I’m glad someone’s getting something out of the two hours I spent manually copying all the DCP2 estimates :)
It looks like you’re using the mean of the DCP2 estimates to estimate the expected value of funding an intervention at random. I believe the correct way to do this would be to take the reciprocals of the cost-effectiveness estimates and then take their arithmetic mean, since that tells us the actual expected value of picking an intervention at random—which is a better analogue to what we’re doing with animal interventions. That gives us a minimum estimate mean of $9.65/DALY and a maximum estimate of $64/DALY. Then the difference between the mean and the best intervention is only about 10x. This suggests that we should expect picking a factory farming intervention at random to have fairly high expected value, if we think animal interventions follow a similar distribution to the interventions in DCP2.
EDIT: I would expect on priors to find that animal interventions are at least 10x more effective than global poverty interventions in general*. If animal interventions do follow a distribution like the DCP2, that suggests that blindly picking an animal intervention should have similar or higher expected value than picking the best global poverty intervention.
*For a few related reasons, including: (1) we spend hundreds of billions of dollars on global poverty but less than $20 million on factory farming; (2) most people (implicitly) discount animals by several orders of magnitude more than they should; (3) there are >10 times more factory-farmed animals than there are humans in extreme poverty.
I’m glad someone’s getting something out of the two hours I spent manually copying all the DCP2 estimates :)
It looks like you’re using the mean of the DCP2 estimates to estimate the expected value of funding an intervention at random. I believe the correct way to do this would be to take the reciprocals of the cost-effectiveness estimates and then take their arithmetic mean, since that tells us the actual expected value of picking an intervention at random—which is a better analogue to what we’re doing with animal interventions. That gives us a minimum estimate mean of $9.65/DALY and a maximum estimate of $64/DALY. Then the difference between the mean and the best intervention is only about 10x. This suggests that we should expect picking a factory farming intervention at random to have fairly high expected value, if we think animal interventions follow a similar distribution to the interventions in DCP2.
EDIT: I would expect on priors to find that animal interventions are at least 10x more effective than global poverty interventions in general*. If animal interventions do follow a distribution like the DCP2, that suggests that blindly picking an animal intervention should have similar or higher expected value than picking the best global poverty intervention.
*For a few related reasons, including: (1) we spend hundreds of billions of dollars on global poverty but less than $20 million on factory farming; (2) most people (implicitly) discount animals by several orders of magnitude more than they should; (3) there are >10 times more factory-farmed animals than there are humans in extreme poverty.