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Faculty Economic and Business Program Master Economics: Industrial Organisation, Regulation and Competition Policy Thesis Supervisor Maarten Pieter Schinkel Author: Patrick Diamandas UvA Net ID 5942624 Date 08-06-2016
The Netherlands, a competitive beer market?
What would be the best way to identify the relevant pilsner beer market in the
Dutch hospitality industry for the competition authorities, to judge about the
forthcoming acquisition of SABMiller by Anheuser-Busch Inbev?
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Content
1.0 Introduction 3
2.0 Theory 5 2.1 Merger History 2.11 Interbrew 2.12 Ambev 2.13 Anheuser-Busch & Inbev 2.14 South African Breweries & Miller Brewing Company 6 2.2 Cartel History 8
2.3 Horizontal Mergers 9 2.4 Coordinated effects 10 2.3 Price Elasticity’s 8 2.4 Geographical Market Definition 8 2.5 Binding Contracts 9 2.6 Merger Guidelines 10
3.0 Relevant Market 11
3.1 SNIPP test 11 3.2 Price Elasticity’s 12 3.3 Cellophane Fallacy 13 3.4 Geographical Market definition 3.5 Binding Contracts 14
4.0 Merger 15
4.1 Merger Guidelines 15 4.2 Finding the relevant market 16 4.3 Elasticity’s Methods 17 4.4 Market power 18 4.5 Market Identification 19
5.0 Method 20 5.1 HHI 20 5.2 Market share deviation 20 5.3 Data reliability 21 5.4 Results 24
6.0 Concluding remarks 26 7.0 References 28
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1. Introduction
The Netherlands, a competitive beer market?
In supermarkets, multiple beer brands are offered next to each other; Albert Heijn
supermarkets, which has the biggest market share of supermarkets in the Netherlands, sells 13
different beer crates containing 24 bottles of 25-33 cl. (AH.nl, 2015). Tremblay (1988) wrote
that pilsener beer is a nearly homogenous product and the only characteristic which
distinguishes beer brands is the image created by the brand. The image is affected by the
quality and intensity of a firms advertising efforts. Tremblay (1988) used multiple previously
done researches which all stated quality between light domestic beers couldn’t be tasted.
Recent research confirmed the fact that it is hard to taste any difference: 138 beer drinkers
showed they couldn’t taste the difference between Budvar, Heineken and Stella Artois
(Almenberg, Dreber, Goldstein, 2014). A combination of displaying multiple homogenous
products next to each other would appear as a competitive market. Currently the nr 1
beerproducer in the world, Anheuser Busch InBev, is acquiring the nr 2, SABMiller. The -
research that will be done is to look at the effects on competitiveness of the Dutch beer
market after this merger.
The Dutch beermarket can be divided into 2 different markets: Bottled beer, which is largly
sold in supermarkets and draft beer, which most hospitality industry is using. The hospitality
industry pays more per liter beer than consumers in supermarkets (Baarsma & Rosenboom,
2013). Total beer sales in the hospitality industry account for 21% of total beer sales,
supermarkets 52 %, liquor stores and other shops account for 23% (Stap.nl, 2015). Previous
research of SEO (Baarsma & Rosenboom, 2013) showed supermarket sales are quite
competitive as multiple brands are sold next to each other, where in the hospitality industry,
mostly 1 brand of pilsener is being sold due to multilple factors; 75 % of beer is being sold by
licensed hospitality venues which are tied to breweries trough guarantee agreements, rental
contracts, finance and loan agreements of equipements. Baarsma & Rosenboom (2013) raised
some question about competitiveness between breweries in the hospitality industry, even
before a merger of the 2 companies with the largest market shares in the world. In the
Netherlands at the end of 2014 Heineken brands: Heineken, Amstel and Brand had a total
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market share in beer sales of 49 %, AB Inbev brands: Jupiler, Hertog Jan and Dommelsch had
a total market share of 22,2 % and SABMiller brand: Grolsch had a market share of 9,5%
(Datlinq, 2014). To satisfy the Federal Trade Commission in the US, SABMiller is selling
their 58% market share in MillerCoors (FD, 2015, October). Further disposal of market share
would probably be necessary in China, the United Kingdom and perhaps in the Netherlands.
In the Netherlands, this could be solved by selling Dommelsch to for example Bavaria (FD,
2015, October). There could be potential anti competitive effects in Great Britain because
Peroni together with Grolsch could exceed the 40% market share threshold that would state
the merger anti competitive. SABMiller and AB Inbev will not reach this 40% threshold in
the Netherlands. Grolsch should perhaps be sold due to a unfortunate construction where
Molson Coors actually dictates Grolsch. In the Netherlands, where the combined company
remains well below the 40 % market share of Heineken, Grolsch should potentially be sold
for anti competitive concerns in the U.K (FD, 2015, December). This was the only potential
threat to disallow the merger by the European Commission according to the “ Financieel
Dagblad” newspaper in the Netherlands. For competition policy, market power is important
to identify. In merger cases, it has to be understood if it will be profitable to raise prices for
merging firms. To identify market power, the market definition should be correct in both the
product and the geographic dimension (Motta, 2004). To find the relevant market the small
but significant non-transitory increase in prices test, simplified SNIPP-test could be done. If a
hypothetical monopolist of the market could gain profit by increasing the price by 5-10%, the
relevant market is chosen. In this research there will be looked at pilsner beer in the Dutch
hospitality industry with the following research question:
What would be the best way to identify the relevant pilsener beer market in the Dutch
hospitality industry for the competition authorities, to judge about the forthcoming
acquisition of SABMiller by Anheuser-Busch Inbev?
