A Parimutuel-like Mechanism from Information Aggregation: A Field Test Inside Intel
Abstract
Field tests of a new Information Aggregation Mechanism (IAM) developed via laboratory experimental methods were implemented inside Intel Corporation for sales forecasting. The IAM, which incorporates selected features of parimutuel betting, is uniquely designed to collect and quantize as probability distributions any dispersed, subjectively held information that might exist. The tests demonstrate the robustness of experimental results and the practical usefulness of the IAM. The IAM yields predicted distributions of future sales that are very accurate at short horizons; indeed, more accurate than Intel's official in-house forecast 59% of the time. A symmetric game model suggests why the IAM works.
Additional Information
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, EIEF Roma, MIT, Rice, UCSD, Universidad Carlos III Madrid, IIOC 2013, and the Econometric Society NASM 2013 for helpful comments.Attached Files
Accepted Version - SSWP1367.pdf
Submitted - IAM_Forecasting_inside_Intel_131114.pdf
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Additional details
- Eprint ID
- 44652
- Resolver ID
- CaltechAUTHORS:20140403-161916829
- Gordon and Betty Moore Foundation
- Caltech Laboratory for Experimental Economics and Political Science
- Caltech Lee Center for Advanced Networking
- Created
-
2014-10-20Created from EPrint's datestamp field
- Updated
-
2019-10-03Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 1367