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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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