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Quantity vs. Quality: An Analysis of Wine
Export Strategies into the U.S. Market
Guenter Schamel
Guenter Schamel [email protected] Free University of Bozen–Bolzano School of Economics and Management Via Sernesi 1, I-39100 Bozen–Bolzano, Italy
January 2010
Paper for the pre-AARES conference workshop on The World’s Wine Markets by 2030: Terroir, Climate Change, R&D and Globalization, Adelaide Convention Centre, Adelaide, South Australia, 7-9 February 2010.
Quantity vs. Quality:
An Analysis of Wine Export Strategies into the U.S. Market
Abstract:
The six largest wine exporters to the US are Italy, Australia, France, Argentina, Chile, and Spain which cover 87% of all wine exports by volume and 88% by value. Each of these countries follows quite different paths in terms of export volumes vs. export values for the ten years 1999-2008. French exports to the US for example have hardly moved in terms of quantity (+1%) during these years but they managed a 5% growth p.a. in terms of export value. In contrast, Australian exports to the US have increased by 20% p.a. in terms of volume but only by 16% p.a. in terms of value. Italian exports to the US have increased by 6% in terms of volume and by more than 10% in terms of value. In this paper, we attempt to analyze and interpret these macro trends using micro-level price-quality relations on an exporting country by country basis. For this purpose, we estimate separate hedonic regressions to determine the impact of quality indicators on consumer willingness to pay. Our analysis suggests that relative to Italy and France, Australian wine achieves a lower quality premium and a higher discount for labels exported in large quantities. This illustrates that the tremendous growth rates in Australian exports to the US has created a generic reputation problem for the country. On the other hand, the high quality wines from Australia struggle to find their market in the U.S. because consumers are not familiar with them and thus will only pay a lower quality premium relative to their European competitors. While rapid export growth has made Australian wine a household name in the US, it also has made it more difficult for high quality producers to differentiate themselves from high volume export brands.
Key Words: wine exports, reputation.
Guenter Schamel Free University of Bozen–Bolzano School of Economics and Management Via Sernesi 1, I-39100 Bozen–Bolzano, Italy E-mail: [email protected]
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1. Introduction
In this paper, we analyze recent price trends in the US wine market which is widely
regarded as the most important international export market for wine. Italy, Australia, France,
Argentina, Chile, and Spain are the six largest wine importers in the US market. In the year
2008, they together accounted for around 87% of all wine imports in the US by volume and of
about 88% by value. Other importers in the US are Germany, New Zealand, South Africa, and
Portugal with market shares between 1% and 3.5%. During the ten years between 1999 and
2008, each of the six major players followed quite different paths in terms of import volume vs.
import value (as shown in Tables 1a/b and Figures 1a/b). France for example exported more or
less the same quantity to the US over these years but it managed a 4.5% average growth rate p.a.
in terms of export value. In contrast to France, Italy’s exports to the US have both increased in
terms of volume (+6%) and in terms value (+10%). Australian exports to the US during these
years have increased on average by more than 20% p.a. in volume terms and by an average of
16% p.a. in value terms. Argentina is a rising star on the US market and has now a volume share
of more than 9% and a value share of around 4 percent with growth rates around 28% p.a. on
average in both volume and value terms. It has recently surpassed Chile in terms of export
volume. In 2008 Chile had US wine market shares of about 8% and 5%, respectively, in volume
and value terms. Spanish exports to the US are also growing rapidly at 9% on average in volume
and close to 11% in value terms. Finally, Germany and New Zealand both have market shares
around 3 percent in value terms and are also growing rapidly in value terms (17% and 33%,
respectively). In this paper, we attempt to analyze and interpret these macro trends using micro-
level price-quality relations for the six largest exporters into the US market.
Another way to look at U.S. import data is to calculate the difference between the volume
and value market shares of the six large importers to the US market (as shown in Figure 1c).
France imports high-quality high-priced wines into the US such that the difference between the
volume and value share is strongly negative ranging between –15% and –21%. Except Spain, all
other major importers have a larger volume share. For Australia and less so for Argentina, the
difference between volume and value share is rising in recent years. Australia in particular
achieved very high growth rates in terms of volume especially between 2001 and 2006 through
lower priced wines widening the gap between its volume and value share of total imports into the
US. Since high priced wines are inextricably linked to high quality, we post the hypothesis that
the reputation of Australian wine for quality is declining, i.e. that American consumers are
willing to pay less for quality of Australian relative to other wine origins. A similar hypothesis
may be posted for Argentina which lags Australia in terms of market penetration in the US. Italy
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on the other hand, seems to replace most of its lower priced imports strengthening its reputation
for quality wines in the US.
In order to support these assertions, we estimate both a full (unrestricted) hedonic model
of the US wine market as well as several restricted models to determine the impact of important
quality indicators on consumer willingness to pay on a country by country basis. Moreover, we
analyze two distinct market segments (above and below $17) in order to differentiate higher and
lower priced wines. Our analysis suggests that relative to Italy and France, Australian wine
achieves a much lower quality premium in particular within the higher price segment above $17,
a relatively high discount for labels exported in large quantities and a relatively low age
premium. Moreover, also in the lower price segment the Australian quality premium is lower
than that of Chile and Spain. This illustrates that the tremendous growth rates in Australian
exports to the US has created a generic reputation problem for the country. High quality wines
from Australia struggle to find their market in the U.S. because consumers are not familiar with
them and thus will only pay a lower quality premium relative to their competitors.