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2. Theory
2.1 Merger History
2.11 Interbrew The Belgium company, Interbrew was formed by a merger of Artois and Piedboef in 1987.
Interbrew started expanding their borders and acquired the Canadian company, Labatt
Brewing Company in 1995, the Russian Sun Group in 1999, and two United Kingdom based
breweries, Whitbread and Bash in 2000. When the Germans Becks was acquired they would
have to sell the Carling part of Bash in 2002 due to competitive constraints in the United
Kingdom. This would make Interbrew competitive with the three largest breweries at that
time; Anheuser-Busch, Heineken N.V. and Miller Brewing Co.
2.12 Ambev
Ambev originated in 1999 from a merger between the two Brazilian company’s, Brahma and
Antartica. To expand in Northern Latin America a joint venture established in 2002 between
Ambev and The Central America Bottling Corporation; Ambev Centroamerica. Subsequently
in 2003 a Southern expansion followed by the aquisition of the largest shares in Quinsa, the
largest shareholder of the largest Argentinian brewery, Quilmes (Ambev.com, 2016) .
2.13 Anheuser-Busch & Inbev
In 2004 the worldwide number three and five brewers, Interbrew and Ambev merged, where
Interbrew changed their name to Inbev and became the largest shareholder of Ambev. Inbev
became the largest brewery by overtaking number one Anheuser-Busch and number two
SABMiller. Anheuser-Busch, the creator of Budweiser and Bud Light firstly sold their most
beer in the United States before conquering the global beer market with their own brands. To
set foot in the Chinese market, they won the 2004 battle with SABMiller to take over the
Chinese fourth largest brewery, Harbin (NY Times, 2004). In 2008 the global number one
brewery, Inbev and number two, Anheuser-Busch merged into Anheuser Busch Inbev. For
this merger to occur it was necessary to sell the US part of Labatt breweries to North
American Breweries to preclude anti competitive concerns in this region. More competitive
concerns rose when Grupo Modelo, the maker of Corona beer, was acquired in 2012. This
will be covered in Chapter Geographical Market Definition.
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2.14 South African Breweries & Miller Brewing Company
South African Breweries brewed their famous Castle beer since 1895. The 1993 acquisition of
the Hungarian Dreher Brewery was the beginning of a game-changing decade of mergers and
acquisitions. In 1994 SAB entered Tanzania, Angola, Mozambique, Zambia and negotiated a
joint control with China Resources, the second largest brewery in Mainland China. The next
years Poland, Romania and Czech followed before the first day of trading on the London
Stock Exchange in 1999. In 2001 SAB was the first international brewery to enter the Central
American market and acquired Miller Brewing Company, at that time the second largest
brewery in the US, changing the company name to SABMiller. The next decade more
acquisitions followed: Colombia’s Bavaria S.A, the second largest brewer in Latin America,
in 2005, Koninlijke Grolsch N.V. in 2007, a joint venture in the U.S. with Molson Coors
started in 2008, The leading Australian brewery, Foster’s in 2011, the Turkish EFES was
acquired in 2012 and the English Meantime Brewery in 2015. Today, in 95% of the markets
where SABMiller is operating, they are the leading, or number two brewery (SABMiller,
2016). In the first figures below the brands brands of InBev are shown and in the second
figure below, the company takeovers to Form Anheuser-Busch Inbev are shown.
Source: (Inbev, 2016)
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2.2 Cartel History
In 2001 the European Commision fined 4 breweries for participating in two secret cartels on
the Belgian beer market between 1993 and 1998 (Europese Commissie IP/01/1739, 2001).
These cartels were unique because they were the first proven cartels where the most important
managers of the large beer breweries were participating. The first cartel involved market
sharing, price fixing and information exchange in the hospitality industry and retail sector
between Interbrew, the then market leader in Belgium and Alken-Maes/Danone, the number
two brewery. Those two companies together with the breweries Haacht and Martens where
involved in the other cartel in the private label industry where the market was allocated and
price wars where prevented. Interbrew and Alken-Maes/Danone were fined respectively EUR
46.487.000 and EUR 44.628.000. Haacht and Martens both received a fine of EUR 540.000.
During the Belgian investigation, Brasserie de Luxembourg Mousel-Diekirch, a subsidiary of
Interbrew, revealed a market-sharing cartel in Luxembourg as well (Europese Commissie
IP/01/1740, 2001) The largest fine of EUR 400.000,- was assigned to SA Brasserie
Nationale-Bofferding, Basserie de Luxembourg was free of charge resulting the
whistleblowing.
After a wholesale acquire increase in France, acquisition costs rose during a short period of
time and where eventually stopped in 1996 by an agreement between Heineken N.V. and
Groupe Danone/Brasserie Kronenbourg S.A. to split the market and balancing the total
volume of beer distributed (Europese Commissie IP/04/1153, 2004). In 2004 Heineken
received a EUR 1.000.000,- fine and Danone EUR 1.500.000,- for the cartel.
In 2007 the European Commission fined 3 of the 4 largest breweries for operating a cartel on
the beer market in the Netherlands. Between 1996 and 1999, the four brewers held multiple
unofficial meetings where prices and price increases were coordinated for the hospitality
industry-, private-label beer and the individual consumption market through supermarkets.
Heineken N.V. & Heineken Nederland B.V. was a giving the largest fine of EUR
219.275.000, -. Grolsch N.V. and Bavaria N.V. were giving fines of respectively EUR
31.658.000, - and EUR 22.850.000, - . InBev was free of charge because they provided
pivotal information about the cartel under the Commissions leniency programme (EC
IP/07/509, 2007). For the hospitality industry there was supposed to be a discount limit of 55
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Guilders per hectolitre (Commissie van de Europese Gemeenschappen, 2007). Furthermore,
negotiations took place to prevent users to switch brand, as it would require high costs for
breweries. The testimonies of Inbev suggested that Heineken and Grolsch refused to increase
their prices for a crate beer until the cheaper “B-quality” private label crate prices would
increase. During the meetings price increases from 9,75 to 10,75 guilders were mentioned for
a crate private-label beer in the supermarket.
