The views expressed here are my own, not those of my employers or reviewers of the draft.
I have collected Ambitious Impact’s (AIM’s) cost-effectiveness estimates of the animal welfare and global health and development interventions they recommended for Charity Entrepreneurship’s incubation programs until 2024. I assumed an increase of 100 welfare points in humans (WPs) and 1 quality-adjusted life-year (QALY) are each equivalent to averting 1 disability-adjusted life-year[1] (DALY), and aggregated the main estimates of each report using the mean.
The table below contains the mean, geometric mean, 5th percentile, median, and 95th percentile cost-effectiveness of the animal welfare and global health and development interventions. All the 5 stats suggest the interventions in animal welfare are much more cost-effective than those in global health and development.
Statistic | Value for animal welfare (DALY/$) | Value for global health and development (DALY/$) | Ratio between the value for animal welfare and global health and development |
Mean | 1.16 | 0.0443 | 26.2 |
Geometric mean | 0.919 | 0.0109 | 84.5 |
5th percentile | 0.364 | 8.44*10^-4 | 432 |
Median | 1.32 | 0.0123 | 107 |
95th percentile | 1.73 | 0.194 | 8.91 |
Joey Savoie (AIM’s CEO) noted:
[AIM’s] welfare points are far less certain estimates when compared to our global health [and development] estimates. This matters a lot, e.g., I would regress weaker CEAs [cost-effectiveness analyses] by over 1 order of magnitude [making them less than 10 % as large] even from the same organization [AIM?] using similar methods, and it could be 3+ orders of magnitude across different orgs and methods. AIM in general is pretty confident e.g. that our best animal charities are not 379x better than a top GiveWell charity even if a first pass CEA might suggest that.
I understand cost-effectiveness estimates across different areas are not directly comparable, even if they are unbiased, because the methodologies differ. However, I believe the large regressions to a lower cost-effectiveness Joey mentioned only apply given a strong (low uncertainty) prior that animal welfare interventions are much less cost-effective[2]. It is unclear to me why one would have such a strong prior, as cost-effectiveness is usually considered to vary significantly across cause areas. All in all, I still consider the analysis of this post some evidence that the best interventions in animal welfare are much more cost-effective than the best in global health and development.
Thanks to Filip Murar, Morgan Fairless and Vicky Cox for feedback on the draft[3].
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Based on inverse-variance weighting, the regressed cost-effectiveness would be the mean between the prior and estimated cost-effectiveness weighted by the reciprocal of their variance. For the regression to be large, the prior cost-effectiveness has to be much lower than the estimated one, and the variance (uncertainty) of the prior cost-effectiveness much smaller than that of the estimated one.
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I listed the names alphabetically.
Does this account for probability of sentience and welfare ranges/moral weights?
Good question, Michael! Strongly upvoted. Vicky commented the cost-effectiveness estimates in WPs/$ account for the probability of sentience. However, I now realise welfare ranges conditional on sentience were apparently not considered. I will ask Vicky about this. "Cross-animal applicability" was one of the goals of the WPs' system, and I assume cost-effectiveness estimates in WPs/$ were directly compared with each other, so I believe the welfare ranges conditional on sentience should have somehow been taken into account.
Vicky confirmed welfare ranges conditional on sentience were not considered. So AIM's cost-effectiveness estimates in WPs/$ are not comparable across species, and I guess ones with lower welfare ranges conditional on sentience were overrated in AIM's analyses (namely, weighted factor models).
I have updated the post adjusting AIM's estimates based on Rethink Priorities’ median welfare ranges. The conclusion qualitatively remains: