As Levitt points out, economists believe that incentives are the building blocks of all economic decision-making. Incentives are the things that motivate people to make certain choices, and we respond to incentives as early as infancy. Varying combinations of economic, social, and moral incentives play a major role in nearly all of the situations that Levitt talks about in Freakonomics, such as the incentives that drive schoolteachers and sumo wrestlers to cheat and the incentives that keep struggling foot soldiers in the business of crack dealing.
Crime and Morality
Though there is no one unifying theme to the stories and anecdotes discussed in this book, many of them center on some kind of crime, whether it is cheating, hate crime, illegal substance dealing, or even murder and homicide. Crime is interesting from an economic perspective, since people who commit crimes are responding to incentives strong enough to counter innate human morality and motivate them to do the wrong thing. But as Levitt points out, there are far more people who don't commit crimes than people who do, suggesting that humans are a lot more moral than they are often given credit for.
Economic models like supply and demand assume that both parties in the transaction—consumers and producers—have perfect information. However, in real-world economics, one party typically has more information than the other. Experts are often in a position to take advantage of this information asymmetry and maximize utility for themselves, misleading the consumer in the process. This features in a number of Levitt's discussions, like those about the KKK and real estate agents;however, Levitt also points out that recent innovations like the internet have been able to diminish information asymmetry and level the playing field between experts and consumers.
Conventional Wisdom is Often Wrong
The moral behind many of the stories that Levitt includes in this book is to not always trust conventional wisdom, because it is often wrong. Conventional wisdom is meant to be comforting and believable, though not necessarily true. Conventional wisdom tells us that drug dealers make a fortune, that certain activities are riskier than others, and that parents' every move influences their children's life outcomes; this book challenges readers to dig deeper and question what we assume is true by looking at concrete data that can reveal the real story.
Levitt also encourages readers to use data to uncover the unexpected causes for certain effects. It is human instinct to believe that effects have immediate, closely related causes, which explains why people were quick to believe that innovative policing strategies or strict gun laws were the reasons behind the 1990s crime drop. But Levitt's analysis shows that this may not always be the case: sometimes these kinds of effects can have distant, subtle causes.
From generation to generation, experts continue to debate proper parenting techniques and the affect that parents' choices have on their children's life outcomes. Parenting is a major theme at the end of Freakonomics, where Levitt shows through close data analysis that what parents do matters much less than who parents are—that is, the life circumstances that a child is born into is far more influential that any actions a parent takes to try and ensure success for them.
Think Outside the Box
While all of the stories that make up the six chapters of Freakonomics are immensely different, through all of them Levitt seeks to encourage readers to think outside the box and question the world around them. Just as Levitt does in this book, readers are implored to explore "the hidden side of everything" (cover) and use data and the tools of economics to uncover the complex truth in seemingly mundane situations.
Freakonomics Questions and Answers
The Question and Answer section for Freakonomics is a great
resource to ask questions, find answers, and discuss the novel.
“A regression analysis can demonstrate correlation, but it doesn’t prove cause. After all, there are several ways in which two variables can be correlated. X can cause Y; Y can cause X; or it may be that some other factor is causing...