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Published by World Advertising Research Center Farm Road, Henley-on-Thames, Oxon RG9 1EJ, UK Tel: +44 (0)1491 411000 Web: www.warc.com |
Vol. 21, No. 4, 2002 |
Bob
Eagle
Independent Consultant
and
Tim
Ambler
London Business School
This
paper addresses the impact of advertising on the size of five European chocolate
confectionery markets: Belgium, France, Germany, the Netherlands and the UK. We
are not concerned with brands or market share. No doubt brand owners advertise
to the extent that their particular brands are advantaged. The question here is
whether it is likely that a reduction in advertising would decrease the demand
for chocolate products as a whole. The literature implies that total market
effects are unlikely but it is not one–sided. Legislators remain inclined to ban
advertising for various categories where it seems that they, at least, expect
total consumption to be reduced as a result.
Concerns
over the nation's diet are an example, especially with respect to children's
health. The Department of Health (2000) reported that four out of five children
aged between 4 and 18 regularly ate snack foods but very little fruit. This
prompted calls from the Food Commission[1]
for stricter government regulation on the promotion of so–called 'unhealthy'
foods. TV advertising is seen by critics as responsible (e.g. Lewis & Hill
1998; Holmquist 2000).
This
paper is organised as follows. After reviewing the literature on the effects of
advertising on market size and the continuing calls for banning advertising in
some sectors, we review briefly the development of the chocolate market in
Europe. We then analyse data from the five largest European chocolate
confectionery markets: Belgium, France, Germany, the Netherlands and the UK.
After discussing the findings, we propose future research and draw conclusions.
First,
we consider the generic research evidence, much of which is associated with
foods. If advertising never changes market size, at least for mature markets,
there would be no case to answer. As the answer appears to be context–specific,
we need to look a little closer. We found no previous work for confectionery
markets but some inferences may be drawn from the work on the alcohol and
tobacco markets.
Borden
(1942), in a pioneering review, concluded that advertising had no effect on
mature market size. Sturgess (1982) tested causality between total advertising
expenditure and aggregate consumption using Box–Jenkins time series analysis.
For the period 1969 to 1980 he found no relationship between them and, rather
robustly, dismissed their linkage as a myth, albeit at the aggregate level of
consumption.
Henry
(1984, 1996) and Duffy (1999) studied food markets and found no meaningful
relationship between changes in advertising spend and market size. Henry's
conclusion was that advertising could be an effective tool of competition
between brands, but in mature food markets there was no discernible effect on
the market size.
We
need to distinguish between brand advertising in static markets, where there can
be no market effect by definition, and using advertising to stimulate the market
as a whole. In the latter case, the category becomes, in effect, the brand.
Forker and Ward (1993) suggest that the category effects of generic advertising
could be different from the cumulative effects of brand advertising because it
is a coordinated effort designed specifically for one purpose – to increase
total category consumption. Table 1 summarises representative findings.
Category |
Effect |
Source |
11 (foods, drinks and wool) | 6 positive sales associations, 3 indeterminate depending on definition of category and 2 none | Forker & Ward 1993 |
Prunes, rasisns | Advertising much weaker than price and income | Green et al. 1991 |
Figs | None | Green et al. 1991 |
Beef | None | Jensen & Schroeter 1992 |
French salmon | Positive | Bjornal et al. 1992 |
Milk in Ontario | Positive | Venkateswaran & Kinnucan 1990 |
Of
course, advertising may fail to increase the category because the advertising
was poor and not because it cannot be done. The importance of this literature is
that at least the advertising was trying to increase the category which is not
necessarily true for brand advertising. In any case, no conclusion can be drawn.
Ambler
et al. (1998) analysed 156
winners of the UK IPA Advertising Effectiveness Awards between 1981 and 1994.
Krona margarine increased the margarine sector at the expense of butter, leaving
the broader yellow fats category unaffected. Viennetta ice cream dessert
similarly increased dairy product sales but not total desserts. On the other
hand, advertising Sanatogen tablets appeared to increase the multivitamins
category without cannibalising other vitamin sectors.
