Quantifying value-for-money wines - part 3

This is the third of a four-part set of blog posts looking at how we might identify value-for-money wines. The topic is not as simple as we might like.

Quantifying value-for-money wines - part 1
   — issues with quantifying value for money
Quantifying value-for-money wines - part 2
   — empirically comparing wines within a specified wine group
Quantifying value-for-money wines - part 3
   — formulae for assessing individual wines against a baseline wine
Quantifying value-for-money wines - part 4
   — empirically comparing wines across wine groups

Formulae for assessing individual wines against a baseline wine

In the previous post (Part 2) I considered empirical methods for trying to quantify value for money as related to wine, which is usually expressed as a quality to price ratio (QPR). The QPR method that I presented involved fitting the exponential (log-linear) model to the price and quality data for a set of comparable wines. Although it is very effective, this approach is not very practical for assessing single wines (eg. in a shop).

In this post I discuss an alternative approach, which is still based on the exponential model (and thus assumes a non-linear relationship between wine price and quality), but which allows individual wines to be compared to the QPR value for a "baseline" wine. This allows the QPR value to be calculated for any wines that are comparable to the base wine. That is, the QPR can be calculated relative to groups of similar wines; for example, red Burgundy, California chardonnay, or Australian shiraz.

The Wellesley Wine Press QPR

This measure of the quality to price ratio (QPR) was developed by Robert Dwyer at the Wellesley Wine Press blog. The wwpQPR approach specifies a particular equation for the QPR relationship and then adjusts it to fit each type of wine. The idea is that the equation is a "one size fits all" version of the empirical method discussed in the previous post, which is then adjusted relative to a specified baseline wine.

For those of you who are mathematically inclined, the equation is an exponential model:

Price = (2^((Quality-90)/3))*20

This can also be represented in a log-linear form:

log2(Price) = ((Quality-90)/3)+log2(20)

The "90" is this equation is the quality score of the baseline wine (using the standard 100-point scale), and the "20" is the price of that wine (in any currency you want to use).

The shape of this QPR equation is shown in the first graph, with two different example baseline wines. The blue line has a baseline wine of Quality 90 = US$ 20, while the pink line has Quality 90 = US$ 40.

For any given wine, the Wellesley Wine Press QPR score is simply:

wwpQPR = (2^((Quality-90)/3))/(Price/20)

A score of 1 means that the wine has the same QPR as the baseline wine; and values greater than 1 indicate a better quality : price ratio. The Wellesley Wine Press blog provides a convenient calculator on the right-hand side of every blog page — all you need to do is enter the information for the baseline wine of your choice, along with the information for the wine you are evaluating.

The choice of baseline wine is the key to success. A different baseline needs to be used for each category of wine, because the prices can vary dramatically between categories. Dwyer suggests that you choose "the price point at which it becomes relatively easy to find a 90-point wine from the category", which he often interprets in practice as being the average price for a 90-point wine. For his own wine evaluations on his blog, these are some of his examples:

Standard California Pinot Noir California Sauvignon Blanc California Zinfandel Napa Cabernet Washington Cabernet Bordeaux red Chateauneuf du Pape red Tuscany red New Zealand Sauvignon Blanc

$20 $30–43 $26 $35 $45–50 $33 $25–40 $30–35 $38 $19

As a specific example, the second graph shows the wwpQPR method applied to the 301 red Bordeaux wines from the 2000 vintage, as used in my previous blog post (Part 2). The black line is the empirical exponential model shown in the previous post (ie. it is the best fit to the data). The darker blue line sets the wwpQPR baseline at Quality 90 = US$ 36, which is the average price for a 90-point wine in the dataset. The lighter blue line sets the wwpQPR baseline at Quality 90 = US$42, which is the price estimated by the exponential model (ie. the black line). Note that these are at the top end of the price range suggested above for Bordeaux wines.

So, wines below each of the three lines are assessed as having good quality : price ratio — the further below the line then the better is the QPR. Obviously, there are slightly different results for each method. The darker blue line is the most "conservative", in the sense that it suggests the fewest wines as having high QPR — it is the lowest line, and so there are fewest wines below it. There is little practical difference between the other two lines, in this example.

RJ Price Per Premium Point

A variant of this idea is presented by Richard Jennings at the RJonWine blog. The RJ-PPPP approach is basically a piecewise version of the wwpQP. That is, it follows the same sort of exponential model but changes the details at certain quality scores. In this case, the equation changes notably at scores of 80, 85, 93 and 95.

