The purpose of this paper is to provide a tutorial of data analysis methods for answering questions that arise in analyzing data from wine-tasting events: (i) measuring agreement of two judges and its extension to m judges; (ii) making comparisons of judges across years; (iii) comparing two wines; (iv) designing tasting procedures to reduce burden of multiple tastings; (v) ranking of judges; and (vi) assessing causes of disagreement. In each case we describe one or more analyses and make recommendations on the conditions of use for each. (JEL Classifications: C10, C12, C13, C59, C90)

Bottles of water vary in price with some priced as if they were bottles of fine wine. This article attempts to explain price differences between over 100 bottled waters included in a guidebook to fine waters by drawing on the hedonic pricing approach, which has been used to try to explain price differences among bottles of wine. As part of that approach, the price of each bottled water is regressed against various characteristics, including those related to its water. Water-related characteristics explain only a small part of the price differences among the bottled waters. Thus, to a large extent, the premium that consumers pay for a more expensive bottled water does not seem to be a premium for its water. (JEL Classifications: C21, Q25)

We provide a mini-history of the craft beer segment of the U.S. brewing industry with particular emphasis on producer-entrepreneurs but also other pioneers involved in the promotion and marketing of craft beer who made contributions to brewing it. In contrast to the more commodity-like lager beer produced by the macrobrewers in the United States, the output of the craft segment more closely resembles the product differentiation and fragmentation in the wine industry. We develop a database that tracks the rise of craft brewing using various statistical measures of output, number of producers, concentration within the segment, and compares output with that of the macro and import segment of the industry. Integrating our database into Geographic Information Systems software enables us to map the spread of the craft beer segment from its taproot in San Francisco across the United States. Finally, we use regression analysis to explore variables influencing the entrants and craft beer production at the state level from 1980 to 2012. We use Tobit estimation for production and negative binomial estimation for the number of brewers. We also analyze whether strategic effects (e.g., locating near competing beer producers) explain the location choices of craft beer producers. (JEL Classifications: L26, L66, N82, R12)

Advanced machine learning techniques like Gaussian process regression and multi-task learning are novel in the area of wine price prediction; previous research in this area being restricted to parametric linear regression models when predicting wine prices. Using historical price data of the 100 wines in the Liv-Ex 100 index, the main contributions of this paper to the field are, firstly, a clustering of the wines into two distinct clusters based on autocorrelation. Secondly, an implementation of Gaussian process regression on these wines with predictive accuracy surpassing both the trivial and simple ARMA and GARCH time series prediction benchmarks. Lastly, an implementation of an algorithm which performs multi-task feature learning with kernels on the wine returns as an extension to our optimal Gaussian process regression model. Using the optimal covariance kernel from Gaussian process regression, we achieve predictive results which are comparable to that of Gaussian process regression. Altogether, our research suggests that there is potential in using advanced machine learning techniques in wine price prediction. (JEL Classifications: C6, G12)

Are wine alcohol labels accurate? If not, why? We explore the high and rising alcohol content of wine and examine incentives for false labeling, including the roles of climate, evolving consumer preferences, and expert ratings. We draw on international time-series data from a large number of countries that experienced different patterns of climate change and influences of policy and demand shifts. We find systematic patterns that suggest that rising wine alcohol content may be a nuisance by-product of producer responses to perceived market preferences for wines having more-intense flavours, possibly in conjunction with evolving climate. (JEL Classifications: D22, L15, L66, Q18, Q54).

Evaluating observed wine-tasting results as a mixture distribution, using linear regression on a transformation of observed results, has been described in the wine-tasting literature. This article advances the use of mixture models by considering that existing work, examining five analyses of ranking and mixture model applications to non-wine food tastings and then deriving a mixture model with specific application to observed wine-tasting results. The mixture model is specified with Plackett-Luce probability mass functions, solved with the expectation maximization algorithm that is standard in the literature, tested on a hypothetical set of wine ranks, tested with a random-ranking Monte Carlo simulation, and then employed to evaluate the results of a blind tasting of Pinot Gris by experienced tasters. The test on a hypothetical set of wine ranks shows that a mixture model is an accurate predictor of observed rank densities. The Monte Carlo simulation yields confirmatory results and an estimate of potential Type I errors (the probability that tasters appear to agree although ranks are actually random). Application of the mixture model to the tasting of Pinot Gris, with over a 95% level of confidence based on the likelihood ratio and t statistics, shows that agreement among tasters exceeds the random expectation of illusory agreement. (JEL Classifications: A10, C10, C00, C12, D12)

We examine the degree of consensus in quality ratings of prominent U.S. wine publications. For the purposes of wine consumption and research, are ratings on the ubiquitous 100-point scale reliable measures of quality? The value of expert judgment has been called into question by a number of studies, especially in the context of wine competitions and tasting events. Using data on 853 wines, we find a moderately high level of consensus, measured by the correlation coefficient, between most pairs of publications, similar to the level found by Ashton (2013). Rank and intraclass correlations are similar. Consensus is not found to be related to the blinding policies (or lack thereof) of the critical publications. (JEL Classifications: C93, D46)

