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Disentangling Wine Judges’ Consensus, Idiosyncratic, and Random Expressions of Quality or Preference*

Published online by Cambridge University Press:  10 November 2017

Jeffrey Bodington
Jeffrey Bodington*
Affiliation:
Bodington & Company, 50 California Street, San Francisco, California, 94111; e-mail: jcb@bodingtonandcompany.com.
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Abstract

Judges confer various awards on wines entered in dozens of wine competitions each year. This article employs data on blind replicates to show that those awards are based on one instance of stochastic ratings assigned by wine judges; awards based on the expected values of those stochastic ratings would be different. This article recognizes the stochastic nature of ratings and builds on the work of many others to propose and test a conditional-probability model that yields maximum-likelihood estimates of judges’ latent consensus, idiosyncratic, and random assignments of scores to wines. The exact p-value for a likelihood test of the null hypothesis that the model's results are random is less than 0.001. Applying the notion of conditional probability may lead to better methods of assigning awards to entries in wine competitions and of assessing the capabilities of wine judges. (JEL Classifications: A10, C10, C00, C12, D12)

Keywords

consensusidiosyncraticrandomstatisticswine tasting
Type
Articles
Information
Journal of Wine Economics , Volume 12 , Issue 3 , August 2017 , pp. 267 - 281
Copyright
Copyright © American Association of Wine Economists 2017 

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Footnotes

*

The author thanks an anonymous reviewer for insightful and constructive comments. All remaining errors are the responsibility of the author alone.

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