In
total, fewer than 20% of all the cases indicated any kind of market size effect.
Importantly, these prize winners are unusually successful examples of
advertising and might be expected to have unusually powerful effects. One
explanation for the differences in results is that it depends on how the 'market'
is defined. Ambler et al. (1998)
argue that in order to find an answer to whether advertising does affect the
overall market, it is critical to define the market first:
Markets
are of different types. There are cases where an effect clearly exists, and
there are others where careful examination has failed to find effects and
advertising, as many manufacturers usually suppose, affects only brand share
(p. 267).
Their
second conclusion was that the category effect depends on its maturity and size.
Increase is less likely if the market is large and mature. Kotler (1991) defines
the initial two phases of the product life cycle in terms of triallists and
these would be expected to be influenced by advertising. Thereafter repeat
purchases tend to dominate and the market turns to brand switching.
Ambler
and Walters (1994, pp. 15–16) define mature market as
a
market where the addition of new products and new consumers is relatively
insignificant to the whole. Product innovation is a feature of any market
and as consumers age through their own life cycles, they too come and go.
Nevertheless the characteristics of the market will not be dominated by
first time buyers. Advertising will be more concerned with reminder than
carrying new information. Most of the competition that intends to join the
market will have joined. It is apparent that, using these characteristics, a
category may grow or decline whilst remaining in the mature stage.
Before
returning to chocolate we will consider two other markets which would appear to
be similar in terms of maturity and level of aggregation: alcohol and tobacco.
Published
studies show no evidence for a causal relationship between advertising spend and
an aggregate demand for alcoholic products, although a weak correlation may
exist (Fisher 1993). Prest (1949) showed that advertising did not significantly
increase primary demand for homogeneous packaged goods such as distilled
spirits. Bourgeois and Barnes (1979) analysed the relationship between alcoholic
beverage advertising and consumption in Canada between 1951 and 1974. This study
examined the relationship between the consumption of beer, wine, distilled
spirits and total alcohol, with a variety of marketing and non–marketing
variables, and found little or no correlation between alcoholic beverage
advertising and per capita alcohol consumption. The authors concluded that total
alcohol consumption is driven more by environmental factors than by those that
firms could control in the short run.
A
number of more recent studies reached similar conclusions. Saffer (1992), of the
US National Bureau of Economic Research, found little consistent evidence that
alcohol advertising affects alcohol sales and drinking, as have other studies
(FTC 1985; Duffy 1989; Smith 1990; Lee & Tremblay 1992). Calfee and Scherage
(1994) looked at France, the UK, the Netherlands and Sweden and found similar
results. Conversely, research in France showed that increases in total alcohol
advertising correlated with reduced
sales. This is presumably explained by a switch from cheap generic wines to more
expensive, branded wines and spirits. The policy option that advertising should
be increased in order to reduce consumption further does not appear to have been
seriously considered by the French government.
This
literature supports the significance of defining the 'market' noted above:
advertising did seem to be linked with the sub–sectors (e.g. wines), but not
with the alcohol sector as a whole.
Schmalensee
(1972) and Hamilton (1972) both concluded that the impact of cigarette
advertising on aggregate consumption was statistically insignificant. The
widespread proposals to ban tobacco advertising and two voluntary arrangements,
in 1985 and 1986, stimulated a significant amount of research assessing the
impact of advertising on tobacco consumption. Waterson (1984, 1986, 1990)
concluded that advertising has little or no effect upon aggregate UK consumption
of cigarettes.
On
the other hand, McGuinness and Cowling (1975), using quarterly UK data for 1957
to 1968, found a significant relationship between advertising and consumption.
Their linear and log–linear regression models included cigarette consumption and
prices, the level of disposable income, the last quarter's level of cigarette
expenditure, advertising and health education. Bishop and Yoo (1985) obtained
similar results for the USA. These results were disputed by the industry, and
Godfrey (1986) found technical flaws in both sides of the debate which related
mainly to whether annual (no relationship) or shorter time periods were used.
