Published March 27, 2014
| Accepted Version
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Information Aggregation Mechanisms: Concept, Design and Implementation for a Sales Forecasting Problem
- Creators
- Plott, Charles R.
- Chen, Kay-Yut
Abstract
Information Aggregation Mechanisms are economics mechanisms designed explicitly for the purpose of collecting and aggregating information. The modern theory of rational expectations, together with the techniques and results of experimental economics, suggest that a set of properly designed markets can be a good information aggregation mechanism. The paper reports on the deployment of such an information aggregation mechanism inside Hewlett-Packard Corporation for the purpose of makings sales forecasts. Results who that IAMs performed better than traditional methods employed inside Hewlett-Packard. The structure of the mechanism, the methodology and the results are reported.
Additional Information
The financial help of the National Science Foundation and DARPA are gratefully acknowledged. Effort sponsored by the Defense Advanced Research Projects Agency (DARPA) and Air Force Research Laboratory, Air Force Material Command, USAF, under agreement number F30602-00-2-0623. The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Defense Advanced Research Projects Agency (DARPA), the Air Force Research Laboratory, or the U.S. Government.Attached Files
Accepted Version - wp1131.pdf
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Additional details
- Eprint ID
- 44358
- Resolver ID
- CaltechAUTHORS:20140317-135547085
- National Science Foundation
- DARPA
- Air Force Research Laboratory, Air Force Material Command
- F30602-00-2-0623
- Created
-
2014-03-27Created 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
- 1131