#3/25: Explaining Social Behavior

The first chapter is generally about explanations in science and more particularly in the social sciences. Elster emphasizes that just-so stories are often not enough. Imagine a story where someone didn’t go to college because he didn’t knew that he could. Does this explain why? No, we should ask why he didn’t knew that he could go to college. The author presents different theories about social science and comes back to them later.
Often mechanisms are used to explain behavior, he argues that outcomes are more important than the internal mechanism. E.g. if people behave with bounded rationality then this doesn’t mean that they calculate utilities for each choice but that they behave in a way that is similar to the prediction made by the mechanism of bounded rationality. There are several other mechanisms, like cognitive dissonance, loss-aversion, reference dependence, etc. The field of behavioral economics covers them mostly today.
The last chapter of the first part talks about interpretation and explanation. Elster argues that the basically the same. E.g. in interpreting a text, one explains its intent or the behavior.

The second part talks about the mind. The authors distinguishes between two types of motivations. There is wanting something, i.e. with the aim to put effort into fulfilling the want and wishing something, i.e. without the aim to put effort into the wish. This is quite interesting and he uses this definitions to argue why people don’t achieve what they planned to achieve because they only wished it not wanted it. Furthermore, there are different kind of requirements of motivation, i.e. general interest, reasoning, e.g. I want a good job therefore I should learn things and passion.

The second part talks about self-interest and altruism. He discusses the view, that I take, that all action is based on self-interest, e.g. altruism is based on an internal want to feel good about oneself. Secondly, there is the great mechanism of reciprocity, i.e. if somebody helped you, you will probably help him in the future.

Myopia and foresight go into the process of motivation for longer time horizons. Planning is in important process which is often underestimated. The characteristic of discounted value or utility is important there. If somebody values the present much stronger than the future, they will be reluctant to give up present utility for future utility. Here comes the weakness of will into play. Elster argues that weakness of will can be explained either by wishful thinking or temporary change in motivation or change over time.

The second last chapter in this section talks about beliefs which are a important topic in behavioral economics. A interesting observation is that experts do often worse than simple statistical models in decision making. I wrote about Atul Gawande who introduced check lists into surgery with phenomenal results. Or I read about using decision charts for classifying deceases which also worked better than a group of experts.
Secondly, there is the big field of biases. Some biases are regression to the mean, i.e. over time a deviation to the mean will move toward the mean. One study which ignored this was about air pilots. The researchers tested if praise and punishment helps to learn better. They praised the pilots if they done well and punished them if they didn’t. Often pilots did worse after they were praised – the researchers thought that it was because of the praises but it was just the regression to the mean, i.e. naturally the couldn’t do well every time.
An other biases is the availability bias, i.e. people see things that just happened as more important. You can see this for example that after a flood more people will buy a insurance and it will slowly decay over time. There are tons of different biases. The RSOAP created a neat file which includes lots of different cognitive biases.
Other belief mechanisms are magical thinking, i.e. you act as if you can influence the outcome but you can’t and rationalization, i.e. you make up a story to explain your behavior ex-post.

The last chapter in this part covers emotions. Generally, emotions influence actions but they decay quite fast. I.e. emotional behavior, e.g. attacking someone because of rage can be controlled if you just take the time to calm down.
An interesting aspect is rationalization of emotions. Elster presents the following example: Somebody envies his neighbors’ car, but he learned that envy isn’t good. Therefore he rationalizes that his neighbor got his wealth/car by immoral means because if he wouldn’t he would realize that he could have got the car if he learned more or worked harder but so he hasn’t to.
An other interesting, and quite famous fallacy in economics, is the sunk-cost fallacy. That is, somebody continues a unprofitable activity instead of accepting failure and doing something profitable. You probably heard it lots of time, e.g. “we invested $20m into this project, we can’t just let it die” or people who are continuing their career although they rather would do something else. The interesting trait of this fallacy is that it becomes worse in time.

The third part talks about actions. Elster defines action as intentional behavior or goal-oriented behavior, i.e. reflexes aren’t action. Action is framed by external and internal filter, e.g. legal or economic restriction or internal filters like beliefs. Furthermore, action depends on desire and opportunities.