The third graph shows a comparison of the TBC index (see Part 1), the wwpQPR (90 = $20), and the RJ-PPPP. The RJ-PPPP assumes a baseline wine of Quality score 90 = $22.

Note that the RJ-PPPP index does not form a smooth curve — this is what "piecewise" means in this case. In this particular comparison, the RJ-PPPP index matches the wwpQPR (90 = $20) only in the quality-score range 81–86 points. On the other hand, in the range 86–91 points the RJ-PPPP actually matches the wwpQPR based on 90 = $22, instead.

As a specific example, the fourth graph shows the RJ-PPPP and wwpQPR methods applied to the 230 US chardonnay wines from grocery stores, as used in an earlier blog post (The relationship of wine quality to price). The black line is the empirical exponential model shown in the previous post (ie. it is the best fit to the data). The pink line sets the wwpQPR baseline at Quality 90 = US$ 22. The light blue line is the RJ-PPPP. As noted earlier, wines below each of the three lines are assessed as having good quality : price ratio — the further below the line then the better is the QPR.

Note that the wwpQPR and RJ-PPPP methods produce very similar results for this dataset, and they are quite different from the results of the empirical method. Indeed, below a quality score of 87 the only wine that all three methods identify as having good QPR is the one highlighted in red, whereas there is more agreement above a score of 89 (ie. in the range $15–20).

So, in practice, the RJ-PPPP is simply a combination of different wwpQPR calculations, with each range of quality scores adjusted to a different baseline price.

Where to from here?

In this series of blog posts I have summarized all of the methods that I have come across for quantifying the wine quality : price ratio (QPR). They are all related in one way or another, and will obviously produce the same results in many cases. What is most obvious is that the calculations need to be different for each wine category (eg. grape type and region), because the prices vary so much between groups.

Nevertheless, there are also important differences between these methods. Perhaps the most important are whether they deal with the non-linear relationship between quality and price, and whether they address the potential confusion cased by the lower boundaries for both quality scores and prices.

The empirical QPR approach (see Part 2) will work best for identifying those wines with a good quality : price ratio, because it provides the best fit to the data for each wine category. However, not too many people are wandering around with a computer full of wine price and quality data in their back pocket. So, it is only practical for doing some research at home (or work!), before purchasing any wine; and even then you need to access a suitable set of data (scores and prices are available at many wine sites).

The wwpQPR approach (see above) is much more practical for on-the-spot decisions when purchasing wine, provided you can access the Wellesley Wine Press web page to do the calculations (or write your own mobile app). Applying the wwpQPR approach is simple, and it produces results that are very similar to the empirical method. However, you need to first choose a baseline wine for each category, which you will have to do from your own past experience. In this sense, the method is somewhat volatile, because a small change in baseline price can have a big effect on the resulting QPR score.

I am interested to know whether anyone has any practical experience at trying any of the methods that I have summarized here.

Quantifying value-for-money wines - part 2

This is the second of a four-part set of blog posts looking at how we might identify value-for-money wines. The topic is not as simple as we might like.

Quantifying value-for-money wines - part 1
   — issues with quantifying value for money
Quantifying value-for-money wines - part 2
   — empirically comparing wines within a specified wine group
Quantifying value-for-money wines - part 3
   — formulae for assessing individual wines against a baseline wine
Quantifying value-for-money wines - part 4
   — empirically comparing wines across wine groups

Empirically comparing wines within a specified wine group

In the previous post I considered the basic issues with trying to quantify value for money as related to wine, which is usually expressed as a quality to price ratio (QPR). As Kim Brebach at the Best Wines Under $20 site has noted: "A $10 wine that scores 91 is a serious bargain, while a $50 wine that scores 91 would not get a recommendation from us. It is the relationship between score and price that is crucial."

Any QPR measure will only ever be an approximation, although hopefully it will be a useful one in practice. There are fundamental problems with quantifying wine quality, and I discussed how these can be overcome. However, the relationship between the price and quality of wines is non-linear, and therefore any simple QPR will be inappropriate.

There are two different approaches to dealing with this issue of non-linearity, which I discuss in this and the next post.

