I run the Centre for Exploratory Altruism Research (CEARCH), a cause prioritization research and grantmaking organization.
I generally agree, and CEARCH uses geomeans for our geographic prioritzation WFMs, but I would also express caution - multiplicative WFM are also more sensitive to errors in individual parameters, so if your data is poor you might prefer the additive model.
Also general comment on geomeans vs normal means - I think of geomeans as useful when you have different estimates of some true value, and the differences reflect methodological differences (vs cases where you are looking to average different estimates that reflect real actual differences, like strength of preference or whatever)
Yep, the idea is more the former. And While GWWC is mainly OP funded, that's not entirely the case (https://forum.effectivealtruism.org/posts/a8wijyw45SjwmeLY6/gwwc-is-funding-constrained-and-prefers-broad-base-support), and could expand on the margin with individual donor contributions.
The point isn't specific to GWWC though - rather, I think it's potentially promising that cause-neutral effective giving organizations have the potential to effectively launder GHD dollars into AW dollars, by persuading GHD donors to support GHD effective giving (rather than persuading them to support animals, which is presumably harder).
This is somewhat offtopic, but getting GHD donors to give to GWWC and other GHD-focused effective giving orgs that also fundraise for AW, is effectively turning GHD dollars (from people who are emotionally uninvested in AW) into AW dollars for ACE et al.
And through this method, no appeal to animals is needed.
Intersectoral reallocation of resources doesn't mean an overall increase in demand, and hence even influx of labour and capital into YIMBY-initiated housebuilding won't cause higher inflation economy-wide - if anything, it pushes it down due to expanded supply bringing down rents, and as you note housing is an important part of PCE.
Generally, you would prefer lower interest rates from the perspective of LMICs, because you risk debt crises when high US interest rates intersect with LMIC dollar denominated debts, plus everything from food subsidies to investing in health/education/infrastructure becomes far more difficult.
Hi James, on the South Asian Air Quality portfolio, would be it be fair to say that OP's grants so far have been focused on research and diagnosing both the problem and potential solutions, rather than executing on interventions themselves? Is the current bottleneck a lack of cost-effective and feasible ideas - and if so, what looks most promising so far?
This is something Sjir's team and myself have discussed at length - we're definitely more pessimistic than GWWC on this point.
CEARCH's view is that the raw numbers look good, but if you regress dollar donated against year since pledging, while controlling for pledge batch (and hence the risk that earlier pledgers are systematically different/more altruistic), there is a positive but statistically insignificant relationship between average annual donations and years since pledging (n.b. increase in 35 dollars per annum at p=0.8). The experts we spoke to were split, with a weak lean towards it increasing over time - some were convinced by the income effects, while others were sceptical that you can beat attrition.
Ultimately, we chose to model a very marginal increase (<0.01% per annum); we're really not confident that you can reasonably expect an increase in giving over time for the 2025 and future pledge batches.
For how expected donations generated by a dollar evolves over time (ignoring discounts), available evidence suggests that it's flat (and so the graph is just a horizontal line terminating around 30 years later). There's a lot of uncertainty, not least on how long the giving lasts, given that we can only observe a little more than a decade of giving at this point.
My own experience, and my sense from talking to other organizations, is that management time is a significant opportunity cost, while the benefit (the work done by the intern) is both highly variable in quality and potentially not that great in expectation - not just because interns may be less experienced, but also because you probably put in fewer resources into the selection process, commensurate to the expected duration, cost and amount of work the intern puts in (all low relative to a full hire).
Some organizations leverage internships better, typically in roles that require time but not a lot of experience/expertise, and that require minimal supervision - but precisely because of that, the internship because less valuable from a talent pipeline perspective (since by definition you already have an existing source of free labour).