Action is also often depended on situations. E.g. people can be talkative at work but be rather silent at home. Elster takes this to explain why kids are often so different at school and at home. Furthermore, he takes the stance that character is often more local than global, i.e. response is situational.
The next chapters talk about rational choice and rationality. Generally, rationality is subjective, i.e. each one’s utility is composed of different parts but we are constrained by costs, i.e. search cost or more general transaction costs and opportunity costs.
He talks about some paradoxes, e.g. voting or the lawn-mowing paradox. That is, that a person would let his lawn mowed by someone else for $x, but also wouldn’t mow an other’s lawn for more than $x. This can generally attributed to loss aversion.

The last chapter talks methods that help dealing with this irrationality. One is adding penalty a priori, e.g. if you eat more than two bars of chocolate you aren’t allowed to watch TV. Empirically, this doesn’t work so well. An other is adding premiums a priori which is just the other side of the coin.
One interesting method is eliminating choice, i.e. just buying one chocolate bar.

The second to last part talks about links between behavior and evidence from natural sciences.
Elster talks about experiments where animals got rewarded a treat for different behavior. In one case the animal got one treat after X times pushing a trigger and the alternative was a machine where you got randomly treats. Interesting enough, the mice favored the latter and it was harder to unlearn. He argues that people and animals try to find patterns and people often think that they see patterns and try to activate a trigger although it was purely random.
An interesting application was natural selection as a mechanism for providing rationality. One example would be competing firms in a market. In the long run only the rational firms will survive, i.e. the mechanism indirectly filters the outcome.

The last part talks about interactions. Elster takes a whole chapter about unintended consequences which is easily one of my favorites topics. I wrote a bit about the topic so I will just talk about the hog effect which, at least, I observe quite often. The hog effect is that future change isn’t anticipated in forecasts. One example is the increase of cigarette taxes in 1993 in Germany. The gov forecast that the tax increase will increase overall tax dramatically. Instead the consumers smoked less, switched to other products which weren’t affected by the tax and some companies created cigarette-like products which didn’t fall under this tax. In the end, the tax increase dramatically lowered the overall tax income.

An other interesting topic is that of trust. Generally, trust is incredible important in human interaction. He talked about the interesting case of diamond merchants which is a quite small community and they are relying heavily on trust. E.g. for them a verbal agreement is as good or better than a written one.
If trust is broken, then in general and of course in the diamond merchant community, ostracism will follow.

Elster points out that social norms are often not rational and can be harmful. One example is the need for mediocrity in some communities which destroys success of people. Or the mistreatment of homosexuals in the past and in some communities today.

The last chapter talks about collective belief formation which is quite interesting. One rather well-known study analyzed the drinking behavior of college students and found that most students drink more than they would like because they think others want to drink more. That leads so a too high level of drinking, also each one individually would drink far less. This is called pluralistic ignorance and basically says that nobody believes in X but everybody thinks that all other people belief in X.
Therefore, you can often see snowballing of non-conformism. That is, if enough people are non-conform than other non-conformists aren’t afraid anymore and present themselves also as non-conformists.

All in all, I really enjoyed this book. It’s a bit lengthy in parts but utterly interesting. I especially liked that Elster uses
proverbs and excerpts of novels to explain behavior which makes it more lively. I think it’s a must-read if you want to learn more about social behavior and is great if you (want to) work as a economists, social scientists or similar.

Fortune: The World’s Billionaires

You may know that Forbes published tons of different and interesting lists, one of them is The World’s Billionaires. I took a look at the data and deepened my R knowledge alongside.

Countries

Let’s start with the countries. There are 1007 persons in this data set with valid Country entries.

You can see that most billionaires are born in the US and then with a big gap in China, India, Germany and Turkey. The relative distribution of billionaires worldwide looks a big different:

It mostly took some time to become a billionaire therefore I expect China and probably India to become stronger in the future.