2.3 Horizontal Mergers
Horizontal mergers could be motivated to exploit scope or scale economies. Wasteful
duplication could be eliminated and information flows can be improved (Pepall, Richards &
Norman, 2011). Merging firms could have reductions in fixed costs, for example the firms
can combine their headquarters, research and development, marketing and distribution
operations. If the merger leads to a decrease in variable costs, this can result in lower prices. .
The greater the cost synergy’s, the more it can benefit the consumers. If the consumers will
benefit from these synergies is dependent on the fact if the decreased competition that evolves
from a merger does not annul the potential consumer profits. Furthermore, horizontal mergers
could also be a way to facilitate a legal cartel. The new corporate entity could now control
what were formally two separate production units and achieve a joint profit-maximizing
outcome. Mergers and their accessory cost savings have two bilateral effects on prices:
downward pressure exerted by lower costs and an upward pressure, by reducing potential
market entrants. Large firms with low marginal costs can keep off potential entrants that are
afraid of competing with a firm that has low marginal costs (Pepall, Richards & Norman,
2011).
Klemperer (1987) wrote about markets with consumer switching costs. In these markets it
could be that the competitive behaviour may look collusive and lead to monopoly rents, but
induce greater competition in the early stages of the market development. He presumes that
welfare is reduced and regulatory policies should lower switching costs.
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2.4 Coordinated effects
Weinberg (2015) did research about horizontal mergers and their effect on competition. He
found empirical evidence that increases in concentrations facilitates coordination among
competitors. The research focussed on the joint venture of SABMiller and Molson Coors
Brewing Company, which was named: MillerCoors. This joint venture took the responsibility
of running the activities in the U.S and Puerto Rico of both companies. The Department of
Justice did an elaborate investigation of eight months , where the DoJ gathered extensive
information from a wide range of market participants, including the companies, rival
breweries, beer distributors and national retailers (Department of Justice, 2008) The outcome
of the research was that the proposed venture between SABMiller and Molson Coors Brewing
Company is not likely to lessen competition substantially. The most important findings were
literly: “In one of the key parts of the investigation, the Division verified that the joint venture
is likely to produce substantial and credible savings that will significantly reduce the
companies’ costs of producing and distributing beer. These savings meet the Division’s
criteria of being verifiable and specifically related to the transaction and include large
reductions in variable costs of the type that are likely to have a beneficial effect on prices. The
large amount of these savings and other evidence obtained by the Division supported the
parties’ contention that the venture should make a lower-cost, and therefore more effective,
beer competitor “(Department of Justice, 2008 p.1). Weinberg (2015) used program
evaluation techniques to track alternations in market outcomes that are corresponding with a
negative supply shock simultaneously with the start of the joint venture. A six percent
average retail price increase was found, both for the joint venture as their biggest rival, AB
Inbev, while sales volumes declined. Weinberg (2015, p.2) estimated a random coefficients
logit and a price competition model that allows for coordinated interactions. The results
indicate that emergent tacit collusion between MillerCoors and AB Inbev best explains the
data. Furthermore, Weinberg (2015) supports this conclusion of the model with qualitative
evidence from publicly available court documents and the financial reports of SABMiller and
AB Inbev.
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3.0 Relevant Market
3.1 SNIPP test
The concept of market power is central to competition policy (Motta, 2004). To define
market power for instance in merger cases it has to be understood if it would be profitable for
the merged firm to raise prices. Some modern econometric techniques are able to estimate the
effect. However, it is usually a good idea to complement the outcomes of econometric data,
especially when there is lack of data, with a more traditional approach. (Motta, 2004) writes
the approach should evaluate the market power by analyzing the operated market. The
relevant market should be defined by looking at a set of products and the particular
geographical areas where the products belong. The definition of the relevant market is the
preparatory step towards defining market power. To find the relevant market antitrust
authorities such as the European Commission and the US Department of Justice and Federal
Trade Commission are using a SNIPP test. SNIPP stands for Small but Significant Non-
transitory Increase in Prices. The idea is that if a hypothetical monopolist would increase its
prices with 5-10 %, the relevant market is defined if this would increase profit. If consumers
would switch to other products due to the price increase, the relevant market is not defined.
Motta uses the example of bananas; if a monopolist would increase prices perhaps people
would switch to kiwis. If this is the case and it would be profitable for a potential monopolist
of bananas and kiwis to increase prices with 5-10%, the relevant market is defined. If not, the
test should continue until a separate market is found. The SNIPP test could have difficulties in
a non-merger situation.
Motta (2004, p105) states the SSNIP test is a useful approach to define the market, however it
can be challenging to elaborate because a hypothetical monopoly means there is no actual
data available. There are a couple tools that can be used to work out this test: own price
elasticity, cross-price elasticity and price correlation tests. Own price elasticity is very useful
information to define the product market. If the products price goes up by 1 per cent, the
percentage change in the demanded quantity would be the own price elasticity. If very few
consumers will switch to another product it could be profitable to increase prices and it could
be likely that the relevant market is stated. But it is important to notice that a price increase
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over a certain period that did not decrease sales could be influenced by other factors. Perhaps
substitutable products had a larger price increase, change in disposable income or other
variables could have an effect as well. Therefore an econometric model that provides
statistically significant results and estimates of elasticity’s that can safely be used for antitrust
analysis should be implemented (Motta, 2004, p106). Cross-price elasticity’s derived from a
good econometric model could help understand competitive constraints from other products
on the researched product. The cross-price elasticity of two products is defined as the
percentage change of a products demand if the other product has a one-percentage change
(Motta, 2004, p107). Another way to find the relevant market is the price correlation test.
