Structural Changes the Danish Alcohol Market

ANDERS MILH0J
•
Structural Changes In
the Danish Alcohol Market
This poper examines annual (1978-1995) and quarterly (1990- 1995) data on the Danish consumption of beer, wine and
spirits, in order to identify changes in their respective market shares as aresult of the major tax cuts introduced for beer
and wine in 1991 and 1992. It is immediately clear that the sales of spirits have decreased while the sales of wine have
increased. The changes are too large to be explained exclusively on the basis of the reduced levelof border trade with Germany, the main motive for the tax reductions.
The statistical analyses give a more detailed picture of the reasons for the decline in the market share of spirits in total
Danish alcohol sales from 14 % in 1990 to 11 % in 1993. It is included that the main part of this fall, at least 2 %, is due
to the tax-induced changes in price relations, while more than l % comes from a trend movement. The market share of
beer has been relatively constant for a number of years. However, this is the net effect of a trend movement tending to reduce its market share and, on the other hand, the reduced price of beer relative to the price of spirits caused by the tax reductions, which has increased its market share. The market share of wine has been steadily increasing since the 1970s.
There is no evidence of any dependencies on the prices of alcohol. This conclusion cannot, however, be sufficiently documented on the basis of the Danish data series, as it is impossible to distinguish between effects due to changing wine prices and effects due to changing beer prices, because of the parallel tax cuts for beer and wine.
Key words: alcohol market, tax reduction, border trade, Denmark
The Danish alcohol market in the 19905
Consurner taxes on beer and wine have been reduced twice in Denmark during the 1990s, i.e. on
1 July 1991 and on 1 October 1992. The reductions
were quite drastic: approximately 10 % in 1991
and as much as 25 % on some low-price brands of
beer in 1992.
The tax reductions were motivated by the high
levelof border trade with Germany. It was common knowledge that, before the tax cut s, no one in
the southern parts of Jutland bought any wine and
only very smal1 quantities of beer, while people
living further away from the German border went
on regular trips to Germany mostly to buy beer
and wine. The Danish government tried to control
this traffic by imposing various restrietions on
how much people were allowed to bring into the
country, but being incompatible with EU intentions, they had to be relaxed.
The high levelof border trade was not only
unacceptable for fiscal reasons, but there was the
additional problem that while in Germany, Danish
people not only bought alcohol but also traded in
other commodities. As beer and wine were considered the main reason for border trading, the retailers in southern Jutland in particular called for a
solution. Danish taxes on beer and wine and also
on petrol were consequently reduced, helping to
achive a significant reduction in the total amount
ofborder trade.
The tax reductions apply of course to the whole
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country, inc1uding the island of Zealand with the
Copenhagen are a, where any significant border
trade was impossible for geographical reasons.
Two previous papers (Milhøj 1993 and 1995) studied the effect of the tax reductions on the total
consumption of alcohol in the whole country as
well as in various areas of the country. The overall
conc1usion was that total alcohol consumption did
not increase as a consequence of the reduced taxation, even though official statistics indicated an
increase in alcohol sales because of the reduced level of border trade.
The dramatic price cuts for beer and wine have,
however, increased their sales at the expense of
spirits, the price of which has remained constant.
This price driven substitution between beer and
wine, on the one hand, and spirits, on the other, is
the subject of the present paper.
and for this reason the calculation of sales volumes
in 100 % alcohol is carried out in two steps. In the
fust step the sales volumes measured in litres in
drinking strength of the various brands are derived from the tax revenue. For the two years 1991
and 1992, such data on the volume in drinking
strength as well as official data on sales in pure
alcohol are available. Based on these figures, the
average strength of beer for both years can then be
calculated as 4.8 %; accordingly, the average
strength of wine is 12.3 %. These strengths are then
used in the second step to transform sales volumes
measured in drinking strength to sales volumes
measured in 100 %alcohol. This procedure is used
to derive quarterly data for the sales of the three
types of alcohol meas ure d in 1 000 litres of pure
alcohol.
