Devil's Economics is not like an economics book, but more like a collection of stories that rationally explore social phenomena.
For example, people who are new parents are enthusiastic about prenatal education and parenting, and on TELEVISION and the Internet, the content of "how to make the baby smarter" is also endless. But do these parenting philosophies really work? If the data shows that families with a large number of books have children's grades generally better, will it be useful to buy a lot of books at home after having children? The answer is of course no, the collection of books may only represent the parents' higher level of knowledge, and the child's good grades are more likely to come from the inheritance of the parents' intelligence, rather than a large collection of books.
In addition to what children's grades correlate, the book explores how real estate agents cheat on customers, teacher cheating, the structure of drug cartels, and the sharp drop in crime in the United States.
Through real data and case studies, the authors reveal the root causes behind simple phenomena.
The book's first author, Steven Levitt, is an odd man from an academic family who studied at Harvard University and MIT as a tenured professor in the Department of Economics at the University of Chicago. Unlike economists in general, Levitt is not good at mathematics and does not like to study exchange rates, currencies, and stock markets, but prefers to ask special questions, simplifying complexity and clarifying the root cause behind the phenomenon of simplicity, that is, how people meet their own needs.
The book's second author, Steven Duberner, is a reporter for The New York Times Magazine, and in an interview with economist Levitt, the two hit it off. Levitt found that Mr. Duberner did not always ask him questions about money and the stock market, as the average journalist did, and Mr. Duberner found levitt's research direction to be unusual, unlike an economist, but rather like an investigator who liked to study fraud, corruption, and crime.
So when The New York Press invited Levitt to write an economics book, Levitt hoped to co-author with Duberner, and Freak economics was born. After the book was published, it was widely acclaimed, and the two authors went on to co-author three books of Freak Economics, the first of which was written in the series of four books.
There is a kindergarten where parents are required to pick up their children by 4 p.m. every day, but every day there are always several parents who are late, which requires leaving a teacher to take care of the children. Two economists came up with an idea: to fine parents who were late. So the kindergarten announced a rule: parents who pick up their children late will be fined $3 per child. So what's the result? There are not fewer late parents, but more!
Why is that? In fact, it is not difficult to understand that $3 is too small and does not play a deterrent role, and parents will not give up what they have at hand for $3. More importantly, how can this measure be understood by replacing moral means with economic means? Parents may be motivated by other things at hand, and picking up their children late creates guilt, and parents weigh the guilt of being late and the importance of other matters, but when a $3 fine can offset the guilt of being late, parents only need to weigh $3 against the matter at hand, then $3 is insignificant.
The failure of the fines measure is because the motivation behind the behavior is ignored. From an economic point of view, motivation is people's desire to meet needs, divided into three kinds of economic motivation, moral motivation and social motivation, corresponding to three different needs: the need to seek economic benefits, the need to follow morality, and the need to integrate into society to achieve self-fulfillment. In the kindergarten example, if the fine were raised to $100, financial motivation might outweigh other needs, and no parent would be late.
The decline of the Ku Klux Klan in the United States is a good example. The Ku Klux Klan was founded after the end of the American Civil War, and at first they were just like-minded friends, using pranks to intimidate black people, and then gradually evolved into white supremacist extremism, distributing pamphlets, setting fires, using lynchings, etc. The Ku Klux Klan was once wiped out and revived during World War II, with more disciples.
At this time, a young man named Stanson Kennedy decided to smash the Ku Klux Klan. Kennedy was a liberal and journalist who attacked racial prejudice and hated violence and intimidation. He broke into the Kkk Klux Klan and became acquainted with another undercover member of the Klux Klan, and gradually learned a lot of the Kkk Klux Klan insider, such as internal structure, hierarchy, joint code, profit model and so on.
Kennedy found that after the 1940s, cases of hangings, arson, shootings and other cases were gradually disappearing, and the Ku Klux Klan used more tactics as intimidation, when the Ku Klux Klan was more like a mysterious brotherhood and should be easily eradicated. Kennedy told some government officials about the information, hoping to eliminate the Ku Klux Klan, but to no avail.
