Noam Nisan asks "should “algorithmic game theory” (in the broad sense) also put significant energy into experimentation? " Or should experiments remain in the province of economists, and market designers who deal with human (as opposed to computer) agents? He sees some possibilities that computer scientists should also entertain experiments, about the connection between computerized systems and their human users.
This of course raises the possibility that the interaction of computer science theorists with economists will expand to include psychologists doing cognitive engineering, the part of human factors engineering most concerned with cognition, and human-computer interaction. (Here's my favorite cognitive engineering website, soon to be updated.)
Nisan also has some interesting asides, and one particularly caught my eye:
"I never quite understood the difference between experimental economics and behavioral economics. My impression is that it is simply a question of your attitude towards game theory: experimental-pro, behavioral-con. The anti-game-theory bias is probably not that of its founders Kahneman and Tversky. Shortly after winning the Nobel prize in economics in 2002, I heard Kahneman talk at a dinner held by the Hebrew University’s rationality center. His point was that while most psychologists would immediately dismiss the economic assmptions of rationality as absurd regarding human beings, the greatness of his co-author Tversky was to realize that there was an important underlying truth to this point of view, and hence that it was interesting to carefully study its limitations. "
I think that this view was more accurate in the early days. Today, I think that "behavioral economics" means the broad effort to include (a little or a lot) psychology in economics, and in that sense (to paraphrase),we are all behavioral economists now, whether or not we do experiments. Experimental economists, however, do experiments.
Sunday, April 12, 2009
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Behavioral Economics v Experimental
Here is a gross, but hopefully useful simplification.
Generally, all economics is the study of behavior. In order to model, we make certain simplifying assumptions. The economic assumptions center around formal notions of expected utility.
Behavioral economics, from the 1950's through to 1980, meant one of two things: bounded rationality, or the careful experiments designed to show one or more axioms required for an expected utility function failed. Allais, Ellsberg and numerous other contributed to this field.
(One of the unexplored areas was just how far the challenges to the standard expected utility model had analogues in bargaining - a result you might expect because of theorem of Al Roth's in his book on Axiomatic Bargaining.)
Tversky and Kahneman changed the focus in two ways. One by introducing framing, which challenged not just a particular axiom set, but the very idea of building a model of preference assuming invariance. Tversky, in particular, has a number of experiments showing how mathematically equivalent decision scenarios are treated differently - as if the decision maker could not deduce a=a.
This is a very powerful, if true, attack on the very idea of abstract model building.
Current academics who style their work as "behavioral economics" are largely adding to the scope of framing effects.
On the other hand, experimental economics as it relates to Vernon's Smith's work is aimed at exploring the circumstances in which markets clear. The original experiment in the 1950's showed that a simple auction device could allow markets to clear at the price level and transactions that the simple supply and demand curve theory predicted.
Smith and others have followed this up with careful experiment showing how the creation of bubbles are possible, even in a world where most of the information is transparent.
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