(Here’s me, looking as scholarly as I can for the camera.)

 

Nat Wilcox's home page

 

My research interests are economic, political and

cognitive science,* experimental methods and

applied econometrics.

 

 

My current vita is here:          Complete curriculum vitae (PDF)

My current research, and some supporting documents for published research, are here:             Working papers

Here is some of my published research:

Austin, A. and N. Wilcox. 2007. Believing in economic theories: Sex, lies, evidence, trust and ideology. Economic Inquiry 45:502-518.

(PDF)

Wilcox, N. 2006. Theories of learning in games and heterogeneity bias. Econometrica 74:1271-1292.

(PDF)

Van Boeing, M. and N. Wilcox. 2005. A limit of bilateral contracting institutions. Economic Inquiry 43:840-854.

(PDF)

Ballinger, T. P., M. Palumbo and N. Wilcox. 2003. Precautionary saving and social learning across generations: An experiment. Economic Journal 113:920-947.

(PDF)

Archibald, G. and N. Wilcox. 2002. A new variant of the winner’s curse in a Coasian contracting game. Experimental Economics 5:155-172.

(PDF)

Ballinger, T.P. and N. Wilcox. 1997. Decisions, error and heterogeneity. Economic Journal 107:1090-1105.

(PDF)

Van Boening, M. and N. Wilcox. 1996. Avoidable cost: Ride a double auction roller coaster. American Economic Review 86: 461-477.

(PDF)

Wilcox, N. 1993. On a lottery pricing anomaly: Time tells the tale. Journal of Risk and Uncertainty 7:311-324.

(PDF)

Wilcox, N. 1993. Lottery choice: Incentives, complexity, and decision time. Economic Journal 103:1397-1417.

(PDF)

 

My contact information

By mail:

By phone:

By email:

In person:

Department of Economics

University of Houston

Houston, TX 77204-5019

tel 713 743 3840

fax 713 743 3798

 nwilcox@mail.uh.edu

McElhinney 209B

Here are materials for my current courses (Fall 2008)

 

 

 

Words to live by:

 

 

            1. Science:                    Seek simplicity, but distrust it.

 

                                                             —Alfred North Whitehead 

 

 

            2. Scholarly writing:      “A silly, infuriatingly unscholarly piece, designed to mislead” is

                                                what one irate…scholar called this…But this is not correct;

                                                rather, what I have written here is a silly, misleadingly

                                                unscholarly piece, designed to infuriate. There is a huge

                                                difference.

           

                                                            —Geoffrey K. Pullum

 

 

            3. Academic output:      Quantity has a quality all its own.

 

                                                            —apocryphal

 

 

            4. Statistics:                  My father was very sure about certain matters pertaining to

                                                 the universe. To him, all good things - trout as well as eternal

                                                salvation - came by grace; and grace comes by art; and art

                                                 does not come easy.

 

                                                            —Norman Maclean

 

 

            5. What they say:          Resistance is futile. You will be assimilated.

 

                                                            —The Borg Collective, Star Trek: Next Generation

 

 

            6. What I think:             I will not comply.

 

                                                            —Seven of Nine, Star Trek: Voyager

 

                                                                       

            7. Food:                       There is some shit I love to eat.

 

                                                            —some stand-up poet riffing on e. e. cummings,

                                                            poetry slam at The Green Mill, Chicago 1986.

 

 

            8. Everything else:         Freedom is its own punishment.

                                                                                                                       

                                                            —P. J. O’Rourke

 

*No, Really—What am I?

 

          Yeah, I know…it sounds ridiculously broad and grandiose to say that your interest is “economic, political and cognitive science.”

 

          My Ph.D. is in economics, but I studied as much cognitive science as economics in grad school, and continue to be influenced by a wide array of cognitive scientists. In today’s academic economics, I would typically be labeled a behavioral economist in light of that (but I resist this label, and many self-identified behavioral economists would not consider me one of them, for reasons I will make clear below). I’m particularly interested in questions of method, like “How do you measure risk aversion?” or “How do you tell the difference between theory X and theory Y?” or “Can we learn about the way people behave in a so-called real world by watching what they do in a so-called lab?”

 

          As a result, I work on a variety of things, ranging from questions about experimental methods to questions about estimators. There’s frequently some sort of epistemic worry that guides my work. In a very amusing essay, the linguist Geoffrey K. Pullum once attacked what he called “methodological moaning.” Pullum was right that methodological moaning can needlessly get in the way of doing progressive science—particularly when it is the evidence-free sort of whining that was Pullum’s chief target. On the other hand, it’s hard to imagine a healthy empirical science in which no practitioners are worrying about, teasing or horsing around with methodological questions in an evidence-based fashion.

