Sharp eye, Vasco! Two things probably drove this result.
(a) Most significantly, we’ve taken into account the fact that different countries have different levels of cost-effectiveness (driven by differing disease burdens, neglectedness, tractability etc); and so an EA funder or fund-adviser targeting the top end of countries (as we are doing ourselves in our charity evaluations) can probably get far higher impact (we estimate the top end is 7x the average, which is plausible to us insofar as even top GiveWell charities like DtW see similarly drastic cost-effectiveness differences across their country projects).
That said, making these geographic adjustments is very time consuming (since you basically have to build a whole geographic prioritization model, which in turn requires a lot of data sourcing and talking to NGOs etc) - so it’s not usually feasible to do in shallow/​intermediate research rounds.
(b) Additionally, in the intermediate CEA, we based our costing estimates on a couple of big global NCD charities. However, subsequent work suggests that this would not be realistic—in the hypertension space, we’ve been following up on our cause priorization research by doing actual evaluations of sodium policy charities, to circulate to our grantmaking and E2G partners. The organizations we’ve been looking at have tended to be smaller local LMIC charities—partly because we are unlikely to move enough money to really help those big global orgs, but also because those local charities are probably more cost-effective (they tend to have pre-existing government connections, but also crucially, much lower salaries). Expecting that the kind of charities we (and other impact-oriented EA donors) will look at in the diabetes space, will similarly be these smaller local LMIC charities, we’ve changed our costing reference class accordingly.
We also looked at an additional bunch of negative factors (like SSB taxes cause substitution towards alcohol, or how much disvalue people place on reduced freedom of choice from taxes) and added more epistemic discounts to the theory of change (particularly around whether taxes impact consumption), but these did not turn out to be as significant as the above two factors.
Sharp eye, Vasco! Two things probably drove this result.
(a) Most significantly, we’ve taken into account the fact that different countries have different levels of cost-effectiveness (driven by differing disease burdens, neglectedness, tractability etc); and so an EA funder or fund-adviser targeting the top end of countries (as we are doing ourselves in our charity evaluations) can probably get far higher impact (we estimate the top end is 7x the average, which is plausible to us insofar as even top GiveWell charities like DtW see similarly drastic cost-effectiveness differences across their country projects).
That said, making these geographic adjustments is very time consuming (since you basically have to build a whole geographic prioritization model, which in turn requires a lot of data sourcing and talking to NGOs etc) - so it’s not usually feasible to do in shallow/​intermediate research rounds.
(b) Additionally, in the intermediate CEA, we based our costing estimates on a couple of big global NCD charities. However, subsequent work suggests that this would not be realistic—in the hypertension space, we’ve been following up on our cause priorization research by doing actual evaluations of sodium policy charities, to circulate to our grantmaking and E2G partners. The organizations we’ve been looking at have tended to be smaller local LMIC charities—partly because we are unlikely to move enough money to really help those big global orgs, but also because those local charities are probably more cost-effective (they tend to have pre-existing government connections, but also crucially, much lower salaries). Expecting that the kind of charities we (and other impact-oriented EA donors) will look at in the diabetes space, will similarly be these smaller local LMIC charities, we’ve changed our costing reference class accordingly.
We also looked at an additional bunch of negative factors (like SSB taxes cause substitution towards alcohol, or how much disvalue people place on reduced freedom of choice from taxes) and added more epistemic discounts to the theory of change (particularly around whether taxes impact consumption), but these did not turn out to be as significant as the above two factors.