Better Together: private property and commons

Debates about spectrum allocation or intellectual property often appear to demand a choice between private and public ownership. There are zealots on both sides: see e.g. IPcentral and Public Knowledge. Each side argues that its preferred ownership method yields the highest social utility.

I believe that the truth lies in between. It’s more than simply a balance between property and commons; a mixture of the two yields more value than each of them individually. It’s not a question of balance and trade-offs; it’s a matter of synergy and mutual benefit.

Tren Griffin got me thinking about this in the context of spectrum allocation by citing the Central Park example. Central Park in New York City is an incredibly valuable piece of real estate; the nominal land value is astronomical, and the social utility is unquestioned. Its monetary value is due to the valuations of the surrounding apartments – but those apartments are valuable in part because they front on the Park. The combination of park and property is worth more than either all-park, or all-property. I suspect one can make a reasonably robust economic case that a mix licensed and unlicensed spectrum allocations will show the same kind of “mix maximization”.

A similar approach can be applied in other policy areas. Intellectual goods immediately come to mind. Intellectual property can encourage innovation since inventors can be assured of a return, but their creativity is built on a large public domain. Without the public domain there would be less innovation, and what did occur would be more expensive. Conversely, without investment in (temporarily) owned intellectual goods, the public domain would stagnate.

The diagram above represents the argument I’m making. I believe the “synergy” model has a higher maximum than either of the purist’s models, though I don’t know what the shape of the curve is. The economics challenge is to develop models that can handle private and public property on an apples-to-apples basis, and that can represent the mutual value add.

I’ve started thinking about brain-dead models of these phenomena to explore how one might represent the value curves and interactions. Different interaction models will lead to different curve shapes. The goal, of course, is to see if modeling can inform the optimal mix percentage. If there’s a sharp maximum, that would easy to decide; on the other hand, a relatively flat value curve (ie a situation where utility doesn’t depend strongly on the mix of ownership models) would lead to endless argument.