Hereby the price changes of different products are compared to see if they move together over
time. If two products belong to the same market their prices will have the same behaviour
over time. If one product has a large price increase, another product in the market could have
a large increase in demand what will lead to higher products as well. A disadvantage of the
cross-price elasticity method is the fact that multiple effects can lead to a wrong conclusion.
For example a wrong time span could lead to a wrong conclusion, as prices tend to adjust
slowly. The biggest problem with cross-price elasticity’s is the fact that multiple common
factors could induce a similar movement in product prices in different markets as for example
inflation.(Motta,2004,p108) The advantage of cross-price elasticity’s is the use of it if
products do not move together over time. Bias can cause much trouble if products prices
move together and could wrongly be found as the same market but the cross-price elasticity
test could be of use as a screening device to find out if products are not in the same market. If
a correlation coefficient between the prices of two products is estimated below a certain
threshold, this gives a strong likelihood that these products are in a different market
(Motta,2004, p108).
3.2 Price Elasticity’s
A way to identify price elasticity’s is to use a survey questionnaire. A drawback of surveys is
that hose could be biased; multiple social studies showed survey questionnaires could reveal
different preferences than actual preferences because people might not state their true
preferences. The difference between actual behaviour and stated preferences often depends
on how the interview is taken: in person, Internet or on the phone. For these reasons a
revealed preferences approach is preferred (TILEC & Howrey, 2010). This would require data
gathering of actual behaviour of market participants. Clemens & Johnson (1983) estimated
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the price elasticity’s of alcoholic drinks in Australia over the period 1955-1977 by combining
quantity sold per capita and prices to illustrate how the approach can be applied to give
insights into the structure of demand for more narrowly defined commodity groups. They
found that, within alcohol, beer and wine are necessities and spirits is a strong luxury. As they
expected, there was only a moderate amount of substitutability between the three beverages.
3.3 Cellophane Fallacy
The “cellophane fallacy” is an example where the SNIPP test did not got a proper outcome.
High price elasticity was found, but this was caused by the dominance of the firm. Dominance
of a firm was tested, however by testing if an increase of prices would increase profit, there
was overlooked to the fact that a dominant firm already has higher prices than competitive
prices, where an increase of prices would not imply higher profits. The hypothetical
monopolist, who increases prices, should be compared to competitive prices instead of current
prices. A SNIPP test would conclude a larger market should be included in the SNIPP test and
therefore find a lower market share and no dominance in the market, which would be the
wrong conclusion. In the Cellophane fallacy the US Supreme court maintained that the high
cross elasticity of demand between cellophane and other wrapping material called for a wide
definition of the market, to include all wrapping materials. During investigation they found
out the firm was setting the price of cellophane so high that consumers would have considered
substituting with inferior products (Motta, 2004, p104). The cellophane fallacy showed that a
price increase that will decrease demand should not be taken as decisive proof that the market
should be defined larger than initially was done.
3.4 Geographical Market definition
The US department of Justice Antitrust Division (2013) complained about the merger of AB
Inbev and the Mexican brewery Gruppo Modelo. The region where consumers buy their beer,
rather than were the breweries are located should define the relevant geographical market for
this merger. Pricing strategies are defined by local factors: demand, competitive conditions
and brand strength. Prices in the US consumer beer market could vary by local market.
Breweries are able to do this because arbitrage across local markets is unlikely to occur.
Consumers usually do not travel elsewhere to buy their beer. Distributors contracts with
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breweries are territorially bounded and each state has different laws and regulations regarding
beer distribution and sales. Eventually the US Department Of Justice looked at the geographic
market and divided the country in 26 distinct local markets. Pricing and promotional
strategies were based on local factors as demand, competitive conditions and brand strength.
Contracts were regionally bounded and prices varied by local markets (EC, 2015). Modelo
were forced to sell all of its brands in the US to the winemaker Constellation so the US
Department of Justice could approve the merger.
3.5 Binding Contracts
Commissioned by the royal hospitality service the Netherlands, EIM (2011), EIM (2012), and
Baarsma & Roosenboom (2013) wrote about the beer market in the Netherlands. In the
Netherlands, large breweries own much property, which imply a compulsory purchase of their
brands. One out of 6 hospitality industry property’s was owned by a brewery (EIM,2011).
Secondly, banks rarely borrow money to the risky hospitality industry, which causes many
entrepreneurs to go to breweries, who are willing to fund these entrepreneurs if they sign
contracts with a mandatory purchase of their products. Furthermore, the hospitality industry
entrepreneurs without any binding contracts with breweries can have a free choice to serve
which brand they would like. However, it can be costly to install cellar beer. This is preferred
over barrels by most bar and restaurant owners because of the essential space to store barrels.
Breweries provide these cellar beer installations if their beer is being bought. Therefore a new
bar without any binding contracts can freely choose which beer brand it wants to sell in its
bar. In the first period breweries will compete to sign a new customer. Beer prices change
every year and contractually bounded customers do not have any influences on these prices.
Only there discounts could be regulated. When a bar owner has a cellar beer installation of
Heineken, it is said the switching costs are low because they can switch brewery in a couple
months. However, switching brewery could be less attractive because of the cellar beer
installation that will have to be paid to the brewery. The new brewery where you will buy
your beer from is most likely to pay for the beer cellar installation (EIM,2012). This, on the
other hand lowers the bargaining power, which could provide a useless switch of brewery.
