(solution) FOR A PRODUCER WHAT IS THE OPPORTUNITY cost of storing wine an

(solution) FOR A PRODUCER WHAT IS THE OPPORTUNITY cost of storing wine an

FOR A PRODUCER WHAT IS THE OPPORTUNITY cost of storing wine an additional year ?

The Economic Journal, 118 (June), F174?F184. Ó The Author(s). Journal compilation Ó Royal Economic Society 2008. Published by
Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. PREDICTING THE QUALITY AND PRICES OF
BORDEAUX WINE*
Orley Ashenfelter
Bordeaux wines have been made in much the same way for centuries. This article shows that the
variability in the quality and prices of Bordeaux vintages is predicted by the weather that created the
grapes. The price equation provides a measure of the real rate of return to holding wines (about
2?3% per annum) and implies far greater variability in the early or Ôen primeurÕ wine prices than is
observed. The analysis provides a useful basis for assessing market inefficiency, the effect of climate
change on the wine industry and the role of expert opinion in determining wine prices. Red wines have been produced in the Bordeaux region of France in much the same
way, for hundreds of years. Yet, there are differences in quality and price from year to
year that can sometimes be quite large. Until very recently, these quality differences
have been considered a great mystery. In this article I show that the factors that affect
fluctuations in wine vintage quality can be explained in a simple quantitative way. In
short, I show that a simple statistical analysis predicts the quality of a vintage, and hence
its price, from the weather during its growing season. Along the way, I show how the
aging of wine affects its price, and under what circumstances it pays to buy wines before
they are at their best for drinking. Since this procedure for predicting wine quality has
now been in use for over a decade, I also provide an appraisal of its successes (and
failures) and a discussion of the role this information has played in the evolution of the
wine trade.
When a red Bordeaux wine is young it is astringent and most people will find it
unpleasant to drink. As a wine ages it loses its astringency. Because Bordeaux wines
taste better when they are older, there is an obvious incentive to store them until they
have come of age. As a result, there is an active market for both younger and older
wines. Traditionally, what has not been so obvious is exactly how good a wine will be
when it matures. This ambiguity leaves room for speculation and, as a result, the price
of the wine when it is first offered in its youth will often not match the price of the wine
when it matures. The primary goal in this article is to study how the price of mature
wines may be predicted from data available when the grapes are picked, and then to
explore the effect that this has on the initial and final prices of the wines. A secondary
goal is to show how this straightforward hedonic method has now been used in many
other grape growing regions to quantify the role the weather plays in determining the
quality of wine vintages.
The study of how wine vintages are priced provides a fascinating window on the
operation of a market that has high visibility in many countries. In more recent years, as
concerns and evidence regarding global warming have mounted, the role of the
weather in determining wine quality and prices has taken on greater urgency. Climate
change will no doubt affect wine production with, as Jones et al. (2005) show, winners
* The author thanks the Editor of this Journal and an anonymous referee for helpful comments. All
interpretations and any errors are the author?s sole responsibility.
[ F174 ] [ J U N E 2008 ] F175 PREDICTING THE QUALITY and losers. The evidence on wine prices and weather provides one avenue for calibrating who the winners and losers are likely to be and how much they may win or lose. 1. Vineyards and Vintages
The best wines of Bordeaux are made from grapes (typically cabernet sauvignon and
merlot) grown on specific vineyard properties and the wine is named after the property, or chateau, that controls where the grapes are grown. In fact, knowledge of the
chateau (essentially the vineyard) and vintage provides most of the information needed
to know the quality of the wine. That is, if there are ten vintages and six chateaux, there
are, in principle, 60 different wines of different quality. It might seem a daunting task
to determine the quality of each wine. However, knowing the reputations of the six
chateaux and the ten vintages gives sufficient data to determine the quality of all 60. In
other words, good vintages produce good wines in all vineyards and the best wines are
produced in the best vineyards in all vintages.
Although this point is sometimes denied by those who produce the wines, and
especially by the sellers of young wines, it is easy to establish its truth by reference to the
prices of the mature wines. To demonstrate the point, Table 1 indicates the market
price in the early 1990s in London of six Bordeaux chateaux from the ten vintages from
1960 to 1969.
These chateaux were selected because they are large producers and their wines are
sold very frequently. A blank in the Table indicates that the wine had not appeared in
the market in some time. (Lower quality vintages are typically the first to leave the
market.) The vintages from 1960 to 1969 are selected because by now these wines are
fully mature and there is no remaining uncertainty about their quality.