2. Literature
The fact that the global wine market has witnessed major changes in recent years is well
documented. New market entrants have increased their exports not only to traditional European
markets but to other importing regions as well, whereas Old World producers have experienced
declining market shares at least in volume terms. Anderson and Berger (1999) review the
developments in international wine market during the 1990s and conclude that Australia as the
leader in New World wine exports had lower growth rates that wine exports from other Southern
Hemisphere countries (including Argentina, Chile, and New Zealand) and did only moderately
well in North America. Moreover, they assert that in terms of quality of exports as reflected in
average export prices, Australia and New Zealand hugely improved their positions to rival the
quality dominance of France. In order to gain export prevalence, the Australian grape and wine
industry has invested heavily in research and promotion efforts. Domestic producers receive
most of the gains from such R&D and they also get a far larger share of the benefit from export
promotions relative to domestic promotions (Zhao, Anderson and Wittwer, 2003).
Labys and Cohen employ econometric methods to analyze the recent major shifts in
world wine market shares and explain whether these are more of a secular trend-setting nature or
of a temporary cyclical nature. They estimate comparative advantage indices which reveal that
the old countries, particularly France, have a strong advantage in exporting sparkling wine.
Australia and Chile have a comparative advantage in exporting bottled and bulk wine while
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South Africa may have an advantage for bulk wine only. A number of previous empirical studies
provide evidence that the wine market is differentiated into multiple segments (Costanigro,
McCluskey and Mittelhammer, 2007; Fogarty, 2006; Gallet, 2007) while studies of alcoholic
beverage demand have been aimed at determining the effects of price on consumption (Nelson,
1997; Nelson and Moran, 1995).
3. Data and Model
Our data covers six vintages (1999 − 2004) of wines above $5 with expert quality ratings
by “The Wine Spectator” being sold in the US market (total sample size: 54220 observations).
On a continuing basis, the magazine publishes sensory wine quality ratings along with release
prices, special expert designations (e.g. value selection BB, etc.) as well as production and/or
import data for premium wines sold in the US. Rabobank (2003) has divided the global wine
market into six segments according to specific price points of which the basic category with
prices below $5 is excluded from our data set and analysis. To ease of the expose of our results,
we grouped the remaining five segments into two larger groups with the lower priced wines
below $17 comprised of the popular premium, premium and super premium segments and the
higher priced wines above $17 comprised of the ultra premium and icon segments.
First, we estimate a full model including 24 major wine regions present in the US market.
Subsequently, we estimate separate restricted models to determine willingness to pay impacts on
a per country basis given that consumers have already made their region of origin decision, i.e.
whether to buy a specific foreign or domestic wine. Moreover, we analyze the market segments
above and below $17 in order to differentiate the effects on higher and lower priced wines. This
allows us to test whether and how quality reputation varies according to price. As explanatory
variables, we include sensory quality ratings based on the 100-point scale (WSP), the number of
cases produced or imported (Cases) to account for any quantity effects due to scarcity or
abundance and the age of the wine at time of sensory expert evaluation (Age). Further control
variables are expert value selections (BB), an indicator for specialty wines (Spec) as well as
categorical dummies for 16 varieties (Var) and 24 regions or countries (Reg).
We use a mixed log-linear functional form to estimate both the full model as well as the
restricted models. Similar models have been used in several papers employing data from Wine
Spectator including Ramirez (2008), Gokcekusa and Fargnoli (2007). Thus, the principal
characterization of the full model estimated in Table 2 is as follows:
log(P) = α + β log(WSP) + γ log(Cases) + δ Age + ω BB + μ Spec + ηj Var + θk Reg + ε
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where log(P) is the logarithm of the suggested release price in US$. Given the functional form,
this equation, β measures the price elasticity for the quality rating and referred to as the quality
premium while γ is an elasticity of product scarcity or abundance subsequently referred to as the
quantity discount. The δ coefficient is the age premium indicating the percentage premium paid
for older and maturing wine. Coefficients μ and ω are percentage premiums/discounts for
specialty wines and any expert value selection while η and θ measure percentage price effects for
regional origin and variety, respectively. Estimating the equation above yields implicit prices for
quality attributes relative to the contribution of the base control variable.
The restricted regional models for Australia, Italy, France, Spain, Argentina and Chile
presented in Tables 3–8 are all similar to the full model presented above, but may include
additional dummies to measure specific country.1
4. Results and Discussion
The results of the unrestricted full model are presented in Table 2 in the full sample
column. The coefficients ω, μ, ηj and θk for expert value selections, specialty wines, variety and
region are presented for completeness but not further discussed. In our subsequent discussion of
the full model we focus on the quality premium, quantity discount and the age premium. In the
full unrestricted model, the quality premium is equal to 4.65, i.e. a 1% increase in the quality
rating would result in a 4.65% increase in price other things equal. For the restricted full models
with prices P<17 and P≥17, this elasticity is 1.39 and 3.98 respectively. Thus, the quality
premium that consumers are willing to pay is almost 3 times larger for higher priced wines
assuming that consumers have not already made their region of origin decision, i.e. whether to
buy a specific foreign or domestic wine. Comparable results can be found for the quantity
discount and the age premium in the full model, which are both around 2.5 times larger for
higher priced wines.
Next, we present the results of restricted models for the six largest importers in the US
market. The regression coefficients may be interpreted as premiums or discounts given that
consumers have a priory made their region of origin buying decision, i.e. to buy a wine from
Italy, Australia, France, Argentina, Chile, or Spain. In Figures 2a/b/c, we present a graphical
analysis of the restricted model estimates discussed next.
1 Dummy variables affect the interpretation of the constant (intercept) term but allow for comparisons of other ordinal independent variables.
