Jointly made decisions are a common feature across economic and social systems. Various decision rules can be used to identify a jointly negotiated offer. One such rule ( MaxJoint ) seeks to maximise the joint payoffs of the two parties and is related to the objective of efficiency. Another rule ( MinDiff ) seeks to minimise the difference in payoff between two parties and is related to the objective of fairness. These two objectives are often in tension, resulting in an efficiency–fairness trade-off. This article explores the dynamics of these and other joint decision rules within the context of negotiation, a form of social decision-making in which parties with conflicting views attempt to reach a jointly agreed-upon settlement. Through Monte Carlo simulation of an illustrative two-party multi-issue negotiation, the existence of this trade-off is confirmed and the price of fairness, that is, the reduction in efficiency by the imposition of a fairness constraint, is quantified. JEL Codes: C78, C63, B410
Zachary A. Collier (Sun,) studied this question.