Quantifying Randomness Versus Consensus in Wine Quality Ratings

Abstract

AbstractThere has been ongoing interest in studying wine judges' performance in evaluating wines. Most of the studies have reached a similar conclusion: a significant lack of consensus exists in wine quality ratings. However, a few studies, to the author's knowledge, have provided direct quantification of how much consensus (as opposed to randomness) exists in wine ratings. In this paper, a permutation-based mixed model is proposed to quantify randomness versus consensus in wine ratings. Specifically, wine ratings under the condition of randomness are generated with a permutation method, and wine ratings under the condition of consensus can be produced by sorting the ratings for each judge. Then the observed wine ratings are modeled as a mixture of ratings under randomness and ratings under consensus. This study shows that the model can provide excellent model fit, which indicates that wine ratings, indeed, consist of a mixture of randomness and consensus. A direct measure is easily computed to quantify randomness versus consensus in wine ratings. The method is demonstrated with data analysis from a major wine competition and a simulation study. (JEL Classifications: C10, C13, C15)