Sydney (UTS) - UTS Business School ( email )

Sydney
Australia

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