Since the argument is strategic, we would side with the use of annual time
periods.
The
Smee Report (Department of Health 1992) used data from 1958 to 1987. The total
number of cigarettes was regressed against implicit average real cigarette
price, personal disposable income per head at 1970 prices, lagged advertising
with a quarterly carry–over of 0.7 for ten periods, and a lagged dependent
variable term. The results showed no significant correlation between advertising
and consumption.
Finally,
Andrews and Franke (1991) employed meta–analysis to summarise the econometric
findings on the relationships between cigarette consumption and advertising,
price and income of 48 studies from 1933 to 1990. Twenty–five of these studies
were from the USA, 13 from the UK and ten from other countries including
Australia, Finland, Papua New Guinea and Germany. The results indicate that
there is a significant relationship between advertising and cigarette
consumption that is independent of study design, although the magnitude of this
relationship varies. The positive impact of advertising on cigarette consumption
has declined over time – an observation consistent with the market maturing.
Although
the literature supports both points of view to some extent, the balance of
expectation is that, for a market as specific and mature as chocolate
confectionery, advertising will not affect market size. If, however, they are
correlated, then we should explore the situation at the level of confectionery
as a whole where we would have even less expectation of seeing linkage. We now
consider the empirical evidence for chocolate confectionery in Western Europe.
Chocolate
was first imported to Europe from the Americas by Spanish gold hunters, and the
first chocolate houses emerged in England in the 1600s (Field Museum 2002). In
the nineteenth century, brands such as Cadbury and Nestlé opened up chocolate
to the mass market.
In
the past 15 years, the cumulative volume growth in Western Europe has been 23%,
and 60% in value terms (Table 2). More recently, however, total and per capita
growth has stalled. The difference between volume consumption and value growth
is explained by inflation and changes in currency exchange rates. Predictions
are inevitably speculative but the same source forecasts 4.7% growth for 2001 to
2005, or about 1% volume growth per annum.
Year |
000 tonnes |
RSV M |
Consumption per capita (kg) |
Value per capita |
|
1987 | 1938 | 14,147 | – | – | |
1988 | 2078 | 15,468 | – | – | |
1989 | 2238 | 16,947 | – | – | |
1990 | 2419 | 18,408 | – | – | |
1991 | 2517 | 20,056 | 5.8 | 46.1 | |
1992 | 2483 | 20,195 | 5.7 | 46.1 | |
1993 | 2357 | 19,559 | 5.3 | 44.4 | |
1994 | 2262 | 19,063 | 5.1 | 43.0 | |
1995 | 2254 | 19,023 | 5.1 | 42.8 | |
1996 | 2262 | 19,279 | 5.1 | 43.1 | |
1997 | 2239 | 20,263 | 5.0 | 45.1 | |
1998 | 2314 | 21,247 | 5.1 | 47.1 | |
1999 | 2283 | 21,800 | 5.0 | 48.1 | |
2000 | 2360 | 22,768 | 5.2 | 50.1 | |
2001 | 2378 | 22,625 | 5.2 | 50.0 | |
CAGR (%) | Last 15 years | 1.6 | 3.5 | – | – |
Last 10 years | –0.5 | 1.3 | – | – | |
Last 5 years | 1.0 | 3.3 | – | – | |
Total growth (%) | Last 15 years | 22.7 | 59.9 | – | – |
Last 10 years | –4.2 | 12.0 | – | – | |
Last 5 years | 6.2 | 11.7 | – | – | |
Source: Euromonitor (2001)
|
The
countries chosen for this study account for 68% of the total European chocolate
confectionery market (Table 3). We now analyse the growth in these five
chocolate confectionery markets.
Germany |
UK |
France |
Belgium |
Netherlands |
|
Market size (000 tonnes) | 627 | 583 | 254 | 88 | 76 |
% of European market | 26 | 24 | 11 | 4 | 3 |
Category by development (kg/per capita) | 7.6 | 9.8 | 4.3 | 8.7 | 4.8 |
Source: authors' estimates based on Euromonitor 2000 |
We
selected Germany, France, Belgium, the Netherlands and the UK as distinct
markets for the 11 years from 1990 to 2000. Variables used in similar studies
are shown in Table 4.
