Electrical circuit model of spatiotemporal trade dynamics: Foundations and derivation of the gravity model

Robinson Pa, Alexander McInnes, Najmeh Sajedianfard, Mark Melatos and James A Henderson

PLOS ONE, 2025, vol. 20, issue 6, 1-32

Abstract: A model of time-dependent trade of goods between spatial locations is formulated via an electric circuit analogy, in which goods are analogous to charge and price to voltage, while producers and consumers are represented by sources and sinks of goods flow, which is represented by current, located at the nodes of a trade network. The core ansatz is that the flow of goods along each network link is driven by the voltage difference across that link, opposed by resistance that represents trade friction. Market prices are then determined indirectly by internal balances of flows, subject to external constraints on supply and demand. The model yields multiple outcomes that support its validity and applicability, including price setting via emergent balance of supply and demand, price fluctuations, traditional and generalized elasticities, network structure-flow relations, competition between producers, and substitution between suppliers, between consumers, and/or between trade links. All these results prove to be consistent with observed features of trade dynamics, thereby supporting the validity of the model. The new model is then used to derive the widely used gravity model of international trade from a mechanistic basis, yielding exponents consistent with published data and leading naturally to core-periphery structure, as observed in real trade networks. The analysis also implies that trade flows self-organize to minimize trade friction in the system as a whole, an emergent global outcome from the purely local dynamics of the populations of producers, consumers, and traders. Possible generalizations and further applications are outlined, including incorporation of asymmetry and capacity limits of trade links, constraints on supply and demand, behavioral responses, and coupling to models of investment strategies.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0326102 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 26102&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0326102

DOI: 10.1371/journal.pone.0326102

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().