I Don’t Think These Count

Economist Karl Smith and I have been going back forth about the nature of the assertions made by economics. In his most recent post on the subject, Smith says this:

I see in one of Jim Manzi old posts he is asking for anyone to come up with 14 non-obvious empirically verified and useful rules made by economists.

He then takes up the challenge by listing 14 propositions that he believes qualify.

The actual challenge in my post was this:

My challenge would be simple: please list 14 useful, non-obvious predictive rules that economics provides that have survived rigorous, replicated falsification trials. [Bold added]

Smith was presumably short-handing, which is fine, but it’s important to keep in mind the bolded terms. A predictive rule has the form “IF observable event X occurs, THEN observable event Y will follow.” Surviving rigorous, replicated falsification trials, means that the predictive rule has been tested by independent investigators attempting to disprove it, by using it to make difficult, measurable, real-world predictions, and seeing if it passes all of them.

A number of the rules that Smith proposes don’t seem to me to be, or map unambiguously to, a predictive rule of the form IF X, THEN Y. In this post, I’ll just focus on some of those that seem to be asserted predictive rules. I think there is a consistent problem with most of them: they are not falsifiable.

Consider Smith’s Rule 5: “An increase in the mass of citizenry will not lead to an increase in the proportional mass of the unemployed.”

What about the fact that between 2000 and 2007 the number of U.S. citizens rose, and the proportion of unemployed subsequently increased?

Of course, you will say: “That’s idiotic. The increase in the mass of the citizenry didn’t lead to the increase in the proportional mass of the unemployed. It was a coincidence.” But this counter-argument begs the crucial question: how do you know that?

I’ve picked an extreme example to make a methodological point. We all know that there was a huge economic crisis at the same time that probably had an enormous role to play in rising unemployment starting in 2008. OK, so should the corrected rule say that “An increase in the mass of citizenry will not be followed by an increase in the proportional mass of the unemployed, unless there is also an economic crisis of the following dimensions”? I don’t think that works, because I can come up so easily with another counter-example that did not occur during a financial crisis, which would then require some other exception. And so on. These aren’t isolated incidents; there are thousands of examples, of varying duration and geographical extent, of population increases followed by unemployment increases. Either you are able to generalize these exceptions into some (potentially probabilistic) rule that can be stated in reasonably compact form, or you’re writing a history book.

If you have built such a rule, then it can be tested; but you don’t get to rescue the rule after it fails a test by stating some new exception, and claiming that the rule is still “basically right.”

Rules like this, that embed terms like “leads to” or “causes,” typically will not really be falsifiable, because they beg the question of causality that falsification testing is meant to establish provisionally.

Consider, in the same light, Smith’s Rule 6: “The total flow of services available to the community cannot, in general, be increased by destroying some stock of assets. I.E. one cannot raise general living standards by breaking glass to give work to the glass maker.”

What about Western Europe between 1939 and 1970? Following the massive destruction of its stock of assets in WWII, Europe rebuilt to provide much greater flow of services to the community. The same problem exists for the counter-argument that “but for the destruction of WII, Europe would have been even richer in 1970.” How do you know that? The rule embeds the assumption of the answer in the form of “be increased by,” so counter-examples can’t disprove the rule.

Or consider Smith’s Rule 9: “Increasing the supply of medicine and vaccines to a preindustrial society will cause living standards to fall.”

What about Europe from before to after the industrial revolution? The supply of medicine and vaccines was increased, and living standards subsequently rose enormously. Same problem again: the rule simply assumes “cause,” and this precludes falsification.

(Cross-posted to The Corner)