Quantifying Randomness Versus Consensus in Wine Quality Ratings

2014 ◽  
Vol 9 (2) ◽  
pp. 202-213 ◽  
Author(s):  
Jing Cao
Keyword(s):  
Data Analysis ◽  
Simulation Study ◽  
Mixed Model ◽  
Model Fit ◽  
Direct Measure ◽  
Wine Quality ◽  
Excellent Model ◽  
Quality Ratings ◽  
Jel Classifications ◽  
Direct Quantification

AbstractThere has been ongoing interest in studying wine judges' performance in evaluating wines. Most of the studies have reached a similar conclusion: a significant lack of consensus exists in wine quality ratings. However, a few studies, to the author's knowledge, have provided direct quantification of how much consensus (as opposed to randomness) exists in wine ratings. In this paper, a permutation-based mixed model is proposed to quantify randomness versus consensus in wine ratings. Specifically, wine ratings under the condition of randomness are generated with a permutation method, and wine ratings under the condition of consensus can be produced by sorting the ratings for each judge. Then the observed wine ratings are modeled as a mixture of ratings under randomness and ratings under consensus. This study shows that the model can provide excellent model fit, which indicates that wine ratings, indeed, consist of a mixture of randomness and consensus. A direct measure is easily computed to quantify randomness versus consensus in wine ratings. The method is demonstrated with data analysis from a major wine competition and a simulation study. (JEL Classifications: C10, C13, C15)

scholarly journals Predicting Italian Wine Quality from Weather Data and Expert Ratings

2019 ◽  
Vol 14 (3) ◽  
pp. 234-251 ◽  
Author(s):  
Alessandro Corsi ◽  
Orley Ashenfelter
Keyword(s):  
Probit Model ◽  
Weather Conditions ◽  
Ordered Probit ◽  
Weather Data ◽  
Ordered Probit Model ◽  
Wine Quality ◽  
Italian Wine ◽  
Quality Ratings ◽  
Expert Ratings ◽  
Jel Classifications

AbstractIn 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)

scholarly journals The Choice of Initial Configurations in Multidimensional Scaling: Local Minima, Fit, and Interpretability

2017 ◽  
Vol 46 (2) ◽  
pp. 19-32 ◽  
Author(s):  
Ingwer Borg ◽  
Patrick Mair
Keyword(s):  
Multidimensional Scaling ◽  
Simulation Study ◽  
Optimal Solution ◽  
Model Fit ◽  
Local Minima ◽  
Excellent Model ◽  
Different Types ◽  
The One

Multidimensional scaling (MDS) algorithms can easily end up in local minima, depending on the starting configuration. This is particularly true for 2-dimensional ordinal MDS. A simulation study shows that there can be many local minima that all have an excellent model fit (i.e., small Stress) even if they do not recover a known latent configuration very well, and even if they differ substantially among each other. MDS programs give the user only one supposedly Stress-optimal solution. We here present a procedure for analyzing all MDS solutions resulting from using a variety of different starting configurations. The solutions are compared in terms of fit and configurational similarity. This allows the MDS user to identify different types of solutions with acceptable Stress, if they exist, and then pick the one that is best interpretable.

The Value of Expert Opinion in the Pricing of Bordeaux Wine Futures

2016 ◽  
Vol 11 (2) ◽  
pp. 261-288 ◽  
Author(s):  
Robert H. Ashton
Keyword(s):  
Research Design ◽  
Expert Opinion ◽  
Futures Market ◽  
Wine Quality ◽  
Related Information ◽  
Expert Opinions ◽  
Quality Ratings ◽  
Wine Experts ◽  
Jel Classifications

AbstractThe value of expert opinion for establishing prices in the Bordeaux futures market is analyzed. The expert opinions examined are the wine quality ratings provided by two of the world's foremost wine experts, Robert Parker and Jancis Robinson, for more than 1,700 red Bordeaux wines over the period 2004–2012. The results show that the experts' ratings have both a statistically and practically significant impact on prices after controlling for the effects of other known determinants of price. Thus, expert opinion has significant value in this setting. The results further show that although Parker's impact on prices is significantly greater than Robinson's, combining the quality ratings of both experts has a significantly greater impact than Parker's ratings alone. As hypothesized, the strength of the results differs for wines produced in different regions of Bordeaux because of differences in the availability of other quality-related information. All results are robust to several alternative sample specifications and other research design choices. (JEL Classifications: C52, G13, L11, L15, M21)

scholarly journals Accommodating Taste and Scale Heterogeneity for Front-Seat Passenger’ Choice of Seat Belt Usage

