I think Nick is fundamentally correct that because uncertainty is so high, sorting isn’t particularly useful. Most grantmaking organizations, to my understanding, prefer to use a cost-effectiveness threshold/funding bar, to decide whether or not to recommend/support a particular cause/intervention/charity.
For ourselves, we use 10x GiveWell for GHD, as (a) most of the money we move is EA and the counterfactual is GiveWell (so to have impact we the ideas we redirect funding/talent to be more cost-effective than GiveWell in expectation, and (b) we have such an aggressive bar because GiveWell is very robust in their discounting relative to us (which takes a lot of time and effort). An aggressive bar helps ensure that even if your estimated cost-effectiveness estimate is too optimistic relative to GiveWell, it can eat a lot of implicit discounts while still ensuring that the true cost-effectiveness is >GiveWell. (so when we say something is >=10x GiveWell it’s not literally so, more of a reasonably high confidence claim that it’s probably more cost-effective (in expectation).
I understand the reasons for ranking relative to a given cost-effectiveness bar (or by a given cost-effectiveness metric). That provides more information than constraining the ranking to a numerical list so I appreciate that.
Btw, if you had 5-10 mins spare I think it’d be really helpful to add explanation notes to the cells in the top row of the spreadsheet. E.g. I don’t know what “MEV” stands for, or what the “cost-effectiveness” or “cause no.” columns are referring to. (Currently these things mean that I probably won’t share the spreadsheet with people because I’d need to do a lot of explaining or caveating to them, whereas I’d be more likely to share it if it was more self-explanatory.)
Hi Jaime, I’ve updated to clarify that the “MEV” column is just “DALYs per USD 100,000″. Have hidden some of the other columns (they’re just for internal administrative/labelling purposes).
Thanks for the thoughts, Jaime and Nick!
For what it’s worth, CEARCH’s list of evaluated causes (or more specifically, top interventions in various causes) and their estimated cost-effectiveness is here: https://docs.google.com/spreadsheets/d/14y9IGAyS6s4kbDLGQCI6_qOhqnbn2jhCfF1o2GfyjQg/edit#gid=0
I think Nick is fundamentally correct that because uncertainty is so high, sorting isn’t particularly useful. Most grantmaking organizations, to my understanding, prefer to use a cost-effectiveness threshold/funding bar, to decide whether or not to recommend/support a particular cause/intervention/charity.
For ourselves, we use 10x GiveWell for GHD, as (a) most of the money we move is EA and the counterfactual is GiveWell (so to have impact we the ideas we redirect funding/talent to be more cost-effective than GiveWell in expectation, and (b) we have such an aggressive bar because GiveWell is very robust in their discounting relative to us (which takes a lot of time and effort). An aggressive bar helps ensure that even if your estimated cost-effectiveness estimate is too optimistic relative to GiveWell, it can eat a lot of implicit discounts while still ensuring that the true cost-effectiveness is >GiveWell. (so when we say something is >=10x GiveWell it’s not literally so, more of a reasonably high confidence claim that it’s probably more cost-effective (in expectation).
Thank you!
I understand the reasons for ranking relative to a given cost-effectiveness bar (or by a given cost-effectiveness metric). That provides more information than constraining the ranking to a numerical list so I appreciate that.
Btw, if you had 5-10 mins spare I think it’d be really helpful to add explanation notes to the cells in the top row of the spreadsheet. E.g. I don’t know what “MEV” stands for, or what the “cost-effectiveness” or “cause no.” columns are referring to. (Currently these things mean that I probably won’t share the spreadsheet with people because I’d need to do a lot of explaining or caveating to them, whereas I’d be more likely to share it if it was more self-explanatory.)
Hi Jaime, I’ve updated to clarify that the “MEV” column is just “DALYs per USD 100,000″. Have hidden some of the other columns (they’re just for internal administrative/labelling purposes).