Age

There are a few famous young billionaires like Mark Zuckerberg but most of them are quite older. The first quartile actually starts at 54, the average billionaire is 63 and the oldest one in this data set is 100.

Education

Only 51% of these people got at least a bachelor degree, 20% has a master degree and only 8.7% earned a doctorate or PhD.
Interestingly, about 5% are drop outs and 40 of these 50 drop outs are from the US.

Martial Status

Marriage is still high for billionaires. About 83% are Married, only 7% are divorced. About 5% are widowed and there are 30 singles.

Children

Children are also rather numerous. There are 176 entries with no data, i.e. either missing or no children.
Most billionaires got either two or three children but there are some outlines with 10 children or more. And there is Sulaiman Al Rajhi who got 23 children.

Net Worth

Most billionaires own between between 1 and 3.6 billion USD. The median billionaire owns 2.1 USD. There are, of course, some famous outlines like Bill Gates, Warren Buffett, Larry Ellison and Carlos Slim Helu. The complete net worth of all these billionaires is just 3.7 trillion USD. For comparison, the total US Debt is 14 trillion, that is nearly four times as much.

Self Made?

This was for me, one of the most interesting questions. I asked myself if there are differences between inherited and self-made billionaires between countries.

I’ll pick some examples.
US 69% are self-made
China 96% are self-made
Germany Only 33% are self made

Generally Emerging/New Countries, more self made, what is expected, but US positive example for an older country.

Source

Let’s talk about the sources. Rather interesting is that industries like oil and software which sound really profitable are rather minor industries. I think that has three reasons.

     investments       realestate      diversified           retail          banking 
              84               84               57               53               40 
 pharmaceuticals       hedgefunds            media           hotels     construction 
              29               28               20               19               18 
          mining              oil          telecom             coal          finance 
              18               18               14               12               12 
leveragedbuyouts    manufacturing         software          oil&gas        insurance 
              12               11               11               10                9 

Firstly, becoming a billionaire takes time. It would be great to look at the first time someone became a billionaire, I think that you would probably see clusters, e.g. manufacturing probably started around 1940 but now there are less manufacturing billionaires.
Secondly, some markets aren’t that big. The global real estate market is probably a lot bigger than the global software market.
Thirdly, the ability to oligopolize markets. Let’s take oil and real estate. Oil is pretty much a commodity and you can distribute it world wide without problems. Real estate is locally limited, you can’t take a building block and just put it somewhere else, this limits the market power of companies in this industry.

You can access the data.csv here.

#2/25: The Economics of Organised Crime

This book is a collection of different papers about organized crime. I try to summarize some of the main points.

You can see organized crime as a state or a firm. There’s evidence for both analogies.
It offers state functions. One is the provision of public goods, like defense and law enforcement. Furthermore, often its industries are regulated to make it harder for new competitors to enter the industry. Also, one goal is to extract rents from its protégées. And of course the monopoly over coercion.
However, you can also look at organized crime as a firm or often better as a conglomerate. It’s mainly focused on the production side, e.g. the production of drugs or the trade of other things.

Besides these activities, organized crime also act in semi-legal markets. One of the biggest income sources are collusions between the crime organization and the government. Mainly by using subsidies or securing public procurement projects.
One author wrote that criminal organization often provide a framework for companies to form a cartel and then bid on public projects. The fixed price however will be higher than the market price. One paper stated that there’s no big public project where the mafia isn’t involved.

The origin of organized crime is quite interesting. The most important actor is the state. Firstly, it defines illegal markets, i.e. provides opportunities for organized crime. Secondly, it misses its chances to coercive in areas, e.g. slums where other coercive organizations overtake the monopoly of force.
Lastly, see above, it provides possibilities for rent extraction with subsidies and public interventions.
If we talk about the origin, we can also talk about the termination. Interesting enough, if markets are legalized, mafias don’t look for new business opportunities but mostly change into legal markets. Especially in families it’s outstanding how the career of the youngest generation changes from crime to legal activities.

The organizational form as a family has some nice characteristics. Firstly, it provides better control over the members which are one of the biggest source of danger for a criminal organization. This leads to high costs of exposure, i.e. high transaction costs which leads to smaller criminal organizations. Sometimes, they include outsiders to the organization but require investments like murder up front.

