Solving for a Bias in the Standardized Expert Wine Score
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Cardebat and Paroissien (2015) have provided a new methodology to express the scores of
different wine expert on the same rating scale. Their method consists in matching the quantiles of
the distributions of each experts’s scores in an exhaustive dataset. However, they use the raw
empirical distribution functions, which is arguably downward biased. This leads to a frequent
upward bias in the converted scores. This paper exhibits the existence of this bias, provides the
sign of the latter, and suggests a simple interpolation to mitigate it. (JEL Classifications: Q13,
L15, C14).