The fact that switching costs are low does not causes many hospitality owners to switch
breweries. In 2012, 85 % beer revenue in the hospitality industry was generated by companies
that are bound to a brewery in one of the three ways of binding explained before.
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Due to these three reasons only 2.4 % of bars, switched brewery per year (Baarsma &
Rosenboom, 2013). Mostly non-bound bars switched in the category non-bound: 26.4 %
switched brewery within six years. For the property bounded hospitality industry this was
0.3%, finance bound was 16% and for cellar beer installation leased bound contracts, 14.5 %
switched in six years (EIM, 2012).
4.0 Merger
4.1 Merger Guidelines
The Herfindahl Hirschman index will be used to determine if a merger could be anti-
competitive. The HHI index can be calculated by summing the squared market shares of all
firms in the particular market. It is desirable to include all firms in the calculation; however
small shares are not critical as they wont affect the HHI significantly (The U.S. Department of
Justice & Federal Trade Commision, 2010). The European Commission (C 31/7, 2004) has
set the following thresholds:
The Commission is unlikely to identify horizontal competition concerns in a market with a
post-merger HHI below 1000. The Commission is also unlikely to identify horizontal
competition concerns in a merger with a post-merger HHI between 1000 and 2000 and a
increase below 250, or a merger with a post-merger HHI above 2000 and a increase below
150, except where special circumstances such as, for instance, one or more of the following
factors are present: A merger involves a potential entrant or a recent entrant with a small
market share. One or more merging parties are important innovators in ways not reflected in
market shares. There are significant cross-shareholdings among the market participants. One
of the merging firms is a maverick firm with a high likelihood of disrupting coordinated
conduct.
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4.2 Finding the relevant market
To conclude if the merger of Ab Inbev and SAB Miller will be anti-competitive, the European
commission should do research about multiple factors to determine the relevant market.
Previous research of beer brewery mergers showed beer is not always a national market; in
the US the country was divided into 26 regions were different prices for beer was maintained.
In the Netherlands, taxes are the same across the country and most supermarkets have
national promotions, which doesn’t change beer prices per region in supermarkets as
determined in the US for the Merger of Ab Inbev and Modelo. However in the Netherlands,
the prices for beer vary per client for the hospitality industry. Research of EIM (2011) showed
a difference in quantity discounts per client, which was explained by the way of binding to the
brewery. To determine the relevant geographical market in the Netherlands their should be
looked at the distribution of contracts throughout the Netherlands. In figure 1 on the next page
it can be seen that market leaders in the beer market are clustered in certain regions. From all
brands below it can be seen that they are all market leader in the municipality of the location
of the brewery except for Brand and Amstel; the Brand brewery is located in the same
municipality as the Gulpener brewery which is the market leader in that municipality,
however in all the direct surrounding municipalities Brand is market leader. The original
Amstel brewery is located in the same municipality as the original Heineken brewery. It can
be concluded that near breweries people drink more beer of that particular brand. The reason
should be determined to find the relevant market for anti competitiveness.
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Figure 1: Beer market leader per municipality (NRCQ, 2015)
4.3 Elasticity’s Methods
It could be possible that breweries have more market power in that region because people
prefer the beer brand. A research of revealed preferences should be conducted to determine if
people prefer particular brands in particular regions to find out if certain brands have more
market power in certain regions. This is preferred above surveys (TILEC & Howrey, 2010).
To find out these revealed preferences there could be looked at promotions. In the retail
business it would be possible to find out if certain brands are revealed preferred over other
brands. It might be the case that people don’t like a particular brand and would never buy this
product. Research has shown it is difficult to taste any difference between pilsner beer brands
(Almenberg, Dreber & Goldstein, 2014) However it could be that a certain person likes to
drink beer but would never drink a beer of a certain brand because of its image. Promotion
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research in the retail industry should be combined with amount of sales to notice potential
preferences between beer brands. Revealed preferences in the hospitality industry are more
difficult to investigate due to possibly more factors: Do people prefer a certain bar because
they serve that particular brand or price of beer? Do people come to a bar for the combination
of wine, beer and available spirits? Or does it depend on other factors as music, particular
visiting people, sound system, et cetera. Multiple researches throughout the Netherlands
should be done to find out the own price elasticity’s and cross-elasticity’s. A method used in
the past by Clements & Johnson (1983) combined quantities of sold of beer, wine and spirits
with prices for a period of twenty-two years to discover price elasticity’s. A comparable
research could be done in the Netherlands, but to find proper elasticity’s perhaps entire
country sales have a different elasticity than for example a bar or a restaurant. In the
hospitality industry most beer is being bought in bars, where wine is preferred in restaurants
(EIM, 2011). Data from sales quantities from restaurants should be compared with prices
restaurants pay for their drinks. The same would apply to bars and clubs. Another possibilities
to find out elasticity’s would be field research: for example a popular bar where there are
spirits promotions. Do these promotions cause beer sales to decrease compared to when there
are no promotions. This could be done between two multiple beer brands or other drinks as
well to identify the cross-price elasticity’s.
4.4 Market power
Furthermore, a reason for more market power in a certain region could possibly be explained
by the fact where EIM (2011), EIM(2012) and Baarsma & Rosenboom (2013) wrote about:
binding contracts. These researches showed that the hospitality industry with a binding to the
brewery tend to pay more for their beer than without a binding contract. The largest deviation
of a hectolitre discount was found with contracts that were property bounded. To discover the
relevant market, the European commission should link the bounded contracts to the regions.
Hereby it could be seen if certain breweries have more power per region than other breweries.