Variable |
Source |
Advertising expenditure | Vacker & Wilcox (1992); Calfee & Scherage (1994); Duffy (1999); Wilcox (2001) |
Country | Calfee & Scherage (1994) |
Per capita income | Vacker & Wilcox (1992); Duffy (1999); Wilcox (2001) |
Consumer price index | Vacker & Wilcox (1992); Duffy (1999); Wilcox (2001) |
Market size (or per capita usage) | Vacker & Wilcox (1992); Calfee & Scherage (1994); Yasin (1995); Duffy (1999) |
Our
dependent variable was taken to be the annual percentage growth in the chocolate
market and, after consideration of those above, five independent variables were
chosen (Table 5).
Variable |
Basis of calculation |
Change in consumer price index | The average consumer price per kilo of chocolate confectionery products deflated by the inflation index. Overall consumption is expected to be elastic, i.e. the higher the retail price, the lower the consumption. |
Change in total advertising expenditure | The total advertising expenditure on chocolate brands deflated by the inflation index of advertising cost. If advertising has a positive correlation, analysis would show heavier advertising weights result in market growth. |
Per capita income | Real gross domestic product (GDP) per capita was taken as a proxy of consumer wealth. |
Time | Successive years were undertaken as an additional variable to identify underlying time–related changes (e.g. in dietary patterns). The objective was to capture a long–term trend independent of the explicit variables in the model. |
Country | Although all chosen markets have similar levels of category development, 'country' was chosen as an additional variable to track any country–specific drivers of the chocolate market growth. However tow models were taken – with and without the 'country' dummy variable. |
The
data on GDP and inflation rate were taken from Euromonitor, the Global Marketing
Information System. The consumer–related data across all the countries were
extracted from the database of AC Nielsen. Data on advertising expenditure and
advertising inflation were collected with the help of media departments of local
advertising agencies.
Analysis
An
initial analysis showed an anomalous growth in the German chocolate market at
the time of that country's reunification. To avoid undue and misleading
influences on the analysis, the data for Germany at that time were excluded.
Plotting
growth in advertising expenditure against market growth suggests little
association, as shown in Figure
1. On the other hand, the elliptical shape of the relationship between price
and market growth shown by Figure
2 provides an expectation of significance.
First,
multiple regressions were made for each individual country separately. In all
models, R–squared was around 0.027 and country parameters were insignificant
(Table 6).
Coefficients |
Standard error |
t stat |
P–value |
|
Netherlands | 0.003 | 0.010 | 0.292 | 0.771 |
France | –0.001 | 0.009 | –0.081 | 0.935 |
UK | 0.003 | 0.010 | 0.322 | 0.748 |
Belgium | 0.005 | 0.009 | 0.571 | 0.571 |
Germany | –0.010 | 0.009 | –1.081 | 0.285 |
Examination
of advertising, per capita income and price coefficients across countries
revealed no significant differences. As a result, we eliminated the country
parameter and pooled all countries. Retail price changes and time were
significantly associated with chocolate confectionery consumption (p < 0.043 and p
< 0.003) but changes in advertising expenditure were not (Table 7).
Coefficients |
Standard error |
t stat |
P–value |
||
Constant | 7.796 | 2.476 | 3.149 | 0.003 | |
Advertising | 0.016 | 0.022 | 0.740 | 0.463 | |
Per capita income | 0.470 | 0.265 | 1.770 | 0.083 | |
Time | –0.004 | 0.001 | –3.144 | 0.003 | |
Price | –0.419 | 0.202 | –2.078 | 0.043 | |
R–squared
|
0.23
|
The
size of the constant, relative to the coefficients of the variables, confirms
that this is a stable market where even the significant variables have a
relatively small effect.
