Last week, the European Commission imposed a record fine of almost €1.5b on a group of firms found to have been involved in price fixing. Between 1996 and 2006 these firms fixed world-wide prices of cathode ray tubes which are used to make TV screens and computer monitors.
The firms involved in fixing the prices in one or both of these markets included household names such as Samsung, Panasonic, Toshiba and Philips. As these tubes accounted for over half the price of a screen this clearly had a significant knock-on effect on the amount final consumers paid. The European competition agency only discovered the cartel when it was informed that it had been in operation by Chunghwa, a Taiwanese company that had also been involved. Therefore, under the Commission’s leniency policy Chunghwa was granted full immunity from the fines.
The cartel members held frequent meetings in cities across Europe and Asia. The top level meetings were known as ‘green meetings’ as they were often followed by a round of golf. Interestingly, this is not the first time the game of golf has featured in an international cartel. In the famous lysine cartel an informant working for the FBI used the quality of the golf courses to convince the cartel members to meet in Hawaii, where the FBI had the jurisdiction to secretly record the meeting as evidence.
The screen tube cartel is one of the most highly organised cartels the European Commission has ever detected. Different prices were even fixed for individual TV and computer manufacturers. Furthermore, compliance with the cartel agreement was strictly monitored with plant visits to audit how much firms were producing. The cartel was also clearly very aware that it was breaking the law and that information needed to be concealed as some of the documents discovered stated that they should be destroyed after they had been read. One document even said that:
“Everybody is requested to keep it as secret as it would be serious damage if it is open to customers or European Commission.”
Another interesting feature of the cartel is that it occurred at a time when the technology was being replaced by LCD and plasma screens. Therefore, the cartel appears to have been partly motivated by a desire to mitigate the negative impact the declining market would have on the firms involved.
According to the Independent newspaper:
“Philips said it would challenge what it called a disproportionate and unjustified penalty. Panasonic and Toshiba are also considering legal challenges. Samsung reserved its comment.
TV makers in record 1.47bn-euro fine BBC News (05/12/12)
TV computer makers fined $1.93 billion for price fixing Corporate Crime Reporter (05/12/12)
European antitrust fines: a new wave of deterrence? EurActiv, Mario Mariniello (11/12/12)
Questions
- What is the impact of a successful cartel on economic welfare?
- Describe the impact declining demand has on firms in a competitive market.
- Why might it have been necessary for the cartel to charge different prices to individual TV and computer manufacturers?
- Why would the cartel need to audit how much members are producing?
- Why do competition authorities offer immunity to firms that inform them about cartel behaviour?
- Based on the evidence in the articles, do you think the firms involved have grounds to appeal the fines imposed?
Previous posts on this blog have discussed key principles of thinking like an economist and also whether this always makes sense. Highly relevant for this question, on her excellent Economists do it with models blog, Jodi Beggs has recently highlighted the fact that the cognitive costs of obtaining the information required to make decisions in this way can sometimes be excessive.
As an example she cites this scenario from the Cheap talk blog:
“You are planning a nice dinner and are shopping for the necessary groceries. After having already passed the green onions you are reminded that you actually need green onions upon discovering exactly that vegetable, in a bunch, bagged, and apparently abandoned by another shopper. Do you grab the bag before you or turn around and go out of your way to select your own bunch?”
I won’t go through the details of the 12 steps (see the above link) taken to infer from where the onions were abandoned that they were either:
“the best onions in the store and therefore poisoned, or they are worse than some onions back in the big pile but then those are poisoned.”
Based on this inference, the conclusion is that you should go for a take-away instead! As Beggs suggests, the level of effort undertaken to make a decision should depend upon the likelihood that this results in a more informed choice. In the above example this is highly questionable! She then provides the following example suggesting that when you obtain cash back in a store it is much better to ask for the money in small denomination notes. Whilst on face value this again seems like a strange conclusion, the economic logic provided suggests that it may be a much more rational decision than in the onion example.
Article
Just for fun: reasons not to data an economist (thanks guys)…Economists do it with models, Jodi Beggs (25/10/12)
Questions
- Can you provide some examples of decisions where the cognitive costs of obtaining relevant information is very high?
- In these examples, would this information typically result in a better decision?
- What might be the opportunity cost of shopping in the manner described in the article?
