Legislative bargaining with heterogeneous disagreement values: Theory and experiments

Luis Miller, Maria Montero and Christoph Vanberg

Suppose a group of decision makers negotiate about the distribution of a resource (such as a budget or ministerial portfolios). Some parties may be in a stronger position than others if negotiations end without agreement. For example, some parties may attach a greater value to the continuing of the status quo, or may have better electoral prospects if new elections are called.

Intuitively, being in a strong position in the event of disagreement is valuable if agreement needs to be unanimous, since a party can veto any agreement that gives them less than their 'disagreement value'. However, if a decision can be reached with the agreement of only a majority, parties with a high disagreement value are likely to be excluded from the agreement (since getting them on board is more expensive) and may end up worse-off.

The authors investigate the effect of disagreement values on final outcomes both theoretically and experimentally. They show that under unanimity rule, equilibrium payoffs are strictly increasing in disagreement values. Under all less-than-unanimity rules, equilibrium payoffs are either decreasing or first increasing and then decreasing in disagreement values. They also conduct experiments where subjects bargain over the division of a number of points, and there is a chance that negotiations break down if a proposal is rejected, in which case subjects get their disagreement value.

The authors find that having a high disagreement value is indeed beneficial under unanimity: subjects with a higher value demand more as proposers and are also offered more by other subjects. Under majority rule, subjects with a higher disagreement value are more likely to be excluded and may earn significantly less than other subjects.

Luis Miller, Maria Montero and Christoph Vanberg, 2018. Legislative Bargaining with Heterogeneous Disagreement Values: Theory and Experiments. Games and Economic Behavior. 107, 60-92. https://doi.org/10.1016/j.geb.2017.11.003

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