We conducted a blind tasting sensory evaluation experiment and a chemical analysis of four craft hard apple ciders from the Pacific Northwest of the USA. Using the sensory and demographic data collected during the experiment, we estimated the consumer willingness-to-pay (WTP), using a contingent valuation model. Overall liking, taste, and aroma, from the sensory evaluation, as well as age of the sampler and if the sampler was a cider drinker, contributed positively to the WTP. In contrast, if the subject was a beer drinker this reduced their WTP. From the chemical analysis we found that tannin level had a positive effect on WTP, but an increased level of sweetness, as part of a ratio of specific gravity to acid, decreased consumer WTP. (JEL Classifications: C91, D12, L66, Q13)

Rank preference and mixture models have been employed to evaluate the ranks assigned by consumers in taste tests of beans, cheese, crackers, salad dressings, soft drinks, sushi, animal feed, and wine. In many wine tastings, including the famous 1976 Judgment of Paris and the 2012 Judgment of Princeton, judges assign scores rather than ranks, and those scores often include ties. This article advances the application of ranking and mixture models to wine-tasting results by modifying the established use of a Plackett-Luce rank preference model to accommodate scores and ties. The modified model is tested and then employed to evaluate the Paris and Princeton wine-tasting results. Test results show that the mixture model is an accurate predictor of observed rank densities. Results for Paris and Princeton show that the group preference orders implied by the mixture model are highly correlated with the orders implied by widely employed rank-sum methods. However, the mixture model satisfies choice axioms that rank-sum methods do not, it yields an estimate of the proportion of scores that appear to be assigned randomly, and it also yields a preference order based on nonrandom preferences that tasters appear to hold in common. (JEL Classifications: A10, C00, C10, C12, D12)

The price of wine is a key topic among market participants interested in valuing their stock, including dealers and restaurants, and consumers who may be interested in optimizing their purchases. A closely related issue, revaluation is the need to regularly update the value of a stock. This need is especially acute in the growing industry of wine as an investment. In this case, fair-value measurement is compulsory by law. We briefly review methods available to funds and introduce a new quantitative method aimed at achieving compliance with IFRS (International Financial Reporting Standard) 13 for fair valuation. Using auction data on 26,640 lots, we apply this method to compute the current fair value of a basket of 232 different wines. (JEL Classifications: C14, C43, Z11)

We use the expectation-disconfirmation and categorization theories to study the effects of sensory versus nonsensory cues relative to a transformed attribute on categorization and typicality judgments relative to a new food product. In an experiment involving 51 participants and low-alcohol wines (new products), we show that categorization and typicality judgments differ according to sensory versus nonsensory cues. The new transformed product is categorized more often in its original category—wine—and perceived as more typical in the nonsensory compared to the sensory condition. (JEL Classifications: L66, M31)

In this paper we provide a simple and transparent non parametric methodology to express the scores of each wine expert on the same rating scale. We discuss the advantage of this methodology over a linear transformation. The non-paramatric method ensures the comparability of scores among experts and allows for a relevant average calculation of available wine scores. (JEL Classifications: Q13, L15, C14).

We present a simple static way of optimizing the prices of bottles of wine for restaurants with a given cellar. In contrast to classical assortment pricing models, we posit that the cellar (i.e., inventory) is given and is not taken as a variable entering the optimization program. In our model, the optimal price is driven mainly by a rating parameter after the effect of initial cost is removed. This parameter plays the role of a dominant characteristic in hedonic models, even though the levels of stocks may also be determinant when they are very low. We provide a numerical sensitivity analysis of prices to various parameters and study a realistic large-scale example based on two wine lists with 50 bottles each. Finally, several extensions are discussed. (JEL Classifications: C61, L11, L83)

This paper examines the ratings of 12 influential wine critics on the Bordeaux en primeur market over the vintages 2003–2012. We hypothesize that wine experts differ significantly in their rating approach and influence on prices. We find that European critics are less transparent and in general more severe in their scoring than their American counterparts. Experts also appear to reach a relatively strong consensus on overall wine quality but have more diverse opinions on wines that achieve a surprising level of quality given the vintage, the ranking, or the appellation from which they originate. Our evidence also suggests that Robert Parker and Jean-Marc Quarin are the most influential critics, as a 10% surprise in their scores leads to a price increase of around 7%. We further find that their impact is higher for appellations and estates that are not covered by the official 1855 classification and for the best vintages. (JEL Classifications: C60, G11, Q11)

In an ever-more-competitive global market, vignerons compete for the attention of consumers by trying to differentiate their product while also responding to technological advances, climate changes and evolving demand patterns. In doing so, they highlight their regional and varietal distinctiveness. This paper examines the extent to which the winegrape varietal mix varies within and among states of the United States and relative to the rest of the world, and how that picture has been evolving. It reports varietal intensity indexes for different regions, indexes of similarity of varietal mix between regions and over time, and price-based quality indexes across regions and varieties within and among the three west-coast States. Broadly speaking, the mix of winegrape varieties in the United States is not very different from that in the rest of the world and, since 2000, it has become even less differentiated and closer to that of France and the world as a whole. But individual U.S. regions vary considerably in the mix of varieties in which they specialize and in the quality of grapes they produce of a given variety; and region-by-variety interactions have complex influences on the pattern of quality and production. We use measures of regional varietal comparative advantage and a Nerlovian partial adjustment model to account for some of the shifting varietal patterns in the U.S. vineyard and in winegrape production. (JEL Classification: D24, L66, Q13)