Explaining social behavior: More nuts and bolts for the social sciences

Once a scholar has identified a suitable mathematical function or a suitable set of dependent or independent variables, she can begin to look for a causal story to provide an intuition to back the findings. When she writes up the results for publication, the sequence is often reversed. She will state that she started with a causal theory; then looked for the most plausible way of transforming it into a formal hypothesis; and then found it confirmed the data. This is bogus science. In the natural sciences there is no need for the “logic of justification” to match or reflect “the logic of discovery.” Once a hypothesis is stated in its final form, its genesis is irrelevant. What matters are its downstream consequences, not its upstream origins. This is so because the hypothesis can be tested on an indefinite number of observations over and above those that inspired the scholar to think of it in the first place. In the social sciences (and in the humanities), most explanations use a finite data set. Because procedures of data collection often are nonstandardized, scholars may not be able to test their hypotheses against new data. [Footnote:] One could get around or at least mitigate this problem by exercising self-restraint. If one has a sufficiently large data set, one can first concentrate on a representative sample and ignore the rest. Once one has done one’s best to explain the subset of observations, one can take the explanation to the full data set and see whether it holds up. If it does, it is less likely to be spurious. Another way of keeping scholars honest would be if journals refused to consider articles submitted for publication unless the hypotheses to be tested together with the procedures for testing them had been deposited with the editor (say) two years in advance.

Because it is often easy to detect the operation of motivated belief formation in others, we tend to disbelieve the conclusions reached in this way, without pausing to see whether the evidence might in fact justify them. Until around 1990 I believed, with most of my friends, that on a scale of evil from 0 to 10 (the worst), Communism scored around 7 or 8. Since the recent revelations I believe that 10 is the appropriate number. The reason for my misperception of the evidence was not an idealistic belief that Communism was a worthy ideal that had been betrayed by actual Communists. In that case, I would simply have been victim of wishful thinking or self-deception. Rather, I was misled by the hysterical character of those who claimed all along that Communism scored 10. My ignorance of their claims was not entirely irrational. On average, it makes sense to discount the claims of the manifestly hysterical. Yet even hysterics can be right, albeit for the wrong reasons. Because I sensed and still believe that many of these fierce anti-Communists would have said the same regardless of the evidence, I could not believe that what they said did in fact correspond to the evidence. I made the mistake of thinking of them as a clock that is always one hour late rather than as a broken clock that shows the right time twice a day.

Delay strategies might seem to hold out the best promise for dealing with emotion-based irrationality. Since emotions tend to have a short half-life, any obstacle to the immediate execution of an action tendency could be an effective remedy. As I note later, public authorities do indeed count on this feature of emotion when they require people to wait before making certain important decisions. It is rare, however, to observe people imposing delays on themselves for the purpose of counteracting passion. The requisite technologies may simply be lacking.

Are the conclusions true? Before I address this issue, I want to observe that it is not clear that they are always intended to be true, that is, to correspond to the actual world. Rather, they sometimes represent a form of science fiction—an analysis of the action and interaction of ideally rational agents, who have never existed and never will. The analysis of ever-more-refined forms of strategic equilibria, for instance, is hardly motivated by a desire to explain or predict the behaviour of actual individuals. Rather, the motivation seems to be an aesthetic one. Two of the most accomplished equilibria theorists, Reinhart Selten and Ariel Rubinstein, have made it quite clear that they do not believe their models have anything to say about the real world. When addressing the workings of the latter, they use some variety of behavioural economics or bounded rationality. To cite another example, social choice theory—the axiomatic study of voting mechanisms—became at one point so mathematically convoluted and so obviously irrelevant to the study of actual politics that one of the most prominent journals in economics, Econometrica, imposed a moratorium on articles in this area.

An interesting question in the psychology and sociology of science is how many secret practitioners there are of economic science fiction—hiding either from themselves or from others the fact that this is indeed what they are practicing. Inventing ingenious mathematical models is a well-paid activity, but except for the likes of Selten and Rubinstein payment will be forthcoming only if the activity can also be claimed to be relevant; hence the incentive for either self-deception or deception. To raise this question might seem out of bounds for academic discourse, but I do not see why it should be. Beyond a certain point, academic norms of politeness ought to be discarded.