Besides illegal markets and public contracts, organized crime can also work in legitimate industries. Mostly, it helps to achieve oligopolies or does organized customer acquisition.
One example are ferries where members of the mafia provide each ferry company a quota of customers. In other highly competitive markets with low entry barriers, the mafia does the same thing, e.g. transportation, restaurants, etc.
One interesting aspect of mafia involvement is that firms in this industry accept that they have to pay the mafia, so that its business runs smoothly.

Generally, corruption happens more often when the distance between relationship is smaller. Especially in parts in south Italy this is prevalent. Relationships also become more important if people have great power. So you can expect more corruption with local politicians in small towns than let’s say with corner store owners in NYC.

In conclusion, I really liked the book besides of some papers which were just theoretical models and probably aimed at theoretical researchers. Otherwise, it delivers a great introduction in the economics of organized crime and is readable for people with basic economics knowledge, i.e. Econ 101, e.g. Mankiw’s Principles of Economics.

#1/25: Information Rules

I want to try out a new format which you could call “book commentary”. I’ll quote some text passages and write a short comment about each passage.

Technology changes. Economic laws do not. If you are struggling to comprehend what the Internet means for you and your business, you can learn a great deal from the advent of the telephone system a hundred years ago.

This is a great advice and I can anybody recommend to read old books about business and economics especially case studies. I already covered some old business books myself here on the blog and I’m always receptive to recommendations.

We think that content owners tend to be too conservative with respect to the management of their intellectual property. The history of the video industry is a good example. Hollywood was petrified by the advent of videotape recorders. The TV industry filed suits to prevent home copying of TV programs, and Disney attempted to distinguish video sales and rentals through licensing arrangements. All of these attempts failed. Ironically, Hollywood now makes more from video than from theater presentations for most productions. The video sales and rental market, once so feared, has become a giant revenue source for Hollywood.

Interesting enough, Hollywood is still trying to fight against piracy. The next step would probably be to offer cheap versions as a stream (ala netflix). However, people don’t want to pay too much for a video stream.
I think it may be comparable with the automotive industry in the beginning of the 20th century. There were lots of car manufactures that produced really high quality cars which were really expensive. Most people couldn’t afford a car at this time. Then came the Ford Model T, which wasn’t as fancy at these other cars but it was cheap and good enough and people bought it.
Maybe Hollywood should think about producing movies which don’t cost $200m but instead only $20m.

In competing to become the standard, or at least to achieve critical mass, consumer expectations are critical. In a very real sense, the product that is expected to become the standard will become the standard. Self-fulfilling expectations are one manifestation of positive-feedback economics and bandwagon effects.

A very interesting observation with great effects. This makes PR much more important than I thought it would be. Especially, if you apply to to startups. Signals like founding and investors become stronger. And it isn’t so much about the product and more about connects, strategic networks, PR and marketing.

The dominant component of the fixed costs of producing information are sunk costs, costs that are not recoverable if production is halted. If you invest in a new office building and you decide you don’t need it, you can recover part of your costs by selling the building. But if your film flops, there isn’t much of a resale market for its script. [...] Sunk costs generally have to be paid up front, before commencing production.

We’ve seen some movies which ran horribly in the cinema but great in DVD markets. So, there’s some recoverability. However, the movie can still suck. One method to cover the costs are upfront investments. Kickstarter is basically allowing this for a mass-market and some game studies took this approach to produce games which wouldn’t be backed by a publisher (see Doublefine Adventures).

The key to reducing average cost in information markets is to increase sales volume. Think of how a TV show is marketed. It’s sold once for prime time play in the United States. Then it’s sold again for reruns during the summer. If it is a hot product, it’s sold abroad and syndicated to local stations. The same good can be sold dozens of times.The most watched TV show in the world is Baywatch, which is available in 110 countries and has more than 1 billion viewers. [...] The shows are cheap to produce, have universal appeal, and are highly reusable.

