To say that markets can be represented by supply and demand “curves” is no less a metaphor than to say that the west wind is the “breath of autumn's being.” (McCloskey 1983, p. 502)

When we tack a “random variable” onto a theoretical model, do we announce our faith in a supreme being, who, for reasons unknowable, endows us with deductive faculties sufficient to formulate a set of alternative hypotheses, one of which is the data-generating process that he or she has constructed to determine our fates? Is data analysis the holy sacrament through which the supreme being incrementally reveals the data-generating process to the faithful? Do we wait patiently until time infinity for the complete revelation, in the meantime forsaking all but consistent estimators?

No, I think not. Models, stochastic or otherwise, are merely metaphors. We are willing for some purposes to proceed as if the data were generated by the hypothesized model just as we are willing for other purposes to proceed as if “econometrics is a piece of cake.”

The basic conceptual error that is made by econometric theorists is their failure to recognize that in practice probabilities are metaphors. A probability metaphor is most compelling when the data come from a designed experiment with explicit randomization of the treatments. But in nonexperimental settings the probability metaphor often stretches the imagination beyond the point of comfort. Nagging but persistent doubts about the aptness of the metaphor leave us with nagging but persistent doubts about the inferences that depend on it.