“Who Will Replace Parker? A Copula Function Analysis of Bordeaux En Primeur Wine Raters” by Don Cyr, Lester Kwong, and Ling Sun is the opening paper of this issue of the Journal of Wine Economics (Cyr, Kwong, and Sun, Reference Cyr, Kwong and Sun2019). Drawing on Bordeaux right bank en primeur wine data from 2005 to 2012, the authors employ copula function analysis and examine which wine critics’ ratings exhibit the closest linear and nonlinear relationship with those of Parker. Their findings suggest that the ratings of James Suckling exhibit the highest rank correlation and bivariate upper tail dependence, identified through copula function analysis, with those of Parker.
David Moroz’ and Bruno Pecchioli's paper, entitled “Should You Invest in an Old Bottle of Whisky or in a Bottle of Old Whisky? A Hedonic Analysis of Vintage Single Malt Scotch Whisky Prices,” analyzes the price determinants of single malt whiskies from Islay in Scotland (Moroz and Pecchioli, Reference Moroz and Pecchioli2019). Focusing on ask prices set by investors, they decompose a whisky's age into cask age (time between distillation and bottling) and bottle age (time from bottling on). Aside from reputation and other effects, their results suggest that cask age has a more pronounced impact (8.9% per year on average) than bottle age (6.7%).
In the third paper of this issue, Harold O. Fried and Loren W. Tauer examine “Efficient Wine Pricing Using Stochastic Frontier Models” for U.S. Riesling wines between 2000 and 2016 to determine possible overpricing and underpricing (Fried and Tauer, Reference Fried and Tauer2019). Using a two-tier stochastic frontier model with only tasting scores (linear and squared) and location data as independent variables, their results suggest that both underpricing and overpricing do not occur simultaneously. Separate one-sided stochastic frontier models showed that “overpricing exists and not underpricing, but the extent of overpricing is minor, suggesting that wineries do an efficient job pricing their wines, given tasting scores, conditional on regional location premiums or discounts” (p. 164).
The next paper, by Benoît Faye and Eric Le Fur, examines whether wine price coefficients found in hedonic analyses are time-invariant (Faye and Le Fur, Reference Faye and Le Fur2019). In “On the Constancy of Hedonic Wine Price Coefficients over Time” they estimate a model on monthly subsamples of a global wine auction database. This yields monthly hedonic coefficient data for the time from 2003 to 2014. In a next step, the authors employ a multivariate autoregressive model to study the stability of these coefficients over time and test for structural or cyclical changes. Their findings suggest that most hedonic coefficients are variable and either exhibit structural or cyclical variations over time. “These findings shed doubt on the relevance of both short- and long-run hedonic estimations” (p. 182).
In the last, short, paper of this issue, Derby Voon and James Fogarty present “A Note on Forecasting Alcohol Demand” (Voon and Fogarty, Reference Voon and Fogarty2019). Drawing on prior work (Fogarty and Voon, Reference Fogarty and Voon2018) and using U.S. alcohol consumption data, the authors compare the performance of various models, such as ARIMA Box–Jenkins, hierarchical ARIMA, neural networks and BATS. Their findings suggest that “no single forecast approach dominates other methods in terms of forecast performance” (p. 208). The paper also demonstrates the capability of the R software platform as a general forecasting tool.