Just when Kennedy was disheartened, he thought of another way, using storytelling, to broadcast the inside story of the Ku Klux Klan on the radio. Some time after Kennedy's radio program aired, strange things happened, fewer members participated in the Ku Klux Klan rally, the number of new members joining the Ku Klux Klan was greatly reduced, and the confidential information that was previously cherished by the Kkk Klux Klan members became information and jokes known to the public, and the leader of the Kkk Klux Klan was also angry, and the Klux Klan began to decline.
The success of this move is due to the information Kennedy knows. Within the Ku Klux Klan, the top brass use internal secrets to collect membership dues, seek private interests and political attempts, while for ordinary members, the mystery of the Ku Klux Klux Klan brings a certain sense of superiority and belonging, which can be said to be a social motivation. Once the organization's information is made public, the ordinary members are unable to realize their needs for self-identification, and the economic interests at the top are weakened, the entire organization falls apart.
The asymmetry of information and the motivation of people to pursue economic interests are the root causes of many phenomena in modern life. For example, a dietary expert will throw out a scientific theory and warn us to eat more nutrients, the doctor may prescribe us more expensive prescription drugs for kickbacks, and the real estate agent may persuade us to accept a lower selling price in order to quickly close the deal.
When we sell houses, we all hope to sell at a higher price, and for the real estate agent, the customer sells 10,000 yuan more than the house price, he can only take 200 yuan more intermediary fees, therefore, the real estate agent prefers to make a single as soon as possible, as much as possible. They will tell customers that "this is already a very high price point, you can sell", "The recent housing market is not very good, it is not easy to have buyers so soon, you can sell". However, whether the price is high or not, how the housing market is, most customers do not know, can only choose to trust the intermediary.
So, how to prove the behavior of real estate agents to persuade customers to sell at low prices? Quite simply, real estate agents also have houses, but also sell houses, if they sell their own private property data, and sell customer property data to do a comparison, you will find that when the agent sells private property, the average advertising time will be about 10 days, the price is also about 3% higher. Of course, we can't say that real estate agents are bad, they are just ordinary people driven by profits, and the economic motivation to quickly become a single has prevailed when helping customers sell their homes.
At the beginning of the 21st century, the United States public schools implemented a high standard of testing, the test is not only the assessment of students, but also a teacher's assessment standard, the student's poor performance of teachers, may be reviewed or cancel the opportunity for promotion and salary increase, the student's good teachers may receive commendations and bonuses. This gives teachers an incentive to cheat, but how do you prove that teachers cheat? This requires data support.
Imagine how a teacher would cheat? You can give students questions and answers in advance, or extend the test time, and there is an easier way to fill in the correct answers directly in the blank space of the answer sheet after the student submits the answer card, or to modify the student's wrong answer. However, no matter what method is used, cheating will be reflected in the student's grades and answer sheets, if the same batch of students in a certain test score greatly improved, and then in the subsequent test, it is likely that the test with good results has cheating behavior; if in some test answer sheets, the simple question error rate is very high, indicating that the student's own performance is poor, but many difficult problems are answered correctly, it is likely that the teacher directly modified the answer sheet.
And the data just proves the characteristics of these cheats. The authors collected 10 years of test data from Chicago Public Schools, and the analysis found that many teachers cheated. Similar to teacher cheating, there are also many cheating phenomena in sports competitions, such as taking drugs, coaching and refereeing transactions, collecting money to play match-fixing, deliberately losing games, and so on.
There is an interesting example of drug trafficking, which can be said to be a profiteering industry, so people often think that drug dealers must be rich, but this is not the case. Why, in the United States, many black drug dealers live in slums, and some even live with their mothers. The reason for this has to start with the structure of drug trafficking organizations.
It was not easy for economists to get information about drug trafficking organizations, but there was a black economist named Vincaster, who grew up in the slums, majored in economics at university, and in a job doing questionnaires for teachers, he accidentally mixed with drug trafficking organizations, became friends with the drug trafficking leaders in the region, and even got the ledger of the drug trafficking organization. Later, Vincaster and Levitt analyzed the ledger to decipher the structure of the drug trafficking organization.
