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Optimal Simple Ratings
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AI
DOI：10.1111/joie.70025.png)
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Abstract
En 中文
We study optimal simple rating systems that partition sellers into a finite number of tiers. We show that optimal ratings must be threshold partitions, and that for linear supply and Cournot competition with constant marginal cost, optimal thresholds solve a k-means clustering problem requiring only the quality distribution. For convex (concave) supply functions, optimal thresholds are higher (lower) than the k-means solution. For log-concave distributions, two-tier certification captures at least 50% of maximum welfare gains from full disclosure, with five tiers typically achieving over 90%. Applications to eBay and Medicare Advantage data illustrate our method.
Keywords:
certification
consumer surplus
producer surplus
simple ratings
Journal
J
IF:
1
Papers:
17
Citations:
0
