Abstract
In this paper we show how business cycles can emerge from the interaction of autonomous agents. We devised an agent-based computational microeconomics model of agents who trade in a network of trading partners. We assume that agents who observe decreased profits change their trading partners. At fixed intervals a new production technology becomes available to a single agent. If an agent introduces a new technology he changes his trading pattern and some of his trade partners can have a decrease in profits. The agents who have lower profits start changing trading partners. The change in the trading network can lead to lower production and decreased profits of other agents. Agents with decreased profits also start changing trade partners. In short, the technology shock triggers a snowball effect of agents changing their trading partners; the GDP decreases. When agents find new trading partners and regain their profits the GDP increases. A business cycle emerges.
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Taghawi-Nejad, D. (2010). Technology Shocks and Trade in a Network. In: Li Calzi, M., Milone, L., Pellizzari, P. (eds) Progress in Artificial Economics. Lecture Notes in Economics and Mathematical Systems, vol 645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13947-5_9
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DOI: https://doi.org/10.1007/978-3-642-13947-5_9
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Online ISBN: 978-3-642-13947-5
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