The more I think about this Andrew Gelman post, the more ridiculous it seems. Gelman argues that economists, especially popular economists, use a pair of contradictory arguments to explain phenomena:
1. People are rational and respond to incentives. Behavior that looks irrational is actually completely rational once you think like an economist.
2. People are irrational and they need economists, with their open minds, to show them how to be rational and efficient.
In the comments, he clarifies his position:
My problem with some pop-economics is not with the use of arguments 1 or 2 but rather with what seems to me as the arbitrariness of the choice, accompanied by blithe certainty in its correctness. This looks more to me like ideology than science.
I have no problem criticizing economists for their blithe certainty, a criticism I’d also to apply to just about everyone, myself included. But I don’t follow Gelman’s criticism of the fact that economists apply different models to different situations. This happens in all disciplines, including Gelman’s field of statistics. For instance, statisticians often apply one of the following arguments:
- Phenomenon X follows a normal distribution.
- Phenomenon X follows a log-normal distribution.
1 and 2 are entirely contradictory, and to a non-statistician, it would appear entirely arbitrary whether to apply 1 or 2. But to a statistician, there is a logic (part science, part art) as to whether to apply 1, 2, both, or neither. Similarly, it may appear arbitrary to Gelman whether to assume rationality or non-rationality in a particular situation, when there is a consistent logic apparent to economists. Ultimately, models should be judged based on the reliability of their predictions, not perceived arbitrariness by outsiders.