Author: Jon Guest

On 13th October 2015 the management team of SABMiller (the second largest brewing business in the world) agreed in principle to a $108 billion takeover offer from AB-InBev (the largest brewing business in the world). When the announcement was made it was clear that the global nature of the businesses involved meant that the deal would have to be cleared by numerous competition authorities from all over the world. This blog focuses on the latest developments in the European Union.

The relevant legislation in Europe that addresses Mergers and Acquisitions (M&As) is the Merger Regulation that came into force on the 1st May 2004. This legislation gives the European Commission (EC) the power to investigate M&As that are said to have an ‘EU dimension’ as they exceed certain turnover thresholds.

Businesses involved in an M&A that meet the ‘EU dimension’ are obliged to pre-notify the EC and obtain clearance before going ahead with the deal. AB-InBev formally notified the European Authorities of its intention to acquire SABMiller on 30th March 2016.

Once official notification has been received, the EC launches a Phase 1 investigation which usually has to be completed in 25 working days. The investigation focuses on whether the M&A would:

“significantly impede effective competition, in the internal market or in a substantial part of it, in particular as a result of the creation or strengthening of a dominant market position” (Article 2(2) and (3))

This is often referred to as the ‘SIEC’ test. In addition to worries that an M&A may create or strengthen ‘single-firm dominance’, the ‘SIEC’ test is also used to test for ‘collective dominance’. Collective dominance is the possibility that the M&A might make either formal or tacit collusion more likely.

The European Competition has expressed concerns that the acquisition of SABMiller by AB-InBev might significantly impede effective competition in the premium lager market. Unconditional clearance of the deal would result in the same business owning many of the best-selling premium lager brands in Europe, including Stella Artois, Beck’s, Budweiser, Corona, Peroni and Grolsh.

As part of the Phase 1 investigation, the management of the businesses involved with the M&A can have ‘State of Play meetings’ with officials from the EC. At these meetings EC staff can raise any competition concerns they have with the deal and the businesses can respond by offering to take specific actions that they hope will address any issues. The most common action is a commitment to sell of some of the assets of the newly merged business.

Any commitments must be made no later than 20 days following the formal notification of the merger and they result in the time frame for the Phase 1 investigation being extended from 25 to 35 working days.

On the 8th April, AB-InBev made a commitment to the EC to sell the SABMiller brands Peroni, Grolsch and Meantime as a potential remedy for their competition concerns. A price of €2.55 billion for the deal was agreed with Asahi – the largest Japanese brewery. The sale of the brands is subject to the acquisition of SABMiller by AB-InBev being completed. Following this commitment, the EC extended the deadline for the Phase 1 investigation to May 24th.

It appears that at subsequent State of Play meetings EC officials expressed concerns that this commitment was not enough to address fully their worries over the impact of the acquisition on competition.

On April 27th (just inside the 20-working-day deadline) AB-InBev made an extended package of commitments to the European Union authorities to try to remedy their continued concerns. The commitments now include the sale of the SABMiller breweries in Eastern Europe (Poland, Hungary, Romania, the Czech Republic and Slovakia). Part of this sale would also include the Pilsner Urquell brand – a best-selling beer in the Czech Republic – and the Drecher brand – a best-selling beer in Hungary.

If the EC decides that the deal still raises concerns and could significantly impede effective competition in the single market, then the acquisition will be referred for a Phase 2 investigation. Phase 2 investigations are far more detailed than at Phase 1 and place far greater burdens on the parties involved. They also take much longer. The initial deadline for completion is 90 working days, but this can be extended to 125 working days in certain circumstances. Taking holidays into account they could last for 6 to 7 months before coming to a final decision.

This may help to explain why AB-InBev is willing to sell off nearly all of SABMiller’s European assets in the hope of obtaining clearance for a deal at the end of the Phase 1 investigation. The company aims to finalise the takeover in autumn of this year and is therefore very keen to avoid any regulatory delay created by a more detailed Phase 2 investigation.