 

          Lurking behind much of my work, there is also a desire for a metaphysically satisfying union of cognitive science, economics, evolutionary biology and moral philosophy. This is not something I explicitly discuss in any of my research papers—it is “bigthink” best left to others—but it lurks between the lines. Since Turing, it seems to me that no intellectually honest economist can ignore computational reality; to do so is metaphysically unsatisfying. Computation is neither instantaneous nor free, the latter being redundant in light of the former to any economist since Becker. Mappings, orderings and problem solutions cannot occur by magic. In this, I most definitely part company with many self-described neoclassicists who, for the most part, will argue that computability is irrelevant in adaptive steady states. I appreciate the argument but suspect that, as an empirical matter, it is rarely relevant, since I suspect that such adaptive steady states rarely prevail.

 

          However, it also seems to me that since Marr (see Chapter 1 of his Vision) one cannot avoid thinking about “computers” (I include here brains, economic and political institutions, etc.), whether of human or evolutionary design, as being for a purpose. Put differently, in the terms of Dennett, to not adopt a design stance or intentional stance when thinking about information-processing—that is, to wholly detach the descriptive from the normative, when theorizing about a retina or decision making or auctions—is also metaphysically unsatisfying and perhaps also ultimately empty from the viewpoint of most kinds of utilitarian moral philosophy which, after all, is where economics came from and what it was originally for. In this, I most definitely part company with most self-described behavioral economists who, for the most part, will argue that the normative has no place in descriptive behavioral science. I believe this is a mistake, since we are biological organisms shaped by evolutionary pressures. Some telos must loom large behind the behavior of evolved organisms, if not the “perfectly perfect” kind imagined by high neoclassicism.

 

          As a result, I find certain extreme positions in both current neoclassical economics (e.g. “I don’t care how this is computed, or even whether it can be computed in real time—this mathematical or logical entity exists, has these testable properties, and that’s all I need to know”) and current behavioral economics (e.g. “the descriptive accuracy of a theory of economic behavior is all that should interest a scientist”) metaphysically unacceptable. And metaphysics, like evidence, matters to me. Therefore, I decline to call myself either a neoclassical or a behavioral economist, since I do not want to associate myself with their particular metaphysical extremes. This is not to say that all (or even most) neoclassical or behavioral economists subscribe to those particular extremes, but I do find that the labels cause exactly those confusions that these two extreme characterizations would suggest.

 

          To put this more concretely in terms of an example, I find expected utility theory unsatisfying because of its empirical inadequacy but, at the same time, I find prospect theory equally unsatisfying because it neither has a defensible normative interpretation, nor has anyone explained how it is the result of computations meant to approximate some evolutionarily defensible goal (but do see Daniel Friedman’s nice story about the S-shaped value function as a constrained optimum…this is an example of what a “Marrian” such as myself wants to see). Glib and vague assurances about something being “generally adaptive” do not constitute such explanations. If Marr’s question “What is computed and why?” remains unanswered by some information-processing theory, then that theory is not a satisfying and complete information-processing theory—at least not in my book. If the algorithm/representation systems that produce “prospect theory behavior” in humans have no explanation in terms of a well-defined and evolutionarily defensible computational theory in Marr’s sense, then I do not understand why those algorithm/representation systems are as they are. It should be clear that “evolutionarily defensible” does not always mean “locally optimal;” for more on that, see Gould and Lewontin. Biological and evolutionary reasons are broader than that; evolutionary history and lack of foresight constrain what evolution can accomplish as adaptive landscapes shift, of course.

 

          Superficial descriptive adequacy is only a part of a satisfying behavioral and social science: We also want to understand how and why biological, cognitive and cultural evolution have left us as we are. Without that understanding, our descriptive achievements are at best incomplete and at worst incompatible with the theoretical and empirical worlds of biology and evolution. That is unsatisfactory, because we are biological organisms as well as social ones and information-processing machines. Yes, these are high demands for a complete behavioral and social science, and we are a long way from meeting them.

 

          If I were free to define a label, I’d like to call myself a “cognitive economist.” Unfortunately the label “cognitive economics” has already been used by others in ways that are most definitely not descriptive of me. So, I’m stuck with saying that my research interests are economic, political and cognitive science. Yes, really.