Quick Thoughts About Mindless Economics

by Will Wilkinson on January 11, 2006

Glancing at the Gul & Pesendorfer paper, “The Case for Mindless Economics,” my first thought was that these guys good really use a good philosophy of science seminar. (Tyler discusses it, as does Bryan Caplan.) Now, I don’t really understand the drive to secure the autonomy of formal economics. Either economics seeks to decribe actual human behavior or it doesn’t. It is fine to create any kind of formal model you like, and to call predicates in your model anything you like. You can, say, create a model that speaks of ‘kittens’, ‘meowing’, and ‘estrus,’ and as long as your model hangs together in the way models should, then that’s nice. Maybe it will even be interesting. But if it has nothing much to do with actual purring furry pets, don’t get upset when a zoologist comes along says that you don’t really have a theory of cats at all, but a theory of ‘cats.’

My sense is that the formal neoclassical theory of economics is a theory of ‘behavior’ not behavior. Models don’t need to be models of the actual world in order to be worthwhile. But you just can’t get away with too much model/world three card monte, maintaining that your model both does apply to the behavior of real people, but cannot be touched by investigations into the sources of the behavior of real people.

Right on page 1, Gul and Pesendorfer say “Neuroscientific evidence cannot refute economic models because the latter make no assumptions and draw no conclusions about the physiology of the brain,” but this just has to be false if economic models are actually supposed to be models of human behavior. Because, see, human beings have brains. And brains are actual phsyical systems that have physical constraints that limit, say, the amount of information that can be processed within a period of time. If an economic model of the agent assumes instantaneous, zero-error updating, or the all-at-once representation of an ordering including the uncountably large number of options in the feasible set, or knowledge of the entire set of all other agents uncountably large preference orderings, then the model is in fact making a large number of assumptions about the information-processing capacities of agents. And if it turns out that human information processing capacities fall far short of these assumptions (and, oh, do they ever) then you have a choice when it comes to the economic model. You can either admit that it is not a model of actual human behavior, but just of some imaginary agent not subject to the laws of physics, such that they can complete all this computation before the heat death of the sun, or the implosion of the Universe. Or you can admit that it is bad model—false, due to non-correspondence—but, perhaps, of some heuristic value in hypothesis formation, or some such thing.

What you can’t do is say you’ve got a model of something that is in fact a biological system, and then argue that real information about the nature of the biological system is irrelevant to the truth of your model. I may be crazy, but that seems to me exactly what Gul and Pesendorfer are trying to argue. If it is, I am completely sure that it won’t work.

  • Great post.

    I suppose the classic Milton Friedman response is that even if the assumptions that neoclassical economics makes about human psychology are false, there are enough domains in which people act like they are true to make it worth while, since using real psychology makes the math really hard.
  • Edgeworth
    Wonderful post Will and spot on. The Friedman argument is ok if you are then willing to consider alternative, equally useful models or extensions of the model. The problem with the Gul/Pesendorfer argument is that it is the last gasp of the theorist. By idolizing simple neoclassical they can justify the research agenda that elevates formalism above everything else. These guys will hem and haw in public. But anyone who has hired theorists knows that theorists really believe the following: Formal models based on neoclassical assumptions are the sine qua non of economics. Any theory which is not as formally dense as existing models DOES NOT QUALIFY AS THEORY regardless of how good its predictions. They are only willing to consider alternatives if they can be shoehorned into an appropriately "interesting" model.

    On the other hand, the best applied work still uses analysis at the formal level of the 1960s. So there is a disjunction between how we use econ vs what constitutes publishable "theory".
  • I reckon that most mainline economists don't want to have to admit that their assumptions about human behavior are just way too strong. If the economic mainstream took the empirical findings of the psychologists seriously, they would have to retreat to the far weaker assumption that humans act with the intent to bring about a state of affairs more preferred than that state of affairs which would come to pass but for their action. Not only is that a mouthful, but you can't say it in the language of real analysis, so I'm not surprised by Gul & Pesendorfer's view.
  • hector mendieta
    this has seemed obvious to me for a long as i've considered such things. hovever you, myself and other readers of your blog are obviously outliers given the popularity of paternalistic solutions. thanks for expressing this more elegantly than i ever could - and for your other good work.
  • hector mendieta
    whoops! posted to the wrong article! belongs to NIM article below.
  • Colin Camerer
    Your discussion is incredibly cogent and right. The GP argument is a throwback to behaviorism in psychology (no discussion of "mentalist" constructs is allowed) and the emergence of the revealed preference approach (which, curiously, they equate with "economics"). As David Colander has pointed out in a working paper, economists including Ramsey, Fisher and Edgeworth were all eager to measure utility directly using a "psychogalvanometer" (Ramsey's term), but lacking one the profession was willing to treat utility as inherently unobservable. But now we have psychogalvanometers.