Its willingness to sell off the European assets also confirms AB InBev’s main motive for its acquisition of SABMiller – to gain access to new and growing markets in Africa and Latin America.

It will be interesting to see the outcome of the Phase 1 investigation on May 24th.

Articles

AB InBev accepts Asahi offer for Peroni and Grolsch Independent (19/4/16)
Asahi laps up Peroni and Grolsch to smoothe AB InBev’s SABMiller deal The Telegraph (19/4/16)
Peroni and Grolsch sold as AB Inbev and SABMiller deal nears The Guardian (19/4/16)
AB InBev offers more SAB Europe assets to win EU deal approval Reuters (29/4/16)
Peroni and Grolsch brands sold by AB InBev to Asahi BBC News (19/4/16)

Questions

  1. What threshold criteria have to be met in order for a merger to be classed as having a European dimension?
  2. Discuss the different types of decision that can be made by the European Commission at the end of a Phase 1 investigation.
  3. Compare the notification system used by the European Commission with the one used by the UK competition authorities.
  4. Discuss some of the market conditions that would make either formal or tacit collusion more likely.
  5. Discuss some factors that might make it in the interests of society for an M&A to go ahead?
  6. To what extent does the evidence suggest that M&As have delivered the benefits predicted by the managers of the businesses involved?

When people think about healthcare in the UK they tend to associate it with the NHS. However, there is a £5 billion private healthcare market. Concerns have been expressed about the lack of effective competition in this sector and it has been investigated by the competition authorities over a 5-year period.

Approximately 4 million people in the UK have a private medical insurance policy. The majority of these are paid for by employers, although some people pay directly. Four companies dominate the health insurance market (AXA PPP, Bupa, Pru Health and Aviva) with a combined market share of over 90%.

Health insurance companies purchase healthcare services for their policy holders from private hospitals. The majority of private hospitals in the UK are owned by the following businesses – BMI, HCA, Nuffield, Ramsey and Spire. Some concerns have been expressed about the lack of competition between private hospitals in some areas of the country.

After its initial analysis into the sector, the Office of Fair Trading (OFT) referred the case to the Competition Commission (CC) in April 2012 to carry out a full market investigation. This process was then taken over by the Competition and Markets Authority (CMA) when it replaced the OFT and CC. The final report was published on April 2nd 2014.

One specific region that was identified in this report as having a lack of effective competition was central London for patients with health insurance. In particular it was concluded that:

The market in central London was heavily concentrated and HCA had a dominant market position – its aggregated share of admissions across 16 specialities (e.g. Oncology, Cardiology, Neurology, Dermatology etc.) was 45% to 55%.
There were significant barriers to entry including substantial sunk costs. A particular issue for a new entrant or existing business was the problem of securing suitable sites in central London to build new hospitals and in obtaining planning permission. It was pointed out in the report that the market structure in central London had changed very little in the previous 10 years despite a rapidly growing demand for private healthcare.
HCA was charging insured patients higher prices for similar treatments than its leading rival – The London Clinic. HCA was also found to be making returns that were in excess of the cost of capital.

One of the key recommendations of the report was that HCA should be forced to sell–off one or two of the hospitals that it owned in central London to increase the level of competition.

Unsurprisingly HCA was very unhappy with the decision and applied to the Competition Appeal Tribunal (CAT) for a review of the case. During this review, economists working for HCA found errors with the analysis carried out by the CMA into the pricing of health services for insured customers.

In January 2015 the CAT concluded that the findings and recommendations of the report on insured patients in central London should be overturned and the CMA should reconsider the case. In November 2015 the CMA announced that having reviewed the case it had come to a similar set of conclusions: i.e. there was a lack of effective competition and HCA should be forced to sell off two of its hospitals in London.

HCA still claimed that the pricing analysis was incorrect because it did not fully take into account that HCA treated patients with more complex conditions than TLC and that was why their prices were higher.

