Each year, GiveWell identifies more great giving opportunities than we are able to fully fund. As a result, in our charity recommendation decisions, we necessarily face very challenging questions, such as: How much funding should we recommend for programs that reduce poverty versus programs that reduce deaths from malaria? How should we prioritize programs that primarily benefit children versus adults? And, how do we compare funding those programs with others that have different good outcomes, such as reducing suffering from chronic health issues like anemia?
We recently received results from research we supported to help us answer these questions from the perspective of communities similar to those our top charities operate in. This blog post provides a brief summary of the project and results. Additional details are available on this page.
Background on the project
We assess charities based on their overall impact per dollar. In order to compare the impact per dollar across programs, we assign quantitative “moral weights” to each good outcome. We have invested a significant amount of time to arrive at these weights, but we still find our conclusions unsatisfying, in large part because of the fundamental difficulty of these questions. We have worked to improve our process for valuing different outcomes over the years, but we believe our current process is far from ideal.
Moral weights seems to be a highly neglected research topic. Limited information exists on how people value different outcomes. In particular, very few researchers have asked people living in low-income countries how they would make these tradeoffs. We see this as a potentially important input into our weights but have been unable to incorporate this information because it largely did not exist.
We recently supported a project intended to help address this gap in the literature. We provided funding and guidance to IDinsight, a data analytics, research, and advisory organization, to survey about 2,000 people living in extreme poverty in Kenya and Ghana in 2019 about how they value different outcomes.
Survey results
The results from this research are now available here. Among other findings, they suggest that survey respondents have higher values for saving lives (relative to reducing poverty) and higher values for averting deaths of children under 5 years old (relative to averting deaths of individuals over 5 years old) than we had previously been using in our decision-making.
Although we see these study results as adding to our understanding, we would caution against putting too much weight on them. Research methods like those used in the survey have major limitations, discussed here. This study is one that should be put in the context of a larger literature about these questions and represents one approach to moral weights among many.
Nevertheless, we see this research as a valuable contribution to the literature on preferences and moral views in communities with high rates of extreme poverty. It seems to be the first study of its kind conducted in sub-Saharan Africa, and the people surveyed for this study had a substantially lower average consumption level than other studies using similar methods.
Preliminary conclusions and updates
We have provisionally updated our moral weights to place more emphasis on programs that avert deaths (relative to those that reduce poverty) and to value programs averting deaths at all ages more equally (relative to our previous assumption of valuing programs that avert deaths of individuals over 5 years old more highly). The direction of these updates was driven by this study and other, independent arguments for putting more weight on health relative to income. However, we have not yet thoroughly debated how to revise our framework for moral weights or fully completed our analysis of these results, so we see our current, provisionally-updated moral weights as a work in progress. We plan to revisit our framework for moral weights in the future.
These updates did not have a major impact on our recommended funding allocation to charities in 2019.
Additional details
We share additional details on the survey and our early interpretation on this page.
Really excited to see this published. This is something I've heard people speculate about a lot over the years ("are people in places with higher child mortality more accepting of it, because it's more normal, and so are we overweighting deaths?") and it's helpful to see what the people we're trying to help actually value.
(And that's on top of us not being able to survey the children!)
+1, good to see empirical work on this
Interesting. In my modeling I valued life of everyone the same at 500-1000 times of one year of income vs 47-85 by Give Well and 230 - 142 from Ghana/Kenya. I value life 2-4 times that of Ghana/Kenya.
Appendix 9 on education is interesting, would have been easier to read if the education numbers were multiplied by 6 and converted to additional years of schooling (assuming secondary education = 12 years of schooling = high school in usa). Ghana/Kenya has totally unschooled kids 10% and 7 % in 2015. How would the results have changed if the question was about choosing between 6 years of primary education vs life? I wonder.
Given the results in Ghana 90+ years of schooling = 1 life, in kenya its 6-30 years My own switching points is 18 years, so roughly on par with Kenya. I wonder why Ghana is so high. Would the results differ among parents who went to school and illiterate grandparents? The theory being parents who went to school know what benefits school brings via lived experience vs others who are illiterate only have second hand understanding.
Thoughts?
Section 4 on subjective wellbeing is interesting.
I notice they only measured life satisfaction. Can you tell me why they didn't also include at least one measure of hedonic wellbeing, such as those used in the evaluations of GiveDirectly? It is really important to understand whether potential GiveWell top charity beneficiaries are actually unhappy (i.e. generally feel bad) or just dissatisfied with their material circumstances when someone with a clipboard asks them about it. (Life satisfaction is much more sensitive to relative wealth and status than is pleasure/misery.) For instance, this may be the critical factor when choosing between life-extending and life-improving interventions.