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The results for the restricted Australian model are presented in Table 3. The quality
premium estimated for the full Australian sample is 4.19, i.e. the percentage premium paid for
Australian wine in response to a 1% increase in the quality rating is 0.46% lower relative to the
unrestricted full model. Moreover, this quality premium is the lowest for Australia compared to
other large importers (comparisons are shown in Figure 2a). Only for lower priced Australian
wines (P<17), the quality premium is not the lowest, reinforcing its value for money reputation
especially relative to Italy and France. The elasticity of product scarcity or abundance or the
quantity discount for the full Australian sample is –0.14 and almost identical to the result for the
unrestricted full model. In comparison, Argentina and Spain fare worse while Chile and Italy do
better (comparisons are shown in Figure 2b). Differentiating between price segments, low priced
wines from Australia do better as they command the lowest quantity discount reinforcing its
value for money reputation while high priced wines do worse especially relative to Italy and
Chile. When it comes to the age premium, the results are more difficult to compare
internationally as the Australian tax system discourages domestic storage such that wines are
sold at a relatively young age. While this may skew the results, the estimated age premium for
Australian wine is also the lowest compared to other importers in the US market (comparisons
are shown in Figure 2c).
It is also very interesting to look at the regional and varietal coefficients in the Australian
model. For lower priced wines, there is hardly any differentiation with respect to varietals and
regions (most coefficients in the P<17 column in Table 3 are red). However, with exceptions for
France, Argentina, and Spain, this is also true for other countries. However, some regional
differentiation is starting to emerge in the lower priced Australian sample, with significant
discounts (–13% to –27%) for the generic appellations (Australia, New South Wales South
Eastern Australia, South Australia) and significant positive premiums for the Adelaide Hills,
Orange and Margaret River. In contrast, there is considerably more differentiation in the higher
priced sample (much less coefficients in the P≥17 column in Table 3 are red) with significant
varietal and regional discounts. However, the overall picture of Australian regional
differentiation is confusing as some of the generic appellations are insignificant relative to a
Barossa Valley Shiraz. This result seems to support the conclusion that high quality producers
have difficulties to differentiate themselves from high volume export brands.
Finally, we examine the regional and varietal coefficients for the other major importers in
the US (Tables 4-8). Italy exhibits very significant regional differentiation for higher priced
wines explaining much of its success gaining US market share in terms of import value relative
to volume (Figure 1c). Similar conclusions can be drawn from the French results. Thus, it is safe
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to claim that the overall picture of French and Italian regional differentiation is much less
confusing to consumers at least relative to Australia. Spain shows a considerable regional and
varietal differentiation for lower priced wines potentially explaining its balanced growth in terms
of import volume and value (Figures 1a/b/c). Argentina exhibits some regional differentiation for
both lower and higher priced wines but the picture is also somewhat confusing with a significant
generic appellation (Argentina relative to Mendoza). Chile also reveals a considerable regional
differentiation for lower priced wine and emerging regional differences for higher priced wines
also explaining its relatively balanced growth in terms of import volume vs. value (Figures 1c).
In conclusion, our analysis suggests that especially relative to Italy and France,
Australian wine exported to the US obtains a lower quality premium and a higher discount for
labels exported in large quantities. This reinforces the conclusion that the tremendous growth
rates in Australian exports to the US created a generic reputation problem for the country. On the
one hand, lower priced Australian wines are considered a value for money bargain by American
consumers while on the other hand high quality wines struggle to find their market in the U.S.
because consumers are not familiar with the overall picture of regional and varietal
differentiation and thus will only pay a lower quality premium relative to their European
competitors. Rapid export growth has made Australian wine a household name in the US, but it
has also made it more difficult for high quality producers to differentiate themselves from high
volume export brands.
Literature:
Anderson, K and Berger, N. (1999) Australia’s Re-Emergence as a Wine Exporter: The First Decade in International Perspective, CIES Wine Policy Brief No 5, October 1999.
Costanigro, M., McCluskey, J.J. and Mittelhammer, R.C. (2007) Segmenting the wine market based on price: hedonic regression when different prices mean different products. Journal of Agricultural Economics, 58, 454–466.
Fogarty, J.J. (2008). The demand for beer, wine, and spirits: insights from a meta-analysis approach. American Association of Wine Economists, Working Paper No. 31.
Gallet, G.C. (2007). The demand for alcohol: a meta-analysis of elasticities. Australian Journal of Agricultural and Resource Economics, 51(2), 121–135.
Gokcekus, O. and Fargnoli, A. (2007). Is globalization good for wine drinkers in the United States? Journal of Wine Economics, 2(2), 187–195.
Labys, W.C. and B.C. Cohen, (2006). Trends versus Cycles in Global Wine Export Shares. Australian Journal of Agricultural and Resource Economics (50):527-537).
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Nelson, J.P. (1997). Economic and demographic factors in U.S. alcohol demand: a growth-accounting analysis. Empirical Economics, 22, 83–102.
Nelson, J.P. and Moran, J.R. (1995). Advertising and U.S. alcoholic beverage demand: system-wide estimates. Applied Economics, 65, 1225–1236.
Rabobank (2003). Wine is business, shifting demand and distribution: major drivers reshaping the wine industry, Food & Agribusiness Research, Utrecht, Rabobank International, 2003.
Ramirez, C. (2008). Wine quality, wine prices, and the weather: is Napa “different”? Journal of Wine Economics, 3(2), 114–131.
Zhao, X., Anderson, K. and Wittwer, G. (2003), ‘Who gains from Australian generic wine pro-motion and R&D’, Australian Journal of Agricultural and Resource Economics 47(2): 181-209.
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Table 1a: Import Volume: US Market Share and Growth
Growth Average Annual Market Share (hl) 1999 vs. 2008 Growth Rate Country 1999 2007 2008
60% 5.6% Italy 35.2% 29.5% 28.3% 368% 20.2% Australia 9.6% 23.4% 22.5%
4% 0.9% France 24.8% 14.6% 13.0% 756% 28.6% Argentina 2.2% 7.6% 9.2% 49% 4.8% Chile 10.4% 6.9% 7.8% 109% 9.0% Spain 5.7% 5.8% 6.0% 168% 12.0% Germany 2.5% 3.6% 3.4% 928% 31.6% New Zealand 0.4% 2.3% 2.3% 739% 27.7% South Africa 0.5% 1.2% 1.9% 34% 3.5% Portugal 1.9% 1.3% 1.3% 30% 5.4% Rest of World 6.9% 3.9% 4.5% 99% 8.1% Total Imports 100% 100% 100%
Source: www.fas.usda.gov Table 1b: Import Value: US Market Share and Growth
Growth Average Annual Importing Market Share (US$) 1999 vs. 2008 Growth Rate Country 1999 2007 2008
140% 10.4% Italy 24.7% 27.6% 28.1% 241% 15.9% Australia 9.2% 17.0% 14.9% 40% 4.5% France 45.6% 30.8% 30.4% 746% 28.1% Argentina 1.0% 2.8% 3.9% 92% 7.8% Chile 5.3% 4.4% 4.8% 139% 10.6% Spain 5.4% 5.8% 6.1% 286% 16.8% Germany 1.7% 3.1% 3.2% 1101% 33.1% New Zealand 0.5% 3.1% 3.1% 435% 22.0% South Africa 0.4% 0.9% 1.0% 18% 2.7% Portugal 2.6% 1.5% 1.5% 73% 7.0% Rest of World 3.6% 2.8% 2.9% 111% 8.8% Total Imports 100% 100% 100%
Source: www.fas.usda.gov
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Figure 1a: US Market Shares by Import Volume
Italy
Australia
France
Argentina
Chile
Spain
Rest of World
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Italy Australia France Argentina Chile SpainGermany New Zealand South Africa Portugal Rest of World
Ger- many
NZ
Figure 1b: US Market Shares by Import Value
25%
26%
27%
28%
28%
28%
28%
28%
28%
28%
9%
12%
15%
17%
19%
21%
20%
18%
17%
15%
46%
40%
35%
33%
34%
30%
29%
31%
31%
30%
5.3%
5.9%
5.9%
5.0%
4.2%
4.3%
4.3%
4.0%
4.4%
4.8%
5.4%
4.7%
4.8%
4.9%
4.8%
5.4%
5.6%
5.7%
5.8%
6.1%3.9%
2.8%
3.2%
3.1%
3.1%
3.1%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Italy Australia France Argentina Chile SpainGermany New Zealand South Africa Portugal Rest of World
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Figure 1c: US Wine Imports (Volume−Value Share)
ItalyAustralia
France
ArgentinaChile
Spain
-21%
-18%
-15%
-12%
-9%
-6%
-3%
0%
3%
6%
9%
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
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Table 2: All Major Regions Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -16.50 -90.10 0 -3.265 -17.72 0 -13.52 -63.93 0log(WSP) 4.653 114.6 0 1.394 33.91 0 3.985 84.88 0log(Cases) -0.138 -103.9 0 -0.047 -39.37 0 -0.112 -66.70 0Age 0.184 69.34 0 0.060 23.75 0 0.144 45.92 0BB -0.273 -18.14 0 -0.106 -12.80 0 -0.338 -10.90 0Spec 0.795 35.01 0 -0.833 -4.16 0 0.774 34.55 0CabBlend 0.014 1.14 0.26 0.042 3.35 0 -0.007 -0.52 0.61Chardonnay -0.141 -14.07 0 -0.005 -0.64 0.52 -0.188 -15.90 0Merlot -0.115 -9.71 0 -0.024 -2.47 0.01 -0.146 -10.40 0OtherRed -0.202 -18.00 0 0.005 0.53 0.60 -0.245 -18.15 0OtherWhite -0.257 -19.13 0 0.001 0.13 0.90 -0.298 -17.26 0PinotGris -0.149 -8.47 0 0.067 5.10 0 -0.185 -7.81 0PinotNoir 0.052 4.72 0 0.048 3.81 0 -0.030 -2.42 0.02RedBlend -0.158 -14.38 0 0.014 1.40 0.16 -0.193 -15.08 0Riesling -0.281 -16.39 0 -0.060 -4.74 0 -0.284 -12.31 0Sangiovese -0.274 -17.94 0 0.010 0.61 0.54 -0.312 -18.56 0SauvBlanc -0.256 -19.74 0 -0.014 -1.41 0.16 -0.293 -16.45 0Shiraz -0.072 -7.05 0 0.003 0.29 0.77 -0.131 -11.27 0Viognier -0.116 -5.50 0 0.068 3.48 0 -0.217 -9.13 0WhiteBlend -0.198 -13.92 0 -0.021 -1.94 0.05 -0.218 -12.15 