They found that the drug cartel was almost identical to McDonald's' structure. The drug trafficking organization that Vincaster infiltrated was only a gang of the large drug cartel, equivalent to the Greater China region of the McDonald's group, and there were dozens of branches under this gang, equivalent to McDonald's branches in different cities in China. The drug trafficking boss that Vincaster knew, the equivalent of a city division manager, had his own members, and the members below him performed their duties, buying cocaine from headquarters on a regular basis and distributing it to his subordinates, who owned the income from the sale of cocaine, but were subject to high monthly taxes. In this way, almost 80% of the income of a branch goes into the pockets of the top management. This way of operating is much the same as that of enterprises, and only a few people at the top can get high salaries.
Why, then, are so many people willing to engage in dangerous and money-free drug trafficking? The answer is simple, just like good-looking people breaking into the entertainment industry, in a highly competitive profiteering industry, once they stand out, they can get rich overnight. The same is true of ordinary people's lives, some people like to buy lottery tickets, and some people start from ordinary employees in the enterprise, hoping to one day get promoted and raise their salaries. The data from the ledger of a drug trafficking organization tells us that drug trafficking and buying lottery tickets, breaking into the entertainment industry, and working in a company are the same in terms of economic motivation.
In the early 1990s, the crime rate in the United States remained high, the people were worried, and experts predicted that the crime rate would become higher and higher in the future, however, from 1995, the crime rate suddenly began to decline, and by 2000, it had dropped by nearly 50%, and the number of homicides had dropped to a record low. Experts who predicted rising crime rates have new interpretations, such as the Gun Control Act, economic prosperity, the implementation of new policing strategies, and so on, and ordinary people have gradually accepted these explanations.
However, these theories are not correct, and there are other reasons for the sharp drop in crime rates. In 1970, a penniless, alcoholic woman wanted to have an abortion because she had no ability to raise the child. At the time, most states in the United States banned abortion, so she, with the help of lawyers and others, launched a class action lawsuit to legalize abortion, which is known as Rowe v. Wade. After three years of litigation, she won, and the united states began to legalize abortion.
But what does it matter if the crime rate has fallen? Perhaps this is the typical butterfly effect, since the victory of Rowe v. Wade in 1973, those expectant mothers who are unmarried and pregnant, poor, and unable to raise their children can choose abortion, and these children who should have been born in unfortunate families are far more likely to embark on the road of crime than children with better families. By 1995, those children were supposed to be young, the age at which they began to commit crimes, and because they were not born, the crime rate began to plummet.
This theory sounds scornful, but does abortion reduce crime? But the data doesn't lie, and different laws are enforced between different states in the United States, which provides good fodder for economic experiments. Data from different states and periods suggest that experts' explanations, such as the economic situation and gun control, are not enough to reduce crime by as much as 50%, and the most reliable new policing strategies can only reduce crime by about 10%. Conversely, because abortion legalization has been introduced in different states in the United States, the available data is enough to show that the number of years that the crime rate began to decline significantly earlier in the states that introduced abortion legalization in the earlier years, which shows that abortion legalization did reduce the crime rate.
Data can reveal the truth behind things. However, the data can also be misinterpreted.
Let's start with what is relevance and causality. When we say that two events are related, we mean that the two indicators are obviously related, one is large and the other is large, which is positively correlated, and one is small and negatively correlated. Causality is well understood, meaning that one event leads to the occurrence of another.
The data can prove correlation, but it is difficult to prove causation. If a is associated with b, one possibility is that a causes b, it is also possible that b causes a, and a third possibility, there is a hidden variable c, which causes both a and b.
For example, if you compare the number of police officers and crime rates in different regions, you will find that there is a positive correlation between the number of police officers and the crime rate, that is, where there are many policemen, the crime rate is also high, will more police lead to more crimes? Of course not, the more likely reason is that because of the high crime rate in a certain place, more police are sent.
For example, counting children's height and vocabulary, it may be found that height and vocabulary are also positively correlated, and tall children have a large vocabulary. Of course not, the correlation between height and vocabulary is more likely to be related to another hidden variable: the age of the child. Older children are naturally taller and have a greater vocabulary.