From Table 1, one can see that knowledge of the average price of the vintage (shown
in the last column) and knowledge of the average chateau price (shown in the last row)
tells much about the price of each wine. For example, by examining the last column of
Table 1 it is clear that 1961 was the best year in this decade and that it was followed by
Table 1
London Auction Prices for Mature Red Bordeaux Wines
Chateaux (Vineyards)
Vintage Lafite Latour 1960
1961*
1962*
1963
1964*
1965
1966*
1967*
1968
1969
Average 494
4,335
889
340
649
190
1,274
374
223
251
1,504 464
5,432
1,064
471
1,114
424
1,537
530
365
319
1,935 Cheval
Blanc
486
3,534
821
1,125
1,260
441
274
1,436 Cos
d?Estournel Montrose Pichon
Lalande 1,170
521
251
315 1,125
456 1,579
281 350 546
213 482
236 410
258
734
243 123
553 84
530 152
649 Notes. Prices are for wines auctioned in 1990 to 1991, and are shown in $US per dozen bottles.
Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 Average
479
4,884
977
406
882
307
1,406
452
294
285 F176 THE ECONOMIC JOURNAL [JUNE 1966, and then 1962 and 1964 in quality (and price). There would be no dispute about
this ranking from wine lovers anywhere in the world. Likewise, in the bottom row the
average prices by chateau indicate that Latour is the most outstanding chateau in the
group. Finding the 1961 Latour entry in the Table, reveals that indeed, this is the best
wine of the decade in this group. In fact, a more advanced statistical analysis reveals that
information on chateau and vintage alone explain over 90% of the variation in the
prices. In short, there is not much room for other factors to play a very big role in price
determination.
A ranking of the chateaux in order of quality based on their prices would be Latour,
Lafite, Cheval Blanc, Pichon-Lalande, Cos d?Estournel, Montrose. In fact, as Edmund
Penning-Rowsell (1985) points out in his classic book The Wines of Bordeaux, the famous
1855 classification of the chateaux of Bordeaux into quality grades was based on a
similar assessment by price alone. Surprisingly, the 1855 classification ranks these
chateaux in only a slightly different order: Lafite, Latour, Pichon-Lalande, Cos
d?Estournel, and Montrose.1 Likewise, a ranking of the quality of the vintages based on
price alone would be 1961, 1966, 1962, 1964, and 1967. The remaining vintages (1960,
1963, 1965, 1968, and 1969) would be ranked inferior to these five, and perhaps
because of this fact, many of the wines from these inferior vintages are no longer sold in
the secondary market.
As is apparent from Table 1, there are two natural dimensions on which to search for
hedonic determinants of wine quality: the vintage and the vineyard. In climatological
terms it is natural to associate the first with ÔweatherÕ variability from year to year and
the second with ÔclimateÕ variability across vineyards. In what follows I focus on the
weather and thus on the factors that determine the nature and quality of the wines
from particular vintages in Bordeaux. However, there is now considerable research on
the climate factors that are the determinants of vineyard quality. Some of the earliest
work dates back to the pioneering viticulturalists Amerine and Winkler (1944), who
mapped the nascent grape growing regions of California. Gladstones (1992) provided a
more nuanced analysis for key Australian vineyards. Econometric analyses using data
from vineyards in France (Combris et al., 1997; Jones and Storchmann, 2001), California (Haeger and Storchmann, 2006) and Germany (Ashenfelter and Storchmann,
2006) all show that heat retention and drainage (to remove excess water when it exists)
are key determinants of vineyardsÕ prices and wine quality. Typically, the cooler sites in
hot regions and the warmer sites in cool regions are the best but the ideal conditions
vary according to the type of grape. 2. Returns to Holding Bordeaux Wine
It is natural to wonder why wines from the same chateau, made by the same winemaker,
and made in the same manner could have such varying prices as indicated by Table 1.
Apparently, there must be some difference generated by the different vintages in which
the wines were made. There are two natural explanations. First, the older wines have
been held longer and this requires a payoff to the investment that has been made in
foregoing the consumption of the wines.
1 Cheval Blanc was not ranked in 1855. Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 2008 ] F177 PREDICTING THE QUALITY ln of price 4.6 2.3
1950 1955 1960
1965
1970
Year of Vintage 1975 1980 Fig. 1. Red Bordeaux Wine Prices, Relative to 1961 Vintage To test this hypothesis I have constructed an index of the price of a portfolio of wines
from each vintage displayed in Figure 1.2 Figure 1 provides a graphical representation
of the results. Since these points represent the average across many cha?teaux in a given
year, the price differences represent differences that are due only to the vintage in
which the wines were produced.