On March 22nd 2016 the CMA announced that it had reversed its ruling and HCA would no longer be expected to sell off any of its hospitals. The reason given for this change in recommendation was the appearance of new entrants into the market. For example, Cleveland Clinic a US-based private healthcare provider has purchased a long-term lease on a property in Belgravia, central London. It plans to convert the office space into a private hospital with 2015 beds.

A spokesperson for Bupa commented that:

“The CMA has confirmed again that there isn’t enough competition in central London, with HCA dominating the private hospital market and charging higher prices. We ask the CMA to act now to address this gap.”

It will be interesting to see the impact these new entrants have on the market in the future.

Articles

London develops as a global healthcare hub Financial Times Gill Plimmer (31/01/16)
Competition watchdog reverses ruling on private hospitals Financial Times Gill Plimmer, (22/03/16)
CMA’s private healthcare provisional decision on remedies CMA 22/03/16
Competition problems provisionally found in private healthcare CMA 10/11/15
CMA welcomes Court of Appeal verdict in private healthcare case CMA 21/05/15

Questions

  1. Define sunk costs using some real-world examples.
  2. Why might the existence of sunk costs create a barrier to entry?
  3. Draw a diagram to illustrate why a profit-maximising business with significant market power might charge higher prices than one in a very competitive environment.
  4. What is the cost of capital? Explain why returns that are greater than the cost of capital might be evidence that a firm is making excessive profits.
  5. Draw a diagram to illustrate the impact of new entrants in a market.

A number of famous Business Schools in the UK and US such as MIT Sloan, NYU Stern and Imperial College have launched new programmes in business analytics. These courses have been nicknamed ‘Big Data finishing school’. Why might qualifications in this area be highly valued by firms?

Employees who have the skills to collect and process Big Data might help firms to successfully implement a pricing strategy that approaches first-degree price discrimination.

First-degree price discrimination is where the seller of a product is able to charge each consumer the maximum price he or she is prepared to pay for each unit of the product. Successfully implementing this type of pricing strategy could enable a firm to make more revenue. It might also lead to an increase in economic efficiency. However, the strategy might be opposed on equity grounds.

In reality, perfect price discrimination is more of a theoretical benchmark than a viable pricing strategy. Discovering the maximum amount each of its customers is willing to pay is an impossible task for a firm.

It may be possible for some sellers to implement a person-specific pricing strategy that approaches first-degree price discrimination. Firms may not be able to charge each customer the maximum amount they are willing to pay but they may be able to charge different prices that reflect customers’ different valuations of the product.

How could a firm go about predicting how much each of its customers is willing to pay? Traditionally smaller sellers might try to ‘size up’ a customer through individual observation and negotiation. The clothes people wear, the cars they drive and their ethnicity/nationality might indicate something about their income. Second-hand car dealers and stall-holders often haggle with customers in an attempt to personalise pricing. The starting point of these negotiations will often be influenced by the visual observations made by the seller.

The problem with this approach is that observation and negotiation is a time-consuming process. The extra costs involved might be greater than the extra revenue generated. This might be especially true for firms that sell a large volume of products. Just imagine how long it would take to shop at a supermarket if each customer had to haggle with a member of staff over each item in their supermarket trolley!! There is also the problem of designing compensation contracts for sales staff that provide appropriate incentives.

However the rise of e-commerce may lead to a very different trading environment. Whenever people use their smart phones, laptops and tablets to purchase goods, they are providing huge amounts of information (perhaps unconsciously) to the seller. This is known as Big Data. If this information can be effectively collected and processed then it could be used by the seller to predict different customers’ willingness to pay.

Some of this Big Data provides information similar to that observed by sellers in traditional off-line transactions. However, instead of visual clues observed by a salesperson, the firm is able to collect and process far greater quantities of information from the devices that people use.

For example, the Internet Protocol (IP) address could be used to identify the geographical location of the customer: i.e. do they live in a relatively affluent or socially deprived area? The operating system and browser might also indicate something about a buyer’s income and willingness to pay. The travel website, Orbitz, found that Apple users were 40 per cent more likely to book four or five star hotel rooms than customers who used Windows.

