In this paper, we develop what we refer to as economic circuit theory. Our purpose is to exploit the proven effectiveness of electrical circuit theory for the design, modeling, and analysis of complex electrical networks to economic systems; in particular, it permits us to incorporate the dynamics of price into those of the flow of physical commodities, analogous to how this is done for magnetic flux and electrical charge. The theory is agent-based, wherein agents are conceptualized as electrical components and the dynamics are determined by matching the agents' behavioral laws with the constitutive equations of the analogous components. We take a modern graph-theoretic approach, identifying the conditions for stock-flow consistency (Kirchhoff's current law) and price clearing (Kirchhoff's voltage law). With this, we develop the theory to model representative agents (equivalent networks), single-good markets (circuits), and general competitive markets (magnetically coupled circuits). The effectiveness of our theory is demonstrated through a dynamic scenario analysis of the economic circuit model for a two-good market.

Current oil modeling techniques lack a comprehensive approach, as long-term oil prices are qualitatively modeled based on first principles, while short-term price transients are modeled using econometric methods. In this paper we propose a comprehensive bond-graph modeling approach in which price dynamics follow from first principles. The first principles that we use are derived from the recently developed economic-engineering theory in which price dynamics are modeled using Newtonian mechanics and price drivers are identified as forces. We reformulate a qualitative first-principles model developed by the Energy Information Administration (EIA) as a bond graph by modeling six identified price-driving factors as port-elements. The constitutive laws of these port-elements generate the price drivers, which through the interconnection structure of the bond graph yield the price dynamics. We demonstrate the bond-graph model by identifying its parameters and letting it estimate the oil price given historic oil supply data. Compared to a benchmark black-box model, we find that the bond graph has two advantages: (i) it achieves a better performance, and (ii) we know what its parameters and variables represent. The latter advantage allows us to validate the bond-graph model by reconstructing the oil inventory stocks and to manually adjust parameters by expert input.