Prediction Market Alternatives for Complex Environments∗

Prediction markets have proven successful in large-scale applications such as elections and sporting events. Consequently, several large corporations have adopted prediction markets for smaller-scale internal applications where information may be complex and the number of traders small. Using laboratory experiments we test the performance of the standard prediction market in complex environments with few traders and compare it to three alternative mechanisms. When information is complex we find that an incentivized iterated poll (or Delphi method) out-performs the prediction market mechanism. We present four behavioral observations that may explain why the poll performs better in these settings. JEL: C72, C91, D82