- Explain how a rational economic actor should evaluate whether to obtain more information in order to facilitate making a decision.
- The article above suggests that there are a number of benefits from requesting small denomination notes, but what might be the costs involved in this strategy?
Most real-world markets are a long way from the perfect information setting assumed in perfectly competitive markets. Many industries therefore rely heavily on word of mouth to increase demand. This is especially true in the digital age where information can spread extremely rapidly and many websites encourage consumer ratings and reviews. Here, information becomes more and more valuable as it is shared with other people.
However, the economist Joshua Gans has suggested that traditional business models are not well suited to fully exploiting the benefits of the sharing of information. This is because, whilst enthusiastic consumers spread the word, the seller has traditionally acted as a gate-keeper, maintaining complete control over who obtains the product. The problem is that this creates a friction which can dampen momentum for the product from building.
In contrast, Gans describes a novel alternative strategy that was used by the band the XX when they released their second album earlier this year. As is becoming more and more common, the band premiered the album as an online stream. However, what was unique about the XX’s approach was that they gave the stream to a single superfan. They hoped that this chosen fan would initiate the spreading of the stream amongst other fans. After a worrying delay in which he enjoyed his monopoly ownership, this is what he eventually did. Just 24 hours later the stream had been player millions of times and the site crashed under the burden.
Of course, one reason why suppliers may need close control is to be able to charge for the product. If the sharing information must involve giving something away for free, it typically makes no commercial sense. However, Gans also points out that recommendations are more credible if the information has been costly to obtain. Otherwise, it may simply be cheap talk and therefore carry little value.
The balancing act for suppliers is therefore to introduce a hurdle cost in obtaining the information whilst trying to ensure that, once it has been passed on, the recipient encounters as little friction as possible in making use of it. Gans suggests that alternative business models can be developed which achieve this balance. If these can profitably encourage the sharing of information a win-win situation for sellers and buyers is created.
Furthermore, Gans is experimenting with selling his new book about sharing information under an example of one such model. Having bought the e-book for $4.99 you will find a coupon at the back which you can pass on to a friend or family member which allows them to buy their own copy of the book for a mere $0.99. However, as he points out, there is a potential danger to this strategy:
“All my readers could form a collective and potentially buy one copy for $4.99 and then a million for $0.99.”
He has said that he plans to be report back on how the book has sold on his blog at a later date, so it will be interesting to see whether or not the experiment was successful.
The folly of replicating the physical world HBR Blog Network, Joshua Gans (17/11/10)
A shared pricing experiment for my book Digitopoly, Joshua Gans (05/10/12)
Information wants to be…..shared O’Reilly Tools of Change for Publishing, Joe Wikert (16/10/12)
Questions
- Why will the problems described above not arise in the model of perfect competition?
- What type of industries are most likely to rely on word of mouth?
- In what type of industries is the friction described above most likely to happen?
- Describe the dangers with the strategy Gans is adopting for selling his book?
- Explain whether you think these dangers are likely to arise in practice.
- How might the business model be modified to avoid these dangers?
A modern day hindrance is spam email clogging up your inbox with, for example, offers for cheap drugs or notifications that you will inherit enough money to retire to the Bahamas. A recent paper by Justin Rao and David Reiley in the Journal of Economic Perspectives investigates the economics of spam mail (which, as I discovered, from the article gets it’s name from a Monty Python sketch). Remarkably, they quote figures suggesting that 88% of worldwide email traffic is spam. Their paper then provides a number of interesting insights into the business of spam mail.
First, given that most recipients simply delete it, why is spam mail sent out? For the benefits of sending it to exceed the costs, it must be that somebody is reading and responding to it and the costs must also be reasonably low. Rao and Reiley are able to quantify these costs and benefits. They estimate that if 8.3 million spam emails are sent, only 1.8% (approximately 150,000) will reach the intended recipients’ inboxes, with the remainder being blocked or filtered out. Of these 150,000, just 0.25% (375) are clicked on. Furthermore, these 375 clicks generate just a single sale of the advertised product which is typically sold for around $50. Assuming that free entry of spammers leads to them earning zero economic profit, this means that it costs the spammers around $50 to send the 8.3 million emails.
Second, spam mail clearly imposes a considerable negative externality on society. This includes wasted time for consumers and the costs of the extra server hardware capacity required. Rao and Reiley are also able to quantify the size of the negative externality created. First, they estimate that:
“American firms and consumers experience costs of almost $20 billion annually due to spam.”
