Pareto efficiency

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In game theory and economics, the concept of Pareto efficiency (or Pareto optimality) is a method to judge the efficiency of a set of decisions made by the participants. It was named after Vilfredo Pareto.

A set of decisions "x/y" (meaning that participant A chooses "x" while participant B chooses "y") is called Pareto optimal if there is no other state in which:

  1. at least one participant can improve his own outcome while
  2. no other participants receives a worse outcome than he does now.

Putting it into less formal style: As long as a player can improve his outcome without hurting anybody else, the situation is not Pareto efficient.

If a participant can improve his outcome without hurting anybody else, the new decision set Pareto dominates the old one.

When Paretto efficiency is not reached - Prisoner's dilemna

B
not confess confess
A not confess A: good / B: good A: bad / B: very good
confess A: very good / B: bad A: OK / B: OK

In the one-stage game shown at the right side, prisoners A and B can concurrently choose between "not confess" and "confess". The result can either be "very good", "good", "OK", or "bad".

The highlighted field ("confess/confess") is the Pareto optimal situation. All other situations can be improved.

For example, in "not confess/confess" ("bad" for A, "very good" for B), A could switch to "confess". The result improves A's result to "OK" while changing B's result also to "OK". However now at "confess/confess", if B changes to "not confess", his result becomes "bad". Thus, "confess/confess" would be the equilibrium outcome.

Generally in a game with finite steps, the equilibrium outcome may not necessarily be the Paretto efficient outcome. However, in a game with infinite steps, it can be shown that the equilibrium outcome is the Paretto efficient outcome.

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