As part of the monthly Danish Consurner Price
Index, the StatisticaI Bureau has given the prices
for the three types of alcohol since 1978:
Data
The Danish StatisticaI Bureau has provided annual
data on the sales of alcohol measured in 100 %
alcohol since 1978. In this paper the variables are
denoted as:
BSALE Volume of beer sales in 1 000 litres 100 %
alcohol
WSALE Volume of wine sales in 1000 litres 100 %
alcohol
SSALE Volume of spirits sales in 1 000 litres 100 %
alcohol.
The total sales of alcohol measured in 100 % alcohol is then given as:
TOTSALE =BSALE + WSALE + SSALE.
These data series are based on data supplied by
the Ministry of Taxation on tax revenue from the
sale of alcohol. Data on tax revenue are, however,
also available for a shorter time interval than one
year. For wine, figures on tax revenue are available on a quarterly basis since the beginning of 1989;
and for beer, monthly data are available since July
1990 and for spirits since May 1989.
The Ministry of Taxation figures are based on
sales of spirits in 100 % alcohol. For wine and beer,
taxation is not directly based on alcohol content,
BPRICE Index numbers for price of beer
WPRICE Index numbers for the price of wine
SPRICE Index numbers for the price of spirits.
The consurner price indices, which are based on
1980 = 100, give the prices as they are met by the
consurners, taxes inc1uded. Yearly figures for the
prices are simply derived as averages of 12 monthlyvalues.
Two parallel analyses are presented in this paper on the basis of these data. First, an analysis of
yearly data is presented on the basis of the data for
the 18 years from 1978 to 1995; then, an analysis is
presented on the basis of 22 quarterly observations
from the third quarter of 1990 to the fourth quarter
of 1995. The first analysis of the yearly data aims to
identify long-term effects in the alcohol market,
while the purpose of the second analysis is to identify short-term effects on the alcohol market from
the tax cuts on beer and wine in 1991 and 1992.
There are, however, some critical remarks that
need to be made on the quality of these data. The
sales data for one specific month are derived on
the basis of the monthly tax revenue, not on the
actual sales during the month. However, the alcohol tax is not paid by the retailers but by the wholesalers, as the goods are delivered to the retailers.
If the shops hold some stock of wine, for instance,
the wine taxed in one period could actually be sold
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Figure 2. Market shares in 1978-1995
Figure 1. Sales of alcohol in 1 OOOlitres 100 % alcohol
for 1978- 1995
Market shares
1000 1100%
60000
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
50000
40000
30000
B BB B B BBB BBBBBB BBB B
20000
10000
W"W"WYf
WWWWWWWWWW
wwWW
S S S S S S S S S S S S S S
0T-~~~'-~~~~~~~~~~~
1975
1980
1985
1990
1995
TT Total BB Beer
WW Wine
LBTOT =10g(BSALE/TOTSALE)
LWTOT = 10g(WSALE/TOTSALE)
LSTOT =10g(SSALE/TOTSALE).
These variables are the logarithmically transformed market shares of the three types of alcohol in
the total Danish alcohol market. In the models these variables are explained in a linear regression
B BB BBBBBBBB BB BB
WWWWWWwWWWW
"WWYf S
WWWW
S S S S S S S S S S S
S S S
0.0 'r--->--'-~"-'~~""-"'r-r~""-"'--'--,-""-",,,,,,,,,,,,,-,--,,
1975
1980
1985
1990
1995
SS Spirits
during alater period. This problem is especially
relevant in the periods around ChristInas and Easter, for which sales data could be misleading beeause alcohol taxed in March, for instance, eould
in faet be sold in April. Another problem is that the
eonsumer price index is based on "normal" priees
from a sample of Danish retail shops. These normal prices do not take temporary priee reductions
etc. into account.
Both the sales and price series are aggregated, so
that beers of various brands, strengths and prices
are considered as one. However, it is clearly possible that the price driven substitution in consumption among the three types of alcohol is more
pronounced for low-price brands of beer, wine
and spirits, than for more expensive brands.
The main subject of the present analysis is to study price driven substitution. For this reason the
market shares of the three types of alcohol are the
variables of interest. These variables are denoted
as:
BB B
BB Beer
WW WIDe
SS Spirits
model by the lag-transformed relative priees
LOGPBW = 10g(BPRICE/WPRICE)
LOGPBS = 10g(BPRICE/SPRICE)
LOGPWS = 10g(WPRICE/SPRICE).
