Freakonomics is a mix of psychology, sociology, and economics.
Steven Levitt, the author, penned a best-seller thanks to a good mix of solid social-psychology principles and fun facts delivered within a frame of good entertainment.
Bullet Summary
- Crime rates dropped because of the abortion law
- Economic incentives can crowd out moral or social incentives
- We all tend to jump to explaining events through apparent causation, but that can be spectacularly wrong
Freakonomics Summary
About The Author: Steven Levitt is an American economist and professor of economics at the University of Chicago. Stephen Dubner is an author and journalist, and he has a radio show and podcast.
Both of them enjoyed much success with Freakonomics, which then followed up with similar titles such as “Super Freakonomics” and “Think Like A Freak”.
Introduction
Freakonomics starts by taking aim at a pillar of old economic theory: that men are purely rational individuals who act on purely rational (and easily to computer) economic incentives.
Financial Incentives Are Just One of Many Incentives
For decades, economists loved the idea of economically rational incentives.
We are all rational, postulated the now almost defunct Homo Economicus framework.
Freakonomics does not deny that rational and monetary incentives play a huge role, but it takes a larger view on incentives.
It also includes social incentives, such as not wanting to look bad, and moral incentives, such as not wanting to do something which feels wrong.
Purely Financial Incentives Can Backfire
Focusing only on one side of the incentive equation, such as the financial ones, can indeed often backfire. The author uses the example of the now-famous daycare center in Hafa, Israel.
To reduce the number of late pick-ups by the parents the school started charging a $3 dollars fine for every time a parent would show up late.
Did that decrease the incidence of late pick-ups? No, it doubled it.
Why? Because the financial fine replaces the moral obligation. Now the parents felt that, by paying the fine, it would be OK for them to show up late.
Sort of a “pay per time”.
Lesson learned?
When you are thinking about introducing incentives, think instead if you can strengthen some already existing natural incentives. For example, the human need to not be unfair, which the daycare center could have leveraged.
If you are interested in the topic, I can highly recommend you read Drive by Daniel Pink.
Which Incentives Work Depends on Context
Imagine a contribution box where people can chip in money in exchange for bagels. It mostly relies on the incentives of wanting to be honest and wanting to look honest by the people who happen to be around.
What can it teach us about contextual incentives?
A lot.
Donations were higher when:
- It was a sunny day
- The overall office mood was higher
- During non-stressful holidays (Christmas and Thanksgiving are labeled as stressful)
- After 9-11 happened, which is probably because of a general surge in empathy
Incentives Are Not Always as Aligned as They Seem
Imagine you want to sell a house.
Theoretically, the interest of a real estate agent is the same as yours: selling it at the highest possible price.
However, the amount of commission the agent would earn for selling your house at a 10% higher price is not much compared to how much time they can save by closing the deal quickly and moving on to the next house.
Indeed data shows that when real estate agents sell their own houses, they keep them on the market longer to wait for a good offer.
How “Experts” Exploit Us
Levitt and Dubner explain how people in possession of specific knowledge can use our relative ignorance to cheat or overcharge us.
Lawyers and accountants are examples of experts who are in the position of overcharging their customers.
But also a car salesman can take the role of an expert when for example he leverages our fear saying that a cheaper model is “not so safe”.
When you feel someone is trying to play on your fears always delay decisions.
And then ask for a second opinion or research. The Internet is a God-send gift here in helping reduce the information disparity.
How Internet Change The Game
In the nineties, the prices of life insurance policies fell dramatically. Why was that? The author says it’s because people were suddenly able to quickly compare prices.
Similarly, if you want to buy a house these days you can easily go online and look at the prices and you don’t need to trust the real estate agent.
Why do cars lose as much as a quarter of their value the day after they have been bought?
The author says it’s because of the asymmetry of information.
Since the buyers cannot know what happened to the car and why you’re really selling, they fear the worst.
Similarly, the very worst thing you can do on an online dating profile is to omit your picture. People will naturally think the worst.
Correlation is Not Causality
This is a mistake that people do all the time.
They see two variables move together and assume that one is causing the other. There might indeed be a correlation between the two variables, but the correlation does not imply causation.
Also read: Fooled by Randomness.
More Money Doesn’t Win Election
A great example is that of money and politics. Usually, the candidate with the most expensive campaign wins. So people tend to think that money wins the election.
But the winner has more money only because people tend to back the favorite candidate at a higher clip. The author says that the winning candidate could cut their campaign spending by half and only lose 1% of the vote.
What’s Near is Causal
When looking at what caused something, we also tend to give a disproportionate amount of attention to whatever is close and easier to be noticed.
For example, when the crime rate dropped precipitously in the early 1990s in the US most commentators said it was because of an improving economy, more police, gun control, and similar.
In reality, it was because of the abortion law. The most likely convict born in poverty in single-parent households. With abortion, fewer likely criminals were coming of age in 1989.
As Cialdini says “what’s focal is causal”.
My Note:
What causes crime to rise or fall is a heavily debated topic and I wouldn’t necessarily jump to the abortion conclusion of the authors (albeit the increase in abortion might have certainly helped).
Real-Life Applications
Don’t Jump to Causal Conclusions!
It’s tempting to see an event, look for a possible cause and automatically explain the event with the first cause we can find.
Especially so if there is an apparent link between the event and the “cause” we found.
But correlation is not causation.
P.S.: as a kid, it annoyed me to no end to see my parents always jumping to causal conclusions.
CONS
Bit Redundant
The second part of the book loses a bit of the edge
PROS
Pushes Us to Ask Deeper Questions
One thing Freakonomics does great and which I really appreciate it for, is to urge people not to stop at the first layer of analysis.
To get to the truth, we often have to first overcome our own biases.
Review
Freakonomics is a book that purports to use an economics approach to answer difficult questions with data and science.
In reality, it’s a book of intriguing facts, data curiosities, and psychological biases.
Since most facts are indeed intriguing, the book has become a big success and a brand in itself.
I personally enjoyed it.
There is some interesting stuff and it’s a good book, but it’s not enough to make it into a must-read book.
Read This Instead:
If you’re into psychological biases, go for “Thinking Fast and Slow“. If you’re interested in behavioral economics, go for “Misbehaving“. And if you’re interested in logical thinking and fallacies go for Nassim Taleb, for example, “Fooled by Randomness“.
In Short:
What Freakonomics does really well is to marry good information with the entertainment factor. So if you are looking for a book to entertain you AND to teach you something, I highly recommend it.
