programmatic monetary policy

Smart contracts can be their own central banker, and programmatically shape their own market(?)

Examples of cryptoeconomic monetary policy

Inflating towards fixed supply:

• Bitcoin: “The result is that the number of bitcoins in existence is not expected to exceed 21 million.[2]”
• Ethereum: “Ether (ETH), the cryptofuel that powers distributed applications on the Ethereum platform, will be issued at a constant annual linear rate via the block mining process” (link)

Inflated/deflated to stabilize value:

• Maker: “The DAI bond is a stable cryptocurrency token that is backed by collateral in various assets that trade on the Ethereum blockchain (initially ETH, BTC, MKR, REP, GLD). Should any of these collateral types see a catastrophic crash that results in the value of the collateral becoming less than the outstanding debt (a black swan event), MKR is autonomously inflated to raise funds to cover the lacking collateral (Maker bailout with forced inflation).”

smart tokens == programmable monetary policy

The ‘monetary policy’ of the token can be anything, and it can be dynamic. In Simon de la Rouviere’s paper on Curation Markets the value of the token is governed by the available supply. He suggests the following formula:

costOfToken = (BaseCost + BaseCost*(1.000001618^AvailableSupply)+BaseCost*AvailableSupply/1000)

This equation has a linear component that dominates when supply is low and an exponential component that dominates when supply is high. This creates an incentive for early adopters to continue investing during the first phase when the marginal cost increase is low. Later, as the network-effect kicks in, the marginal cost of buying additional tokens increases. This suggests that the author expected the market for this token to have two distinct phases — and early phase during which the market needed to encourage adoption, and then a second phase once the token is sufficiently established.

The example above has two phases and is based on the available supply of tokens, but we can imagine arbitrarily complex policies. The purpose of these equations is to shape the growth of the network. These equations are essentially predictions about how the network will grow, with different incentives tailored to shape the different dynamics that we expect to appear through time.

use policy as a tool to achieve project goals

Bitcoin and Ethereum need a steady supply of computation, so their policy of steady inflation makes sense. Each project will have a different desired market dynamic. For example, we could design a policy to encourage trading volume by pricing the token based on the token transaction volume and/or the number of active traders.

a general policy for humans?

There may be a good general policy that is optimal for encouraging humans to form groups. Can anyone point to any work that’s been done on this?

a policy for network effect?

Or we could tie the value of the token more directly to the utility that it produces. Metcalfe’s law suggests an exponential relationship between the value of the network and the number of nodes–maybe we can use that to price the token:

costOfToken = (number of nodes in the network^utility coefficient)/AvailableSupply

in this case the token would become a unit of ‘network-effect’(?).

Author’s note: I might be the last person to realize all of this, or this might all be a terrible idea. YMMV : )

This might be a fun, two-phase policy: