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
