Our goal with hosting quarterly open threads is to give blog readers an opportunity to publicly raise comments or questions about GiveWell or related topics (in the comments section below). As always, you’re also welcome to email us at email@example.com or to request a call with GiveWell staff if you have feedback or questions you’d prefer to discuss privately. We’ll try to respond promptly to questions or comments.
You can view previous open threads here.
Since 2020, I have learned from the meticulous cost-effectiveness spreadsheets for each top-charity.
In 2022, an estimate of risk would inform my allocation of donations. For example, I would learn from estimating the amount of risk and uncertainty for AMF to save a life. AMF Cost to Save a Life Apr 2022 ranges from about $4000 to $9000.
1. Is that an average estimate?
2. Do you know of a pessimistic estimate?
3. Do you know of a technique to derive a pessimistic estimate?
At the moment, a naïve notion might be to copy the spreadsheet and refer to the column with the highest estimate $9050 in Chad. Then to naively recalculate each risky or uncertain row with an extra margin. A naïve example of an extra margin might be 5% worse. Meaning it would multiply the cell value by 1.05 or divide by 1.05, depending on whichever operation raises the cost to save a life. Obviously this fiddling is unscientific and below the high standard GiveWell has for auditing an intervention. Yet, with my ignorance and limited free time, I would still learn from some way of estimating risk and uncertainty. Of course, GiveWell has already estimated some risk and uncertainty into the estimate, yet at first glance, it is unclear what kind of range of expected values would be plausible in a pessimistic scenario.
The cost per life saved estimates we provide for our top charities in the spreadsheet you link to are our best guesses for each program in each location. They’re not averages, although many of the inputs that go into our cost-effectiveness analyses are averages (e.g., in the AMF tab you link to, we use 10 as the average number of years between net distribution and when long-term benefits start to accrue). We don’t provide a pessimistic estimate of cost-effectiveness for our top charities; we just get as close as possible, given a number of uncertain inputs, to what we think the actual cost per life saved is. At times, we do conduct sensitivity analyses for parameters that are particularly uncertain, or that will have a big impact on our bottom line, to figure out the most extreme value we could use while still getting a result that meets our cost-effectiveness bar.
Coming up with a pessimistic estimate for each location in our analysis for, e.g., AMF, wouldn’t be a very straightforward process. It would require figuring out which individual parameters in the analysis need to be adjusted upward or downward, and by how much to change them. Starting with only the highest cost per life saved, for Chad, and adjusting from there would probably result in a significant overestimate for other locations. There are also some hard-coded inputs in our public cost-effectiveness analysis that would prevent it from updating correctly if you made a copy and adjusted key parameters.
We have at times included pessimistic or optimistic scenarios in our cost-effectiveness analyses for other grants to other programs. For example, in this analysis of Evidence Action’s program to support maternal syphilis screening and treatment in Liberia, we’ve included “pessimistic,” “optimistic,” and “best guess” figures (those highlighted in blue) for some of the values in the “Assumptions” tab. The parameters here aren’t the same as those used in our top-charity models; this is just to illustrate how we came up with a pessimistic scenario in another instance.
I hope that’s somewhat helpful!
Hi GiveWell team, I have a question around using ln(consumption):
When ln(consumption) is used in GiveWell’s CEA to measure the impact of income/consumption raising charities, this implies diminishing marginal returns to additional consumption. Under this assumption, if I understand correctly, it would be better to increase lots of people’s incomes by a little bit than a few people’s incomes by a lot.
I believe GiveWell’s CEA takes the log of average effects. For example, for deworming, ln(consumption) is calculated from the average effect of deworming. However, if interventions raise income much more for some people than others (e.g.
children with heavy worm burdens or severe vitamin A deficiency), this could lead to much larger effects for some people than others. Therefore, does using the log of an average effect actually overestimate the positive impact of the intervention (because, in reality, some beneficiaries are gaining large amounts of income with diminishing returns, while others don’t benefit at all)?
Has GiveWell thought about whether the 100 to 1 moral weight (life-saving vs consumption) is still appropriate given this factor?
Hello am a pastor pastoring a small village church in kenya. My request for you to help with musical instruments such as mixer, speakers, piano keyboard, microphones, guitars, drum set,power amplifier. Our members are mostly youths an kid who are jobless. Pls assist so us we can maintain this generation to Christ. Your consideration is highly appreciated. Pr Jesse wanjala. cff church.
Why is there no list of top 10 best charities per region of the world? I see this might have a bad taste for some. But we live in a world with borders, that are relevant to many of those who give in the world. Huge segments of the world think most about what happens in their backyard or have ties to a certain region of the world they are concerned about. If this were true you would attract many more givers to give to the best orgs working in Mexico, Indonesia, and so on where they have ties. I believe more individuals would be willing to give this way. As a company started in the US, I would think that some would like to chose a North American fund that y’all would pick the top 10 charities serving North American causes.
