Thanks so much. This is a tour de force! I have one more suggestion about this model. I know that GiveWell has strong reasons to use its own metrics rather than DALYs or QALYs. The problem is that DALYs and QALYs are much more widely used in the academic literature.
My suggestion is the model should report estimated $/DALY averted in addition to (not instead of) the preferred units of cost-effectiveness as a multiple of cash transfers. This would:
Provide up-to-date benchmarks to catalyze shallow investigations of new cause areas. There’s no need to do a lot of modeling to quickly evaluate a new intervention that reports in units of $/DALY averted.
Allow for a quick “reality check” of these models. Do they lead to results that are in the same ballpark as published estimates from the literature?
Even if the EA cost-effectiveness units are indisputably better, the benefits of being able to engage more directly with the research community seem to outweigh the costs of adding a few rows to the model.
I don’t think this works to achieve the same end, because $/DALY is specific to measuring health benefits—it doesn’t provide any way to capture increased income, consumption, etc. Nonetheless, evaluations like “AMF saves a life for $4,000” must have been derived from a $/DALY estimate at some point in the pipeline so I suspect it is being calculated somewhere already.
That’s not true – GW’s AMF CEA goes straight to mortality reduction, no $/DALY intermediate step. None of the other GW CEAs use D/QALY either; if they don’t use mortality reduction they use 2x income.
Thanks so much. This is a tour de force! I have one more suggestion about this model. I know that GiveWell has strong reasons to use its own metrics rather than DALYs or QALYs. The problem is that DALYs and QALYs are much more widely used in the academic literature.
My suggestion is the model should report estimated $/DALY averted in addition to (not instead of) the preferred units of cost-effectiveness as a multiple of cash transfers. This would:
Provide up-to-date benchmarks to catalyze shallow investigations of new cause areas. There’s no need to do a lot of modeling to quickly evaluate a new intervention that reports in units of $/DALY averted.
Allow for a quick “reality check” of these models. Do they lead to results that are in the same ballpark as published estimates from the literature?
Even if the EA cost-effectiveness units are indisputably better, the benefits of being able to engage more directly with the research community seem to outweigh the costs of adding a few rows to the model.
I don’t think this works to achieve the same end, because $/DALY is specific to measuring health benefits—it doesn’t provide any way to capture increased income, consumption, etc. Nonetheless, evaluations like “AMF saves a life for $4,000” must have been derived from a $/DALY estimate at some point in the pipeline so I suspect it is being calculated somewhere already.
That’s not true – GW’s AMF CEA goes straight to mortality reduction, no $/DALY intermediate step. None of the other GW CEAs use D/QALY either; if they don’t use mortality reduction they use 2x income.