In this post I consider how to quantify QPR when we are looking at a dataset consisting of a group of wines of a similar type; for example, red Burgundy, California chardonnay, or Australian shiraz. The data will consist of values of both the quality and the price of each wine in the set. We are interested in identifying those wines within the dataset that have a good QPR score.

As a specific example, the first graph shows the data for 303 red Bordeaux wines from the 2000 vintage. Each point represents a single wine, located according to its quality score (horizontally) and its price (vertically). Are there any good QPR wines among these 303?

The data are taken from the September 2004 issue of the QPRwines newsletter, produced by Neil Monnens. This was the premier issue; the newsletter was later revamped as The Wine Blue Book, in 2007; and it sadly ceased publication in 2012.

The QPRwines index

Each issue of the QPRwines newsletter consisted of a compilation of QPR scores for a large set of wines; the contents of each issue are still listed at the Wine Lovers Page web site. Here I will describe the derivation of these QPR scores. [Note: Even though this newsletter is no longer published, the QPR method outlined here is still used by, for example, the Wine Peeps blog.]

The wine prices used in the QPRwines calculations were compiled from the Wine-Searcher web site, as explained in an interview Monnens gave to the Napa Valley Register. In the same interview, the compilation of the quality scores is described like this:

[Monnens] checks eight web sites that use the 100-point scoring method (he has subscriptions so he can have access to all the scores, but declines to reveal the sites). Since not all sites review the same wines, he must have a minimum of two scores for each wine in order to include that wine.

This is a robust method for dealing with the inherent variability of wine quality scores, as I discussed in the previous post (Part 1). However, I also noted that the scores need to be standardized for inter-assessor variability, before calculating their average, which may not have been done.

In the original press release for the newsletter (still available at the Vinography web site), the QPRwines index is described in this manner:

A wine's QPR is how much more or less it costs compared to the average price of similarly scored wines (critics' average scores). For example, the average price for a 93-rated 2000 Bordeaux is $119. But the 2000 Chateau Pontet-Canet from Pauillac costs only $50 — a number that is 42% of the average price for a 93-point wine. Pontet-Canet thus has a QPR of 42%.

So, the QPRwines index works in reverse, with lower values indicating good value for money.

This procedure is illustrated in the next graph for the Bordeaux wines, where I have added (in pink) the average wine price for each quality score. Wines below the average have good QPR (within that score group), while wines above it have poor QPR.

This method for quantifying QPR seems to be effective in general. In particular, it works well when there are a lot of wines in each quality-score group. However, it is important to note the QPR values are calculated separately for each group, and not all groups have many wines, particularly for the highest quality scores.

Thus, the graph makes clear the method's essential limitation — the price averages are not necessarily comparable between quality scores. That is, the average price for any given score may be higher or lower than for neighboring scores, so that there is no concept of a general relationship between price and quality. Each measurement of QPR thus depends solely on what other wines have been given the same score. It thus becomes possible to have every inconsistent results between adjacent categories (increasing the quality can actually decrease the QPR!).

This issue becomes particularly obvious when we consider the effect of the two luxury wines that are evident in the dataset (see the post on Luxury wines and the relationship of quality to price). These two wines (Château Petrus and Château Lafleur) have outrageous prices that are not comparable to any of the other wines. Importantly, they distort the calculation of the average price for their respective quality-score groups, by artificially raising the average price.

In turn, this has the effect of increasing the number of wines that will be identified as having a good QPR (ie. they will be a long way below the inflated average). For example, the cheapest wine in the 96-point group (Château Léoville Barton) is identified by the QPRwines index as having "Great value", and the second cheapest (Château L'Église Clinet) as having "Value", solely because the average price for their score-group is artificially high (due to the price of the luxury wine Château Lafleur).

An improved method

This issue can be dealt with by calculating the "average" prices simultaneously using all of the quality scores, not just the prices for each score separately. I have outlined this method in a previous blog post (The relationship of wine quality to price).

The basic idea is to recognize that the relationship between wine price and quality fits an exponential (or log-linear) model. This is a standard model in economics, which represents the idea that the prices are multiplied as the quality increases, and that the multiplier also increases with quality.

So, all we have to do is fit the exponential model to the dataset of wines, and we will have a line on the graph that simultaneously represents the average price for all quality scores (ie. the line represents QPR=1). This is shown in the next graph.