Perhaps the most controversial element to Big Data is the large amount of individual-level information that exists about the behaviour of customers. In particular, browsing histories can be used to find out (a) what types of goods people have viewed (b) how long they typically spend on-line and (c) their previous purchase history. This behavioural information might accurately predict price sensitivity and was never available in off-line transactions.

Interestingly, there has been very little evidence to date that firms are implementing personalised pricing on the internet. One possible explanation is that effective techniques to process the mass of available information have not been fully developed. This would help to explain the growth in business analytics courses offered by universities. PricewaterhouseCoopers recently announced its aim to recruit one thousand more data scientists over the next two years.

Another possible explanation is that firms fear a backlash from customers who are deeply opposed to this type of pricing. In a widely cited survey of consumers, 91% of the respondents believed that first-degree price discrimination was unfair.

Articles

Big data is coming for your purchase history – to charge you more money The Guardian, Anna Bernasek and DT Mongan (29/5/15)
Big data is an economic justice issue, not just a Privacy Problem The Huffington Post, Nathan Newman (16/5/15)
MIT’s $75,000 Big Data finishing school (and its many rivals) Financial Times, Adam Jones (20/3/16)
The Government’s consumer data watchdog New York Times, Natasha Singer (23/5/2015)
The economics of big data and differential pricing The Whitehouse blog, Jason Furman, Tim Simcoe (6/2/2015)

Questions

  1. Explain the difference between first- and third-degree price discrimination.
  2. Using an appropriate diagram, explain why perfect price discrimination might result in an economically more efficient outcome than uniform pricing.
  3. Draw a diagram to illustrate how a policy of first-degree price discrimination could lead to greater revenue but lower profits for a firm.
  4. Why would it be so difficult for a firm to discover the maximum amount each of its customers was willing to pay?
  5. Explain how the large amount of information on the individual behaviour of customers (so-called Big Data) could be used to predict differences in their willingness to pay.
  6. What factors might prevent a firm from successfully implementing a policy of personalised pricing?

The European Commission has recently carried out a number of investigations into the various sectors of the industry that supplies parts to car manufacturers. Firms have been found guilty of engaging in anti-competitive practices in the supply of bearings, wire harnesses and the foam used in car seats. The latest completed case relates to firms that supply alternators and starters – both important components in a car engine.

On January 27th the European Commission announced that it was imposing fines on some Japanese manufacturing companies. Melco (Mitsubishi Electric), Hitachi and Denso were found guilty of participating in a cartel between September 2004 and February 2010 that restricted competition in the supply alternators and starters to car manufacturers.

The Commission gathered evidence showing that senior managers in the three businesses held discussions about how to implement various anti-competitive practices. These either took place on the phone or at meetings in offices/restaurants. In particular the firms agreed:

to co-ordinate their responses to tenders issued by car manufacturers. This involved them agreeing on the price each firm would bid.
to exchange commercially sensitive information about pricing and marketing strategies.
which of them would supply each car manufacturer with alternators and starters.

These activities are in breach of Article 101 of the Treaty on the Functioning of the European Union (2009). The European Commissioner for Competition, Margrethe Vestager, stated that:

“Today’s decision sanctions three car part producers whose collusion affected component costs for a number of car manufacturers selling cars in Europe, and ultimately European consumers buying them. If European consumers are affected by a cartel, the Commission will investigate it even if the cartel meetings took place outside of Europe”

The fines imposed on the three businesses were as follows:

– Denso €0
– Hitachi €26 860 000
– Melco €110 929 000

How are these fines calculated? When calculating the size of the fine to impose on a firm the Commission takes into account a number of factors. These include:

the size of its annual sales affected by the anti-competitive activities.
its market share.
the geographical area of its sales.
how long it had taken part in the cartel.
whether it had previously been found guilty of engaging in anti-competitive practices.
if it initiated the cartel in the first place i.e. was it the ring leader?

In this particular case the size of the fine imposed on both Hitachi and Melco was increased because they had both previously been found guilty of breaking EU competition rules.

