The double auction trading institution (DA) has been highly efficient across diverse marginal-cost market structures, whether human subjects or "zero-intelligence" robots populated those markets. Accordingly, many researchers suspect that DA performance transcends market structure and agent strategy. But we show that (1) large avoidable costs undermine the efficiency and stability of human subject DAs, and (2) these low human efficiencies are simultaneously well above zero-intelligence efficiencies. Our results dramatically illustrate the potential havoc wrought by highly competitive institutions when they must cope with nonconvex technologies.

We conduct an experimental analysis of final offer arbitration (FOA) with differentially informed players. Under FOA, the arbitrator must choose one of the two submitted offers. In our control, the uninformed player makes an offer to the informed player prior to the submission of offers to the arbitrator. The treatment allows negotiation after offers are submitted to the arbitrator. Because these offers are potentially binding, they may transmit privately held information and, thereby, lower the dispute rate. We find that allowing negotiation in the face of potentially binding offers lowers the dispute rate by 27 percentage points.

The double auction trading institution has been highly efficient across diverse marginal-cost market structures, whether human subjects or 'zero-intelligence' robots populated those markets. Accordingly, many researchers suspect that double auction performance transcends market structure and agent strategy. But the authors show that large avoidable costs undermine the efficiency and stability of human subject double auctions and these low human efficiencies are simultaneously well above zero-intelligence efficiencies. Their results dramatically illustrate the potential havoc wrought by highly competitive institutions when they must cope with nonconvex technologies. Copyright 1996 by American Economic Association.