First, however, it is important to note that I have deleted the two luxury wines from the dataset. As I explained in the earlier post on the topic (Luxury wines and the relationship of quality to price), the price-quality relationship needs to be modeled separately for the luxury and non-luxury wines. (With only two wines, we cannot calculate QPR for the luxury wines here.)

So, wines below the pink dashes have high QPR under the QPRwines method, while wines below the solid line have high QPR for my version.

As you can see, the wines identified as being good value for money by the QPRwines method and my own differ only for those scores where a very high-priced wine has artificially raised the average price (eg. scores 93, 96, 98). The exponential model smooths out the averages, and allows a more equitable assessment of QPR across the quality range.

For example, the Château L'Église Clinet wine mentioned above as having QPR "Value" is actually above the line for the exponential-model average price, rather than below it — it has low QPR not high! My method thus identifies fewer wines as having a high QPR, but it does so in a more consistent manner, and is thus an improvement.

Where to from here?

Clearly, the empirical approach outlined here can only be used if you happen to have access to a database of prices and quality scores. This works if you are publishing a newsletter or a blog; but it is not very convenient if you are standing in a wine shop wondering which wine to buy.

In the next post I will discuss some QPR approaches that allow a single wine to be assessed based on very little information.

Quantifying value-for-money wines - part 1

This is the first of a four-part set of blog posts looking at how we might identify value-for-money wines. The topic is not as simple as we might like.

Quantifying value-for-money wines - part 1
   — issues with quantifying value for money
Quantifying value-for-money wines - part 2
   — empirically comparing wines within a specified wine group
Quantifying value-for-money wines - part 3
   — formulae for assessing individual wines against a baseline wine
Quantifying value-for-money wines - part 4
   — empirically comparing wines across wine groups

Issues with quantifying value for money

Good value for money is a rather vague concept, which is presumably why so much has been written about it, often in a rather vague way. So, in order to get started we need to be more specific. Products that are good value for money are often identified using their quality to price ratio (QPR) — high quality for low money = good value. So, for the purposes of these posts I will be talking about QPR.

The principal way of recognizing good QPR is that you expected the product to cost more money than it does, compared to other similar products. QPR is often treated as being a subjective and relative concept. That is, you first have to like the product and, second, everyone’s idea of “value” is likely to be somewhat different. Almost every wine forum has a discussion of the topic (eg. see QPR: fact or fiction?), with almost as many opinions as there are commentators.

This attitude cuts no ice in the world of economics, which is the world inhabited by those people looking for bargains. The basic issue is that subjective assessments of QPR tend to focus on the money not the value. That is, the product must be cheap in order to have good QPR. However, quality costs money, and therefore must be paid for. So, good QPR can involve a lot of money when the quality is high enough. Furthermore, many people think that you have to actually like the product, or it isn't good value. However, good value exists even if it is not valuable to you personally.

The quality : price ratio

Therefore, it should be possible to quantify QPR, at least approximately, so that rational purchasing decisions can be made. QPR can never be exact, of course, because there can be no precise measure of quality, nor will there be a precise price to be paid (price varies through time and space). However, lack of exactness should not stop us from producing a suitable approximation, from which we can make decisions in practice. In the wine world, this means choosing a wine for reasons other than that you simply like the label!

So, QPR needs to be an actual number. In any normal business it should be possible to get that number by dividing some measure of quality by some measure of the price. That way, large QPR values would represent good value-for-money and small values would not. Unfortunately, the wine business is not normal, by any means, and thus measures of quality and price can be rather tricky.

We can leave aside price for the moment. Price obviously varies from country to country, and from state to state within any one country. Price also varies with currency fluctuations, since an awful lot of wine in any given country is imported (see the post on Global wine imports). There is little we can do about price variation.

Measuring quality

Quality, on the other hand, is a very tricky thing for wine. Wine is an "experience good", and therefore perceived quality is tied up with personal experience. Nevertheless, there are plenty of ways to measure wine quality, including scales using three glasses, five stars, and points with a maximum of 10, 20 or 100. Sadly, the only thing these have in common is that more glasses / stars / points is intended to mean more quality.

I won't go into detail here, but these scoring schemes can show a lot of variation, resulting from the fact that they are all based on personal assessment when tasting the wine. These assessments can differ due to: varying preference or experience of the assessors; different expectations among the assessors; varying sensory perception of any one assessor at different times; different environmental circumstances of the tastings; variation among bottles of the same wine; different interpretations of how to apply the scoring system being used; and so on. So, any given quality score is potentially not directly comparable to any other score.