EIM (2011), EIM(2012) and Baarsma & Rosenboom (2013) used data from the Royal Dutch
Hospitality database HorecaDNA. This database however does not provide data about
brewery contracts per region, only national data is provided. The research that has been
conducted by EIM (2011) should be repeated, but this time with additional information. EIM
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(2011) gathered information about the hospitality industry and their contracts. A proper
research should be done to determine which breweries have bounded contracts per region to
determine the relevant market. In the Netherlands 85% of the beer revenue in the hospitality
industry comes from bounded venues. If certain breweries have a larger share bounded
contracts in a particular regions, this could result in more market power. Therefore it could be
profitable for a hypothetical monopolist in that region to increase prices 5-10 % higher than
competitive prices in a certain region, which would imply that to be the relevant market
regarding the SNIPP test.
4.5 Market Identification
A possible focus with the SNIPP test to identify the right market is the previously mentioned
cellophane case. In the Netherlands the taxes on alcohol are higher than Germany, especially
on spirits but also for beer and wine. This causes consumers and even hospitality industry
owners to illegally buy their drinks across the border. Interviewed wholesale employees told
they regularly found across the border bought wine, crates of beer and spirits in the storage of
customers when they delivered their products there (Kruis & Schreijenberg, 2013). Bottled
beer, which is cheaper in the Netherlands than draft beer (EIM, 2011) could be included in the
market as a possible substitute for draft beer. In large bars where most beer is consumed, one
of the reasons they prefer draft beer to bottled beer is the storage space necessary for bottled
beer compared to the beer cellar installation. To include bottled beer in the market could
possible provide comparable problems that occurred with the cellophane case. The market
was too largely defined due to the inclusion of inferior products to the SSNIP-test. This could
happen because the prices of cellophane were already high and a price increase would make
consumers substitute to inferior products. Bottled beer could possible not be excluded with a
cross-price elasticity test as well as because bottled beer prices increased when draft beer
increased as well over the last decade (EIM, 2011).
20
5 Method
5.1 Herfindahl Hirschman Index
After the relevant market is found, the HHI can be estimated. The Netherlands is divided into
12 provinces where beer breweries have different market shares. To have an idea about the
distribution of market shares in the Netherlands and to see that the Netherlands might have to
be divided in multiple regions to conduct a proper research with a SSNIP, market share data
from the hospitality service sector is being used to gain insights. Data is obtained from the
second quarter 2014 (Datlinq, 2014). HHI is being calculated by summing the squares of the
market shares of the largest shareholders before and after a possible merger between Ab Inbev
and SABMiller. Speculations in the media (FD,2015) suggested a disposal of Dommelsch to
Bavaria could be a solution to satisfy the competition authorities. This option is also included.
The option were Grolsch would be sold is not included as Grolsch is the only noteworthy
brand from SABMiller that is included in the dataset. To determine market shares per
company, the owned brand market shares are summed per company. Heineken, Amstel,
Brand are owned by Heineken B.V..Ab Inbev owns Hertogh Jan, Dommelsch and Jupiler.
SABMiller owns Grolsch and Bavaria is not owned by another larger brewery.
5.2 Market share deviation
To determine if a merger approval should focus on an entire country or a particular region,
statistics could provide insights. To determine if the market share of a particular region
actually differs significantly from the country’s market share a two-tailed one-sample t test
could be done; A two-tailed test is done whenever the alternative hypothesis specifies that the
mean is not the same to the value of the null hypothesis (Keller p 366, 2014). A value that
deviates more than twice the standard deviation can be seen as an outlier. Outliers normally
should be checked to determine that they are not the result of an error in recording the values.
However, outliers can also represent unusual observations that should be investigated (Keller
p 118, 2014). For this research it could be usefull to determine those outliers as they imply to
be different.
The following hypotheses are used:
21
H0: µi = µi0
H1: µi ≠ µi0
Where the country’s market share per brewery is compared to the market share per i province
in the Netherlands.
The market shares per province are compared to the nation market share by:
- calculating the sample standard deviations of the 12 provinces
- determine the upper and lower bound of outliers that deviate more than twice the standard
deviation from the population mean.
Sum of squared differences = Σ (µi-µi0)2
Sample variance = ! (!!!!!")! !!!
Standard deviation = ! (!!!!!")! !!!
The upper and lower bound of the sample to determine outliers is twice the standard deviation
from the sample mean and will be calculated per brewery owner. This can indicate if it could
be assumed with a probability of 0,95 that the certain value deviates from the population
mean.
5.3 Data reliability
Data is obtained from Datlinq. The data is gathered through 25.000 venues in the hospitality
industry representing al the main hospitality industry segments: attractions parks, bar, cafés,
event centers, hotels, hostels, nightclubs, entertainment, restaurants, societies , sports clubs,
entertainment and culture (Datlinq Market Monitor Drinks Q2, 2014). Baarsma &
Rosenboom (2013) wrote there are over 45.000 venues of cafes, hotels and restaurants in
2012. A limitation of the data could be the sample size of 25.000 venues. The data represents
markets shares of breweries per province and provide the national market shares as well from
the Netherlands. To identify market power it could be of use to have the information about the
brewery that have a binding contract with particular venues in a particular region. This could
possible provide smaller regions than the provinces that are used as geographical market for
this research. Unfortunately this information was not available. If however this data provides
an indication that brewery provincial market shares actually differ from the nations market
22
share, it could indicate certain breweries have different market power in particular regions.
Another shortcoming of the data set could possible be the smaller brands that are not named
in the dataset besides the main selling brands: Heineken, Amstel, Brand, Grolsch, Jupiler,
Bavaria, Hertogh Jan and Dommelsch. The remaining smaller brands have a market share of
12,9% in the Netherlands but it is not shown if some brands are owned by the larger already
mentioned brands. This could possibly have an effect on the market shares and therefore the
HHI index results. Furthermore, it could have an effect as well on the comparison between the
nation market shares compared to the province market share.
