Summary
Stephen Levitt begins the introduction by discussing the drastic rise in crime in the early 1990s. Violent crime was constant, and experts predicted it was only going to get worse. The media always portrayed each criminal as a heartless thug and insinuated that there was a whole generation of killers behind him. Even President Clinton said that something had to be done about the juvenile problem or America would be plunged into chaos.
Suddenly, though, crime began to fall, consistently decreasing year after year. All categories of crime fell, not just certain ones, and the teenage murder rate fell more than 50 percent within five years. By the year 2000, the overall murder rate was the lowest it had been in 35 years. No one, not even the experts, had anticipated this.
Seeking to explain the drop, experts proposed a handful of new theories, such as the roaring 1990s economy, gun control laws, and innovative policing strategies.
Instead, though, Levitt explains the drop with the story of Norma McCorvey, a young Dallas woman who wanted an abortion more than 20 years before. Poor, uneducated, and unskilled, she had given up two children the year before and had become pregnant again. In Texas, like most other states, abortion was illegal, and she became the main plaintiff for a court case that many important people supported. Her case made it to the Supreme Court, where her name was disguised as Jane Roe. This became the famous Roe v. Wade case. In the end, the court ruled in her favor, legalizing abortion throughout the country.
A generation later, Levitt argues that this led to the crime drop because all the poor, uneducated women whose children were more likely to grow up to be criminals were not being born, because these women had gotten abortions. The pool of criminals had drastically shrunk, so crime went down. But no crime-drop experts ever cited legalized abortion as a cause.
Levitt then switches to a discussion of the way we rely on and trust "experts" who have an in informational advantage over us. We believe that these experts are using this informational advantage to help us get exactly what we want for the best price, but unfortunately, this is not always the case. Just like any human, experts respond to incentives, and sometimes an expert's incentives may work against the client. The best way to detect whether or not an expert is abusing his informational advantage is to compare how an expert performs a service for you versus how he performs the same service for himself.
He uses the example of real estate agents selling their own homes to illustrate this. Since only about 1.5% of the sale profit of your house would go directly into the real estate agent's pocket, she might not be willing to put in all the extra work to sell your house for $310,000 rather than $300,000 since the difference in profit for her is only $150, while for you, the seller, it would be a lot more. However, the data reveals that when selling her own house, a real estate agent would keep her home on the market for an average of ten days longer, selling for an extra 3 percent or more. When selling your house, the agent's goal is to get you to close the deal fast so she can move on, but when selling her own, she will hold out for the best offer.
Levitt moves on to a discussion of correlation versus causation, disputing the commonplace assumption that more money makes candidates win elections. He postulates instead that the more appealing candidate who is more likely to win anyway will attract the most money, saying that the candidate's appeal wins him both the money and the votes. This can be proven by examining the same two Congressional candidates running against each other in consecutive elections, which show that a candidate increasing money spent on his campaign will have little-to-no effect on the amount of votes he receives.
Levitt ends the introduction by bringing all of these anecdotes together to explain what this book is about. The book will ask questions and dig beneath the surface of everyday life to find answers in data. He distinguishes between morality, the way people would like the world to work, and economics, which is the way the world actually does work. It will apply the tools of economics to interesting and sometimes odd scenarios.
The books is based on a few fundamental ideas: Incentives drive modern life. Conventional wisdom is often wrong. Dramatic effects sometimes have distant and subtle causes. Finally, experts use their informational advantage in their own favor. Knowing what to measure and how to measure it can help make the world less complicated, and this book's goal is to explore the hidden side of everything.
Analysis
Most readers conceptualize the field of economics as having to do solely with finance or commerce. Freakonomics, however, immediately defies this conception, calling economics a discipline that examines the way the world actually works and distinguishing it from morality, which is an idealized version of the way people think the world should work. It applies the same tools used in economics to all kinds of unconventional situations so that readers can understand how these phenomena operate in daily life.
Levitt uses the introduction to outline the key points of the book. Rather than go in-depth on each of them, though, he only brushes the surface, priming readers to tackle these concepts later in the book and getting them exercising their minds and thinking about these things early on. Rather than use complex academic jargon, he explains things in simple terms so that even readers who have had no exposure to economics can understand. This is part of what has made this book so popular.
The first of the major concepts that Freakonomics explores is the existence of incentives and the way they drive daily life. We respond to incentives in our school, our work, and our relationships: they are things that motivate or deter us from pursuing certain actions. It is important to note, though, that experts respond to incentives too, and often the incentives of the professionals we trust may not exactly align with our own. With the detailed perspective on incentives that this book provides, readers can view the choices and actions of the people with whom they interact more critically in order to determine which incentives are motivating them.
Another important concept discussed in this book is information. In economics and in the behavior of people, information is its own currency, and can be used and abused by the people who hold it the same ways money itself can. In our daily interactions, there is often an information imbalance, with one party having more information than the other. According to Levitt, it is in these situations that an informational advantage may be abused.
Next, Levitt explains a concept that is the cornerstone of any data analysis: correlation does not prove causation. A correlation is the relationship between two different sets of data, or two different phenomena. However, one thing being correlated with another does not mean that it causes that thing. It could be that one caused the other or vice versa, or it could be that a completely unrelated thing is causing both phenomena. It is important to understand the idea of correlation vs. causation when approaching any data analysis in economics.
Levitt explains these concepts through flashy, exciting, out-of-the-box anecdotes that catch a reader's attention and draw them deeper into the analysis. He begins the introduction with the story of the 1990s crime drop and presents it like a mystery, slowly revealing more information about the occurrence until finally he provides the real explanation. He uses this strategy repeatedly throughout the book, and it allows him to engage readers who otherwise would not be interested enough to grapple with the concepts he discusses.
