The theoretical spatial pricing mechanism is similar to non-spatial pricing, where the interaction of demand and supply determines the market price. However, in spatial pricing both the demand and supply need be spatial in their character and the markets need to be product as well as geographically delineated.The spatial price determination model (SpPDM) is developed for spatial pricing of multi-market heterogeneously distributed resources. The theoretical spatial pricing mechanism is similar to non-spatial pricing, where the interaction of demand and supply determines the market price. However, in spatial pricing both the demand and supply need be spatial in their character and the markets need to be product as well as geographically delineated. The product delineation is based on resource categorisations, while the geographical delineation is based on a system of two-dimensional quadratic shaped gridcells. That is, each gridcell represents a separate market, where transactions between the resource suppliers and users can occur, thus generating spatial price equilibrium for each categorised resource.
Spatial structure of supply
The on-site supply, i.e., the supply in each gridcell, is derived based on a bottom-up approach using gridcell-specific resource availability and extraction costs for each type of resource. Each gridcell has a single observed availability per type of resource and a unique extraction cost associated with that availability. The gridcell-specific availability and extraction cost is the fundamental building block for the quantity-cost relationship of the spatial supply.
The spatial structure of the supply is captured by aggregating the on-site availability with that of adjacent gridcells, creating a supply area for each gridcell. The number of adjacent gridcells to include is based on assumptions on transportation distance. Aggregated, regional supply curves are constructed for each gridcell and resource, using a merit-order framework.
Spatial structure of demand
The main rationale for using a merit-order approach for constructing the supply curves is twofold. First, the need to make strict theoretical assumption on the quantity-cost relationship is eliminated. Second, it allows the use of empirical data that often are availability for heterogeneously distributed resources, such as forestry and agricultural resources.
The spatial demand structure is represented by two demand concepts: Site demand and demand pressure. They are aggregated in each gridcell and for each resource to create an aggregate demand per resource in each gridcell. The site demand is representing the demanded quantity of a resource by all the users in a specific gridcell. The demand pressure is measuring the spatial interaction across gridcell with a site demand. The estimation of the demand pressure is based on a distance-decay framework. The demand pressure is monotonically decreasing with distance until it eventually disappears. The only reason a gridcell might not have an aggregated demand is if it is located too far away from a site demand so that the demand pressure drops to zero.
The market price determination is given by the intersection of the aggregate demand and the regional supply curve. Equilibrium is established for each market, but no general equilibrium is solved. Instead, the equilibrium should be interpreted as partial since no price equalising condition is imposed between markets. The spatial price equilibrium is stable if no user can decrease its cost by changing procurement markets, i.e., buying the resource from another gridcell. In this framework, resource owners can make excess profits due to locational cost advantages.
The method can be used for a wide range of applications assessing spatial heterogeneously distributed resources, e.g., forest and agricultural resources. Based on the application, the method can also be used to assess direct policy options and their implications on market conditions. It allows the modelling of a wide range of pricing behaviours, especially when considering the interaction of competitive policies. By also including conjectural variation into the demand structure, it is possible to identify interdependencies between spatial markets.