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 460 ◽  
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Mixed Model ◽  
Seat Belt ◽  
Model Fit ◽  
Model Parameters ◽  
Extended Model ◽  
Random Parameters ◽  
Front Seat ◽  
Scale Heterogeneity ◽  
Error Terms ◽  
The Cost

There is growing interest in implementation of the mixed model to account for heterogeneity across population observations. However, it has been argued that the assumption of independent and identically distributed (i.i.d) error terms might not be realistic, and for some observations the scale of the error is greater than others. Consequently, that might result in the error terms’ scale to be varied across those observations. As the standard mixed model could not account for the aforementioned attribute of the observations, extended model, allowing for scale heterogeneity, has been proposed to relax the equal error terms across observations. Thus, in this study we extended the mixed model to the model with heterogeneity in scale, or generalized multinomial logit model (GMNL), to see if accounting for the scale heterogeneity, by adding more flexibility to the distribution, would result in an improvement in the model fit. The study used the choice data related to wearing seat belt across front-seat passengers in Wyoming, with all attributes being individual-specific. The results highlighted that although the effect of the scale parameter was significant, the scale effect was trivial, and accounting for the effect at the cost of added parameters would result in a loss of model fit compared with the standard mixed model. Besides considering the standard mixed and the GMNL, the models with correlated random parameters were considered. The results highlighted that despite having significant correlation across the majority of the random parameters, the goodness of fits favors more parsimonious models with no correlation. The results of this study are specific to the dataset used in this study, and due to the possible fact that the heterogeneity in observations related to the front-seat passengers seat belt use might not be extreme, and do not require extra layer to account for the scale heterogeneity, or accounting for the scale heterogeneity at the cost of added parameters might not be required. Extensive discussion has been made in the content of this paper about the model parameters’ estimations and the mathematical formulation of the methods.

Criteria for Accrediting Expert Wine Judges

2013 ◽  
Vol 9 (1) ◽  
pp. 62-74 ◽  
Author(s):  
Robert Hodgson ◽  
Jing Cao
Keyword(s):  
Probability Distribution ◽  
Wine Industry ◽  
Ordinal Scale ◽  
Professional Experience ◽  
Wine Quality ◽  
Basic Premise ◽  
Definition Of ◽  
Jel Classifications

AbstractA 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)

Don't Judge a Wine by Its Closure: Price Premiums for Corks in the U.S. Wine Market

2019 ◽  
Vol 14 (01) ◽  
pp. 3-25 ◽  
Author(s):  
Anton Bekkerman ◽  
Gary W. Brester
Keyword(s):  
Ordinary Least Squares ◽  
Grocery Stores ◽  
Purchase Decisions ◽  
Limited Information ◽  
Quantile Regressions ◽  
Wine Quality ◽  
Additional Information ◽  
Price Premiums ◽  
The U.S ◽  
Jel Classifications

AbstractFor many purchases, consumers often possess only limited information about product quality. Thus, observable product characteristics are used to determine expected quality levels when making purchase decisions. We use more than 1 million weekly scanner-level observations from grocery stores across ten U.S. markets between September 2009 and August 2012 to examine how consumers value a wine bottle's closure type (i.e., cork or screw cap). We focus on lower-priced wines—those with sale prices less than $30 per 750 milliliter bottle—to more accurately evaluate decisions of consumers for whom seeking additional information about wine quality is likely more costly than the benefits derived from that information. Using both pooled ordinary least squares and quantile regressions to estimate price premiums for bottles with corks or screw caps, we find that U.S. consumers are willing to pay, on average, approximately 8% more (about $1.00) for a bottle of wine that has a cork closure. In addition, we show that the size of this premium increases as wine prices decline. (JEL Classifications: D81, M31, Q11)

Linear mixed model better than repeated measures analysis

2019 ◽  
Vol 30 (6) ◽  
pp. NP1-NP2 ◽  
Author(s):  
Işıl Kutluturk Karagoz ◽  
Berhan Keskin ◽  
Flora Özkalaycı ◽  
Ali Karagöz
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Time ◽  
Case Series ◽  
Model Fit ◽  
Repeated Measures Analysis ◽  
Technical Issues ◽  
Better Than

We have some criticism regarding some technical issues. Mixed models have begun to play a pivotal role in statistical analyses and offer many advantages over more conventional analyses regarding repeated variance analyses. First, they allow to avoid conducting multiple t-tests; second, they can accommodate for within-patient correlation; third, they allow to incorporate not only a random coefficient, but also a random slope, typically ‘linear’ time in longitudinal case series when there are enough data and patients’ trajectories vary a lot and improving model fit.

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