As a parent, it is bound to be a child into a dragon and a daughter to become a phoenix, which makes the childcare market and the education industry flourish. In order to send their children to better schools, parents will pay a lot of money, but is this really useful? The data may tell the story.
Chicago public schools have long opened up the right to choose schools, unlike China's primary and secondary school entrance examinations, in order to control the number of applications, the Chicago public school system adopted a lottery system. Drawing lots means random, and random data is the best object for economists to study. After the opening of the school choice, on the surface, the students who successfully transferred to good schools by lottery did improve their grades. But this is only an illusion, and more in-depth data analysis shows that students who participated in the lottery but did not win the lottery scored on a par with those who successfully chose a school. This shows that better schools are not the reason for improved grades, but because there are participants in the lottery itself, why? When parents and students themselves have higher IQs and pursue academic pursuits, they will want to choose schools by lottery, so whether these students eventually succeed in transferring schools, their grades will not be bad.
There is also a project called the "Longitudinal Study of Early Childhood", which analyzes and compares a large number of data on children's family environment, parental behavior and academic performance. It was found that factors such as high parents' education, high economic status, a large collection of books at home, and mothers giving birth after the age of 30 were positively correlated with the child's grades, while the family integrity, the mother was a full-time mother, often beaten, often watched TV, often went to the museum, and listened to the parents read every day, all had nothing to do with the child's grades.
What does this mean? Most of the so-called educational methods come from the phenomenon we observe, that is, the correlation between parental behavior and children's ability, and these correlations ignore a hidden variable: the parent's genes. Numerous studies have shown that more than 50% of children's personality and abilities are genetically determined. The characteristics of high education, high income, and large collection of books indicate that parents themselves have a high level of intelligence and knowledge, and reading for him after birth, taking him to museums, and letting him go to good schools cannot improve children's grades.
Today, there are many studies that have shown that genes play a greater role than nurturing. One study followed more than 200 adopted children and found that children's personalities were not associated with those of their adoptive parents. Observational studies of twins raised separately are the best proof of genetic strength, and a large number of facts show that twins raised by their biological and adoptive parents, respectively, even if they have never met, are highly similar in personality characteristics, education levels, and even behavior patterns.
For parents and parenting experts who like to delve into parenting, these conclusions may be a basin of cold water, but in fact, the role of parenting is indeed overestimated. This is not to say that parents have no influence on the child, but that when the child is born, the influence is over, and it is the characteristics of the parents themselves, not what they do, that affect the future of the child.
This book uses many interesting examples to provide us with three basic ideas for understanding the truth of life and things.
First of all, in order to understand people's behavior, it is necessary to understand the motivation behind the behavior, motivation is people's desire to meet needs, divided into three kinds of economic motivation, moral motivation and social motivation, and the value of different motivations in people's minds is different. Many times, the key to solving the problem is to replace a weaker motivation with a stronger motivation. For example, in order to avoid being late, higher fines can be imposed; in order to prevent theft, surveillance is installed to bring thieves to justice; people pay to join a certain high-class club in order to show their identity... These are examples of one stronger motivation replacing another.
If understanding motivation is the first step in making assumptions and uncovering the truth, then information and data are evidence of the truth. A large number of test score data can catch cheating teachers; birth rate and crime rate data can prove that abortion reduces the crime rate; drug dealers' ledgers can depict the economic structure of drug cartels. So we say that people lie, and data never lie.
However, the conclusions drawn by the data are often misused, and the data can prove the relevance of events, but it is difficult to prove that there is a causal relationship between them. Just like in elections, well-funded candidates are more likely to win elections, but in fact, people only invest in candidates with a high probability of winning, so it is difficult to say whether candidates attract money or money attract votes. In addition, the correlation between the two events may also stem from another hidden variable, such as a family with a large number of books, the child's grades are good, not necessarily the book collection motivates the child to learn, more likely because the child inherits the high IQ of parents who are good at reading.
The first is to understand people's behavior by starting from motivation and understanding how people meet their needs.
The second is that data is a tool to reveal the truth, people lie, and data does not lie.
The third is that correlation does not equal causality, and two events are related, which does not mean that there is a causal relationship.