One possible way to deal with this issue is by combining scores from as many assessors as possible. The main trick when doing this is to know how the different assessors have used their scoring schemes — we can't just average the raw scores, because 16/20 for one person is not necessarily the same as 16/20 for the next person. The scores thus need to be standardized before averaging — I have briefly discussed this topic for Bordeaux wines (see the post on Luxury wines and the relationship of quality to price). A subsidiary issue is how many scores must be combined to get a meaningful average score. Two is the minimum, but more is obviously better.

Clearly, the 3-glasses and 5-stars scoring schemes are very coarse (there are not many levels), and they are not likely to give us much variation in QPR (most wines tend to be assigned the middle level). Nevertheless, in these cases the QPR is straightforward to calculate, and it can therefore provide some guidance for purchasing.

Unfortunately, this is not so for the point-scoring schemes. This is because there are minimum values below which scores do not occur. For example, the 100-point scheme has a minimum possible score of 50 (not 0); and below a score of 70 the fluid is not drinkable as wine (although it may be very good wine vinegar). Indeed, you will rarely encounter a wine score below 80 — even the cheapest wine widely available in the USA (the infamous Two Buck Chuck, produced by Charles Shaw winery) scores an average of 80 points on the CellarTracker site. So, the 100-point scale is effectively a 20-point or 30-point scale, in practice.

In the same vein, there is also a minimum price below which wines do not normally occur in practice. For example, in the USA the Two Buck Chuck wines cost US$ 2–3, depending on the state.

So, these non-zero minimums for quality and price mean that simply dividing the quality score by the price will produce a meaningless QPR score for wines. The QPR would look like it was measured in points per dollar (euro, pound ...), but that would not be how it actually is.

The POP score

This issue has been partly addressed by the Liv-ex wine marketplace, which monitors the global auction market. They have devised their POP score, which they describe as follows:

A wine’s POP score is its price-over-points ratio, our loose measure of value. It is calculated by dividing the price of a dozen case of wine by a shortened 20-point score. We have calculated this 20-point score by simply subtracting 80 from the rating, on the basis that any wine under 80 points is unlikely to appear on the auction market.

That is, they subtract a minimum value from the quality score of each wine, before doing the QPR calculation. This addresses the issue of a non-zero minimum score, but not the issue of a non-zero minimum price.

The TBC index

Mike Veseth, at the Wine Economist blog, has proposed dealing with this issue by having a baseline for both quality and price. That is, we subtract a minimum value from both the quality score and the price of each wine, before we do the QPR calculation. He calls the resulting QPR score the Two Buck Chuck (TBC) index. This approach means that any wine with a score of TBC=1 has the same QPR as the baseline wine chosen (ie. the wine with the minimum score and price).

He proposed using 70 as the minimum score when measuring quality on the 100-point scale, and US$2 as the minimum price. So, TBC = (Quality - 70) / (Price - 2). [TBC is thus a bit of a misnomer, since the Charles Shaw wines actually cost US$3 in most places and score c. 80 points.] However, any wine can be chosen as the baseline.

The first graph shows the prices for wines with TBC=1 given the quality=70 and price=2 baseline wine. Any wine whose price and quality places them below the line would be considered good value for money, and anything above the line would be poor value.

Also shown are red dots representing the two wines that Veseth uses as his examples. (1) An 88 point wine for $20 would have a TBC score of (88-70 points)/($20-$2) = 18 points / $18 or a dollar a point — this wine thus lies on the line. (2) An 86 point wine for $10 would have TBC = (86-70)/(10-2) = 16 points / $8 = two points per dollar — this wine lies below the line, and is thus better value for money.

It is important to remember that TBC values depend on the baseline wine, and cannot be compared between different baselines. So, a suitable baseline needs to be chosen for different types of wine, and value-for-money comparisons can only be made within that wine type. The line shown on the graph will move up if a higher price is used for the baseline, and will move to the right if a higher baseline score is used.

The obvious limitation of this simple approach to quantifying QPR is that the relationship between price and quality is assumed to be linear (ie. the graph shows a straight line). However, I have shown in previous blog posts that this relationship is actually exponential (log-linear) — see The relationship of wine quality to price and Luxury wines and the relationship of quality to price. So, the TBC approach is not realistic, because the line in the graph should be a curve.