0Zinfandel -0.212 -14.88 0 0.021 1.34 0.18 -0.292 -18.86 0Argentina -0.542 -34.74 0 -0.259 -16.36 0 -0.290 -12.87 0Australia -0.468 -44.95 0 -0.167 -11.47 0 -0.373 -32.37 0Chile -0.581 -43.21 0 -0.253 -17.11 0 -0.372 -16.58 0New Zealand -0.391 -27.44 0 -0.007 -0.44 0.66 -0.376 -22.95 0Bay Central Coast -0.282 -16.31 0 -0.083 -3.98 0 -0.226 -12.18 0Carneros -0.170 -9.03 0 0.074 1.47 0.14 -0.194 -10.32 0Oregon -0.493 -35.94 0 -0.185 -10.29 0 -0.396 -26.84 0Rest North America -0.578 -39.26 0 -0.156 -9.76 0 -0.484 -25.80 0Rest California -0.458 -36.52 0 -0.174 -11.90 0 -0.301 -18.49 0Sonoma -0.223 -20.36 0 0.025 1.45 0.15 -0.213 -18.87 0South Coast -0.355 -26.61 0 -0.034 -1.69 0.09 -0.333 -24.10 0Washington -0.564 -46.90 0 -0.247 -15.56 0 -0.479 -36.64 0Bordeaux -0.176 -11.73 0 -0.129 -6.27 0 -0.109 -6.89 0Burgundy -0.079 -6.76 0 -0.066 -3.44 0 -0.014 -1.13 0.26Languedoc-Rouss -0.771 -49.45 0 -0.314 -20.22 0 -0.557 -22.18 0Rest France -0.409 -31.19 0 -0.133 -8.55 0 -0.316 -19.67 0Rhone -0.129 -10.06 0 -0.154 -9.17 0 -0.005 -0.32 0.75Northern Italy -0.404 -29.87 0 -0.114 -7.12 0 -0.345 -22.02 0Piedmont -0.101 -7.86 0 -0.037 -2.19 0.03 -0.013 -0.88 0.38Tuscany -0.058 -4.08 0 -0.044 -2.35 0.02 -0.034 -2.25 0.02Rest Italy -0.299 -21.06 0 -0.163 -10.32 0 -0.127 -7.28 0Spain -0.408 -29.81 0 -0.235 -15.14 0 -0.160 -9.29 0Germany -0.352 -18.05 0 -0.066 -3.31 0 -0.298 -12.13 0Adj. R2 / F-Ratio 62.99 1988 36.36 185.2 45.30 702.4 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Napa Valley Cabernet Sauvignon; Source: Own Calculation
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Table 3: Australia Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -14.64 -20.25 0 -4.283 -5.59 0 -12.45 -14.52 0Log(WSP) 4.187 26.10 0 1.593 9.26 0 3.715 19.55 0Log(Cases) -0.138 -34.81 0 -0.034 -9.77 0 -0.128 -23.32 0Age 0.124 15.55 0 0.046 6.17 0 0.094 9.51 0BB -0.185 -5.52 0 -0.093 -5.12 0 -0.286 -3.34 0CabBlend -0.071 -2.78 0.01 -0.012 -0.59 0.55 -0.036 -1.12 0.26CabSauv -0.064 -3.08 0 0.012 0.64 0.52 -0.081 -3.23 0Chardonnay -0.170 -8.66 0 -0.010 -0.69 0.49 -0.179 -6.00 0Merlot -0.154 -4.06 0 -0.026 -1.15 0.25 -0.099 -1.49 0.14OtherRed -0.155 -4.68 0 0.023 0.58 0.56 -0.167 -4.50 0OtherWhite -0.322 -8.05 0 0.029 1.02 0.31 -0.394 -6.63 0PinotGris -0.304 -2.58 0.01 0.168 1.28 0.20 -0.390 -2.90 0PinotNoir 0.057 1.41 0.16 0.085 2.12 0.03 0.027 0.55 0.58RedBlend -0.188 -5.81 0 -0.021 -0.66 0.51 -0.183 -4.83 0Riesling -0.378 -9.92 0 -0.031 -1.05 0.29 -0.402 -7.78 0SauvBlanc -0.259 -5.97 0 -0.026 -0.95 0.34 -0.201 -2.64 0.01Viognier -0.337 -4.26 0 -0.117 -1.26 0.21 -0.436 -4.84 0WhiteBlend -0.272 -7.29 0 -0.058 -2.66 0.01 -0.282 -3.78 0McLarenVale 0.006 0.30 0.76 -0.035 -1.37 0.17 -0.005 -0.22 0.82SouthEasternAustr -0.319 -11.87 0 -0.275 -13.04 0 -0.100 -1.57 0.12SouthAustralia -0.209 -7.97 0 -0.129 -6.03 0 0.026 0.66 0.51Victoria -0.202 -6.72 0 -0.062 -2.38 0.02 -0.095 -2.43 0.01ClareValley -0.253 -8.29 0 -0.020 -0.66 0.51 -0.248 -6.85 0MargaretRiver -0.083 -2.67 0.01 0.052 1.68 0.09 -0.097 -2.58 0.01AdelaideHills -0.133 -3.87 0 0.090 2.71 0.01 -0.156 -3.71 0WesternAustralia -0.191 -5.52 0 0.011 0.43 0.67 -0.158 -3.18 0Coonawarra -0.114 -3.17 0 -0.054 -1.36 0.17 -0.105 -2.58 0.01YarraValley -0.165 -4.00 0 0.041 0.95 0.34 -0.168 -3.43 0HunterValley -0.112 -2.84 0 -0.047 -1.51 0.13 -0.043 -0.83 0.41LanghorneCreek -0.179 -4.23 0 -0.014 -0.30 0.77 -0.184 -3.83 0EdenValley -0.060 -1.21 0.23 -0.039 -0.67 0.50 -0.030 -0.52 0.60Heathcote 