Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach

Catalano, M; Di Guilmi, C

Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach

Catalano, M Di Guilmi, C

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Publication Type:: Journal Article
Citation:: Journal of Economic Behavior and Organization, 2019, 157 pp. 117 - 144
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Catalano, M	en_US
dc.contributor.author	Di Guilmi, C https://orcid.org/0000-0001-7786-039X	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Journal of Economic Behavior and Organization, 2019, 157 pp. 117 - 144	en_US
dc.identifier.issn	0167-2681	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131801
dc.description.abstract	© 2017 Elsevier B.V. The paper proposes an innovative approach for the analytical solution of agent-based models. The approach is termed dynamic stochastic generalized aggregation (DSGA) 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 properties 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 DSGA approach with intertemporal optimal control allows the identification of multiple equilibria and their qualitative classification.	en_US
dc.relation.ispartof	Journal of Economic Behavior and Organization	en_US
dc.relation.isbasedon	10.1016/j.jebo.2017.10.006	en_US
dc.subject.classification	Economics	en_US
dc.title	Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach	en_US
dc.type	Journal Article
utslib.citation.volume	157	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	1401 Economic Theory	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	157	en_US

Abstract:

© 2017 Elsevier B.V. The paper proposes an innovative approach for the analytical solution of agent-based models. The approach is termed dynamic stochastic generalized aggregation (DSGA) 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 properties 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 DSGA approach with intertemporal optimal control allows the identification of multiple equilibria and their qualitative classification.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/131244