Judd and Kearns, EC 2008

From Cohen Courses
Revision as of 01:52, 31 March 2011 by Kdelaros (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search

Citation

Judd, J. S, and M. Kearns. 2008. Behavioral experiments in networked trade. In Proceedings of the 9th ACM conference on Electronic commerce, 150–159.

Online version

From CiteSeer

Summary

This paper the authors' describe the results of a series of highly controlled human subject experiments in networked trade. Their experiments are focused on a simple bipartite network exchange model, where, in each experiment, 36 subjects simultaneously engage in trade over this bipartite network and are only allowed to trade with neighbors via a limit order mechanism for real financial incentive, and are aimed testing various equilibrium, economic, and social network theories.

In the authors' experiments network model consists of two populations: those with Milk and those with Wheat. The following restrictions are imposed on the players to induce trade:

  • Milk and Wheat players start with one divisible unit of their commodity
  • Players have no utility for their commodity, and linear commodity for the other commodity (i.e. Milk players have no use for milk, but a linear utility for wheat).

In total, 28 experiments were conducted with variations of 10 different topological families, shown in Figure 1. Each experimented lasted 2 minutes, and are intense with all players acting simultaneously. At any given time subjects express global limit orders to all of their neighbors, and any moment that two neighbors limit orders cross a trade takes place. The subject pool population was 36 undergraduates from Penn, and after all the experiments a cash incentive of $2 per 10 units of neighbors goods was able trade for was given.

Judd kearns 2008 fig1.png

Main Results The authors main experimental results are as follows (from their summary):

  • Behavioral collective performance is generally strong with market efficiency close to 90% in all experiments
  • Different network topologies strongly influence individual wealth levels
  • Greater equilibrium wealth disparity leads to greater behavior wealth disparity (contrary to some established equilibrium theory)
  • Equilibrium theory is highly relevant to behavioral outcomes, but a networked form of inequality aversion is their best predictor (nudges equilibrium toward uniform wealth distribution)

Related papers