This can then be compared to the benefits senders of spam get:
“….. we estimate that spammers and spam-advertised merchants collect gross worldwide revenues on the order of $200 million per year. Thus, the ‘externality ratio’ of external costs to internal benefits for spam is around 100:1.”
They then compare this to estimates for other negative externalities such as car pollution and conclude that the size of the negative externality from spam is significantly greater.
Finally, they also point out that it is predominantly the larger email service providers i.e. Yahoo! Mail, Microsoft Hotmail, and Google Gmail who have both the incentives and resources to fund interventions to eradicate spam. For example, in 2009 Microsoft and Pfizer (the manufacturer of Viagra which faces competition from counterfeit versions often advertised by spam) financially supported the successful operation to shut down the largest spam distributor. Clearly, such operations have large positive spillovers for email users. However, as they also discuss, anti-spam technology also increases the fixed costs of competing as an email provider and they suggest that this has contributed to the increased concentration in the market.
The unpalatable business of spam The undercover economist, Tim Harford (19/07/12)
Huge spam botnet Grum is taken out by security researchers BBC News (19/07/12)
Spammers make a combined $200 million a year while costing society $20 billion BGR, Dan Graziano (28/08/12)
Questions
- Explain why free entry results in zero economic profit.
- Explain how an increase in fixed costs can lead to an increase in concentration.
- Why does Microsoft have large incentives to eradicate spam mail?
- In what ways does the externality created by spam mail differ from other forms of advertising?
- How might government policies alter the costs and benefits of sending spam mail?
Last year, an academic discovered that the only two firms on Amazon selling new copies of a classic biology textbook were charging well over $1 million (plus $3.99 for shipping!). Furthermore, when he checked the next day, prices had risen even further to nearly $2.8 million! Intrigued by this strange pricing behaviour, he started to investigate the prices further.
In oligopoly markets with a small number of players, firms must make strategic decisions taking into account how they expect their rivals will react. One option in today’s online market places is for firms to use computer algorithms which automatically adjust their prices according to the prices their rivals are charging. The results of his investigation suggested that this was exactly what was causing the prices for this textbook to be so high.
One of the firms appeared to adopt a pricing rule which set its price at 0.9983 times the price of the other firm. This seems to make sense – this firm wants to undercut its rival in order to be more likely to sell its copy. However, if both firms operated under this strategy, we would expect to see prices falling over time (see also). In contrast, the strategy of the other firm appeared to be to price 1.270589 above its rival’s price. Why would it want to try to make sure it was always more expensive that its rival? The academic’s plausible explanation was that:
“…they do not actually possess the book. Rather, they noticed that someone else listed a copy for sale, and so they put it up as well – relying on their better feedback record to attract buyers. But, of course, if someone actually orders the book, they have to get it – so they have to set their price significantly higher – say 1.27059 times higher – than the price they’d have to pay to get the book elsewhere.”
Put both of these pricing rules together and prices will continuously rise over time! This was exactly what the academic observed for over a week, until human intervention appears to have returned prices to a more sensible level.
As Tim Harford discusses in his recent blog post, it had been hoped that online market places would result in very low prices because the high degree of price transparency increases competition. Clearly the prices Amazon was initially charging for the textbook didn’t support this theory and even after human intervention prices would seem to be well above marginal production costs. However, as the blog post goes on to explain, we should not necessarily expect price transparency always to lead to low prices. Economic theory shows us that in oligopoly markets, when a small number of players interact repeatedly, they may be able to collude tacitly on high prices. Furthermore, a high degree of price transparency may help such collusive behaviour because it makes it easier for firms to detect cheating by a rival.
Amazon’s $23,698,655.93 Book About Flies (SCREENSHOT) The Huffington Post, Steven Hoffer (26/04/11)
Questions
- What are the key features of competition between book sellers on Amazon?
- What price setting rule would the two firms have to use for prices to continuously fall over time? Provide an illustrative example.
- What are the pros and cons for a firm of relying on a computer algorithm to set its prices?
- How might a firm program its price setting algorithm if it wanted to collude tacitly with its rivals?
- Can you think of any other explanations for the pricing strategies that the two Amazon sellers adopted?