A graphical analysis
In this section diagrams for all variables used will
be presented using both yearly and quarterly figures. As the quarterly sales data contain some seasonal variation, the series are seasonally adjusted
by a simple applicatian of seasonal dummies,
which are also used in the statistical analyses.
Figure 1 shows the total sales of alcohol in Denmark from 1978 to 1995. As we can see, sales increase d from 1978 to 1983, declined somewhat in the
late 1980s and has recently started to increase
again. However, the movements in the total sales
of alcohol are af only minor importance and could
to someextent be explained by changes in the volume of border trade.
Figure 1 also shows the sales of the three types
of alcohol for the same period. The sale of wine has
steadily increased, while spirits sales have declined each year since 1986 and the sale of beer has
been more or less constant throughout the whole
period. In spring 1985 there was a long strike at the
breweries in Copenhagen. The effects of this strike
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Figure 3. Price of alcoholic beverages as indices with
Figure 4. Price relation beer to wine for 1978-1995 with
1980 = 100 for 1978-1995
1980= l
Price indices
Price relation
200
180
160
140
120
100
80
60
40
20
1.10
1.05
1.00
B~'W3VJ3W BW
BW
0.95
0.90
0.85
0.80
0.75
0T-~~~'-~~~-'~~~~~~~~
1975
1980
BB Beer
1985
1990
WW Wine
1995
0.70 T-~~~-r--~~~-r--~~~,....,~~-.--.r
1975
1980
1985
1990
1995
SS Spirits
BW Beer/Wine
Figure 5. Price relation beer to spirits for 1978-1995 with
Figure 6. Price relation wine to spirits for 1978- 1995 with
1980= l
1980= l
Price relation
Price relation
1.10
1.10
1.05
1.00
0.95
BS
BS
BSBS
BS
BS
BS
BS
BS
WS
1.05
1.00
BS
BSBSBS
0.95
0.90
BS
0.90
BS
0.85
0.80
WS
0.85
0.80
BSBSBS
0.75
w~s ws
jN9NgmYv~f't.ns
ws
wjY1'i'
WS
0.75
0.70 T-~~~--r-~~~--'-~~~--,-~~~r-r
1975
1980
1985
1990
1995
0.70 T-~~~--r-~~~--,-~~~--,-~-'-~"""
1975
1980
1985
1990
1995
BS Beer/Spirits
WS Wine/Spirits
\
on beer sales are easily seen in the diagrams: in
1985 sales figures for beer were lower than
expected, while the sale of wine in particular was
increased.
Figure 2 shows yearly series for the market shares of the three types of alcohol, that is the variables LBTOT, LWTOT and LSTOT before the logtransformation. Clearly, the market share of wine
has steadily increased, while the figures for beer
and spirits have decreased, for spirits especially in
1992 and 1993. Moreover, the effect of the 1985 bre-
weries strike is obvious.
Figure 3 presents yearly price series for the three
types of alcohol. Of course, inflation produces a
steady upward trend in the prices, but the effects
of the frequent minor adjustments in alcohol taxation in 1982-1986 are also evident. The tax cuts for
beer and wine are clearly seen, but apart from that
the prices for all types of alcohol and especially
beer have changed very little in recent years, with
the rate of inflation in Denmark being very low in
the 1990s. A similar picture emerges from Figures
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Figure 7. Sales of alcoholic beverages in 1 OOOlitres
Figure 8. Price of alcoholic beverages as indices with
100 % alcohol for the quarters 1990.3-1995.4
1980 = 100 for the quarters 1990.3-1995.4
1000 l 100%
14000
Price indices
T
T
T
T
12000
8000
B
B
B
200
T
B
180
160
BB
BB
BB
B
6000
T
T
T
10000
T
B
2000
W~W
BBBB BBBBB
140
W
4000
WWW
SSSSSSSSSSSSS
WWWWWWWWWWWWW
BBBBBBBBBBBBB
120
S
O
100
90Ql
91Ql
92Ql
TT Total BB Beer
93Ql
94Ql
WW Wine
95Ql
96Ql
90Ql
SS Spirits
4-6, which present the relative prices, that is
LOGPBW, LOGPBS and LOGPWS without the
log-transformation. As the series starts from the
base value 1980 = 1 we can see that the price of
beer has decreased relative to both wine and spirits. However, the price relation between beer and
wine has been almost constant, whereas the price
of spirits has increased considerably compared
with the prices of both beer and wine due to the
tax reductions in the 1990s. This very parallel development of beer and wine prices gives rise to some technical problems in the analyses because of
multicollinearity.