If a member of the cartel comes forward with information that helps the Commission with its investigation, a reduction in the size of the fine can be applied under a provision called a Leniency Notice (2006). Timing as well as the quality of the information provided influences the size of this reduction. For example, only the first firm to come forward with relevant information can receive a reduction of up to 100% i.e. obtain full immunity. This explains how Denso could be found guilty but not have to pay a fine. (This firm’s initial approach to the Commission actually triggered the investigation.) Any subsequent firms that come forward with information receive smaller fine reductions. Hitachi and Melco received reductions of 30% and 28% respectively.

If a firm accepts the Commission’s decision a further reduction of up to 10% can be applied. This is called a Settlement Notice (2008). All three firms were awarded the full 10% discount in this case.

The European Commission is currently investigating the behaviour of firms that supply car thermal systems, seatbelts and exhaust systems.

Articles

Car parts price-fixing fines for Hitachi and Mitsubishi Electric BBC News 27/01/16
EU antitrust regulators to fine Japanese car part makers: sources Tech News 26/01/16
Mitsubishi Electric and Hitachi get $150 EU cartel fine Bloomberg 27/01/16
EU fines Mitsubishi Electric, Hitachi for car part cartel Reuters 27/1/16

Questions

  1. What market conditions would make the formation of a cartel more likely?
  2. Draw a diagram to illustrate the impact of a profit maximising cartel agreement on the price, output and profit in an industry.
  3. Draw a diagram to illustrate the incentive that each firm has to cheat on an agreed cartel price and output.
  4. Why did the European Commission introduce Settlement Notices?

Recent reports in the media have included headlines such as “Sexist surcharge” and “Pink premium?” Various claims have been made that women pay significantly higher prices for similar products than men.

The Times newspaper recently published the results from an investigation it carried out on the prices of hundreds of similar products that were marketed at both men and women. The study found that those products marketed at women cost 37% more on average than similar versions that were marketed at men. Examples included:

  • Disposable razors: Tesco priced a packet of five of its own-brand disposable razors for women at £1. The key characteristic that targeted the razors at female customers was the colour – they were pink. For the same price, a packet targeted at male customers (i.e. they were blue) contained 10 disposable razors.
  • Ballpoint pens: Staples priced a packet of five pastel-coloured Bic pens marketed ‘for her’ at £2.99. A packet of five Bic pens that were not in the ‘for her’ range (i.e. they had transparent barrels) were priced at £1.98.
  • Scooters: Argos increased the price of a child’s scooter by £5 if it was pink instead of blue.

Maria Miller, the chair of the Women and Equalities Select Committee, stated that:

“It is unacceptable that women face higher costs for the same product just because they are targeted at women. Retailers have got to explain why they do this.”

A more detailed study carried out by New York City’s Department of Consumer Affairs was published in December 2015. Average prices were collected for 794 individual items across 5 different industries. The key findings were that products marketed at women were:

  • 7 per cent more for toys and accessories
  • 4 per cent more for children’s clothing
  • 8 per cent more for adult clothing
  • 13 per cent more for personal care products
  • 8 per cent more for health products

Interestingly whereas the investigation in the UK only found examples of women paying higher prices than men, the New York study found some goods where the price was higher for men.

Reports in the media have claimed that this is clear evidence of price discrimination. Although this is likely to be true, it is impossible to say for certain without more detailed information on costs.

For example, when referring to the higher price for the razors marketed at women in the UK study, Richard Hyman, an analyst at RAH Advisory, stated that:

“the packaging will be different and they will sell fewer so it could be to do with the volume”

If economies of scale and the different costs of packaging can fully account for the difference in prices between the razors then it is not an example of price discrimination.

Articles

Questions

  1. Define price discrimination.
  2. Outline and explain the three different categories of price discrimination.
  3. Could a situation where a firms charges all of its customers the same price for a good or service ever be classed as an example of price discrimination?
  4. A firm with market power may still not be able to successfully implement a policy of price discrimination. Explain why.
  5. Under what circumstances could price discrimination improve allocative efficiency?