Some fellow who got rich once he was in office, Ro Khana, claims Elon Musk, who got rich outside office, is responsible for some preposterous number of deaths, something into the millions, because of Musk’s involvement with the once-happy bureau called the Department of Government Efficiency.
You recall DOGE was doing too good at its named job, cutting spending, which is forbidden in government, so it had to go. But not before it cut off the firehose of funds, the system which took my money, and probably yours too, and sprayed it out over the world. The reason the government gave for this seizure and redistribution was that I had money, the rest of the world did not have my money, and therefore the rest of the world deserved it and had to have it.
USAID was the name of the government entity that removed my money, and probably yours too, and gave it to people elsewhere. This provided great power to politicians, and a modest penury in you. Musk was instrumental in stopping USAID, which naturally incensed those used to and dependent upon the largess.
This accounts for why since USAID was folded up, there have been any number of claims of how stopping my money from being shipped overseas is somehow killing foreigners. This is, of course, absurd, as we’ll see. But even if it were true, it is not my duty to stop these deaths.
The peer-reviewed paper is “Evaluating the impact of two decades of USAID interventions and projecting the effects of defunding on mortality up to 2030: a retrospective impact evaluation and forecasting analysis” by Cavalcanti and a slew of others in the political journal The Lancet.
Their Background:
The US Agency for International Development (USAID) is the largest funding agency for humanitarian and development aid worldwide. The aim of this study is to comprehensively evaluate the effect of all USAID funding on adult and child mortality over the past two decades and forecast the future effect of its defunding.
Now this will turn out to a thoroughly asinine paper, which is to science what “lived experience” is to politics. Which is to say, fevered fiction. Regular readers will not be surprised at any of this.
Suppose your neighbor hasn’t a hammer and asks to borrow yours. You give it to him, he uses it to some benefit. Later you need it back and take it. Yet your neighbor has not completed his project. What is the best action your neighbor can take?
- A: Suffer and let his project rot for want of a hammer,
- B: Get his own hammer.
There will, of course, be a good number of indigent, unintelligent, and just plain lazy people who opt for A. Everybody else with go with B.
As will the countries who find their small cuts of my money have dried up. Not forgetting, of course, like with the vast majority of NGO-like entities, most of the monies end up in the pockets of politicians, activists, and organizers, with only the smallest trickle leaking to (the amusingly labeled) beneficiaries.
Everybody knows of this kind of corruption. That “everybody” ought to include researchers who build models to “prove” how missing USAID funds kill people. Meaning those models ought to include adjustments for the certain fraud that occurred. Did those models include adjustments for fraud? No, sir, they did not.
Indeed, the models assumed option A would be the case everywhere and for all peoples. Our researchers could not envision anybody could find a way to cope with the loss of USAID. They could only suffer.
The rest of the paper is yet another instance of the epidemiologist fallacy. This is when a researcher announces “X causes Y” but where X is never measured, and sometimes Y isn’t either, and proxies are given in their place, and where the cause is “confirmed” with wee P-values, which is always, no exceptions, a logical fallacy.
Yes. That “no exceptions” means even the studies you like, or the ones you did yourself.
Here are their Methods (feel free to scan):
In this retrospective impact evaluation integrated with forecasting analysis, we used panel data from 133 countries and territories— including all low-income and middle-income countries (LMICs)—with USAID support ranging from none to very high. First, we used fixed-effects multivariable Poisson models with robust SEs adjusted for demographic, socioeconomic, and health-care factors to estimate the impact of USAID funding on all-age and all-cause mortality from 2001 to 2021. Second, we evaluated its effects by age-specific, sex-specific, and cause-specific groups. Third, we did several sensitivity and triangulation analyses. Lastly, we integrated the retrospective evaluation with validated dynamic microsimulation models to estimate effects up to 2030.
No amount of USAID funding any person was given was measured, and neither was it measured whether any person lived or died because of that funding. In other words, X was not measured, nor was Y. Yet the claim (we see next) will be “X caused Y”. Instead, we get things like this: “Our modelling approach, based on previous studies, was done in two stages: first, we created a synthetic cohort of all countries for the years 2024–30, extrapolating and modelling each country-level independent variable from the retrospective dataset…”
Here are their Findings (cutting out the boring stuff, so please check the original):
Higher levels of USAID funding—primarily directed toward LMICs, particularly African countries—were associated with a 15% reduction in age-standardised all-cause mortality… and a 32% reduction in under-five mortality … This finding indicates that 91 839 663 … all-age deaths, including 30 391 980 … in children younger than 5 years, were prevented by USAID funding over the 21-year study period. USAID funding was associated with a 65% reduction … in mortality from HIV/AIDS (representing 25·5 million deaths) … Forecasting models predicted that the current steep funding cuts could result in more than 14 051 750 (uncertainty interval 8 475 990–19 662 191) additional all-age deaths, including 4 537 157 (3 124 796–5 910 791) in children younger than age 5 years, by 2030.
You see it: the direct claim of causality (deaths in children “prevented by USAID funding”) from a regression, which is forbidden in statistics, but of course happens all the time.
This model is really no different than the vast majority of economics models. It builds in the cause: it assumes the cause. The cause is assumed here by saying the positive correlation of USAID money caused the lives saved. The model is then run, and lo!, some researcher announces “We have discovered the cause we built into the model is the cause.”
For all models only say what they are told to say.
One of the main arguments against psychic abilities is the complete absence of psychics among the worlds trillionaires, or even billionaires. If people really could foresee the future or read minds they would have been able by now to have used these talents to observable effect. We do not observe these effects, and we are therefore rational to predict people who call themselves psychics are frauds.
The same argument works for economists.
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