5.4 Results
The HHI is calculated based on the market shares per brewery per province and compared
with the nations HHI.
Market Shares in % per brand per province in Q2 2014 (Datlinq, 2014) DR FL FR GE GR LI NB NH OV UT ZE ZH NL
Heineken 28,1 47,8 41,1 33 40,3 12,2 20,1 45,4 24,6 32 39,6 47,5 34,4
Amstel 11,3 4,1 12,4 4,4 7,2 5,6 4,9 14,6 2,4 8,5 4,2 4,6 7,3
Brand 3 1,7 4,7 6,3 6,6 26 6,9 4,4 5,3 4,9 7,4 4,3 7,3
Grolsch 14,5 4,8 8,4 16,2 9,4 3,3 5,1 5,1 43,9 8,7 7,5 6 9,5
Jupiler 2,9 9,2 6,7 5,7 3,9 6,8 15,9 6,5 2,3 8,9 25,9 10,4 9,1
Bavaria 3,8 5,5 2 5 4,3 6,9 19,1 3,5 1,9 8,5 2 3,4 6,4
Hertogh Jan 17,5 12,9 11,8 11,6 12,6 5,7 9,3 4,6 9,6 11 3,2 10 8,7
Dommelsch 3,3 5,2 3,2 3,5 3,5 2 12 2,3 3,3 3,7 0,6 4,5 4,4
Other Brands 15,7 8,8 9,6 14,4 12,3 31,4 6,8 13,5 6,7 13,7 9,8 9,4 12,9
Market shares per company Heineken B.V. 42,4 53,6 58,2 43,7 54,1 43,8 31,9 64,4 32,3 45,4 51,2 56,4 49
AB Inbev 23,7 27,3 21,7 20,8 20 14,5 37,2 13,4 15,2 23,6 29,7 24,9 22,2
SABMiller 14,5 4,8 8,4 16,2 9,4 3,3 5,1 5,1 43,9 8,7 7,5 6 9,5
AB Inbev & SABMiller 38,2 32,1 30,1 37 29,4 17,8 42,3 18,5 59,1 32,3 37,2 30,9 31,7
Bavaria 3,8 5,5 2 5 4,3 6,9 19,1 3,5 1,9 8,5 2 3,4 6,4 AB Inbev & SABMiller without Dommelsch 34,9 26,9 26,9 33,5 25,9 15,8 30,3 16,2 55,8 28,6 36,6 26,4 27,3
Bavaria & Dommelsch 7,1 10,7 5,2 8,5 7,8 8,9 31,1 5,8 5,2 12,2 2,6 7,9 10,8
HHI Before Merger 2584 3672 3933 2630 3434 2187 2792 4365 3205 2766 3564 3849 3025
HHI After Merger 3271 3934 4297 3304 3810 2283 3172 4502 4540 3177 4009 4147 3447
HHI After Merger + Dom sold to Bav 3066 3711 4138 3104 3658 2247 2903 4443 4184 3028 3968 3940 3263
Delta HHI 687 262 365 674 376 96 379 137 1335 411 446 299 422
Delta HHI selling Dommelsch 482 40 205 474 225 60 111 78 979 262 404 92 238
23
From the results it can be seen that all provinces have a post-merger HHI higher than 2000 in
both cases. For the provinces where the delta HHI is higher than 150, European Commission
thresholds would classify this as likely to identify horizontal competition concerns (European
Commission ,C 31/7, 2004). It can be seen that the HHI of the Netherlands would increase by
422, which suggest anti competitive concerns for the Netherlands if the merger would
proceed. Even if Dommelsch would be sold it would still provide an increase in HHI of 238,
which is still above the non-concern about competitive concerns threshold. If we look at
province level with the merger without disposal of any brands the only provinces that have a
lower HHI delta than 150 are the provinces Noord-Holland and Limburg. Those provinces
would classify as unlikely to identify horizontal competition concerns. If Dommelsch would
be sold to Bavaria, the provinces Flevoland, Limburg, Noord-Brabant, Noord-Holland and
Zuid-Holland would be classified as unlikely to identify horizontal competition concerns. On
the contrary, the provinces Drenthe, Friesland, Gelderland, Groningen, Overijssel, Utrecht
and Zeeland would not be classified as unlikely to identify horizontal competition concerns in
both cases. If Grolsch would be sold to a non included company in this dataset, the merger
could possible be classified as unlikely to identify horizontal competition concerns. This is
simply explained by the fact that Grolsch is the only brand from SABMiller that is taken into
account in this dataset. Another brand from SABMiller, Peroni is probably included in the
other brands section. However the region distribution determined by the SSNIP test might
not be the 12 provinces, it does show that there might be a difference between regions in the
Netherlands as regards to breweries and their potential market power.
24
To determine differences between a province market share and national market shares,
standard deviations were calculated to determine if certain provinces are outliers and therefore
suggest particular breweries to have a different market share than the nations market share
with a probability of 0,95.
