Many of our decisions, both inside and outside the investment world, are often based on anecdotal information, anomalies, emotions, or existing opinions. SuperFreakonomics illustrates how applying an economic approach can help us change this. Investors can use the tools described in this book, including better and more prevalent use of data, along with an an understanding of the power of incentives to make better decisions.
This final chapter focuses on the issue of global warming, but draws on many of the other concepts discussed in the book. First, the book debunks many of the misleading and exaggerated facts disseminated by the media. There appears to be scientific consensus that the earth is warming, and that humans are contributing to this. But how humans are contributing appears to be wildly misunderstood. For example, ruminants contribute 50% more greenhouse gases than the entire transportation sector! If humans changed their diets from say beef to kangaroo, it would do far more to help the environment than if they all drove hybrids.
The authors stress that negative environmental effects are due to externalities. In theory, we could determine the negative environmental externalities associated with a particular activity, tax it, and use that money to pay the costs that others experience as a result of the activity. Unfortunately, the world's climate operates under such a complex system that the authors argue this is virtually impossible.
Others believe the problem of global warming can be solved by encouraging (or perhaps forcing) people to make sacrifices. But people are not philanthropic enough to make this happen (this topic was more fully discussed in a previous chapter) and therefore this is unlikely to work on a grand scale.
Instead, they believe the challenges of global warming can be met by the same force that has solved environmental issues of the past: technological innovation. The authors describe various attempts at solving the problem of global warming. Many of them are quite simple, yet still sound effective. For more on some of these solutions and the ensuing controversies that followed, see here.
Many of our decisions, both inside and outside the investment world, are often based on anecdotal information, anomalies, emotions, or existing opinions. SuperFreakonomics illustrates how applying an economic approach can help us change this. Investors can use the tools described in this book, including better and more prevalent use of data, along with an an understanding of the power of incentives to make better decisions.
This chapter discusses some of the simple solutions that have improved the lives of humanity over time, and contrasts them with some complex solutions that have actually done more harm than good. While people love to complain and refer to the good old days when everything was better, the authors argue that the reality is that our lives have consistently improved over the last 100 years.
The authors discuss a few examples of innovations that have improved our lives. One of these is the seat belt, a simple but effective solution to what used to be high traffic fatality rates. The authors argue that the seat belt has reduced the risk of driving fatalities by 70%.
One of the sub-themes of this chapter is the contrast between solutions from the private sector and those of the government. Because the private sector is focused on profit, their solutions to problems tend to be fairly simple, low-cost fixes. When governments get involved, however, the complexity rises and often results in unintended consequences that actually make the problem worse (e.g. the American Disabilities Act has reduced hires of the disabled because the disabled are harder to fire, protections for endangered species actually do more damage to endangered species because they encourage land owners to make their properties uninhabitable etc.)
The authors end with a look at a future innovation that may save the US billions of dollars worth of damage annually. A group of researchers is working on a relatively simple method of preventing hurricanes using a simple, low-cost, non-polluting device. More on this device, the man behind it, and some of his firm's other inventions are discussed here.
Many of our decisions, both inside and outside the investment world, are often based on anecdotal information, anomalies, emotions, or existing opinions. SuperFreakonomics illustrates how applying an economic approach can help us change this. Investors can use the tools described in this book, including better and more prevalent use of data, along with an an understanding of the power of incentives to make better decisions.
This chapter is about altruism. In classical economics, the belief is that everyone is out for themselves and so people will make decisions only if it helps them out. However, recent studies and experiments (including the Dictator Game) have suggested that people are also altruistic to some degree, which has thrown a wrench into the idea that people are rational, self-interested beings who make decisions that are in their best interests.
The authors spend a fair bit of time debunking the idea that people are unselfishly altruistic. Yes, people will help out others, but they often do so for self-serving reasons, including reducing their own guilt, or because they hope to receive similar benefits when they are in need, or because someone is watching. The authors cite a few variants of the Dictator Game introduced by John List (the economist, not the mass murderer) that suggest people are not as altruistic as originally thought.
Though people may give money away in supervised games, outside of the laboratory the authors suggest the practical evidence suggests people are not all that altruistic (prompting the quip: "sure it may work in practice, but does it work in theory?")
One example the authors use to illustrate this has to do with organ donation. Would a stranger give another stranger one of his kidneys out of the goodness of his heart? To the detriment of those needing a transplant, US law prohibits monetary gain from organ donation. As a result, there are 80,000 people in need of a kidney in the US, but only 16,000 transplants will be performed this year. In Iran, where donors are paid, there is no such gap. While the authors recognize that Iran is not considered a forward-thinking country, it should receive some credit for recognizing that incentives, not altruism, are a more effective method in saving lives.
