Freakonomics is an interesting, easy to read a book that analyses various social issues from an economic perspective. The book takes the form of six chapters. Below is a brief summary of the 4th chapter.
In the early 1900s, crime rates began to drastically fall in the U.S. Experts from various fields cited a number of explanations for this observation. The authors discuss eight of these hypotheses and concluded that the number-one cause for the drop in crime was never mentioned in newspapers at all.
The strong economy, which was a highly cited cause, had not been proven to be correlated with a crime drop at all. Other popular theories for the decline included new policing strategies, capital punishment, and new gun-control laws. But the authors showed that all these had little effect — the policies were put in place in big cities like New York well after the crime had begun to fall, executions were rare, & despite new gun control laws, there was a thriving black market.
The author argues that the main reason for the decline in crime rates was a decision taken on January 22, 1973 — legalize abortions across the entire country. As a result, after 1973, many women, unmarried or in their teens, living in impoverished communities had abortions where they would otherwise have had unwanted children. Had these children been born, they would have been 50 per cent more likely to live in poverty and thus extremely likely to have a criminal future.
This hypothesis also had data to back the claims — states with higher abortion rates had higher drops in crime, and states that legalized abortion earlier saw crime start to drop before other states. The effect didn’t become clear until the mid-90s, because the post-legalised abortion generation entered its twenties only by then.
The primary takeaway from this chapter is that large effects sometimes have distant, unexpected causes. No one cited the effect of abortions as a reason because it happened 20 years ago. The other takeaway is that correlation does not always prove causation — further analysis of the data through isolation of the variables in question is necessary in order to prove causation.
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From the desk of Aditya Khanduri
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