If you're a data nerd like me, I've got a book for you: Freakonomics by Steven Levitt, an economist at the University of Chicago, and Stephen Dubner, a former New York Times reporter, who through brilliant data mining blow up conventional wisdom on subjects ranging from criminology to commerce and from politics to parenting.
An unconventional economist to say the least, Levitt describes himself this way: "I just don't know very much about the field of economics. I'm not good at math, I don't know a lot of econometrics, and I don't know how to do theory." Instead, he uses the powerful tools of economic measurement to deal with more interesting issues than the standard economic fare.
Why did the crime rate fall precipitously in the early 1990s, despite predictions by all the experts that it would continue to skyrocket as it did in the '80s? Does having more money really win elections? How much do good schools matter?
In Freakonomics (the authors are said to be working on a sequel, and run a blog at www.freakonomics.com) Levitt answers these and dozens more penetrating questions. His steadfast adherence to measurable facts, without regard for any social agenda, political view, or even the implications of his conclusions is like a shot of Vitamin B12 to those of us who are sick to death of spin doctors and disinformation. What's more, his methodology provides insights into questions far beyond his topics, including the current state of the financial services industry.
While Levitt's specific analyses are mind-blowing, the thing that makes his book truly great is that his approach is so simple we can all use it to better understand our own worlds. His work is based on five basic principals, two of which you've probably surmised by now: "Conventional wisdom is often wrong," and "Dramatic effects often have distant, even subtle, causes." His overriding premise is: "Knowing what to measure and how to measure it makes a complicated world much less so."
Why You Should Care
The last two ideas are more directly applicable to our world of financial advice. "Incentives are the cornerstone of modern life, and understanding them–or, often ferreting them out–is the key to solving just about any riddle…." This would be just as true if we were to substitute "the financial services industry" for "modern life."
Levitt provides myriad examples of incentives at work, including obstetricians doing more revenue-generating Caesarian sections during economic slowdowns, and teachers helping students to cheat on standardized tests when their compensation depends on the results. His most powerful and relevant analysis, which combines both incentives and expert use of information, happens to concern the real estate business.
Most people believe their real estate agent will get them as much for their house as possible because his commission is based on the sale price.
But according to Levitt, the data shows that real estate agents are actually given incentives to use their expert knowledge against their selling clients. The proof? When real estate agents sell their own homes, they keep them on the market for 10 more days and sell them for 3% more, on average, than clients' homes.
If agents make more when a house sells for more, why wouldn't they use their obvious expertise to maximize client sales? The answer is simple economics: On a client's $500,000 home, the commission is 6%, or $30,000. That's split first between the buyer's and seller's agents, and then split again between the agent and her broker. So the seller's agent would get $7,500.