Basically the Hollywood argument I made above. Lower the production costs but produce more variety and stimulate more innovation.

With information you usually produce the high-quality version first, and then subtract value from it to get the low-quality version.

This is really important for the customer. You don’t want to feel that you paid the normal price for the inferior product. One example are some games which come with lesser content in the normal version but still costs $50-60. Don’t do that.

The coupons are worthwhile only if they segment the market. A coupon says “I’m a price-sensitive consumer. You know that’s true since I went to all this trouble to collect the coupons.” Economist say that a coupon is a credible signal of willingness to pay. [...] What does this have to do with information pricing? Well, suppose that information technology lowers search costs so that everyone can “costlessly” find the lowest price. This means that sales are no longer a very good way to segment the market. Or suppose that software agents can costlessly search the net for cents-off coupons. In this case, the coupons serve no useful function.

I found this passage quite interesting. Basically sites like Groupon are too easy to use, so that people don’t segment themselves that good. Furthermore, there are lots of sites which offer coupon codes, so that today a sale for most online shops is probably more appropriate.

The rights management strategy is a twist on the versioning strategy described in Chapter 3. There we argued that you should offer a whole product line of information goods. The cheap versions (which can even be free) serve as advertisements for the high-priced versions.

Freemium described over 12 years ago. Interesting enough, McAfee used a freemium model since 1993 and before that they used a “pay what you think“-model, which was also quite revolutionary for that time.

Of course, a new brand can emerge that is easy to learn, thus reducing switching costs. Indeed, one strategy for breaking into a market with significant brand-specific customer training is to imitate existing brands or otherwise develop a product that is easy to learn. Borland tried this with Quattro Pro, aimed at Lotus 1-2-3 users, and Microsoft World has built-in, specially designed help for (former!) WordPerfect users.

We’ve seen this in the online market quite recently, e.g. with WordPress and tumblr. I wonder if you see a better word processor in the future.

What happens when perfect competition meets lock-in? [...] Think about the extreme case in which you face fierce competition from equally capable rivals to attract customers in the first place. Both you and your rivals know that each customer will be locked into whatever vendor he or she selects. The result is that competition indeed wrings excess profits out of the market, but only on a life-cycle basis. The inescapable conclusion: firms will lose money (invest) in attracting customers, and (just) recoup these investments from profitable sales to locked-in customers.

Normally, you would assume that lock-in leads to excessive profit in a market but it doesn’t. You can talk about quasi-profits, i.e. the lock-in needs negative investment at the start and if you locked-in a customer, he will return the investment costs over his life-time. That is, if you want to make excessive profit, you have to still rely on product differentiation and/or cost leadership.

If you give your product away, anticipating juicy follow-on sales based on consumer loyalty/switching costs, you are in for a rude surprise if those switching costs turn out to be modest.

That’s when freemium goes wrong. If you are in a market with low or non-existing lock-in costs, i.e. trash mail provider or image uploading sites, freemium probably won’t work.

An other approach is to rely on versioning by offering long-standing customers enhanced services or functionality. Extra information makes a great gift: it is cheap to offer, and long-standing customers are likely to place a relatively high value on enhancements.

I really like this idea. Often you see introductory offers, like 20% off of the subscription but after this period, you either don’t care about the price, feel ripped-off, because you have to pay more or cancel your current account and get another introductory offer.
However, if you reward long-term customers with some useful addons, they have no incentive to do the latter and probably will appreciate the extra addon. Varian and Shapiro talk about this in the book in greater length.

The beautiful if frightening implication: success and failure are driven as much by consumer expectations and luck as by the underlying value of the product. A nudge in the right direction, at the right time, can make all the difference. Marketing strategy designed to influence consumer expectations is critical in network markets.

See the quote above. Early adopters are really important and early press coverage can greatly introduce the probability of success.

The revolution strategy involves brute force: offer a product so much better than what people are using that enough users will bear the pain of switching to it. [...] The revolution strategy is inherently risky. It cannot work on a small scale and usually requires powerful allies.

