If I had to pick one paper to represent why the Class is so important, about why so much which passes for science is unworthy, it might be the peer-reviewed creation of Derek Lemoine which he called “Climate change has already made the United States poorer” and which, inexplicably, the Proceedings of the National Academy of Science published.
I say ‘inexplicably’ because PNAS used to be a journal of science, and a paper which began with the words “Climate change is already here” would have been summarily rejected, not so much for its bad science, but so the author, and editor, wouldn’t embarrass themselves. I’ll save the punchline until the bottom.
There has not been even one day since earth formed which the climate has not changed. The climate is in constant flux. Even worse for the Lemoines of professional science, there is no power on earth, or off earth, that can stop “climate change”.
Ignore all that and let’s see what Lemoine got up to. From the Abstract (which he later echoed in the paper opening):
The climate is already changing. The present study shows that these changes have already affected the U.S. economy. It develops a formal framework that accounts for how climate change has affected each county’s economy by altering current and past weather, both locally and elsewhere around the country. The results show that climate change is already reducing annual U.S. income by 0.32% [95% CI: -0.17 to 0.82%] by altering counties’ current, local temperatures, with losses concentrated in the Great Plains and Midwest.
That “formal framework” means Lemoine has a model (before I read it, I guessed what kind). The results mean that according to a parameter in his model, “climate change” might have had a negative reduction in annual US income. That’s what the “-0.017%” means: a negative reduction.
Which means an increase.
Which is hilarious.
How would you go about proving that “climate change” caused—the very strictest word in all science—the per capita income in the USA (or anywhere) to change?
Answer: you could not. The idea is absurd. Best you could ever hope for is some loose imprecise vague suspicious watery correlation. Which no one would be obligated to believe.
Of course, one could point to individual events, say a hard freeze over a Florida orange crop, and calculate a rough loss (which event should be rarer under global warming). Or the opposite, show how slightly warmer, sunnier, and a far more pleasant spring boosted production. You’d still be left with correlation and some fairly wide plus-or-minuses, because weather is only one condition of price, which is only one input to income. But such a move would more or less defensible.
Try the same for a scarcely noticeable changes in temperature over a continent and those changes’ interaction with the entire economy, and that economy’s interaction with average income, and, well, you have fantasy.
Highly numerate fantasy. Here part of Lemoine’s model for “the percentage change in income per capita due to climate change”.
The y are incomes, w are “weather” variables, and W is “an index of weather variable n around the country”. The Greek letters are parameters. He says “The right-hand side of Eq. 1 captures how climate change affects income via its direct effect on contemporary weather, via ex post adaptation to the history of weather shocks, and via ex ante adaptation based on beliefs about coming weather”.
That lower-case lambda “capture[s] the effect on income per capita of changes in contemporary weather, which may matter for income both directly and by affecting the contemporary local capital stock.” And so on for the other Greeks.
Don’t worry if you can’t understand the math. The idea is that (log of) income can be tied to weather in his equation. The model is purely correlational, and is silly. To say the entire (average) income of a country can be definitively tied to weather in just this linear way is a mighty boast, which cannot be defended.
Here’s some of the details, given for those who know how to read such things. We really only need that second sentence.
Basically it’s one large regression model using counterfactual guesses of what the weather would have been had man not been around: that’s what the absence of human influences in the second sentence means.
Of course, Lemoine forgets that if man was not around, and thus there were no human influences on climate, there would be no economy.
The economy, and thus incomes, are deeply intertwined with the products of the economy that Lemoine thinks change the weather. People drive to work, they use electricity to buy and sell. Etc. Meaning even if Lemoine’s counterfactual guesses about the weather were perfectly correct, which they most certainly are not, and that even if his model were perfectly accurate and causal, which suggestion is laughable, his project is worthless. He’d have some loose correlations with counterfactual changes in weather, in which there would be no economy because no human influence, and changes in income, which he began by assuming would be affected by changes in weather. And affected (it seems) by nothing else.
How he missed this we can only guess. Perhaps it was the usual desire to jump on the Funding Bandwagon, and look cool in front of his colleagues. Maybe he just wanted to show off his math skills. It takes some doing to fit equations like the above. It really does take a high degree of learning to make his intricate plots.
But it’s all in service of a bizarre fantasy. Though passed off as, and taken as, Science by the mighty powers above us.
And that’s why those who can, ought to be taking the Class.
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