Figure 7 gives seasonally adjusted as well as
actual observed quarterly data for sales of the
three types of alcohol and the total sales of alcohol.
Figure 8 similarly presents the actual quarterly
price series, which show no seasonal variation.
The reductions in the prices of beer and wine relative to spirits caused by the tax cuts in 1991 and
1992 are clearly seen. The tax cut in 1991 has reduced the price of beer more so than the price of wine, while the reduction in 1992 did not change the
beer / wine price ratio.
91Ql
92Ql
BB Beer
93Ql
WW Wine
94Ql
95Ql
96Ql
SS Spirits
The statisticai model
The basic statisticai model presented here will be
used for both yearly and quarterly data. The model is constructed in such a way that it is particularly well suited for studying the effects of relative
price changes of wine, beer and spirits on their
market shares. To this end linear regression models are used with the market shares LBTOT etc. as
response variables and the relative prices LOGPBS
etc. as explanatory variables.
As demonstrated by the graphical analyses, the
market share of wine has been steadily increasing
over the past years, while the market share of spirits has been decreasing. It is possibie then that
market shares change for other reasons than relative price changes. It seems reasonable to suggest,
for instance, that Danish people have acquired a
stronger taste for wine partly because of changes
in eating habits and partly because of their more
frequent travel in southern Europe. In the statisticai models such a steady development can easily
be described by a trend variable, that is an explanatory variable, TREND, which simply equals the
observation number.
With both relative prices and the trend as expla-
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natory variables, the basic model for the market
share of spirits, for instance, is written as:
LSTOT = ~INT + ~BsLOGPBS + ~wsLOGPWS +
Models for the market share af beer
The estimated basic model for the market share of
beer is:
~TRENDTREND.
In this model the market share of spirits rather
than the actual sales volume of spirits is used as
the response variable. Therefore changes in the total sales of alcohol have no effect on the response
variable as long as the sales of the three types of
alcohol change proportionally. Many factors that
could possibly influence the total sales of alcohol
such as income, other taxes, prices for other goods
e.g. housing, will under this condition have no influence on the market shares. Under these circumstances changes in the population size could also
be excluded from the model. However, if the effects of external factors on the three types of alcohol are not proportional, the effects are probably
included in the trend. For instance, changes in
drinking habits caused by older generations preferring beer or akvavit, and younger people preferring wine, could be included in the trend.
FiHed models for yearly data
This section describes the results of estimations of
parameters from the various versions of the basic
model, as fitted models using the estimated parameters. Some technical comments are also made.
Finally, the concluding section is devoted to a more intuitive discussion of the results.
In all the models presented, the actual numerical
value of the intercept is of no direct interest and is
hence omitted. Moreover, as some of the estimated
parameters are insignificant, significant values
using a two-sided test at a 5 % level are identified
by giving the numbers in bold face.
The fitted relations are checked by the usual
control procedures for regression models. As is
usual for time series data, all the models present a
good fit with high values of R2. For time series data
it is especially important to note that the models
contain no autocorrelation in the residuals, as the
hypotheses of no autocorrelation are accepted by
Durbin-Watson tests.
LBTOT = !NT - 0.04 LOGPBW - 0.05 LOGPBS 0.009 TREND
In this model only the parameter representing the
trend is significant. To further study the effect of
relative price changes, models with only one relative price were fitted, but the price ratios were still
found to be insignificant, when tested at a 5 % level. If both price ratios are excluded from the model, only the trend remains
LBTOT = INT - 0.008 TREND,
a relation that, measured by R2, is nearly as good as
the model also using the price ratios as explanatory variables.
In summary, the development in the market
share of beer is dominated by the downward sloping trend, and the price ratios are of no importance. The data clearly indicate that the relative
beer I wine price ratio has no significance with regard to the market share of beer. This is because
the beer I wine price ratio in Denmark has been
more or less constant during the period concerned,
and therefore it is impossible to study the effect of
changes in this price ratio on the market share of
beer, The effect of the beer I spirits price ratio is
hardly significant, but an effect of the beer I spirits
price ratio is consistent with the effect of the
beer I spirits price ratio for the market share of spirits, as seen below.