Figure 1 is a scatter diagram of the price of the wines of a vintage against the vintage
year. Examining either the data points or the Ôbest-fit-lineÕ, it is apparent that there is a
negative relationship between the two variables. The slope of the best-fit-line line is
0.035 and, as I have learned from further experimentation, as long as the sample
includes at least 20 vintages, a slope of around 0.03 is invariably obtained. This means
that the older a wine, the greater is its value. However, as can be seen in Figure 1, this
also clearly leaves much variation in average prices across vintages that is unexplained. 3. Vintages and the Weather
It is well known that the quality of any fruit, in general, depends on the weather during
the growing season that produced the fruit. What is not so widely understood is that in
some localities the weather will vary dramatically from one year to the next. In California, for example, it never rains in the summer and it is always warm in the summer.
There is a simple reason for this. In California a high-pressure weather system settles
each summer over the California coast and produces a warm, dry growing season for
the grapes planted there. In Bordeaux this sometimes happens ? but sometimes it does
not. Australia is an intermediate case, where summers are usually dry, though not
always. Summers in Bordeaux can be hot and dry, hot and wet, cool and dry, and, most
unpleasant of all, cool and wet. In general, high quality vintages for Bordeaux wines
2
In the remainder of the article I use an index based on the wines of several chateaux as a measure of the
price. See Ashenfelter, et al. (1995). The chateaux are deliberately selected to represent the most expensive
wines (Lafite, Latour, Margaux, Cheval Blanc) as well as a selection of wines that are less expensive (Ducru
Beaucaillou, Leoville Las Cases, Palmer, Pichon Lalande, Beychevelle, Cos d?Estournel, Giscours, GruaudLarose, and Lynch-Bages). A different selection of chateaux for the portfolio would have very little effect on
the results. Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 F178 [JUNE THE ECONOMIC JOURNAL 0
78
77
14.5 56
63 72 61 62
80
57
67
79 54
74 53
66 70
71 64
73 18.5 55
58 75 52 69 59 Summer
Temperature 76 65
68 60
350 Harvest
Rain Above Average Price
Below Average Price Fig. 2. Bordeaux Summer Temperature and Harvest Rain, 1952?1980 correspond to the years in which August and September are dry, the growing season is
warm, and the previous winter has been wet. Except in places where irrigation is
common to make up for low winter rainfalls, this finding will not surprise winemakers
anywhere in the world.
Figure 2 establishes that it is hot, dry summers that produce the vintages in which the
mature wines obtain the higher prices. This Figure displays for each vintage the summer temperature from low to high as you move from left to right, and the harvest rain
from low to high as you move from top to bottom. Vintages that sell for an above
average price are displayed with dark points, and vintages that sell for a below average
price are displayed with light points.
If the weather is the key determinant of wine quality, then the dark points should
be in the northeast quadrant of the diagram and the light points should be in the
southwest quadrant of the diagram, and the other two quadrants should have a
mixture of dark and light points. It is apparent that this is precisely the case. Even
anomalies, like the 1973 vintage, tend to corroborate the fact that the weather
determines the quality of the wines, because although the wines of this vintage, which
are of somewhat above average quality, have always sold at relatively low prices,
insiders know that they are often bargains (and indeed I have bought and consumed
a lot of them!)
Ideally, the weather?s effect on wine quality and price could be tested with a controlled laboratory experiment. However this is obviously not feasible as there is no way
to control the weather in France (yet!). This inability to create a controlled experiment
leads to the use of so called Ônatural experimentsÕ. A natural experiment is a set of
circumstances that occurs naturally (or at least is external to our control) and exhibits
sufficient variation to identify the causal effects of interest. The case of weather in
Bordeaux presents a very nice natural experiment. The weather differs sufficiently from
year to year and the quality of the grapes is recorded sufficiently (through wine prices)
to measure weather?s true effects on quality.
Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 2008 ] F179 PREDICTING THE QUALITY Table 2
Regressions of Log Wine Price on Climate Variables
Independent variables
Age of vintage
Average temperature over growing
season (April?September)
Rain in August
Rain in the months preceding
the vintage (October?March)
Average temperature in September
R-squared
Root mean squared error (1)
0.0354
? (0.0137) (2) (3) 0.0238
0.6160 (0.0072)
(0.0952) 0.2400
0.6080 (0.0075)
(0.1160) ?
