Richard Thaler on behavioral economics and nudges

Since the Nobel Prize committee decided to honor the rationality of the markets (or lack thereof), here’s a well-timed interview with behavioral economist RIchard Thaler:

Region: It’s hard to summarize the field, but you’ve written that there are three characteristics that differentiate Homo economicus from Homo sapiens: bounded rationality, bounded self-interest and bounded self-control.

Thaler: Those are the three things that—in the terminology Cass Sunstein and I use in our book Nudge.—distinguish humans from “econs,” short for Homo economicus. But I’ve now added a fourth “bound” that we also need in order to have behavioral economics: bounded markets.

If you had asked me in 1980 to say which field do you think you have your best shot at affecting, finance would have been the least likely, essentially because of the arguments that Becker’s making: The stakes are really high, and you don’t survive very long if you’re a trader who loses money.

Region: And you found that investors overreacted to both good and bad news; also, they were overconfident in their investing ability. The implication was that market prices weren’t always right. In other words, markets weren’t necessarily efficient, in contradiction to the efficient market hypothesis (EMH). Then in 2001, with Owen Lamont, you studied equity carve-outs and found more evidence that markets aren’t good at estimating fundamental value.

Thaler: Yes. Those papers highlight the two aspects of the efficient market hypothesis that I sometimes call the “no free lunch” part and the “price is right” part.
De Bondt and Thaler, “Does the Stock Market Overreact?” was about the no- free-lunch argument. When we were writing that paper in the early ’80s, it was generally thought by economists that the one thing we knew for sure is that you can’t predict future stock prices from past stock prices.

He goes on and talks about his work with the British government putting in successful ‘nudges’ and his relationship with Fama (they sit in mirror opposite offices at Chicago). He points out that when behavioral economics started with ‘bounded rationality’, a lot of the criticism was that it didn’t appear consistently or at the macro level. If you can’t aggregate the behavior, who cares? Well the more we investigate, the more important it turns out to be. I think neuroeconomics is in a similar stage – I’m not sure many economists really care, yet, because it will take time to figure out how to aggregate it. I wish I knew what Thaler thought about neuroeconomics. Anyone have a link to remarks of his on the topic?

Here’s an interview with Shiller who is teaming up with Akerlof to write a book about manipulation and deception in markets.

One thought on “Richard Thaler on behavioral economics and nudges

  1. Then in 2001, with Owen Lamont, you studied equity carve-outs and found more evidence that markets aren’t good at estimating fundamental value.

    You can show this concretely using computational complexity arguments. CDOs/CDSs can’t be priced correctly (i.e. their risk estimated) by any realistic valuation model. Realistic here means efficient in the computational sense, and doesn’t need to apply at the level of individuals making decisions. You can take the whole firm as the decision maker, and they still won’t be rational enough to be rational. This is similar to how not being able to crack RSA cryptosystem is not an artifact of biases in individual human thinking or emotions, but even all of the NSA can’t do it.

    For this reason, I actually think that finance is one of the best places to start seriously studying bounded rationality, at least via the algorithmic lens. It is also a new field with little interaction with theoretical computer science so far and so a great candidate for answering some fundamental problems. Although research interaction with cstheory is low, the quants themselves are using algorithms and taking bounded rationality seriously and applying it practically (even if they don’t realize it). This is most obvious in high frequency trading (mostly because the computational bound is so restrictive that it is very easy to notice in practice) where for instance quote spamming exploits the bounded rationality of competing algorithms and throws them into a misleading market micro-structure in which they can’t process and act on their information quickly enough without making systematic mistakes.

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