As far as your example on counterfactual funding—we could gauge what the government was spending on malaria prevention before AMF started up operations in the area, and what it was spending after. If pre-AMF spending on malaria prevention in an area were low, that sets the ceiling on how much AMF spending could be crowding out local government spending in that area. I think GiveWell tries to account for crowding out local funding.
You could give money to the subnational government earmarked for a specific purpose that you’re confident that the government wouldn’t have counterfactually funded. However, that burdens the developing country public health services with managing your and 100 other donor earmarks, and potentially destroys some of the advantages of working within the public system.
Perhaps you could try a fancier earmark, conditioning a grant for more health workers on the government funding as many workers as it had before. But that’s going to require even more monitoring, and you may also be locking the government into spending its own money in a way that’s suboptimal to meet your grant terms.
If you don’t earmark to something that wouldn’t have otherwise been funded, you risk an equivalent reduction in public spending and the net effect of your donation going to better roads or something (not trivial, but just a general donation to the government). That’s a 100 percent slippage.
So while I agree that there’s likely some substitution effect in all cases, the magnitude of that effect (as well as the administrative difficulty and cost of mitigating the risk) could vary by an order of magnitude.
That’s not to say you couldn’t find a way to do what you’re suggesting without incurring more-than-AMF levels of substitution effects . . . only that I think it would be rather challenging.
As far as your example on counterfactual funding—we could gauge what the government was spending on malaria prevention before AMF started up operations in the area, and what it was spending after. If pre-AMF spending on malaria prevention in an area were low, that sets the ceiling on how much AMF spending could be crowding out local government spending in that area. I think GiveWell tries to account for crowding out local funding.
You could give money to the subnational government earmarked for a specific purpose that you’re confident that the government wouldn’t have counterfactually funded. However, that burdens the developing country public health services with managing your and 100 other donor earmarks, and potentially destroys some of the advantages of working within the public system.
Perhaps you could try a fancier earmark, conditioning a grant for more health workers on the government funding as many workers as it had before. But that’s going to require even more monitoring, and you may also be locking the government into spending its own money in a way that’s suboptimal to meet your grant terms.
If you don’t earmark to something that wouldn’t have otherwise been funded, you risk an equivalent reduction in public spending and the net effect of your donation going to better roads or something (not trivial, but just a general donation to the government). That’s a 100 percent slippage.
So while I agree that there’s likely some substitution effect in all cases, the magnitude of that effect (as well as the administrative difficulty and cost of mitigating the risk) could vary by an order of magnitude.
That’s not to say you couldn’t find a way to do what you’re suggesting without incurring more-than-AMF levels of substitution effects . . . only that I think it would be rather challenging.