Market Shares per brewery per province in Q2, 2014. DR FL FR GE GR LI NB NH OV UT ZE ZH NL
Heineken B.V. 42,4 53,6 58,2 43,7 54,1 43,8 31,9 64,4 32,3 45,4 51,2 56,4 49
AB Inbev 23,7 27,3 21,7 20,8 20 14,5 37,2 13,4 15,2 23,6 29,7 24,9 22,2
SABMiller 14,5 4,8 8,4 16,2 9,4 3,3 5,1 5,1 43,9 8,7 7,5 6 9,5
AB Inbev & SABMiller 38,2 32,1 30,1 37 29,4 17,8 42,3 18,5 59,1 32,3 37,2 30,9 31,7
Bavaria 3,8 5,5 2 5 4,3 6,9 19,1 3,5 1,9 8,5 2 3,4 6,4 AB Inbev & SABMiller without Dommelsch 34,9 26,9 26,9 33,5 25,9 15,8 30,3 16,2 55,8 28,6 36,6 26,4 27,3
Bavaria & Dommelsch 7,1 10,7 5,2 8,5 7,8 8,9 31,1 5,8 5,2 12,2 2,6 7,9 10,8
Variance
Standard deviation 2 times s d
lower bound market share
higher bound market share
Heineken B.V. 101,0 10,1 20,1 28,9 69,1
AB Inbev 46,5 6,8 13,6 8,6 35,8
SABMiller 124,6 11,2 22,3 -12,8 31,8
AB Inbev & SABMiller 121,8 11,0 22,1 9,6 53,8
Bavaria 23,3 4,8 9,7 -3,3 16,1 AB Inbev & SABMiller without Dommelsch 114,9 10,7 21,4 5,9 48,7
Bavaria & Dommelsch 55,4 7,4 14,9 -4,1 25,7
The following hypotheses were used
H0: µi = µi0
H1: µi ≠ µi0
Where the country’s market share per brewery is compared to the market share per i province
in the Netherlands.
The upper and lower bound of the sample to determine outliers is twice the standard deviation
from the nations mean and is calculated per brewery owner. This can indicate if it could be
assumed with a probability of 0,95 that the certain value deviates from the population mean.
25
For the province Noord-Brabant the null hypothesis would be rejected for the breweries: AB
Inbev, Bavaria and a combination of a hypothetical merger between Bavaria and Dommelsch.
For the other breweries and brewery combination the null hypothesis will not be rejected and
based on this test it could not be said that the breweries market share deviates from the
nations market share of that particular brewery.
For the province Overijssel the null hypothesis would be rejected for the breweries:
SABMiller and a merger between AB Inbev and SABMiller. For the other breweries and
brewery combination the null hypothesis will not be rejected and based on this test it could
not be said that the breweries market share deviates from the nations market share of that
particular brewery.
In the provinces Drenthe, Flevoland, Friesland, Gelderland, Groningen, Limburg, Noord-
Holland, Utrecht ,Zeeland and Zuid- Holland the null hypothesis will not be rejected and
based on this test it could not be said that the breweries market share deviates from the
nations market share of that particular brewery in those provinces.
26
6. Concluding remarks
To be able to identify the relevant pilsner beer market in the Dutch hospitality industry there
are a couple important things that need to be investigated before the competition authorities
could judge about the forthcoming acquisition of SABMiller by AB Inbev. Only looking at
market shares of sold beer in the Netherlands might not be the proper way as showed before
in for example the merger of AB Inbev and Modelo in the United States. Different regions
might be considered as different markets instead of an entire country. To find these relevant
markets the competition authorities should do an SSNIP-test. To properly do this test, some
price elasticity’s in the pilsner beer industry in the Netherlands would be necessary to
ascertain. A combination of field research for revealed preferences together with a similar
research as Clements and Johnson (1983) used to determine elasticity’s, should give a reliable
elasticity that can be used to determine the relevant market. The failed conclusion by the
competition authorities where cellophane was determined as a larger market should be seen as
an example to determine the relevant market because there could be some similarities with the
cellophane case. The reason prices of draft beer are structurally larger per litre than bottled
beer in the Netherlands is explained by market power by previous research of EIM (2011),
EIM (2012) and Baarsma & Roosenboom (2013). This warns for the execution of the SSNIP
test to not overestimate the size of the market. Furthermore an important part of the research
should be taken into account are the binding contracts in the hospitality industry. A further
analysis of the geographical location of the bounded contracts would give new insights in the
possibility to switch breweries for an amount of hospitality industry owners. 1 out of six
venues is owned by a brewery so determined price elasticity’s could possibly not apply to
property bounded hospitality industry venues as switching can be more difficult. If price
elasticity’s are measured, the SSNIP test will provide information about the relevant market.
These facts make it difficult to estimate the actual market power of a brewery. Knowing there
where multiple cartels in the beermarket. The European commission should be extra cautious
by allowing a merger of this size. The Herfindahl Hirschmann Index indicated that the merger
between AB Inbev and SABMiller can be declared as anti competitive in the Netherlands.
Data analysis from the twelve provinces in the Netherlands shows with a probability of 95%
that the market has a different distribution of market shares of Bavaria and InBev in Noord-
Brabant and for SABMiller in Overijssel compared to the nations market shares. This could
causes some anti competiveness concerns for these particular provinces. The calculation of
the HHI based on twelve separate provinces in the Netherlands gives new insights to the
27
distribution of potential market power as market shares differ between the regions and could
be determined by the location of the brewery as shown by the market leaders per
municipality. While breweries own many venues and market shares are different per location
it could be the case that these ownerships strengthen the market power of the particular
brewery that is already a market leader in that particular region. With the assumptions that the
geographical market in the Netherlands can be divided into the twelve provinces, and the
product market would be pilsner beer in the hospitality industry, it can be said that the merger
would rise anti competitive concerns for the potential merger between AB Inbev and
SABmiller. The assumption about the geographical market and product market are
speculative and the European Commission could approach the markets by the in this research
shown analysis to have a better estimate of a merger allowance. The HHI and the compared
market shares in this research gives an assessment that it could be a possibility to split up the
Netherlands as a relevant market into smaller geographical regions before determining if a
merger should be allowed.
28
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