Glimcher: Neuroeconomic Analysis 2: Because vs. As-If

The life blood of the theoretician is constraint.

To understand why, one must look to the size of conceptspace. The cardinality of conceptspace is formidable. For every fact, how can there be only a countable number of explanations for that fact? How many theories of physics have managed to explain what it means for an apple to fall from a tree? Putting on our Church-Turing goggles, we know that every event can be at least approximated by a string of binary code, that represents that data.
The number of programs that can be fed to a Turing Machine to generate that particular string is unbounded.

Constraint is how theoreticians slice away ambiguity, how they localize truth in conceptspace. To say “no”, to say “that is not possible”, is a creative and generative act. Constraint is a goal, not a limitation.

After summarizing each of the three fields he seeks to link, Glimcher spends an entire chapter responding to a particular claim of Milton Friedman, which permeates the economic climate of modernity. Friedman argued that it is enough for economics to model behavior *as if* it is congruent to some specified mathematical structure. In his words:

“Now of course businessmen do not actually solve the system of simultaneous equations in terms of which the mathematical economist finds it convenient to express this hypothesis… The billiard player, if asked how he decides where to hit the ball, may say that he “just figures it out” then also rubs a rabbit’s foot just to make sure… the one statement is about as helpful as the other, and neither is a relevant test of the associated hypothesis”.

This, Glimcher argues, is precisely the wrong way to go about economics, and scientific inquiry in general. Because human beings are embodied, there exist physical, causal mechanisms that generate their economic behavior. To turn attention away from causal models is to throw away an enormously useful source of constraint. It is time for economics to move towards a Because Model, a Hard model, that is willing to speak of the causal web.

Despite this strong critique of economic neo-classicism, Glimcher is unwilling to abandon its traditions in favor of the emerging school of behavioral economics. Glimcher insists that the logical starting place of neoclassicism – the concise set of axioms – retains its fecundity. Instead, he calls for a causal revolution within theories such as expected utility; from Soft-EU to Hard-EU.

According to Glimcher, “the central linking hypothesis” of neuroeconomics is that, when choice behavior conforms to the neoclassical axioms (GARP), then the new neurological natural kind of the Subjective Value must obey the constraints imposed by GARP. Restated, within its predictive domain, classical economics constrain neuroscience because utility IS a neural encoding known as a subjective value.

Glimcher then goes on to establish more linkages, which he uses to constrain the data deluge currently experienced within neuroscience. Simultaneously, he employs known impossibilities of the human nervous system to close the door on physically non-realizable economic models. It is to neuroscience that we turn next.