Cryptoeconomic Theory: Pareto Efficiency

Foundations of Game Theory and Cryptoeconomics

This is part 3 of the weekly Cryptoeconomics series

Let’s say you’re designing a new set of protocols for a blockchain-based organization. If you’re attempting to be helpful, you’d ask questions along the lines of: “How do we design the interaction of individuals that leads to an aggregate outcome that is “socially good”?

Unfortunately that doesn’t get anyone far at all. What does “good” even mean? How are two protocols compared to see which is “better”? And further, what does “better” even mean?

Efficient Outcomes

One criterion for evaluating the outcome of a social interaction is that it should be efficient. More specifically– resources in an economic state should be allocated in the most efficient manner, every time, no matter the interaction.

There are two things we want from an ideal outcome:

An outcome maximizes total payoff (total surplus) over all other sets of feasible outcomes. An outcome is preferred by an individual (economic agent) over all other sets of feasible outcomes.

Notice how every condition refers to a relative comparison between two outcomes. The potential movement from potential outcome A to potential outcome B that provides the most practical value is the core basis of all game theory.

A transition from outcome A to B that makes someone better off (a winner) without making anybody else worse off (a loser) is a Pareto improvement (PI).

An outcome is called Pareto Efficient when there is no possibility for Pareto improvement, i.e. there exists no other feasible outcome (using available resources and technologies) that would make at least one person better off without making anyone worse off.

To simplify: there are winners and losers when moving from outcome A to outcome B. The concept of Pareto Efficiency states that even though there are some losers, the winners can compensate the losers, and thus the outcome is “socially good”.