Are there GiveWell-style estimates of the cost-effectiveness of the world’s most popular charities (say UNICEF), preferably by independent sources and/or based on past results? I want to be able to talk to quantitatively-minded people and have more data than just saying some interventions are 1000x more effective.
Unfortunately most cost-effectiveness estimates are calculated by focusing on the specific intervention the charity implements, a method which is a poor fit for large diversified charities.
Hmm, that’s what I suspected. Maybe it’s possible to estimate anyway though—quick and dirty method would be to identify the most effective interventions a large charity has, estimate that the rest follow a power law, take the average and add error bars upwards for the possibility we underestimated an intervention’s effectiveness?
One argument against the effectiveness from mega charities who does a bunch of different, unrelated interventions is that from the Central Limit Theorem (https://en.m.wikipedia.org/wiki/Central_limit_theorem) the average effectiveness of a large sample of interventions is apriori more likely to be close to the population mean effectiveness—that is the mean effectiveness of all relevant interventions. In other words, it’s hard to be one of the very best if you are doing lots of different stuff. Even if some of the interventions you do are really effective, your average effectiveness will be dragged down by the other interventions.
Are there GiveWell-style estimates of the cost-effectiveness of the world’s most popular charities (say UNICEF), preferably by independent sources and/or based on past results? I want to be able to talk to quantitatively-minded people and have more data than just saying some interventions are 1000x more effective.
Unfortunately most cost-effectiveness estimates are calculated by focusing on the specific intervention the charity implements, a method which is a poor fit for large diversified charities.
Hmm, that’s what I suspected. Maybe it’s possible to estimate anyway though—quick and dirty method would be to identify the most effective interventions a large charity has, estimate that the rest follow a power law, take the average and add error bars upwards for the possibility we underestimated an intervention’s effectiveness?
One argument against the effectiveness from mega charities who does a bunch of different, unrelated interventions is that from the Central Limit Theorem (https://en.m.wikipedia.org/wiki/Central_limit_theorem) the average effectiveness of a large sample of interventions is apriori more likely to be close to the population mean effectiveness—that is the mean effectiveness of all relevant interventions. In other words, it’s hard to be one of the very best if you are doing lots of different stuff. Even if some of the interventions you do are really effective, your average effectiveness will be dragged down by the other interventions.