Transcript PPT

THE PRICE OF PERFECTION
PRELIMINARY RESULTS – PLEASE DO NOT QUOTE
P. MASSET, J.-P. WEISSKOPF & P. CHAROSKY
23 JUNE 2016
Introduction
Literature
Data
Methodology
Results
Conclusion
INTRODUCTION (I)
•
In culture and arts, the opinion is generally
that perfection is an ideal that artists often
pursue but which is impossible to achieve.
•
For wine the concept of perfection transcends
technical perfection and also encompasses a
sense of aesthetic and gustative ideal.
•
For wine, the creator is not just the human, but it also includes the sky (the weather) and the soil
(the terroir).
•
The conjunction of perfect natural conditions with perfect winemaker’s decisions is perhaps even
less likely to occur than in the case of other forms of human creations.
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Introduction
Literature
Data
Methodology
Results
Conclusion
INTRODUCTION (II)
• How do wine & spirits editors know when they encounter perfection?
o
“My perfect-scorers have certain things in common, including finesse, radiance and
complexity. But it was their impeccable, seamless balance that completely blew me away.”
Kerin O’Keefe
o
“I remember the balance first, the fact that its fruit was so direct, its tannins so ripe. You could
almost drink it there and then. But then I thought—this wine will outlive grandchildren, not just
me. It had that supreme quality of a really great wine. As it ages, it will constantly fascinate
and amaze.” Roger Voss
o
“Perfect is a highly subjective assessment, one that, like true love, cannot be hunted down. It
must find you. When it does, you will know. It kept dogging me, like a dream you can’t shake,
whispering to me, ‘100 points, 100 points, 100 points’.” Paul Gregutt.
Source: Newman (2016)
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Introduction
Literature
Data
Methodology
Results
Conclusion
INTRODUCTION (III)
• Until the end of 2015, Robert Parker has
awarded scores of 96 points or more to 394
red wines from Bordeaux. Among them 85
have received a perfect 100 score.
• By definition, a perfect 100 score corresponds
to a perfect wine. Of course, the notion of
perfection, especially for wine, appears
subjective and personal.
• The symbolic value attached to such a perfect
score is nevertheless extremely strong and is
likely to have a tremendous influence on the
price people are willing to pay for owning such
an iconic wine.
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Introduction
Literature
Data
Methodology
Results
Conclusion
INTRODUCTION (IV)
• In this paper we want to study the concept of perfection on the fine wine market along two lines.
•
What is the impact of a perfect 100 score on
prices?
We want to analyse how Parker scores and
especially perfect 100 scores relate to wine prices
and if they lead to a premium. In other words, what
is the price of perfection?
•
What does it take to get a perfect 100 score
and how is it described?
Robert Parker not only attributes scores but also
writes tasting notes. How does he describe a perfect
wine? What wording does he use and how can
readers get a better feeling for deciphering
perfection?
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Introduction
Literature
Data
Methodology
Results
Conclusion
LITERATURE
• Relationship between expert scores and wine prices
Positive “Parker effect” (Hadj Ali et al., 2010; Dubois & Nauges, 2010; Hay, 2010).
o Jones & Storchmann (2001) show that each additional Parker point typically leads
to a price increase of 4% to 10%.
o Ginsburgh et al. (1994), Di Vittorio & Ginsburgh (1996), Kugler & Kugler (2010)
indicate that Parker scores do not explain more than the 1855 classification.
o
• Tasting notes, their wording and their value
English and Spanish descriptors in wine tasting (López Arroyo-Roberts, 2014).
o Translation of sensory perceptions on wine’s color, aroma, taste, and touch into
text (Paradis, 2009; Paradis-Eeg Olofsson, 2013).
o Length of note and non-analytical wording add value (Ramirez, 2007).
o
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Introduction
Literature
Data
Methodology
Results
Conclusion
DATA
• 77 wines from Bordeaux
o
28 St. Emilion, 15 Pomerol, 7 Pessac & 27 left bank
• Robert Parker sample
o
o
o
88 Vintages, from 1874 up to 2012
6’915 data points from Robert Parker & Neal Martin
Scores and tasting comments from 1992 to 2014
• Auction sample
o
o
o
160’230 auction prices
Sold over the period 1996 to 2015
2 Chicago-based auction houses (TCWC and HDH)
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Introduction
Literature
Data
Methodology
Results
Conclusion
METHODOLOGY
Estimating the price of perfection:
• Hedonic regressions of wine attributes on wine prices
Bottle size, time dummies, vintage dummies, chatêaux dummies, expert scores
o Interactions between perfect 100 scores and appelation, bottle size & status
o
Understanding what is a perfect wine:
• Text mining of Parker tasting notes
Structure and length of the tasting note.
o Words and terms used to describe the wines dependent on their score.
o
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Introduction
Literature
Data
RESULTS (I)
General takeaway:
• Huge premium for
perfect 100 scores.
