After criticizing Patrick Thaddeus Jackson‘s antiscientific and dangerous attack on Rational Choice Theory, I then turned around and attacked Rational Choice Theory itself for not being a scientific theory (though it can be a useful tool).
The lesson, I guess, is that simply having the right enemies does not make you right yourself.
My critiqued of both Jackson and Rational Choice attracted the attention of Phil Arena, both regarding antiscience and, more interestingly, regarding Rational Choice. Phil was kind enough to provide with me two articles, “Does Preference Cycling Invalidate “Rational Choice Theory”?,” and “Rat Choice Apologetics II” in which he had previously attempted to defend Rational Choice Theory from similar attacks.
Phil’s posts emphasize that Rational Choice is not a scientific theory.
The first post, on preference cycling, is an extended “just-so” defense of Rational Choice theorizing against laboratory falsification. Phil writes:
My big point here is that those who seek to justify a wholesale rejection of “rational choice theory” by observing that some laboratory experiments have found that some individuals exhibit behavior that appears to reflect cyclical preferences are overplaying their hand.
But Phil’s bigger points seems to be that any laboratory finding does not falsify Rational Choice, because some collection of mathematical formulas can be modified post-hoc to account for the behavior observed. This speeks to the cleverness of the Rational Choice theorists — like Freudians or Jungians, any observation of evidence of their model.
Rational Choice is like Interviewing, because just as no experimental result can falsify Rational Choice, no experimental result can falsify the feelings of an interview subject. Few who are planning a complex intervention would do so without interviews of one sort or another, and it may be that Rational Choice is likewise useful. But just as the interview is a tool, not a scientific theory, Rational Choice is a tool, not a scientific theory.
In the follow-up Post, Phil goes farther to protect not just Rational Choice Theory, but any implementation of a rational choice theory, from falsification:
Amongst formal theorists, there is significant disagreement about how to evaluate models in general. On one end of the spectrum, you have the strict interpretation of EITM, as espoused here and seems to be Morton’s preferred view here, though she does discuss other views. This view holds that formal models are important for ensuring logical consistency of theoretical arguments, but the value of these arguments is ultimately judged empirically. On the other, you have Primo and Clarke, who argue that there are many different roles we could ask our models to serve, some of which do not require any kind of empirical assessment. My own views, as I’ve indicated before, are closer to those of Primo and Clarke.
This is not scientifically serious. But Rational Choice Theory is not a scientific theory, so of course it doesn’t have to be. The purpose of science is to improve, predict, or control behavior (at whatever unit of analysis we are working), but the purpose of tools such as interviews, case study, and rational choice is to inspire scientists to come up with scientific theories that can make control, predict, and improve behavior.
Phil’s a clear writer, so his point is written clearly. And he’s write that science has certain requirements — such as predictive validity — that are as hard to get away from as Rational Choice Theory’s unfalsifiable assumptions:
When we evaluate arguments empirically, we make a huge, non-falsifiable assumption that the future will be like the past. Otherwise, it would be meaningless to claim to be testing the claim that X causes Y by observing historical patterns of association between X and Y. On a certain level, we all understand this. That is why folks worry about omitted variable bias with observational studies and external validity with experiments. But I’m not sure how many people really appreciate the depth of the problem.
But of course the difference is that the scientific requirement for predictive validity enables it to fulfill its mission of predicting, improving, and controlling behavior (at whatever unit of analysis we are functioning). Rational Choice Theory rejects the scientific need to predict, improve, or control behavior, because it is a “formal model” which are “logical consistency” and thus do not need “empirical assessment.” That is, Rational Choice is a form of “qualitative” (or better, investigatory) analysis, where mathematical equation balancing takes the place of interviews or subjective impressions.
Rational Choice has a place in science, like any investigatory or qualitative method (introspection, interviews, case studies, etc): to generate hypotheses. Rational Choice should be a part of science to the extent its scientifically useful. But like interviews, case studies, and the such, we can’t generalize from rational choice theorizing, but of course we can generalize from the empirical findings such theorizing might lead us to.