? 0.00386
0.00117 (0.00081)
(0.00048) 0.00380
0.00115 (0.00095)
(0.00051) ?
0.212
0.575 ?
0.828
0.287 0.0077
0.828
0.293 (0.0565) Notes. All regressions are of the (logarithm of) the price of different vintages of a portfolio of Bordeaux
chateau wines on climate variables, using as data the vintages of 1952?80, excluding the 1954 and 1956
vintages, which are now rarely sold; all regressions contain an intercept, which is not reported. Standard
errors are in parentheses. The result of a regression of the prices of the wines on the weather variables is
reported in Table 2.3 Although the weather data are taken from a single station in
Merignac, a part of the Bordeaux region, Lecocq and Visser (2006) have shown that the
weather variability across components of the small Bordeaux region are so similar that
more detailed data add little to the analysis. The results indicate that in a model that
includes four variables, the age of the vintage, the average temperature over the
growing season (April?September), the amount of rain in September and August, and
the amount of rain in the months preceding the vintage (October?March), about 80%
of the variation in the average price of Bordeaux wine vintages is explained. Analysis of
the effects of age alone produces a model that explains only slightly more than 20%,
suggesting that the weather is an extremely important determinant of the quality of a
wine vintage and its price at maturation.
With this model, it is possible to predict the relative price at which the new vintage
should be sold as soon as the growing season is complete. The basic idea for these
predictions is displayed in Figure 3. This Figure adds to Figure 2 the data for the
vintages from 1981?2003 but keeps the axes in the same place, based on the historical
normal rainfall and temperature data.
Two things are immediately apparent from Figure 3. First, all but one of these recent
vintages (1986) was produced by a growing season that was warmer than what is historically ÔnormalÕ. Indeed a test of whether the mean temperature in the later period is
different from the mean temperature in the earlier period strongly rejects equality in
favour of warmer temperatures in the later period. On the other hand, the average
rainfall during the harvest in later period shows no difference from ÔnormalÕ. Indeed,
the prevalence of such warm weather in the summer in the last two decades no doubt
accounts, in part, for the deeply held conviction that many Europeans hold that global
warming is already upon us. This unusual run of extraordinary weather has resulted in
a huge quantity of excellent red Bordeaux wines. Although it is rarely remarked upon
by anyone but economists, global warming creates both winners and losers.
3
All analyses use as data the vintages of 1952?1980, excluding the 1954 and 1956 vintages, which are now
rarely sold. Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 F180 [JUNE THE ECONOMIC JOURNAL Harvest
Rain
85 0
78 62
80 77
14.5 56
63 72
54 57
67
79 75
58 52 03 00 66 53
70
64
81
84 71
73
87 55 83 86
74 61
88 90
89 01
02 82
59 95 91 98 97 19.5
18.5
Summer
Temperature 94
69
65
68 60 76 96 99 93 92 350 1981?2003
Fig. 3. Rainfall and Temperature in Bordeaux: 1952?2003 Second, the weather that created the vintages of 1989, 1990, 2000 and 2003 appears
to be quite exceptional by any standard. Indeed, the question must be asked, is it
appropriate to predict that the wines of these vintages will be of outstanding quality
when the temperature that produced them is so far outside the normal range?
Before making the predictions for 1989 or 1990 I asked the late Lincoln Moses, a
distinguished Stanford statistician, for advice. Moses suggested two informal tests.
(a) Would the last major Ôout of sampleÕ prediction have been correct? The idea
here is to use the past to indirectly test the ability of the relationship to stretch
beyond the available data. In fact, the last major Ôout of sampleÕ prediction for
which all uncertainty had been resolved was the vintage of 1961, which had the
lowest August?September rainfall in Bordeaux history. Just as the unusual
weather predicted, the market (see Table 1), and most wine lovers, have come
to consider this an outstanding vintage.
(b) Was the warmth of the 1989 and 1990 growing seasons in Bordeaux greater than
the normal warmth in other places where similar grapes are grown? The idea
here is to determine whether the temperature in Bordeaux is abnormal by
comparison with grape growing regions that may be even warmer. In fact, the
temperature in 1989 or 1990 in Bordeaux was no higher than the average
temperature in the Barossa Valley of South Australia or the Napa Valley in
California, places where high quality red wines are made from similar grape
types.
Based on these two informal tests, I decided in 1991 to predict that both the 1989 and
1990 vintages in Bordeaux were likely to be outstanding. Ironically, many professional
wine writers did not concur with this prediction at the time. In the years that have
Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 2008 ] PREDICTING THE QUALITY F181 followed minds have been changed; and there is now virtually unanimous agreement
that 1989 and 1990 are two of the outstanding vintages of the last 50 years.