Thank you for your comment! GiveWell aims to direct funding that we believe will do as much good as possible per dollar spent, which for us means directing it to programs operating in the poorest parts of the world—most often communities in sub-Saharan Africa or south Asia. (Though most of our funding at the moment goes toward programs in sub-Saharan Africa, we will consider a grant in any location where we estimate the program is cost-effective enough to meet our bar. We have directed funds toward, e.g., Deworm the World Initiative and IRD Global in Pakistan, and Fortify Health in India.)
In these places, very cheap and relatively straightforward interventions to improve health or well-being can have an outsize impact, and some can be life-saving. This doesn’t mean that saving or improving lives in wealthier countries isn’t important, but it generally requires more complex, expensive interventions, so a dollar spent doesn’t go as far. You can read more about this guiding principle behind our work here.
We realize that not everyone shares this value, and many people, as you say, are interested in effective giving opportunities within their region. Although this is outside our scope of work, we aim to promote effective giving in general, and we would be happy to see another research organization create something like our top charities list that’s limited to programs working in, say, Europe or South America.
I hope that’s helpful!
That is helpful. We would love to partner with you if you have interest in sharing lessons learned and seeing something like this follow a similar model as your own. Certainly a synergistic opportunity.
Thank you for this thoughtful question! This is a good point, and we’re planning to consider an additional adjustment in our cost-effectiveness analysis to account for it, but are unsure how much of a difference this would ultimately make to our estimate of deworming’s cost-effectiveness.
We’ve used average benefits in the past because it simplifies our model, but it’s true that aggregate ln(benefits) will be lower if only some of the population gets a bigger earnings increase. Although we’re very uncertain about the proportion of the Miguel and Kremer deworming cohort that’s getting economic benefits, it’s probably less than 100%. We did some rough calculations to test out the importance of this factor, and our best guess is that it would only lead to a small update. If we assume that benefits accrue to 33% of the cohort, ln(benefits) are cut by only about 10%. We think that one-third of the participants benefiting is in a plausible range for this parameter, but we’re very uncertain about the actual value.
We’re adding this to a list of potential changes to our cost-effectiveness analysis that we’ll look into, though it’s unlikely to be a high priority for now because we suspect it will not have much of an impact on our cost-effectiveness estimates.
Thank you again for your engagement and for bringing this to our attention!
Thank you very much for engaging with my question and providing a detailed response.
I wonder if 33% may be too high given GiveWell’s worm burden adjustment assumes light worm burdens have zero impact, and on average only 1.34% of children in current programmes have moderate or heavy burdens (see columns E and F): https://docs.google.com/spreadsheets/d/11ADiprPvSNdqHyZdQaqdo2rXRr7gab-f10CX-m5Lct0/edit#gid=1920981014
However, perhaps it could be argued that small productivity improvements benefit a large number of people across the economy.
Looking forward to seeing further research on this and whether it is incorporated into GiveWell’s CEA!
I have not been able to find commentary from effective altruists regarding donations to famine relief — though I am new to the space and am not sure where best to look. Currently, multiple sources are reporting on a famine or near famine in the Horn of Africa, specifically in Somalia, Ethiopia and Kenya. Apparently it is related to grain scarcity due to the war in Ukraine.
We might suppose that this could be very efficient giving, after all, if lives are at stake and a typical EA project can save a life for $4000 (or whatever I’ve seen quoted), that same funding level could presumably provide over a year’s worth of food for an individual.
However, there may be massive inefficiencies at work. It may be very expensive indeed to get the food and supplies from source to destination. And there may not be a philanthropic opportunity — not if governments are hard at work at solving it already. There are reports of a grain caravan getting underway from Ukraine now.
So does a crisis end up allowing for efficient philanthropy or not? No doubt it depends on the particular crisis. Insight appreciated.
We sympathize with the desire to help people suffering from a crisis. Unfortunately, right now we don’t have any recommendations for giving to alleviate famine conditions.
Our impression has been that the biggest bottleneck to helping with disasters like famines isn’t lack of funding—both because high international attention to these events leads to an influx of donations, and because there are often logistical challenges in getting aid to the people who need it. We believe there’s greater potential for donors to help people in combating the everyday diseases that claim many lives each year, like malaria. We would guess that in general, our top charities represent more cost-effective giving opportunities than options for alleviating suffering from acute crises.
Disaster relief efforts also require a very fast response, and our intensive approach to investigations, which can sometimes require hundreds or thousands of hours of research to complete, isn’t well suited to coming up with recommendations very quickly.
We’ve written about this topic in blog posts here, here, and here, although we note that all of these posts are more than 10 years old. We also wrote a post (originally from 2013, reposted in 2017) with tips on giving more effectively to disaster relief if you decide to pursue it.
I hope that’s helpful!
Give Directly is the best and perfect donations to individual in Uganda
Comments are closed.