Consumers are always looking for new types of wines. Producers compete for their attention by trying to product differentiate at the same time as they are responding to technological improvements, climate change, and evolving demand patterns. In doing so, wineries are increasingly highlighting their regional and varietal distinctiveness. This paper examines the extent to which the choice of winegrape varieties in wine regions has already changed over the first decade of the twenty-first century in both the Old World and New World. In doing so, it reports a varietal intensity index of different regions and an index of similarity of varietal mix between regions. The study is based on a new database of vine-bearing areas circa 2000 and 2010 for nearly 1,300 DNA-distinct winegrape varieties, spanning over 600 regions in 44 countries that together account for 99 percent of the world's wine production. (JEL Classifications: D24, L66, Q13, Q15)

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)

This study tests the prevalence of choice overload (CO) in the U.S. beer market. We reveal that even if CO exists, sellers have mechanisms to reduce CO's negative consequences. The article describes the implementation of search cost-reducing private nudges (i.e., product quality scores and prominently listed specials) sellers commonly utilize to minimize CO's negative consequences. Our results suggest that, while CO exists for some buyers, it can be eliminated by market interactions on the part of the seller. (JEL Classifications: C93, D03, Q13)

The prior literature disregards the time-varying conditional correlation and its importance for portfolio diversification when it assesses the risk-return profile of fine wine with that of stocks. To address this limitation, this paper applies a dynamic conditional correlation model and examines the co-movements between fine wine and stock prices in the United Kingdom (UK). Based on monthly data from January 2001 to February 2014, we find that fine wine is a hedge against movements in UK stocks. Nevertheless, it cannot act as an effective safe haven during market turmoil. Those findings have noteworthy implications for financial advisors and portfolio managers who are interested in alternative investments. (JEL Classifications: G1, G11, Q1, Q14)

Hop production has expanded dramatically in recent years along with the number of local craft breweries, but to date the relationship between these two phenomena has not been explored systematically. Using a state-level pooled count data model with observations from 2007, 2012, and 2017, we examine the independent lagged effects of breweries on the number of hop farms and acres grown, holding constant fixed effects and key economic and geographic factors. Our results confirm that the number of breweries is associated with more hop production (farms and acres) five years later, while warmer temperatures and higher land prices discourage it. (JEL Classifications: L66, Q11, R30)

This study examines a framework developed by Cardebat, Figuet, and Paroissien in a 2014 Journal of Wine Economics article for identifying the impacts of both objective and subjective quality on wine prices. We recognize how various specifications are observationally equivalent and that the interpretation of model estimates depends crucially on the posited assumption for the relation between price and objective and subjective quality. The proposed framework is applied to Australian premium wines. Results indicate that the price impact of expert personal opinions is similar to the impact of objective quality as estimated via weather, vintage, and producer fixed effects. The relative importance of objective quality compared with subjective quality depends crucially on the ability of expert scores to accurately reflect objective quality. (JEL Classifications: C21, Q11, Q54)

The purpose of this paper is to measure the impact of Robert Parker's oenological grades on Bordeaux wine prices. We study their impact on the so-called en primeur wine prices, i.e., the prices determined by the château owners when the wines are still extremely young. The Parker grades are usually published in the spring of each year, before the wine prices are established. However, the wine grades attributed in 2003 have been published much later, in the autumn, after the determination of the prices. This unusual reversal is exploited to estimate a Parker effect. We find that, on average, the effect is equal to 2.80 euros per bottle of wine. We also estimate grade-specific effects, and use these estimates to predict what the prices would have been had Parker attended the spring tasting in 2003. (JEL Classification: C21, D89, L15).

The Norwegian per capita sales of wine have more than doubled over the past 20 years, while the sales of sprits and beer have declined. These changes are likely to be the effect of changes in economic, demographic, and attitudinal factors as well as the availability of wine. We estimated age-period-cohort (APC) logit models using data from a large repeated cross-sectional survey over the period 1991–2015. The estimation results indicate substantial effects of the APC variables as well as income, availability, and attitudes. The model was used to simulate wine consumption over the life cycle in different birth cohorts. The simulation results indicate that wine consumption frequency increases by age, and younger cohorts are expected to increase their consumption frequencies more than older cohorts, which suggests an increased wine consumption over time. (JEL Classifications: D12, J10, Q13)

