If President Obama has a legacy in the history books of the future, it will likely be the utter ignorance of and contempt for economics expressed in his policies. Assuming, of course, that the next president is not even worse (which is not unlikely).
The debate following the proposal to raise the minimum wage to $10.10 is just the most recent example of Obama’s view of the world. (Central planning of health care is another.)
Granted, there is an ongoing debate among economists about the “real effects” (by which is meant: measurable, statistically significant effects in collected data) of minimum wage regulation. As Bob Murphy shows, this is not really a debate on the effect of outlawing low-paying jobs (which is what we are really talking about) but about empirical measuring techniques, data selection, econometric formulae, and statistical juggling.
The academic minimum wage debate is really only a symptom of the real problem: economics as an empirical science. Since economics is a social science, the “data” it relies on are necessarily interpreted and selected before plugged into lacking equations the statistical results of which must then be interpreted again. But “data” somehow still gives the results an air of untainted, unquestionable objectivity.
Nevertheless, modern economists seem to have swallowed the “data” illusion hook, line, and sinker. And while at it, they throw out all the babies they can find with what little bathwater they’re already pushing out the window.
Peter Coy, economics editor at Bloomberg BusinessWeek (and, I assume, an economist), shows – though by all accounts inadvertently – that while the debate attempts to sound like economics it clearly is not. Rather, it is just the common political statistics-throwing to support one’s own position on the matter (whether or not unfounded). Coy takes projection data from the CBO as potential facts about the future, and then dresses the argument in terms of ”reasonableness” to sound… well, reasonable. “Reasonable people,” he says, “can disagree” and do so. About what? Well, not the “data” (they’re objective, of course). But “about the point where the bad begins to outweigh the good.”
Please excuse a poor economist, but – economically speaking - how do we find that point?
To Coy the problem is weighing the effects (again, in the “data”): “it could make sense to raise the minimum wage even if some jobs are lost because of the benefits of higher pay to people who do have jobs.” Yes, you read that correctly: even if outlawing low-paying jobs would cause “some” unemployment (obviously an outlandish thought), it might “be worth it.”
“Worth it” to whom one might ask. Obviously not the people who either lose their jobs or lose their ability to get jobs. I guess it is “worth it” to Coy and his statistics-munching, central planning buddies. You see, if 900,000 people are “raised” above the “poverty line” by this policy and only 500,000 people are unemployed because of it (figures from Coy’s article), then we can simply do the math: what’s more beneficial for “society” (not the actual people affected)? Coy again: “This is a painful question of trade-offs, to which there is no clear right or wrong answer.”
See what he did there? He quickly passes over the fact that he uses aggregates of the utility of literally hundreds of thousands of people, that he adds them together and then compares them, and then quickly moves to saying it is a “trade-off” where it is a matter of being “reasonable” about aggregate gains and losses. It therefore seems to be an economic statement referring to aggregate opportunity costs, which somehow should be scientific.
Of course, this is assuming CBO is right and outlawing certain jobs means there will be comparatively fewer jobs available (duh!). But, Coy notes, this is not necessarily the case: “The CBO report is one more voice in the debate.”
A debate about what? That’s right, the debate about measurement and political manipulation of society and the aggregates in the economy. It really has nothing to do with economic science, but those involved in the public debate work very hard to make it seem scientific. If there is “data,” then there is truth (even if only projections). Consequently, to establish our truth, all we need to do is pick the right data, the right methods, and then present the irrefutable-because-statistically-significant results.
One then needs to be “reasonable” (that is, one cannot be dogmatic about economic law) in weighing some people’s undeserved (policy-forced) luck to other people’s (politically created) misfortune. What is reasonable? No need to be scientific here, since reasonableness can be established by referring to authority. Indeed, why debate this at all when we know that “seven Nobel prize-winning economists and four former presidents of the American Economic Association, along with more than 600 other economists, signed a letter to Congress urging passage of the $10.10 floor.”
I guess being opposed to the political condemnation of a few hundred thousand people to rather inescapable economic misery is “unreasonable.” It is fortunate that we have a reasonable president to lead the way. At least this means those below the “poverty line” may have some hope (though many of them will soon be begging for change).