I’d also add it would be great if there was more work to empirically analyse ex ante and ex post spread among hits based interventions with multiple outcomes. I could imagine it leading to a somewhat different picture, though I think the general thrust will still hold, and I still thinking looking at spread among measurable interventions can help to inform intuitions about the hits based case.
One example of work in this area is this piece by OP, where they say they believe they found some 100x and a few 1000x multipliers on cash transfers to US citizens by e.g. supporting advocacy into land use reform. But this involves an element of cause selection as well as solution selection, cash transfers seem likely below the mean, and this was based on BOTECs that will contain a lot of model error and so should be further regressed. Overall I’d say this is consistent with within-cause differences of ~10x from top to mean, and doesn’t support > 100x differences.
I agree that this would be great to exist, though it is likely very hard and the examples that will exist soon will not be the strongest ones (given how effects can become visible over longer time-frames, e.g. how OP discusses green revolution and other interventions that took many years to have the large effects we can now observe).
One small extra data point that might be useful: I made a rough estimate for smallpox eradication in the post, finding it fell in the top 0.1% of the distribution for global health, so it seemed consistent.
I’d also add it would be great if there was more work to empirically analyse ex ante and ex post spread among hits based interventions with multiple outcomes. I could imagine it leading to a somewhat different picture, though I think the general thrust will still hold, and I still thinking looking at spread among measurable interventions can help to inform intuitions about the hits based case.
One example of work in this area is this piece by OP, where they say they believe they found some 100x and a few 1000x multipliers on cash transfers to US citizens by e.g. supporting advocacy into land use reform. But this involves an element of cause selection as well as solution selection, cash transfers seem likely below the mean, and this was based on BOTECs that will contain a lot of model error and so should be further regressed. Overall I’d say this is consistent with within-cause differences of ~10x from top to mean, and doesn’t support > 100x differences.
I agree that this would be great to exist, though it is likely very hard and the examples that will exist soon will not be the strongest ones (given how effects can become visible over longer time-frames, e.g. how OP discusses green revolution and other interventions that took many years to have the large effects we can now observe).
One small extra data point that might be useful: I made a rough estimate for smallpox eradication in the post, finding it fell in the top 0.1% of the distribution for global health, so it seemed consistent.