In this article, we evaluate how sensory qualities of wine, such as astringency, bitterness, aroma, and flavor, affect consumers' willingness to pay for wine. In order to accomplish this objective, we utilize data collected from untrained consumers, a trained panel, and laboratory measurements of tannin intensity. From this data, a consumer-preference model, a consumer-intensity model, a trained-panel model, and an instrumental-measurement model are estimated and compared. Overall, the consumer-preference model is the most accurate in predicting consumers' willingness to pay. As expected, the closer a wine is to a consumer's ideal, the more they are willing to pay. Astringency has a mostly positive effect, and bitterness has a negative effect. Comparing the accuracy of the other models, the instrumental-measurement model is the next best, followed by trained-panel model, and the consumer-intensity model. This suggests that the instrumental measurements can be used as an effective alternative to trained panels. This is important because trained panels may be less practical to use on an ongoing basis. (JEL Classification: Q13, M31)

In this paper we estimate how a variety of subjective measures of quality taken from the published opinions of several experts on Italian wines (Barolo and Barbaresco) are determined by the weather conditions during the relevant season, in order to assess their reliability. Since these measures of quality are only ordinal, we estimate their determinants using an ordered probit model. The method provides measures of the determinants of vintage quality ratings and suggestions on the reliability of each expert. (JEL Classifications: D12, Q11, Q13)

In the author's earlier research, five quite reliable and six quite unreliable subsets of tasters were identified, from among the full sample of eleven wine tasters, at the heralded 1976 Paris blind Chardonnay and Bordeaux/Cabernets wine competitions. This study shows quite conclusively that the consistent tasters and the inconsistent ones provided quite different results when compared both to each other and to the results based upon the full sample of eleven tasters. Results demonstrate the following: one should be wary of findings based solely upon an omnibus approach (i.e., results based only on the full sample of 11 tasters); that a next logical step is not only to continue to identify consistent tasters, but to design future studies in which these reliable judges are used to teach neophyte imbibers to also achieve high levels of wine tasting consistency; and that in continuing to investigate other important empirically derived oenological information, we should not, in the process, lose sight of the sheer hedonic pleasure of the next glass of wine.

This article examines the survival rates of cooperatives in the French wine industry. Traditional theory claims that cooperatives are inefficient and consequently are prone to failure, but recent literature suggests a higher resilience. Can cooperatives cope better? We find that French wine cooperatives survive longer than corporations. This result is robust in semi-parametric and parametric models, even when we control for mergers and acquisitions. The higher survival rate of wine cooperatives seems to be associated with their ability to pass changes in their business environments on to their members. (JEL Classifications: C41, G30, Q13)

The European Union's (EU) long-standing financial support for its wine industry has been nontrivial but very difficult to estimate. The Organization for Economic Cooperation and Development's (OECD) generic producer support estimate methodology has been able to capture some of the supports, but it excludes such measures as subsidized distillation of low-quality wine, grants to promote wine generically, protection via import tariffs, and grubbing-up premiums. Nor does the OECD disaggregate EU supports to individual member countries. This article provides a new set of more complete estimates of support to EU wine producers. It also reveals how unevenly those supports are spread across EU member countries. The new estimates suggest that during 2007–2012, annual assistance amounted to approximately 700 euros per hectare of vines or 0.15 euros per liter of wine produced in the EU as measured at the winery gate. That is equivalent to a nominal rate of direct plus indirect producer assistance of approximately 20%. (JEL Classifications: F14, H25, L66, Q18)

This paper conducts a meta-analysis of price and income elasticities for wine and distilled spirits, which correct for outliers and publication bias. The sample of wine elasticities is obtained from 104 primary studies, and the sample of spirits elasticities is obtained from 111 primary studies. Robust weighted-means and meta-regressions are reported that correct for outliers, heterogeneity, heteroskedasticity, dependence, and publication bias. Compared to unweighted averages previously reported in the literature, the analysis yields less-elastic demands for both price and income. Average price elasticities obtained using cumulative meta-analysis are −0.45 for wine and −0.55 for spirits. Average income elasticities are 1.0 for both beverages. Bias due to publication selectivity is important. Country-level differences also are noted for both wine and spirits. Policy implications are discussed for pricing and taxation of alcohol beverages. (JEL Classifications: Q11, C18, I12)

A test for evaluating wine judge performance is developed. The test is based on the premise that an expert wine judge will award similar scores to an identical wine. The definition of “similar” is parameterized to include varying numbers of adjacent awards on an ordinal scale, from No Award to Gold. For each index of similarity, a probability distribution is developed to determine the likelihood that a judge might pass the test by chance alone. When the test is applied to the results from a major wine competition, few judges pass the test. Of greater interest is that many judges who fail the test have vast professional experience in the wine industry. This leads to us to question the basic premise that experts are able to provide consistent evaluations in wine competitions and, hence, that wine competitions do not provide reliable recommendations of wine quality. (JEL Classifications: C02, C12, D81)

This article describes a new empirical model of the world's markets for alcoholic beverages and, to illustrate its usefulness, reports results from projections of those markets from 2016–2018 to 2025 under various scenarios. It not only revises and updates a model of the world's wine markets (Wittwer, Berger, and Anderson, 2003), but also adds beer and spirits so as to capture the substitutability of those beverages among consumers. The model has some of the features of an economy-wide computable general equilibrium model, with international trade linking the markets of its 44 countries and seven residual regions. It is used to simulate prospects for these markets by 2025 (business-as-usual), which points to Asia's rise. Then two alternative scenarios to 2025 are explored: one simulates the withdrawal of the United Kingdom from the European Union (EU); the other simulates the effects of the recent imposition of additional 25% tariffs on selected beverages imported by the United States from several EU member countries. Future applications of the model are discussed in the concluding section. (JEL Classifications: C53, F11, F17, Q13)

Winemaking is a highly complex technology. It needs inputs over which there is no control (good weather conditions), initial endowments which can hardly be modified (soil, exposure of the slopes), inputs which take 20 to 30 years before producing good quality outputs (vines), manual operations (picking), mechanical operations (crushing, racking) and chemical processes (during fermentation). In the paper, we disentangle the production technology, and try to quantify the impact on prices (qualities) of each of the many inputs (including weather conditions) and steps used in producing wine in Médoc. We show that technology and weather conditions are able to explain two thirds of the variance of prices; when reputation effects (based on the wine classification made in 1855) are included, this proportion rises to almost 85%. This suggests either that “classified” producers are able to charge higher prices, or that the classification is a measure of quality reflected by prices. We also show that two of the more recent attempts at classifying wines are not as good at explaining prices than the official (and old) 1855 classification. (JEL Classification: L66, Z19, C5, D4)

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)

Statistics on the wine market in countries where it is not traditionally produced or consumed are estimates using simple methods. In northeast Asia those statistics are exaggerated for a combination of several reasons. One is a labelling issue: imported bulk wine is able to be added to domestically produced wine without the front label having to declare the bottle may contain foreign product. Similar freedom applies to wine made from imported grape juice concentrate. A second (particularly in China) is a double-counting issue: domestic wine produced in one region of the country may be blended with wine produced in and packaged for final sale from another region, with both regions claiming it as their contribution to national wine output. A third possibility is a smuggling issue: some wine re-exports and imports are unrecorded. These possibilities of the wine market being exaggerated are significant for firms seeking to export to and sell in such countries, especially in the fast-growing ones of northeast Asia. This article shows the extent to which estimates for the region could change for such indicators as per capita wine consumption, wine self-sufficiency, and the region's share of global wine consumption, when alternative assumptions are made in response to these issues. (JEL classifications: F14, L66, Q13, Y10)

In the Old-World vineyards of Europe, a key concept that plays an important role in the production and appreciation of wines is terroir, which refers to the special characteristics of a place that impart unique qualities to the wine produced. We examine whether terroir matters in the New-World wines produced in California's Napa and Sonoma Counties by conducting a hedonic price analysis of vineyard sales over the period 1991 to 2007 to determine the relative effects on vineyard sales prices of designated appellations versus biophysical site attributes commonly associated with terroir, such as slope, aspect, elevation, and climate. Because vineyards that are sold are not necessarily representative of the universe of vineyards, we employ Heckman's two-stage econometric approach to control for possible sample-selection bias. We find that intrinsic site attributes and designated appellations influence vineyard prices, although our results are stronger and more consistent with regard to the influence of appellations. This finding indicates that terroir matters economically, even if the designated appellations have relatively less connection in reality with terroir. (JEL Classifications: C2, Q11)