15
Jun 11

## The dismal science

I’ve begun reading some of the recent works by what are called “behavioral economists”. A staple of their work seems to be research into how humans fail to be perfectly rational economic actors, the most famous book of this sort being Dan Ariley’s Predictably Irrational. No doubt there is a lot of value in understanding how humans tend to deviate from behavior we (or, perhaps, academics) might expect. At the same time, I see many of these experiments as deeply flawed, in a way directly related to these economists’ failures to understand probability. In particular, they seem incapable of understanding the (often very rational) role that uncertainty plays in the minds of the participants. You can think of this uncertainty is as subjective probability, related to our degrees of belief. As human beings, we all have invisible, imperfect Bayesian calculators in our heads which crunch the data from our world and make implicit judgments about the information we take in. Right now, as you read this, how much credibility does what I’m saying have in your mind? How would your “uncertainty” about my arguments change if I made a clear mistakeee?

To see where the economists fail, consider the following experiment: A stranger approaches you and offers to give you \$100 in cash right now, or to pay you \$1000 in exactly one year. I can say right away that I would pocket the \$100. To an economist, this would mean that I have an (implied) internal rate of interest of 1000% per annum, since \$100 right now is equal in my mind to \$1000 in a year. From there, the economist could easily ask me a few other questions to show that my internal rate of return isn’t really 1000%, in fact it’s all over the pace. My preferences are fully inconsistent and therefore irrational.

But is my behavior really all that irrational? In taking the \$100 now, what I’ve really done is an implicit probability calculation. What is the chance that I will actually get paid that \$1000 in a year? \$100 in my hand right now is simple. A payment I have to wait a year for is complicated. How will I receive it? Who will pay out? How many mental resources will I spend over the course of the year thinking (or worrying) about this \$1000 payment from an unknown person? Complexity always adds uncertainty; the two cannot be disentangled. The economist has failed to understand people’s (rational) uncertainties, and has ignored the psychological cost of living with that uncertainty, especially over long periods of time.

Here’s another experiment. Imagine you asked your neighbor to look after your dog for you while you were gone for the weekend. How much compensation might she expect? If she’s particularly sociable, she might be willing to look after your dog for free, or be happy with a \$50 payment. But now imagine you offered her \$2000 right away, would she accept that? If not, than she has what economists call an downward sloping supply curve: giving her more money leads to less of the same service. Downward sloping supply curves, especially on the personal (micro) level, get economists all hot and bothered. They seem incoherent and rife with opportunities for exploitation.

Again though, is this really a case of irrational behavior? All things being equal (a deadly assumption that’s often made by economists), there’s no doubt that your neighbor would prefer \$2000 to \$50 for providing the same service. But of course in this example all things aren’t equal. The amount you offer her is a signal. It tells her something about your assessment of the underlying value of the service you are requesting. \$50 tells her that you appreciate the minor inconvenience of caring for your poodle. \$2000 tells her that something screwy is going on. Is your dog a terror? Will it chew up her furniture? Pee everywhere? Is there some kind of legal issue that she has no idea about? The key here is the importance of conditional probability. Specifically, what is the difference in the probability that taking care of this dog is equivalent to stepping into a mine field, given that \$50 is being offered, versus given that \$2000 is being offered? Human beings in general have incredibly sophisticated minds, capable of spotting hidden uncertainties and performing fuzzy, but essentially correct Bayesian updates of our prior beliefs given new information. Unfortunately, such skills seem to be lacking from many modern economists.