The Reverse Wine Snob rating system

A similar limitation applies to the QPR rating system used by the Reverse Wine Snob web site. This approach uses a scale of 1-10 for quality (Taste) and 0-10 for price (Cost; a high Cost score represents a low price). The QPR rating is then a combination of these two scores. This approach thus neatly side-steps the non-zero issues raised above, because there is a pre-defined baseline wine.

The RWS-QPR score for any given wine is calculated by starting with a perfect score of 10, for a wine with Taste=10 and Cost=10, and then subtracting 0.25 for each decrease in Cost score and subtracting 0.75 for each decrease in Taste score. A final QPR score > 7 indicates a wine with good quality : price ratio.

This system is illustrated in the final graph. Note that the calculations form a series of straight lines, one for each Cost-score level. This makes clear the linear nature of the RWS-QPR. This may be quite reasonable in this case, because the Reverse Wine Snob site is all about wines with a price less than US$ 20, and within this narrow range the relationship between quality and price may well be approximately linear.

Where to from here?

In the next two posts I will discuss some QPR approaches that address the non-linearity of the quality-price relationship of wines, and thus produce more realistic measures of the quality : price ratio.

Glasses for sweet wines

Demonstrating that different wine glasses suit different wines is a straightforward thing to do. Even novices can usually detect a difference, when given the same wine in different glasses. The trick, then, is finding the "right" glass for each wine — the one in which the wine seems to smell and taste best.

So, we have a selection of glasses in our house, and we often try the first glass of any bottle of wine in at least two different glasses, to see which one is most suitable. Most of these glasses are from the Spiegelau Vino Grande series, because that was what was on special at the time we first decided to acquire a selection. However, we also have a few glasses from the Riedel Vinum series.

Recently, we decided to try some new glasses for sweet (dessert) wines. The three that we tried are shown here.

From left t right in the first photo they are:
    Riedel Vinum Extreme Icewine
    Riedel Sommeliers Sauternes
    Riedel Vinum Port
The Port and Icewine glasses are machine-made crystal, while the Sauternes glass is hand-blown; and each one of the latter therefore costs about one-third more than a pair of the other glasses.

The first wine used for testing (as shown in the photo) was a half-bottle of Château Raymond-Lafon Sauternes 2003, a moderately good vintage for the sweet wines of Bordeaux. It was probably right in the middle of its best drinking window, with aromas of lemon, apple, honey, pineapple, and dried apricot.

In the comparison, there was little to choose between the Vinum Port and Vinum Extreme Icewine glasses, both of which nicely focussed the nose of the wine. However, the surprise outcome was that the Sommeliers Sauternes glass performed very poorly, with a very muted presentation of the aromas. That being said, I might choose the Extreme Icewine glass for this type of wine, as the larger volume displays the wine's colour well.

The second test wine was a half-bottle of Don PX Gran Reserva 1983, a pedro ximénez wine by Bodegas Toro Albalá, from Montilla-Moriles in the south of Spain. This is a much stronger and more syrupy wine than the sauternes, as shown by its colour; and it is still a youngster despite its 30+ years of age. It usually scores at least a couple of points better on sites like CellarTracker.

This comparison was completely inconclusive. No matter in what order the glasses were examined, the first one smelt strong, the second was muted, and the third one had almost no detectable aroma! So, the glasses had to be examined individually, rather than directly compared.

The Vinum Port glass emphasized the liquorice (and orange zest?) aspects of the aroma, while the Vinum Extreme Icewine glass emphasized the plum and clay pot aromas, and the Sommeliers Sauternes glass emphasized the plum and roasted coffee aromas. All three glasses nicely presented scents of raisins, dried figs, molasses, prunes, burnt caramel, honey, tar and chocolate. Stunning!

Since there is so little to choose between the glasses for this particular wine, I would use the smallest glass, in order to control the volume — this wine is simply too strong-tasting to want to drink much at a time (the after-taste lasts for minutes).

The third test was intended as a complete contrast to the previous wine. This was a 500 ml bottle of Swedish apple wine known as Maglehem n:o 4:15. This is a 15% alcohol wine made by Maglehems Musteri, using mainly Cox Pomona, Ingrid Marie, Cox Orange and Ribston apples, and then matured for 18 months in French oak. It is only mildly (ie. apple-juice) sweet.