Models for sales af wine
When the basic model is fitted to the market share
of wine, only the trend variable is significant, while neither the relative beer I wine price nor the relative wine I spirits price give a significant contribution to the model:
LWTOT
= !NT - 0.08 LOGPBW - 0.14 LOGPWS +
0.029 TREND.
This is still true when only one of the price ratios is
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used as an explanatory variable in the model.
Hence it is conduded that the market share of wine only depends on the trend:
LWTOT =!NT + 0.031 TREND.
This upward trend is highly significant, giving a
sharply increasing market share for wine in Denmark, probably due to changing habits, e.g. dietary habits, and is not caused by changing price relations.
feds of changes in the winel spirits price ratio.
However, when comparing the R2-values, it seems
that the price ratio of beer to spirits is of most importance.
To sum up, the coefficients to LOGPBS and
LOGPWS add up to one in all relations involving
the relative prices. In all models the negative trend
is significant, which means that the effeds of
changes in the price relations could be distinguished from the slowly decreasing market share of
spirits due to changing drinking habits caused by
other reasons.
Models for the sales af spirits
Analysis of quarterly data
For the market share of spirits the trend is of some
importance, but the price ratios also enter the model. Using both the beer I spirits and the winel spirits price ratios and the trend variable, we find:
LSTOT = INT + 0.97 LOGPBS + 0.10 LOGPWS0.010 TREND.
Although it seems on the basis of this relation that
only the beer I spirits price ratio and not the winel spirits price ratio is of importance, this condusion could be astatistical artifad due to multicollinearity. When only one of the relative prices is
used as an explanatory variable, we find:
LSTOT = !NT + 1.05 LOGPWS - 0.017 TREND
In the application of the basic model to quarterly
data, seasonal dummies are induded in order to
model the seasonal variation. This provides a
description of the systematic seasonal variation in
drinking habits, but as this is of no interest in the
present study, the estimated values for the coefficients to the seasonal dummies are not reported
here.
All the models pass the usual graphical and numerical tests. It is particularly noteworthy that no
autocorrelation is found. In the same way as in the
analyses of yearly data series, trends are induded
in all relations, but as quarterly observations are
only available for a period of three and a half
years, it is impossible to give a precise estimate of
the trend.
and
Models for the market share af beer
LSTOT = INT + 1.04 LOGPBS - 0.009 TREND.
As both coefficients to the relative prices are now
individually significant, we see that these relations
are significantly betler than the model which only
indudes the trend:
LSTOT = !NT - 0.024 TREND.
The condusion is that the price ratios of beer to
spirits and wine to spirits enter the relation with a
coefficient dose to one, if only a single price ratio
is applied. However, as the two price ratios show a
parallel development during the period under study, it is impossible to distinguish the effeds of
changes in the beer I spirits price ratio from the ef-
The fitted basic model for the market share of beer
is:
LBTOT = INT + 0.04 LOGPBW - 0.14 LOGPBS 0.005 TREND + seasonal dummies.
In this relation the price ratios are of no significance, but if the trend is exduded price ratios become significant. However, all models with the
trend variable exduded give R2-values smaller
than the model using only the trend:
LBTOT = INT - 0.003 TREND + seasonal dummies,
and hence this model is preferred.
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Models for the market share af wine
The fitted version of the basic model is:
LWTOT = INT - 0.94 LOGPBW - 0.18 LOGPWS
+0.009 TREND + seasonal dummies.
Using various combinations of the explanatory variables, we find that models including the trend
are superior to all other models, and in summary
the final model using only the trend seems most
reasonable:
LWTOT
mies.
= INT
When these relations are compared with regard to
R2, it is obvious that the trend is unimportant, but
equally obvious that at least one of the price ratios
should be included in the model. However, it is
not clear which price ratio, beer to spirits or wine
to spirits, should be used in the model due to the
multicollinearity, as the price ratios shift in parallel. As for the yearly data series, it is clear that the
coefficients to LOGPBS and LOGPWS add up to
one in all relations. Moreover, it seems that the price ratio of beer to spirits is to some extent more
important than the price ratio of wine to spirits.
