A Pari-mutuel like Mechanism for Information Aggregation: A Field Test Inside Intel∗

A new Information Aggregation Mechanism (IAM), developed via laboratory experimental methods, is implemented inside Intel Corporation in a long-running field test. The IAM, incorporating features of pari-mutuel betting, is uniquely designed to collect and quantize as probability distributions dispersed, subjectively held information. IAM participants’ incentives support timely information revelation and the emergence of consensus beliefs over future outcomes. Empirical tests demonstrate the robustness of experimental results and the IAM’s practical usefulness in addressing real-world problems. The IAM’s predictive distributions forecasting sales are very accurate, especially for short horizons and direct sales channels, often proving more accurate than Intel’s internal forecast. ∗The financial support of the Lee Center for Advanced Networking, the Gordon and Betty Moore Foundation, and the Laboratory of Experimental Economics and Political Science is gratefully acknowledged. We thank Dan Zhou for providing excellent research assistance, and Chew Soo Hong, Erik Snowberg, Allan Timmermann, Michael Waldman, and seminar audiences at Arizona State, Columbia, EIEF Roma, MIT, Rice, UCSD, Universidad Carlos III Madrid, IIOC 2013, and the Econometric Society NASM 2013 for helpful comments.