To
examine the possibility of delayed effects, i.e. advertising expenditure growth
affecting sales in the subsequent year, the model was re–run with the previous
year's weight of advertising as an additional variable. The fit of the model
barely changed and there was still no significant effect of advertising weight
on market growth (Table 8).
Coefficients |
Standard error |
t stat |
P–value |
||
Constant | 8.186 | 2.525 | 3.241 | 0.002 | |
Price | –0.409 | 0.202 | –2.020 | 0.049 | |
Per capita income | 0.508 | 0.270 | 1.882 | 0.066 | |
Time | –0.004 | 0.001 | –3.237 | 0.002 | |
Advertising (current year) | 0.014 | 0.022 | 0.633 | 0.530 | |
Advertising (previous year) | –0.019 | 0.022 | –0.846 | 0.401 | |
R–squared
|
0.24
|
Table
9 shows that excluding the advertising variable did not damage the overall model
but slightly improved the fit for the remaining variables.
Coefficients |
Standard error |
t stat |
P–value |
||
Constant | 8.131 | 2.423 | 3.356 | 0.002 | |
Per capita income | 0.483 | 0.264 | 1.831 | 0.073 | |
Time | –0.004 | 0.001 | –3.351 | 0.002 | |
Price | –0.420 | 0.201 | –2.094 | 0.041 | |
R–squared
|
0.22
|
Time
is a significant negative variable, as would be expected from the downward trend
in the overall volumes over the past ten years (Table 2). Whether Euromonitor is
right to project the last five years' uplift of 1% per annum into the next five
is beyond the data in this paper. We can speculate, however, that two
demographic forces are competing. Children make up a declining share of the
population in these countries, but that is offset by increasing per capita
income which was significant at the 90% level.
The
other significant variable was price with – as would be expected – a
negative effect on market growth. Again that must be in competition with
incomes. In other words, if incomes are increasing faster than price inflation
the net price effects are unlikely to be material.
No
significant effects were found for advertising, lagged or otherwise, per capita
income or country. While we expected the results for advertising, the absence of
apparent country effects is more surprising. Although the countries share a
number of characteristics such as maturity, adjacency, membership of the EU and
per capita disposable income, we had not expected such consistency in the
results.
At
the same time, the model explains only about 24% of the variance. This result is
significant at the p < 0.01
level and is typical for analyses of this type (e.g. Vacker & Wilcox 1992;
Calfee & Scherage 1994; Duffy 1999; Wilcox 2001). We were, of course,
seeking to explain changes in market size and therefore the lagged effects of
the sales of one year on the next do not arise. They are, of course, reflected
in the relatively large constant.
This
paper was prompted by suggestions that European public health could be improved
by reducing chocolate confectionery consumption which in turn could be achieved
by reducing brand advertising in that sector. This echoes previous calls to ban
alcohol and tobacco advertising along with any advertising to children.
As
noted in the limitations section below, data were not available to analyse the
children's market separately. Much of the purchasing and consumption is within
the family context. Advertising no doubt includes younger consumers, but it
would, in general, be inefficient to target children with separate ads. Table 10
shows that there has been a slight decline in the proportion of under–15s.
Year |
Belgium |
France |
Germany |
Netherlands |
UK |
Total |
1991 | 18.2 | 20.0 | 16.3 | 18.2 | 19.2 | 18.2 |
1992 | 18.2 | 20.0 | 16.3 | 18.3 | 19.3 | 18.3 |
1993 | 18.2 | 19.9 | 16.3 | 18.3 | 19.4 | 18.3 |
1994 | 18.1 | 19.7 | 16.3 | 18.4 | 19.5 | 18.2 |
1995 | 18.0 | 19.6 | 16.2 | 18.4 | 19.4 | 18.2 |
1996 | 17.9 | 19.4 | 16.1 | 18.4 | 19.3 | 18.0 |
1997 | 17.8 | 19.2 | 16.0 | 18.3 | 19.3 | 17.9 |
1998 | 17.7 | 19.0 | 15.9 | 18.4 | 19.2 | 17.8 |
1999 | 17.6 | 18.9 | 15.8 | 18.4 | 19.2 | 17.8 |
2000 | 17.5 | 18.8 | 15.7 | 18.4 | 19.0 | 17.7 |
2001 | 17.5 | 18.7 | 15.6 | 18.4 | 18.9 | 17.5 |
Source: US Bureau of the Census, International Database, Table 094. Mid–year population by age and sex |
During
this time period, the population of the five countries increased by 4% to 228.5
million. About half of the increase was due to longevity: the population of over–65s increased by 4 million. The actual number of
under–15s, however, was
static at 40 million. It seems unlikely therefore that changes in chocolate
consumption can be attributed to any change in the population of under–15s.