0.097 2.13 0.03 0.028 0.38 0.71 0.069 1.39 0.16LimestoneCoast -0.246 -4.86 0 0.041 1.01 0.31 -0.228 -3.41 0MorningtonPeninsu -0.142 -2.47 0.01 -0.124 -1.23 0.22 -0.155 -2.44 0.01NewSouthWales -0.281 -5.11 0 -0.191 -5.15 0 -0.089 -1.03 0.30Australia -0.311 -5.16 0 -0.211 -5.90 0 -0.171 -1.28 0.20Padthaway 0.121 2.11 0.03 0.076 1.19 0.23 0.124 1.90 0.06Bendigo -0.337 -5.06 0 0.034 0.64 0.52 -0.368 -4.21 0Tasmania -0.038 -0.49 0.62 0.085 0.99 0.32 -0.037 -0.43 0.67Pyrenees 0.150 1.99 0.05 0.023 0.18 0.86 0.130 1.61 0.11Mudgee -0.140 -1.78 0.07 0.066 0.92 0.36 -0.180 -1.89 0.06Orange -0.154 -1.97 0.05 0.137 2.05 0.04 -0.206 -2.12 0.03Adj. R2 / F-Ratio 65.10 194.0 0 55.05 45.38 0 39.38 44.68 0 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Barossa Valley Shiraz; Source: Own Calculation
14
Table 4: Italy Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -18.38 -41.47 0 -1.308 -3.39 0 -15.87 -30.2 0log(WSP) 4.946 49.97 0 0.948 10.9 0 4.367 37.2 0log(Cases) -0.102 -30.67 0 -0.046 -17.9 0 -0.063 -15.4 0Age 0.183 31.29 0 0.039 6.92 0 0.127 19.3 0BB -0.433 -10.89 0 -0.127 -5.99 0 -0.458 -6.09 0Spec 0.401 10.56 0 -0.780 -4.40 0 0.335 8.86 0CabBlend 0.325 12.94 0 0.038 0.95 0.34 0.302 12.1 0CabSauv 0.177 4.61 0 -0.160 -3.91 0 0.225 5.65 0Chardonnay -0.013 -0.48 0.63 -0.066 -3.14 0 0.017 0.57 0.57Merlot 0.228 7.72 0 -0.113 -4.01 0 0.319 10.0 0OtherRed -0.016 -0.73 0.47 0.027 1.44 0.15 -0.035 -1.45 0.15OtherWhite 0.009 0.42 0.67 0.003 0.20 0.84 -0.029 -1.09 0.27PinotGris 0.090 2.89 0 0.008 0.35 0.73 0.016 0.39 0.69PinotNoir 0.124 2.08 0.04 -0.134 -1.50 0.13 0.115 1.96 0.05RedBlend 0.146 6.98 0 -0.016 -0.85 0.40 0.177 7.80 0SauvBlanc 0.038 1.12 0.26 -0.017 -0.59 0.55 -0.004 -0.10 0.92Shiraz 0.132 3.02 0 -0.001 -0.02 0.98 0.159 3.53 0WhiteBlend -0.004 -0.17 0.86 -0.043 -2.37 0.02 0.026 0.91 0.36Zinfandel -0.132 -2.50 0.01 -0.014 -0.42 0.67 -0.188 -2.37 0.02Chianti -0.135 -8.82 0 0.017 1.24 0.21 -0.156 -9.29 0Brunello 0.158 5.11 0 0.259 8.39 0Barbera -0.006 -0.29 0.77 -0.030 -1.61 0.11 -0.023 -1.00 0.32Barolo 0.345 14.14 0 0.129 2.16 0.03 0.380 14.7 0Barbaresco 0.414 14.71 0 0.383 13.5 0Northern Italy -0.322 -17.41 0 -0.022 -1.35 0.18 -0.236 -11.0 0Piedmont -0.143 -7.26 0 0.005 0.29 0.77 -0.077 -3.53 0Rest Italy -0.255 -14.11 0 -0.102 -6.77 0 -0.083 -3.91 0Adj. R2 / F-Ratio 64.77 657.2 29.98 45.43 54.76 313.4 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Tuscany Sangiovese; Source: Own Calculation
15
Table 5: France Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -15.24 -38.6 0 -1.232 -3.46 0 -14.54 -31.8 0log(WSP) 4.372 49.9 0 0.903 11.3 0 4.229 41.7 0log(Cases) -0.137 -40.1 0 -0.037 -13.3 0 -0.123 -28.7 0Age 0.146 18.1 0 0.064 10.6 0 0.104 10.4 0BB -0.261 -5.46 0 -0.121 -5.44 0 -0.351 -3.43 0FirstGrowth 1.555 12.9 0 1.534 12.6 0Vin de Pays -0.199 -6.95 0 -0.120 -7.95 0 0.008 0.15 0.88CabBlend -0.339 -6.59 0 0.082 2.41 0.02 -0.265 -3.20 0CabSauv -0.269 -4.16 0 -0.065 -1.89 0.06 -0.340 -1.76 0.08Chardonnay -0.088 -5.09 0 -0.034 -1.27 0.20 -0.054 -2.91 0Merlot -0.149 -2.33 0.02 -0.077 -2.28 0.02 0.285 1.14 0.25OtherRed -0.225 -4.61 0 0.111 3.43 0 -0.325 -4.00 0OtherWhite -0.295 -6.49 0 -0.032 -1.02 0.31 -0.206 -2.86 0PinotGris -0.123 -2.08 0.04 0.116 2.36 0.02 -0.086 -1.04 0.30RedBlend -0.344 -8.06 0 0.006 0.22 0.83 -0.246 -3.28 0Riesling -0.267 -4.74 0 0.033 0.74 0.46 -0.223 -2.78 0.01SauvBlanc -0.115 -2.39 0.02 -0.055 -1.67 0.10 -0.020 -0.26 0.79Shiraz 0.011 0.25 0.80 0.052 1.65 0.10 0.031 0.40 0.69Viognier 0.273 4.78 0 0.126 2.92 0 0.268 3.04 0WhiteBlend -0.204 -4.60 0 -0.016 -0.52 0.60 -0.117 -1.56 0.12Bordeaux -0.188 -3.42 0 -0.127 -4.00 0 -0.120 -1.36 0.17Lang_Rous -0.515 -11.5 0 -0.184 -7.20 0 -0.453 -5.83 0Rhone -0.165 -3.78 0 -0.099 -3.89 0 -0.143 -1.88 0.06Alsace -0.174 -3.63 0 0.006 0.18 0.86 -0.219 -2.98 0RoFRA -0.461 -11.2 0 -0.114 -4.72 0 -0.439 -6.39 0Beaujolais -0.032 -0.53 0.60 -0.215 -8.32 0 0.088 0.26 0.79Côte_Rôtie 0.507 11.8 0 0.433 9.74 0Châteauneuf 0.589 24.3 0 0.078 0.42 0.68 0.397 14.1 0Meursault 0.105 3.44 0 0.036 1.16 0.25Gevrey Chambertin 0.093 2.64 0.01 0.075 2.10 0.04Chablis -0.033 -1.23 0.22 0.107 2.72 0.01 -0.115 -3.98 0Sancerre 0.208 4.33 0 0.323 7.42 0 0.048 0.79 0.43Pessac_Léognan 0.387 8.44 0 0.082 1.57 0.12 0.250 4.71 0St_Estèphe 0.413 7.07 0 0.122 1.28 0.20 0.231 3.62 0St_Julien 0.631 10.3 0 -0.080 -0.42 0.67 0.434 6.58 0Pomerol 0.768 18.9 0 0.065 0.48 0.63 0.589 12.7 0Pauillac 0.677 12.5 0 0.113 0.60 0.55 0.475 8.10 0St_Emilion 0.517 11.0 0 0.059 1.42 0.16 0.372 5.86 0Margaux 0.425 9.11 0 0.049 0.52 0.61 0.243 4.66 0Adj. R2 / F-Ratio 63.97 514.5 42.68 55.92 45.03 182.1 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Burgundy Pinot Noir; Source: Own Calculation
16
Table 6: Spain Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -22.31 -17.6 0 -5.249 -5.83 0 -17.96 -9.11 0log(WSP) 5.906 21.1 0 1.781 8.79 0 5.051 11.6 0log(Cases) -0.158 -22.8 0 -0.037 -7.50 0 -0.165 -14.7 0Age 0.128 10.3 0 0.065 7.96 0 0.068 3.30 0BB -0.385 -5.14 0 -0.137 -3.44 0 -0.444 -2.67 0.01VinodelaTerra 0.056 0.84 0.40 -0.129 -3.19 0 0.078 0.71 0.48CabBlend 0.295 3.36 0 0.156 2.91 0 0.148 1.02 0.31CabSauv 0.076 0.80 0.42 0.158 3.02 0 -0.300 -1.63 0.10Chardonnay 0.240 3.02 0 0.097 2.22 0.03 0.230 1.42 0.16Merlot 0.121 1.31 0.19 0.137 2.83 0 -0.024 -0.12 0.91OtherRed 0.030 0.57 0.57 -0.024 -0.76 0.45 -0.011 -0.12 0.90OtherWhite 0.045 0.62 0.53 0.061 1.55 0.12 -0.343 -2.28 0.02RedBlend 0.085 2.22 0.03 0.007 0.29 0.77 -0.058 -0.85 0.39SauvBlanc 0.143 1.03 0.30 0.055 0.76 0.45 0.215 0.62 0.53Shiraz 0.123 1.66 0.10 0.074 1.38 0.17 -0.170 -1.56 0.12WhiteBlend -0.050 -0.93 0.35 -0.001 -0.03 0.98 -0.365 -3.70 0RoSpain -0.131 -2.48 0.01 -0.065 -2.02 0.04 -0.100 -1.17 0.24Murcia -0.459 -4.08 0 -0.140 -2.39 0.02 -0.435 -1.59 0.11Utiel_Requena -0.308 -2.96 0 -0.174 -3.05 0 -0.106 -0.50 0.62Bierzo -0.113 -1.31 0.19 0.128 1.84 0.07 -0.277 -2.31 0.02Montsant -0.317 -4.63 0 0.006 0.11 0.91 -0.309 -3.39 0Catalunya -0.203 -2.93 0 -0.041 -0.99 0.32 -0.185 -1.50 0.13CastillayLeón -0.208 -2.51 0.01 -0.024 -0.47 0.64 -0.037 -0.28 0.78Toro -0.033 -0.53 0.60 -0.091 -2.05 0.04 -0.108 -1.21 0.23Jumilla -0.371 -6.09 0 -0.114 -3.21 0 -0.299 -2.67 0.01Aragon -0.340 -5.27 0 -0.228 -6.32 0 -0.159 -1.16 0.25Navarra -0.421 -7.18 0 -0.152 -4.61 0 -0.406 -3.21 0Rueda -0.275 -3.30 0 -0.089 -1.97 0.05 0.024 0.12 0.91Baixas 0.078 0.94 0.35 0.186 3.68 0 0.162 1.05 0.29CastillaLaMancha -0.236 -3.63 0 -0.170 -4.64 0 -0.086 -0.70 0.48Penedès -0.258 -4.80 0 -0.098 -3.08 0 -0.111 -1.15 0.25Priorat 0.181 3.83 0 0.051 0.67 0.50 0.058 0.99 0.32RiberadelDuero 0.154 3.19 0 0.074 2.12 0.03 0.017 0.23 0.82Adj. R2 / F-Ratio 64.87 101.5 39.29 18.86 43.74 21.83 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Rioja Tempranillo; Source: Own Calculation
