This paper uses data from the 2021 Swiss edition of the Gault&Millau food guide to analyze the probability with which restaurant owners decide to share their wine list with the public. This is an important question relating to the amount of information circulating in markets characterized by information asymmetry in the context of experience and credence goods. We find that restaurant owners are more willing to share wine lists with others if competition is limited or their wine list does not contain idiosyncratic information that competitors may use strategically. Interviews indicate the challenge for restaurants to balance the risk of sharing information with competitors and the opportunity to attract wine lovers by revealing an appealing wine list. We also show that this decision depends on cultural considerations.

Consumers often struggle to make their choice in the highly diversified wine market. With wine being an experience good, consumers must rely on extrinsic characteristics, e.g., information on the label. Thus, easily available quality signals like consumer ratings have become an increasingly useful and widespread tool. Vivino is one of the largest online wine communities with over 60 million users, which have more than doubled since 2018. Hence, users have easy access to peer ratings, while established wine expert ratings are being challenged. This study analyzes data from Vivino to explore factors affecting consumer ratings at different price points, considering several wine attributes like geographical indications, brand, and the so-called “community effect.” We show that there is a small but significant community effect on wine's perceived quality related to its popularity among users of the Vivino community, as well as effects from specific wine attributes. Moreover, we estimate a hedonic quantile model on similar price ranges to compare the effect of the same regressors on wine prices. Results contribute to a better understanding of how different factors affect consumers’ wine evaluations, allowing to compare their effect on the “pure” consumer preference (i.e., consumer ratings) and market value.

The wine industry, considered to be male-dominated, has seen a growing share of women winemakers. Using a randomized online experiment, we investigate how the producer’s gender influences consumers’ willingness to pay for the wine. Gender can be identified either from the first name of the producer or from a gendered group of wine producers. Using a Tobit and a double-hurdle model, our results suggest that consumers’ willingness to pay is lower for wine produced by female winemaker groups. This reduction appears to be particularly pronounced when the consumer is male.

Can we predict fine wine and alcohol prices? Yes, but it depends on the forecasting horizon. We make this point by considering the Liv-ex Fine Wine 100 and 50 Indices, the retail and wholesale alcohol prices in the United States for the period going from January 1992 to March 2022. We use rich and diverse datasets of economic, survey, and financial variables as potential price drivers and adopt several combination/dimension reduction techniques to extract the most relevant determinants. We build a comprehensive set of models and compare forecast performances across different selling levels and alcohol categories. We show that it is possible to predict fine wine prices for the 2-year horizon and retail/wholesale alcohol prices at horizons ranging from 1 month to 2 years. Our findings stress the importance of including consumer survey data and macroeconomic factors, such as international economic factors and developed markets equity risk factors, to enhance the precision of predictions of retail/wholesale (fine wine) prices.