Small numbers matching markets: Unstable and inefficient due to over-competition?

The extant literature on matching markets assumes ordinal preferences for matches, while bargaining within matches is mostly excluded. Central for this paper, however, is the bargaining over joint profits from potential matches. We investigate, both theoretically and experimentally, a seemingly simple allocation task in a 2x2 market with repeated negotiations. More than 75% of the experimental allocations are unstable, and 40% of the matches are inefficient (in cases where inefficiency is possible). By defining the novel concept 'altruistic core', we can explain the occurrence of inefficient matches as well as the significant behavioral differences among our six treatments. --matching market,price negotiation,optimal allocation,altruism

Time evolution of the extremely diluted Blume-Emery-Griffiths neural network

The time evolution of the extremely diluted Blume-Emery-Griffiths neural network model is studied, and a detailed equilibrium phase diagram is obtained exhibiting pattern retrieval, fluctuation retrieval and self-sustained activity phases. It is shown that saddle-point solutions associated with fluctuation overlaps slow down considerably the flow of the network states towards the retrieval fixed points. A comparison of the performance with other three-state networks is also presented.Comment: 8 pages, 5 figure