Among current vintages, Figure 3 indicates that the 2000 and 2003 vintages are in a
league similar to the outstanding vintages of 1989 and 1990. And what does the wine
press say about these vintages? It is not hard to find out, as these wines have been
advertised for sale over the last several years using the fantastic praise heaped upon
them. For example, Robert Parker widely considered the most influential taster says,
Ô2000 is the greatest vintage Bordeaux has ever produced. Remarkably consistent from
top to bottom, there has never been a year where so many exceptional wines were
produced.Õ He is no less ecstatic about the 2003 vintage. And yet we learned this without
tasting a single drop of wine.
In recent years the hedonic approach to analysing wine vintages has been applied in
several other areas, including Australia (Ashenfelter and Byron, 1995; Wood and
Anderson, 2006) and Italy (Corsi and Ashenfelter, 2001). Fair (2002) even reports a
series of independent tests of the ex post forecasting ability of the weather model for
Bordeaux, concluding that it provides accurate predictions so long as the purpose is to
drink (as opposed to collect) the wines.
One of the most interesting issues raised by the study of these hedonic models of
vintage quality is the role it implies for expert opinion in the determination of wine
prices. Ian Ayes recent book, Super Crunchers (2007), is an exploration of this topic
using examples from several fields of economics including the study of wine pricing.
Related papers include those by Ashenfelter and Jones (2000) and Ali et al. (2008).
Although it is difficult to summarise the conclusions of this ongoing area of research,
there is evidence that ÔexpertÕ opinion that is unrelated (that is, orthogonal) to the
fundamental determinants of wine quality plays a role in determining wine prices, at
least in the short run. This naturally raises the unresolved question of just what
determines the ÔdemandÕ for expert opinion. 4. Market Inefficiency
Given that the weather plays such a large role in determining the quality and prices of
the mature wines of a vintage, does the market take account of this information when
the young wines are priced? In short, were the relative prices of the vintages when they
were first sold at market good forecasts of the relative prices of the wines when they
matured, and if so, were these forecasts as good as the predictions made using the data
on weather alone?
Table 3 reveals the answer to both of these questions. The entries for each of the
vintages in the Table are index prices of the wines in the market in each calendar year
from 1971 to 1989. The index method used here is to simply put the price of the wine
relative to the Ôbenchmark portfolioÕ listed in column 1 of the Table.4 For example, in
Table 3 an entry of 1.0 would represent a vintage with equal value to the benchmark
portfolio in a given year and an entry of 0.5 would be a vintage with half the value of the
benchmark portfolio. In the bottom row of the Table is listed the predicted relative
4
The benchmark portfolio is the average price of the wines from the 1961, 1962, 1964 and 1966 vintages.
This is done for statistical ease, and these vintages were chosen for their superior quality. Ó The Author(s). Journal compilation Ó Royal Economic Society 2008 F182 [JUNE THE ECONOMIC JOURNAL Table 3
Relative Prices per Case of Wines from a Portfolio of Bordeaux Chateaux
Vintage
Year of Sale Benchmark
Portfolio* 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1971
£54
1972
£97
1973
£119
1974
£85
1975
£76
1976
£109
1977
£165
1978
£215
1979
£274
1981
£296
1982
£420
1983
£586
1985
£952
1986
£888
1987
£901
1988
£854
1989
£1,048
Predicted Price** 1.68
1.58
1.62
1.31
1.65
1.67
1.67
1.67
1.61
1.75
1.80
1.77
2.19
2.10
2.11
2.01
2.09
1.74 0.79
0.76
0.71
0.77
0.77
0.83
0.83
0.76
0.73
0.62
0.71
0.53
0.53
0.56
0.56
0.56
0.61
0.72 0.41
0.26
0.28
0.39
0.29
0.30
0.26
0.26
0.20
0.22
0.15
0.10
0.12
0.25
0.21
0.28
0.29 0.76
0.70
0.74
0.84
0.78
0.66
0.63
0.65
0.66
0.70
0.60
0.59
0.50
0.54
0.53
0.61
0.53
0.76 0.27
0.24
0.35
0.29
0.26
0.18
0.23
0.04
0.18
0.18
0.21
0.17
0.14
0.19
0.16 0.79
0.96
0.93
1.08
0.60
0.65
0.87
0.91
1.00
0.93
0.89
1.11
0.78
0.80
0.80
0.82
0.7…