In all three glasses, the wine had a bitter-sweet sensation of apples, quince, marmalade and basil. In addition, the Vinum Port glass emphasized an aroma of flowers and over-ripe apples, while the Vinum Extreme Icewine glass emphasized orange peel and dusty road (after being fairly muted at first). The Sommeliers Sauternes glass picked up the aroma of over-ripe apples, but less strongly, plus the dusty road, and added some bitter almonds. So, the latter glass probably edged out the other two.

The fourth, and final, test wine was a bottle of Framersheimer Kreuzweg Trockenbeerenauslese 1976, from Walter Kürner Weingut in Rheinhessen, in Germany. In strength and sweetness it is somewhere in between the first two wines. It is certainly the most mature of the four, while still being firmly in its best period.

All three glasses produced a profound sensation of raisins, honey and citrus, in both the aroma and the taste, and in that sense they were all good presenters of the wine. However, in this case the Vinum Extreme Icewine glass was the clear favorite, with a stronger and more taste-rich experience compared to the other two glasses. The Sommeliers Sauternes glass placed a bit more emphasis on a grapefruit-skin bitterness; and the Vinum Port glass showed a bit more plum aroma.

So, the bottom line from these four comparisons is that there was no consistent difference between the three glasses, that we could detect. These combined results contradict some other comparisons of these three glasses, such as that in the comments to this particular blog post: The Ultimate Glass Test.

Anyway, given that you should only buy wine glasses that you can afford to replace on a regular basis, the expensive Riedel Sommeliers glass may end up being put away in storage; as may the unnecessarily tall Riedel Vinum Extreme Icewine glass.

United States wine imports and exports

Today, the USA is the fourth largest producer of wine by volume, with 2.21 billion litres in 2015. The US is thus a considerable exporter of wine, as well as an importer.

Indeed. the first graph shows that the over the past few years the USA has imported roughly three times as much wine as it has exported. Clearly, demand exceeds supply.

The imports and exports are often broken down into: packaged still wine (bottles, bag-in-box), sparkling wine in bottles, and bulk wine (usually delivered in huge bladders, and then bottled in the destination country). About 25% of the imported wine in 2015 arrived in the USA in bulk, while approximately 44% of the exported wine was sent in bulk. Bulk wine is, of course, at the cheap end of the price spectrum.

The wine exports go to a wide range of countries, as shown in the next graph for the bottled wine in 2015. However, last year Canada and the United Kingdom accounted for 46% of the exports between them. Not unexpectedly, most of the countries on this export list do not have a large wine industry of their own.

However, in spite of its own large wine industry, the United States imports a very large amount of wine. Indeed, in 2015 only about 72% of the wine consumed in the USA was provided by US wineries.

Much of the wine that is imported in bulk disappears into generic bottles. For example, during the boom for merlot wines in the 1990s, when demand in the USA exceeded supply, inexpensive French merlot wine was imported by a number of California wineries, and sold under their regular label or blended with California wine (by US law, only 75% of a wine bottle's contents needs to match the label).

Moving on, in 2015 roughly 12% of the packaged wine imported was of the sparkling variety. Nearly 51% of this sparkling wine came from Italy, mostly at the cheap end of the scale, with an average price of $5.27 per liter. On the other hand, the 28% that came from France was much more expensive, at $23.36 per liter on average.

Of the packaged still wine in 2015, the largest proportion also came from Italy, as shown in the next graph. Indeed, Italy accounted for more than one-third of the still-wine imports by volume (35%).

The average price per litre of the imported wine was $5.68, but this varied widely between the source countries, as shown in the final graph. Assuming that price reflects quality (to some extent, at least), then France and New Zealand were clearly purveyors of much higher-quality wine was than anyone else.

As I have noted before (Global wine exports), Australia has been one of the main suppliers of cheap wine for the world. This is also apparent for the wine supplied to individual countries such as the USA. In this case, Australia makes less money per liter out of its wine exports to the USA than does anyone else, in spite of being the second-largest supplier. This does not make economic sense, and reflects the current crisis reported in the Australian wine industry. For example, way back in 1994, Edward Oczkowski noted: "Most industry commentators point out that given the prospect of relatively flat domestic demand for wine, the industry's future prosperity rests with the exporting of premium table wines." This does not match the situation 20 years later,

The data for the above graphs has been taken from the 2016 report at the Wine by Numbers website.