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Title: The Role of Solidarity and Reputation Building in Coordinating Collective Resistance

Author: Mary Rigdon

Abstract:

Our research — building on experimental results of Cason and Mui (2007) — examines why a subordinate in a leader–subordinate relationship is willing to pay a cost to help prevent exploita- tion of another subordinate by the leader. Using a stylized game capturing essential features of the leader–subordinate relationship, Cason and Mui find that when the leader attempts to “divide- and-conquer” the subordinates, the subordinate not targeted for exploitation will still choose to challenge the leader’s exploitation a significant fraction of the time, even though challenging is costly and there is no direct material benefit. As a result, subordinates achieve coordinated joint resistance more than equilibrium analysis would predict. While Cason and Mui suggest that coor- dinated resistance is due to a fairness norm — the non-targeted subordinate shows solidarity with the targeted subordinate — another motive may be at play: an incentive to gain a reputation for challenging. Each subordinate has an equal chance of being the victim of future leader exploitation. As a result, there is an incentive to create an expectation among leaders that “divide-and-conquer” style exploitation will be met with coordinated resistance: each subordinate secures a higher payoff on average if the leader chooses not to transgress. Furthermore, a subordinate has an incentive to challenge now if they think it will increase the likelihood that joint resistance will be successful in the future. Our experimental design systematically removes the incentive to reputation build. It is designed to test whether the willingness of subordinates to help resist exploitation of fellow subordinates is motivated by a solidarity preference specific to hierarchical relationships or as an attempt to influence the behavior of the leader — and other subordinates — in the future. We find that the role of solidarity among subordinates best explains the data.