Many of our decisions, both inside and outside the investment world, are often based on anecdotal information, anomalies, emotions, or existing opinions. SuperFreakonomics illustrates how applying an economic approach can help us change this. Investors can use the tools described in this book, including better and more prevalent use of data, along with an an understanding of the power of incentives to make better decisions.
In this chapter, the authors describe several instances of how the use of data can be employed to make better decisions. The authors start by explaining some strange anomalies with respect to one's birth month. Those who believe in horoscopes can point to many cases where birth months appear to play an abnormal role in predicting an outcome; the authors delve into the data to explain why.
For example, babies born in a certain month of the year (for 2010, it would be May) are 20% more likely to have a learning disability. This is because of religious fasting during the month of Ramadan; when pregnant mothers fast, their children are more likely to have disorders.
In other examples, a US-born child is 50% more likely to play professional baseball if he is born in August (vs July), whereas a British-born child is far more likely to play pro soccer if he is born in January (vs December). This is because the cut-off dates for little league baseball and youth soccer are July 31st and December 31st respectively, and so kids that excel under that format are given the most encouragement, confidence and playing time. (That is, a four-year old born in August will be much more able than his teammate born almost a year later in July.)
The authors then detail how such data mining can be applied to help improve our lives. Mining medical records can help identify the best (and worst) doctors. Mining banking data can help identify terrorists.
Using outed terrorists as a guide, the authors sought to create a banking profile to help identify terrorists still living among us. This is a challenging exercise for many reasons, not the least of which is the fact that because there are so few terrorists, inaccuracies in prediction are liable to yield scores of false positives, the investigation of which would overburden authorities. The authors provide some examples of the behaviours of terrorists (and omit some, because of the top secret nature of this work), including the fact that terrorists do not buy life insurance, do not have savings accounts, and were unlikely to use an ATM on a Friday afternoon (potentially due to prayers). This work is ongoing, but the authors believe the progress and future potential of this work is strong.
Many of our decisions, both inside and outside the investment world, are often based on anecdotal information, anomalies, emotions, or existing opinions. SuperFreakonomics illustrates how applying an economic approach can help us change this. Investors can use the tools described in this book, including better and more prevalent use of data, along with an an understanding of the power of incentives to make better decisions.
This chapter examines the economic forces that exist in the world's oldest profession. First, the authors contrast some main differences between prostitution today and one hundred years ago. Prices have fallen dramatically, despite a fewer per capita supply of prostitutes. Demand for sex is still high, so what has changed? Due to the acceptability of pre-marital sex in today's society, men are able to satisfy their demands without requiring a prostitute. (More than 20% of men 80 years ago lost their virginity to a prostitute while only 5% do so today, whereas 70% of men today have had sex before marriage, compared to just 33% previously.)
The way prostitution is dealt with by law enforcement serves to highlight the principal-agent problem we have discussed with respect to shareholders and management. Police chiefs (in this case, the principals) likely wish to see more arrests and fewer prostitutes, but there is a conflict of interest with the beat cops (agents). As it turns out, based on the data gathered by the authors and their associates, a prostitute is much more likely to have to give a freebie to a cop than be arrested by a cop.
The way law enforcement attempts to deal with illegal activities is also a problem. As in the drug trade, when law enforcement gets serious, it does so by stepping up its efforts at trying to curb the suppliers of illegal goods/services rather than the consumers. But this serves to increase the price of the product, thereby encouraging more suppliers to join the fray!
The authors also examine the effects of pimps, and compares their effects on prostitution to the effects of using real-estate agents to sell homes. Using data gathered from first-hand study, they find that the use of pimps, holding all other variables constant (including the same prostitutes in many cases), results in an increase in prostitute wages even after commissions, whereas real estate agents don't garner much in the way of benefits to home sellers (and may in fact be a net negative). The main reason for this, the authors conclude, is that pimps are able to market to clients in demographics and geographies that prostitutes are unable to reach. On the other hand, the internet has made it so that real estate agents are not adding much in the way of value for clients, so their value-add is low.
Finally, the authors profile a highly successful prostitute who employs economic techniques to improve her profits. She is a twice-divorced computer programmer who quit that job because it was boring and tedious. She enjoys the fact that she now works for herself, enjoys low overhead (markets by internet), employs price discrimination (higher rates for clients she doesn't enjoy as much), understands elasticity of demand (she can raise prices to certain levels without seeing a drop in demand), and understands market forces (she hopes prostitution stays illegal, because that's part of the reason she can charge such high rates).