• Wines below 93
points trigger a
discount.
• Bottle size has an
impact on prices.
Variables used:
Bottle size dummies
Time dummies
Chateaux dummies
Status dummies
AOC dummies
Age
Vintage dummies
R2
up to 79
80 to 84
85 to 89
90 to 92
93 to 95
96
97
98
99
Perfection!
1.5L
3.0L
6.0L
Methodology
Results
Conclusion
Specification 1a
Specification 1b
Specification 2
R
R
R
R
R
R
R
R
R
R
R
R
0.79 Premium /
Discount
Coeff.
-63.0%
-0.99***
-50.7%
-0.71***
-35.3%
-0.43***
-15.7%
-0.17***
25.3%
0.23***
44.8%
0.37***
105.6%
0.72***
124.2%
0.81***
130.4%
0.83***
240.1%
1.22***
0.92***
1.75***
2.39***
151.6%
472.6%
992.2%
0.88 Premium /
Discount
Coeff.
-59.1%
-0.89***
-47.5%
-0.64***
-31.7%
-0.38***
-9.3%
-0.1***
25.5%
0.23***
59.6%
0.47***
127.1%
0.82***
110.6%
0.74***
99.3%
0.69***
210.2%
1.13***
0.87***
1.64***
2.32***
139.0%
413.5%
913.7%
R
0.91 Premium /
Discount
Coeff.
-38.0%
-0.48***
-31.0%
-0.37***
-23.3%
-0.26***
-8.1%
-0.08***
16.6%
0.15***
37.3%
0.32***
88.7%
0.63***
68.9%
0.52***
65.7%
0.51***
125.8%
0.81***
0.85***
1.62***
2.31***
133.4%
403.3%
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905.5%
Introduction
Literature
RESULTS (II)
General takeaway:
• Bottle size has no
real influence.
• More pronounced for
right bank wines.
Data
Variables used:
Bottle size dummies
Time dummies
Chateaux dummies
Vintage dummies
Methodology
Results
Conclusion
Specification 3a
Specification 3b
Specification 3c
R
R
R
R
R
R
R
R
R
R
R
R
Interaction: 100/100 & Bottle size
R
Interaction: 100/100 & Status
Interaction: 100/100 & AOC
Interaction: 100/100 & Age
Reference:
Normal bottle (0.75L)
R2
0.89 Premium /
Coeff.
Discount
Perfection!
0.81***
124.1%
Perfection × 1.50
0.01
0.6%
Perfection × 3.00
0.03
3.1%
Perfection × 6.00
0.08**
8.2%
Perfection × 1GCC A
Perfection × 1GCC B
Perfection × 2GCC
Perfection × 5GCC
Perfection × non-classified
Perfection × St-Estèphe
Perfection × St-Julien
Perfection × Margaux
Perfection × Pessac
Perfection × Pomerol
Perfection × St-Emilion
R
R
1GCC
0.91 Premium /
Coeff.
Discount
0.73***
108.3%
0.35***
0.92***
0.1***
0.25***
0.11***
Pauillac
0.91 Premium /
Coeff.
Discount
0.71***
103.2%
41.9%
151.2%
11.1%
28.0%
11.1%
0.36***
-0.16***
0.05***
0.1***
0.14***
0.48***
42.96%
-15.02%
4.63%
10.7%
14.5%
10 62.0%
Introduction
Literature
Data
Methodology
Results
Conclusion
RESULTS (III)
General structure of the tasting note
50-94
95-99
100
# paragraphs
1.26
1.42
1.56
# words
82.05
127.04
154.26
# characters
513.62
790.23
946.06
0.05
0.19
0.43
# exclamation mark
• The better the score, the longer and more descriptive the note.
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Introduction
Literature
Data
Methodology
Results
Conclusion
RESULTS (IV)
For less than perfect wines it is about:
• (Medium) body
• Fruit
• Sweetness
• Tannin
• Color (black, purple)
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Introduction
Literature
Data
Methodology
Results
Conclusion
RESULTS (V)
For perfect 100 score wines it is all about:
• Concentration
• (Full) body
• Fruit
• Richness
• Great vintages
• Positive adjectives
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Introduction
Literature
Data
Methodology
Results
Conclusion
CONCLUSION
• We analyse the influence perfect 100 Parker scores have on wine prices and the how
these wines are described in Parker’s tasting notes.
• Use of hedonic regression and text mining.
• Perfect 100 scores have a significantly positive impact on wine prices.
• Robert Parker uses specific wording to describe perfect wines.
• Next step: Dig deeper into tasting notes and their link to prices.
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