Forecasting in a complex environment: machine learning sales expectations in a stock flow consistent agent-based simulation model

DOI10.1016/j.jedc.2022.104405zbMath1492.91204OpenAlexW3016063156MaRDI QIDQ2152314

Mauro Gallegati, Alberto Russo, Ermanno Catullo

Publication date: 8 July 2022

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jedc.2022.104405

zbMATH Keywords

genetic algorithmforecastingmachine learningagent-based modelpolicy shocks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Economic growth models (91B62)

Cites Work

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• Agent based-stock flow consistent macroeconomics: towards a benchmark model
• Macroeconomies as constructively rational games
• Economic convergence: policy implications from a heterogeneous agent model
• Validating and calibrating agent-based models: a case study

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