No
doubt excessive consumption of chocolate is harmful along with excessive
consumption of almost anything. Apparently carrots can be dangerous. At the same
time, moderate consumption of most of these products, including alcohol, carrots
and chocolate, is beneficial. Identifying the benefits and dangers of any such
commodity, and the borderline between the two, is beyond this paper but we need
to recognise the context in order to position the role of advertising.
While
individual campaigns can not only move brands but their markets too, as witness
the winners of the IPA Awards, others have only a weak impact at the brand level
and some have none at all. Ehrenberg (1974) (and subsequently) has argued that
advertising is usually a weak force reinforcing the brand experience. In other
words, it maintains share in a competitive market and brand shares are
remarkably stable.
Yet
the literature shows that advertising does sometimes affect market size, most
obviously when the market is immature. When mature markets are thought to be
flagging, generic campaigns may reinvigorate sales but here again the picture is
mixed, even though the objective, unlike brand advertising, is specifically to
increase market size.
It
seems likely that those calling for curtailing advertising are seeking a
convenient scapegoat rather than attempting to understand either how advertising
works or when it increases category demand, or when it increases the dangers of
the product relative to the benefits. This is not to say that their solution is
wrong but only that alternative solutions to a perceived problem, such as public
health, ought to receive more careful analysis. In this particular case, namely
chocolate confectionery, curtailing advertising does not appear to be a valid
solution.
A
number of other variables could be examined to explain changes in consumption to
the extent that data are available. For example, Yasin (1995) considered the
impact of private label. Similarly under retailer control are the number and
depth of promotions that may vary from year to year. Total advertising
expenditure is only a proxy for its effectiveness. Examination of advertising at
brand level would be needed to establish effectiveness, but it is possible that
there was some variation in total impact from year to year.
Mela
et al. (1998) argue that omitted
variable bias is controlled by a macroeconomic variable (GDP in our case) and a
lagged dependent variable. Since we took the growth in sales as the dependent
variable, we suggest that the lagged variable is implicit.
Chocolate
consumption is seasonal and more associated with cold weather; this raises the
possibility that average temperature, or even rainfall, may have an impact.
Limitations arise from the data which are subject to the accuracy of the source
and the selection of years as the unit of analysis. As Godfrey (1986), among
others, has shown different time periods can affect the associations.
Finally,
lack of data prevented us from isolating the advertising seen by children, and
their consumption of chocolate, from the market as a whole. Since such
consumption is likely to be predominantly in a family context, we see no reason
to expect that our findings would be different. On the other hand, balanced
research into solutions to reduce excessive consumption, without damaging the
benefits from moderate consumption, would require more detailed research.
Chocolate
confectionery in Western Europe is a mature market where the rate of growth is
in slow decline. This study looked for correlation primarily between advertising
and the year–to–year changes in market size of five countries: Belgium, France,
Germany, the Netherlands and the UK. Since we found no significant association,
advertising cannot be driving changes in market size. We also found no lagged
effects.
As
was expected, there was a negative correlation between market size and price.
The results were consistent across the five countries. The perhaps surprisingly
low (90%) level of correlation significance for per capita income might be
strengthened with more data. The underlying trend, which works against the price
and wealth effects, was directionally of gentle decline.
These results are consistent with prior research for other categories.
The
authors are grateful to Julia Tishchenko and to executives at Masterfoods for
their valuable contributions to this paper.
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