The authors quote Grove’s 10X as a revolutionary metric. I got two nice examples which fit to this quote.
Firstly, Google+ which hasn’t offered a 10X and wasn’t a evolution of Facebook either. Furthermore, the group in the beta phase was too small.
An other example, are open source clones of proprietary products. More often than not, free source code or enhanced privacy aren’t 10X.

In addition to launching your product early, you need to be aggressive early on to build an installed base of customers. Find the “pioneers” who ware most keen to try new technology and sign them up swiftly.

Really important, see Crossing the Chasm.

All in all, I really liked this book. I think it’s probably a must-read for internet entrepreneurs. What I personally found really interesting to see which people endorsed this book and one of them is Eric Schmidt (Google’s ex CEO). And he said in an interview about Google+ and its chance to beat Facebook: “It’s very hard to beat a fast-moving incumbent in exactly same game in technology because it changes so quickly.

If you are interested in more detail about the content of the book, its website offers free presentation material for college courses. Great book, great writing.

25 Books in 2012


So, I decided to do an other book challenge this year. The starting date is maybe a bit late but that’s OK. This year, I want to do a reading challenge again not because I haven’t read any books but rather because I was too lazy to write some review/summary about the books I’ve read.

In comparison to last year’s challenge where I read mostly business books, this year I will read mostly books about economics and statistics. You can see the preliminary reading list in the picture. Some books may change but the volume will probably be the same.

264 days and 25 books left. Let’s start!

Visualize This


This book was sitting on my shelves for nearly two months and I finally read it. It’s written by Nathan Yau, the guy behind FlowingData.

Visualize this starts of with a intro into one of my favorites topics, i.e. data collecting and cleaning. Yau uses Python, which is a great choice for such tasks. Chapter after chapter he introduces new tools (e.g., Illustrator, R, Google Maps) and shows how to get started with them. I think that pretty much resembles the book. It’s about how to get started in data visualization and its tools.

One critique is that the target group isn’t clear, is it for programmers or graphic designers or statisticians? It’s got a bit for everybody but no thorough path through the book. The examples are quite good and I love it that he shows different steps of creating graphics. The paper and print quality is really good, which is really important for books about graphics and visualization.
All in all, I’m quite happy with this book. It shows how to start and is written by someone who is more connected to the open source/internet world than to academia or corporate one which it quite cool because you don’t have to invest in expensive software to try the examples out.

Provide services, not just products

In the last two weeks there were some discussions about (enterprise) software sales [1, 2] on hacker news. The main complaint is that software sales are often nontransparent, complicated and highly time consuming.

I think this comment sums the problem up:

As you imply, there are segments in every market. Of course there is a segment of companies with hundreds or even thousands of employees with gigantic budgets. These guys are going to do RFP’s and spend months evaluating the different payroll providers.

Then there is the segment of small guys lik me who have under 10 employees who frankly don’t need anything too complicated. You can say “I am only going to serve large enterprise customers through a complex sales process” and that’s completely fine with me. But don’t pretend to cater to my segment if you are not to adapt your model. –labaraka

The last sentences is probably the most important. Don’t pretend to serve a segment just to be “present” in this segment. If your sales process sucks for this segment then it’s better not to serve this segment at all.
Some big software companies tried to enter the SMB market but most failed. Why? I think that it is really hard to sell for 10-20 years products to big cooperations who want customized modules, pay for consultants and don’t care if a basic module costs $100k and then to try to reduce one’s product, make it easy and create a new sales process for said businesses.
The great thing about this is that there’s always a market for software for SMB even if there are big names out there. Salesforce is such an example. At the time there were big names like Microsoft, SAP or Oracle who fought over market shares for CRM systems but Salesforce decided to gather a different market – a market where people don’t have a multiple millions IT budget or even a IT staff.
But even Salesforce can’t serve the whole tail. Still, there are companies that are overwhelmed by Salesforce’s offer or don’t feel adequately served by them.

In conclusion, as a customer I want to know that somebody cares about my company or my segment. If you are just trying to be present in a segment without really caring, people will go to other companies that care. This will allow entrepreneurs to create companies for different niches that other companies don’t really care about. Care about your customers.