    The goal of neuroeconomics is to make better predictions, which is entirely in line with Friedman's desire too. We part company with Friedman et al by presuming that more accurate assumptions lead to more accurate predictions. And yes, the math *is* harder, but is not "too hard" as the first poster said, and the ability to do very difficult math has skyrocketed in academic economics anyway.
  • Suresh Krishna
    In defense of Gul and Pesendorfer: To me, after a quick glance at the issues, this debate seems quite similar to asking whether models of behavior would be better off by being based on realistic neurons and patterns of functional connectivity. At the moment, this is clearly not the case: models of behavior with patently unrealistic (or absolutely no) notions of the underlying brain units or architecture may do a far better job of capturing behavior than unwieldy models that attempt to model behavior from the base upwards by being faithful to whatever little is known about neural structure. Needless to say, both levels of analysis have their own uses, but there is not that much evidence that an attempt to merge the two levels will lead to an enormous growth in our ability to predict things.

    I am entirely open to being corrected ! Be altruistic :)
  • Suresh Krishna
    ps. I just read the Caplan note referenced in the post above; I find that entirely reasonable. Indeed, on a case-by-case basis, there may be something to be gained from an understanding of both areas, but this is a tempered and moderate assesment that is quite far from the wideranging and sweeping claims made by vociferous propagandists for neuroeconomics.
  • Sean Muller
    Although I see your point, I disagree. It seems to me that what Gul and Pesendorfer do is precisely what James suggests above, they retreat to the corec concept of revealed preference.

    If you really want a comprehensive look at these questions I would recommend Ross (2005)[http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10526] but my problem is less the content of the Gul&Pesendorfer paper than what others are trying to use it for - as a way of keeping out important behavioural criticisms of formal models, and a basis for arguing that cognitive science is not relevant to the field of decision theory. I don't think the arguments in the paper can actually be used to support such claims.
  • Colin Camerer
    Suresh-- what are the "w*ideranging and s*weeping claims made by v*ociferous p*ropagandists for neuroeconomics"? Please quote in detail and in context. Outside of newspaper reporting (which is not propaganda; it is entirely separate from academics thinking about this topic), most claims *are* tempered. I doubt the terms denoted like t*his in my revision of your quotation hold up as assertions about what people have said. Furthermore, to the extent that any such claims are sweeping, they are meant to apply many decades in the future as the quality of neural data-- and micro theory-- improve. Your earlier post says "there is not much evidence..." of improvement from neural detail. Of course there is not; nobody says there has been so you are driving by looking in the rearview mirror. Are you asserting there will not be such evidence in the next 20 years?
  • Hi, Colin.

    I would like to contribute to this, since I take exception to Gul and Pesendorfer's paper on quite different grounds that no one seems to mention. That in a moment, but first I want to offer a half-defense. This is, of course, strictly wrong:

    “Neuroscientific evidence cannot refute economic models because the latter make no assumptions and draw no conclusions about the physiology of the brain.”

    It is wrong because of computability and complexity. Mappings can't be computed instantaneously or by magic. If we simply want to score debating points, we are done. But scoring debating points is for sophomores in debate club.

    I think that, in their own innocent-of-cognitive-science way, Gul and Pesendorfer are trying to articulate what David Marr articulated so well. From the "Marrian" perspective, formal neoclassical economic theory is "computational theory:" An attempt to guess at what is computed and why. It is like addition, or the mathematics of stereopsis. Nonlinear optimization, addition and stereopsis can all be handled by a great number of alternative algorithm/representation combinations, and those in turn can all be realized in a large number of physical types of hardware. So, there is some sense in skepticism about looking at hardware, if you are really more interested in what is computed and why. At best, knowing the hardware could put some limits on the kinds of algorithms that are running on the hardware. But, there would (for most big parallel machines) be a huge number of algorithms that could in turn approximate a bewilderingly large number of mathematical mappings with all kinds of error characteristics. Under these circumstances, can you really blame someone for being skeptical about looking at hardware?

    Marr's question is basically this. Suppose visiting alien A is given a hand calculator and opens it up and studies its circuits, while visiting alien B is shown the calculator and told it approximates an operation that is commutative, reflexive, associative, etc., with some known biases. Which alien now has more interesting knowledge about the calculator? It depends on what interests you. If you are interested in building adding machines, maybe you want to be alien A. If on the other hand, you are a social scientist interested in the significance the hand calculator has in this culture, you probably want to be alien B.

    The really, real problem with Gul and Pesendorfer, in my own opinion, is that it erases the notion of algorithmic bias in computing mappings. Put differently, it must rule out competence/performance gaps. Indeed, the whole notion of performance as something that can be anything other than maximal gets erased by Gul and Pesendorfer's worldview. The paper really should have been called "The case for machine-free, algorithm-free economics."

    To the extent algorithms exist in Gul and Pesendorfer's world, they all perfectly compute all mappings that are relevant to human economic situations. There are no performance failures. If there is something metaphysically ridiculous about their view, surely this must be it; in Gul and Pesendorfer's metaphysical universe, Alan Turing, Donald Knuth, etc. never said anything of fundamental importance.
  • Hello there.
    Just found your site. Great job!
    I like it much.
    look here http://live.com
blog comments powered by Disqus

Previous post:

Next post: