The Binarized Scoring Rule

We introduce a simple method for constructing a scoring rule to elicit an agent's belief about a random variable that is incentive compatible irrespective of her risk-preference. The agent receives a fixed prize when her prediction error, defined by a loss function specified in the incentive sc...

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Bibliographic Details
Published in:The Review of economic studies 2013-07, Vol.80 (3 (284)), p.984-1001
Main Authors: HOSSAIN, TANJIM, OKUI, RYO
Format: Article
Language:English
Subjects:
Agency theory
Analytical forecasting
Economic analysis
Economic incentives
Economic theory
Error
Expected utility
Financial risk
Lotteries
Probabilities
Probability
Probability theory
Random numbers
Random variables
Risk theory
Studies
Utility functions
Utility theory
Working papers
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Summary:We introduce a simple method for constructing a scoring rule to elicit an agent's belief about a random variable that is incentive compatible irrespective of her risk-preference. The agent receives a fixed prize when her prediction error, defined by a loss function specified in the incentive scheme, is smaller than an independently generated random number and earns a smaller prize otherwise. Adjusting the loss function according to the belief elicitation objective, the scoring rule can be used in a rich assortment of situations. Moreover, the scoring rule can be incentive compatible even when the agent is not an expected utility maximizer. Results from our probability elicitation experiments show that subjects' predictions are closer to the true probability under this scoring rule compared to the quadratic scoring rule.
ISSN:0034-6527
1467-937X
DOI:10.1093/restud/rdt006