+0.012 TREND + seasonal dumConclusion
It seems that the market share of wine has increased because of changing drinking habits and
not because of changing price relations.
Models for the market share af spirits
The relations for the market share of spirits present some multicollinearity problems, in this case
because of the parallel behaviour of the beer / spirits and the wine/ spirits price ratio. The fitted basic model is:
LSTOT = INT +2.54 LOGPBS - 1.54 LOGPWS +
0.000 TREND + seasonal dummies,
in which only the coefficient to the beer / spirits
price ratio is significant. The negative sign of the
coefficient to the wine/ spirits price ratio is
unexpected, but as the coefficient of the beer / spirits price ratio is correspondingly high, this is probably due to multicollinearity.
If the trend is excluded, the model becomes:
LSTOT = INT +2.65 LOGPBS - 1.62 LOGPWS +
seasonal dummies.
Even this relation suffers from multicollinearity,
which is easily seen when models with only one
price ratio as an explanatory variable are fitted
LSTOT = INT + 1.14 LOGPBS + seasonal dummies,
LSTOT = INT + 1.20 LOGPWS + seasonal dummies.
Interpretation af the models for
quarterly and yearly data
In all relations based on yearly data, the trend makes a significant contribution to the model fit. For
the sales of beer, the trend parameter around the
value ~TREND = - 0.008 corresponds to a redudion
in the market share of almost 1 % per year. As the
ratio BSALE/TOTSALE is approximately 60 %,
this implies a redudion of the ratio to 59.4 %
within the following year.
For the sales of wine, the trend parameter ~TREND
= 0.030 corresponds to ayearly increase of 3 % in
the market share of wine, which in view of the
actual ratio of around 30 % gives an increase to
30.9 %within the next year.
For spirits a downward trend parameter ~TREND
is estimated within the range of between - 0.020
and -0.010, depending on whether the price ratios
are included in the models or not. As the market
share of spirits is approximately 10 %, this makes a
reduction to between 9.8 % and 9.9 % within a
year.
In the relations base d on quarterly data, the
trend estimates involve much greater uncertainty,
partly because of multicollinearity and partly because data is only available since 1990. The estimated parameter values of around ~TREND = - 0.004 for
the quarterly market share of beer corresponds to
a parameter value for yearly data approximately
four times higher, that is ~TREND = - 0.016. This is an
even greater reduction in the beer market share
than is found using yearly data for the total period
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T able l. Comparison of relative alcohol prices in 1991 and 1993
Year
Beer/wine
LOGPBW
price ratio
1991
1993
0.94
0.93
Beerl
LOG PBS
spirits
price ratio
- 0.061
- 0.070
Winel
LOGPWS
spirits
price ratio
-0.049
-0.251
0.95
0.78
1.01
0.84
0.012
- 0.180
Table 2. Comparison of market shares for the three types of alcohol in 1990 and 1993
Year
market
share of
beer
1990
1993
0.59
0.57
LBTOT
- 0.52
- 0.55
market
share of
wine
LWTOT
market
share of
spirits
0.27
0.31
- 1.31
-1.16
0.14
0.11
1978 - 1993. Similarly, the trend parameter f3 TREND
= 0.012 for the market share of wine gives a more
pronounced increasing market share than is established in the analysis of the whole period. One
possible interpretation of this is that the trend has
accelerated in recent years. For spirits the trend
did not appear significant.
The fitted models for both quarterly and yearly
data point at a significant contribution of variations in the beer / spirits or wine / spirits price ratios on the market share of spirits with coefficients
f3BS and f3 ws' which sum to one. This implies, for
instance, that a 10 % reduction in the relative
beer / spirits and wine / spirits prices causes a
decrease of 10 % in the market share of spirits,
which, if the market share is initially at 10 %,
corresponds to a reduction to 9 %. However,
because of multicollinearity, the effeds of the two
price ratios cannot be separated.
It is of course self-contradictory that a price dri-:
ven substitution is found for the market share of
spirits but not for the market shares of beer or wine. This, however, is easily explained by weaknesses of the data, as some of the substitution in disfavour of spirits is in favour of the sales of beer
and some in favour of the sales of wine, so that the
largest substitution is found for spirits. The minor
LSTOT
-2.00
-2.20
effects of changing prices upon the market shares
of beer and wine then become insignificant, and
they are to some extent considered as part of the
trend in the fitted models.