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Table 7: Argentina Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -17.60 -16.38 0 -4.474 -5.65 0 -16.53 -7.10 0log(WSP) 4.806 20.47 0 1.620 9.18 0 4.617 9.00 0log(Cases) -0.172 -18.97 0 -0.057 -8.05 0 -0.159 -10.24 0Age 0.208 13.54 0 0.083 7.17 0 0.145 5.71 0BB -0.160 -2.78 0.01 -0.019 -0.54 0.59 -0.075 -0.52 0.60CabBlend 0.260 4.67 0 0.054 0.99 0.32 0.288 4.28 0CabSauv -0.061 -1.71 0.09 0.016 0.67 0.50 0.000 0.00 0.99Chardonnay -0.039 -0.89 0.37 -0.026 -0.87 0.39 0.012 0.14 0.89Merlot -0.090 -1.75 0.08 -0.039 -1.18 0.24 0.031 0.30 0.77OtherRed -0.269 -4.50 0 -0.110 -2.80 0.01 -0.171 -1.48 0.14OtherWhite -0.149 -1.59 0.11 -0.072 -1.31 0.19 0.062 0.17 0.86PinotGris 0.079 0.41 0.68 0.038 0.35 0.73PinotNoir -0.095 -0.50 0.62 -0.092 -0.73 0.46 0.659 1.77 0.08RedBlend 0.142 3.18 0 0.039 0.93 0.35 0.053 0.96 0.34Sangiovese -0.354 -2.79 0.01 -0.262 -3.67 0SauvBlanc 0.015 0.15 0.88 -0.024 -0.38 0.71 0.472 2.10 0.04Shiraz -0.173 -3.50 0 -0.024 -0.76 0.45 -0.176 -1.66 0.10Viognier -0.125 -1.07 0.28 0.048 0.73 0.47WhiteBlend -0.077 -0.60 0.55 -0.073 -1.02 0.31Salta 0.180 2.39 0.02 0.172 3.40 0 0.294 2.21 0.03Argentina 0.237 3.17 0 0.093 1.67 0.09 0.513 4.56 0SanJuanLaRioja 0.101 1.69 0.09 -0.013 -0.35 0.72 0.366 2.74 0.01UcoValley -0.171 -4.06 0 -0.092 -3.10 0 -0.069 -0.99 0.32SanRafael -0.045 -0.69 0.49 0.022 0.48 0.63 -0.070 -0.62 0.54Cuyo -0.078 -1.71 0.09 0.081 2.60 0.01 -0.105 -1.30 0.19Adj. R2 / F-Ratio 64.91 80.8 28.29 11.56 46.59 18.14 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Mendoza Malbec; Source: Own Calculation
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Table 8: Chile Dependent variable log(Price)
Full Sample Price<17 Price≥17Parameter estimate t-stat p-value estimate t-stat p-value estimate t-stat p-valueCONSTANT -19.55 -22.7 0 -6.518 -9.07 0 -18.0 -9.23 0log(WSP) 5.134 26.6 0 2.101 12.9 0 4.826 11.08 0log(Cases) -0.107 -15.3 0 -0.063 -11.7 0 -0.067 -4.20 0Age 0.169 14.6 0 0.104 11.9 0 0.089 3.26 0BB -0.194 -5.12 0 -0.041 -1.50 0.13 -0.349 -3.85 0CabBlend 0.222 6.12 0 0.070 2.16 0.03 0.240 4.09 0Chardonnay -0.017 -0.55 0.58 -0.012 -0.55 0.58 0.074 0.80 0.42Merlot -0.046 -1.61 0.11 0.007 0.34 0.73 -0.111 -1.29 0.20OtherRed -0.079 -2.56 0.01 -0.012 -0.55 0.58 -0.135 -1.97 0.05OtherWhite -0.196 -2.19 0.03 -0.115 -1.85 0.06 -0.272 -1.09 0.28PinotNoir 0.135 1.81 0.07 0.077 1.17 0.24 0.163 1.27 0.20RedBlend 0.230 4.67 0 0.081 1.57 0.12 0.144 2.01 0.05SauvBlanc -0.082 -2.10 0.04 -0.036 -1.35 0.18 0.011 0.07 0.94Shiraz 0.006 0.14 0.89 -0.035 -1.07 0.29 -0.064 -0.97 0.33SanAntonio 0.125 1.49 0.14 0.047 0.42 0.67 -0.102 -0.87 0.39Limarí 0.163 1.51 0.13 0.012 0.18 0.86Curicó 0.018 0.50 0.62 -0.010 -0.38 0.70 -0.098 -1.18 0.24Lontué 0.100 1.70 0.09 -0.030 -0.76 0.45 0.599 1.74 0.08Casablanca -0.016 -0.39 0.69 -0.010 -0.33 0.74 -0.218 -2.35 0.02Aconcagua 0.109 2.45 0.01 -0.192 -5.12 0 0.224 2.99 0Rapel -0.050 -1.56 0.12 -0.098 -4.20 0 -0.009 -0.12 0.91Central -0.035 -1.03 0.30 -0.131 -5.27 0 -0.127 -1.53 0.13Colchagua -0.031 -1.21 0.23 -0.046 -2.33 0.02 0.001 0.02 0.98Maule -0.002 -0.07 0.94 -0.051 -2.04 0.04 -0.039 -0.41 0.68Adj. R2 / F-Ratio 64.34 119.2 42.65 37.51 45.70 15.42 Colors indicate Significance at the 1%, 5%, 10% and <10% level, respectively. Base Category: Maipo Valley Cabernet Sauvignon; Source: Own Calculation
19
Figure 2a: Quality Premium (Restricted Model)
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Figure 2b: Quantity Discount (Restricted Model)
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Figure 2c: Age Premium (Restricted Model)
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