Effects af tax reductians
In June 1991, just before the tax cut on beer and wine on 1 July 1991, the consumer price index was
160 for beer, 170 for wine and 168 for spirits. Two
years later, in June 1993, the figures were 137, 147
and 176, respectively, indicating that the price of
beer had declined by 14.4 %, the price of wine by
13.5 %, and that the price of spirits had increased
by 4.8 %. Table 1 gives the relative priees as well as
the actual values of the logarithmically transformed priee ratios. It appears that the beer / wine price ratio has been almost unaffected by the tax reductions, while spirits compared with both beer
and wine have become much more expensive.
Total sales of alcohol, measured in 1 000 litres of
100 % alcohol, have inereased by only 2.5 % from
49 643 in 1990 to 50 879 in 1993, but the market
shares of all three types of alcohol have ehanged
considerably, as we ean see from Table 2 above.
The sales volume of beer measured in 100 % aleo-
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hol is almost unchanged at 29 479 in 1990 and
29236 in 1993, but the market shares have changed
so that the sales of wine have increased from
13 435 to 16 018 and the sales of spirits dropped
from 6 729 to 5 620. The sales data are presented in
Table 2 with 1990 as a reference year, as this was
the last calendar year before the first tax reduction,
and moreover relative prices were steady from
1990 to June 1991.
In the relations for the market share of spirits,
both the price ratios beer to spirits and wine to spirits are of potential importance. If both parameters
are estimated simultaneously, the estimates add
up to one, but if one of the parameters f3 BS and f3 ws
is set to zero, the remaining parameter is estimated
as dose to one. The variables LOGPBS and
LOGPWS have declined by 0.20 and 0.17, respeetively, and hence the model implies a 17-20 % reduction of LSTOT, the logarithmically transformed market share of spirits. As the market share
of spirits in 1990 was 14 %, the reduction in LSTOT
corresponds to a reduction in the market share to
below 12 % caused by the tax reductions for wine
and beer. It is remarkable that this reduetion in the
market share of spirits due to changes in the relative prices is found besides the downward sloping
trend, which considered over a three year period
gives a further reduction of approximately 0.7 %in
the market share of spirits, which added to the reduction caused by the changing price relations has
led to a further reduetion in the market share to
11 %.
During this three-year period the market share
of beer has been reduced, while the market share
of wine has increased because of the trend movement, However, when the fitted parameters for the
trends are considered, we find that the market shares of beer and wine are greater than explained by
the trend, because of the substitution caused by
the changed price relations.
The tax cuts for beer and wine, together with the
cuts for petrol, were intended to reduce the level
of border trade with Germany. The data series here show that border trade has in faet been reduced.
Sales of beer in southern Jutland have increased to
some extent, while sales of wine have increased
more sharply in southern Jutland than in other
parts of Denmark.
As noted ab ove, total sales of alcohol in Denmark have increased by 2.5 % from 1990 to 1993,
mainly because of increasing wine sales and probably folIowing the reduced levelof the border
trade. This means that even constant sales of spirits would cut back the market share of spirits, but
the reduetion in the market share for this reason is
small, only from 14 %to 14/1.025 = 13.66 %. As the
decrease in the market share of spirits to 11 % is
more dramatic, it cannot be solely explained by
increasing sales of other types of alcohol, caused
by reductions in border trade.
Moreover, the reduced levelof legal border trade with beer and wine mayaIso have reduced the
illegal border trade with spirits. Sales figures
(albeit undocumented) indicate that sales of spirits
have increased in southern Jutland, implying that
the (partly illegal) private import of spirits has
been reduced.
REFERENCES
Milhøj, A.: Virkningen af afgiftsnedsættelser på øl- og vins alget i Danmark. Nordisk Alkoholtidskrift 10 (1993): 6, 319 - 329
Milhøj, A.: Udviklingen i danske familiers øl- og vinindkøb
1990 -1993. Nordisk Alkoholtidskrift 12 (1995): 4, 181-193.
The article is a revised version of an article previously published in Danish in Nordisk Alkoholtidskrift 2/1996.
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