I wish we had a lot more posts that worked through charitiesâ cost-effectiveness claims in this way â even charities that are very unlikely to be competitive with standard âtop choicesâ, and even if the estimates include a high degree of uncertainty (as long as this is communicated).
As a community, it seems good for EA to routinely âkeep in touchâ with a wide range of areas, for a few reasons:
Weâre less likely to miss a genuinely strong opportunity from outside our usual focus areas.
Weâre able to provide useful information to people interested in specific areas (even a highly uncertain analysis > having nothing but the charityâs claims to work from).
We get lots of practice in building, reading, and discussing models of the world, and are constantly exposed to many different methods of evaluation.
Thanks for this, and thanks Michael for the post. This made me think we should perhaps have an overall evaluation of the cause area âHelping refugees migrateâ from different countries in crisis (e.g., South Sudan, Afghanistan, Haiti, NK etc.) and corresponding projects in receiving countriesâsuch as comparing LINK and GiveDirectlyâs cash transfers to refugess in Uganda.
I think that, for some countries, a useful proxy would be avg life expectancy, and maybe HDI differences (though HDI is not a cardinal measure, I think differences could help assess differences in life chancesâespecially if one can adjust for inequality). I made a personal rough evaluation about helping a specific Haitian family this way. However, I donât think this would extrapolate well for other countries (where HDI data is unreliable) or for people fleeing from persecution (where the counterfactual is not the average life, but just death); plus, in some cases (like NK and Afghanistan), it would be interesting to take into account political factors (point 4), but I have no idea about how to start to even begin to quantify this.
This is fantastic!
I wish we had a lot more posts that worked through charitiesâ cost-effectiveness claims in this way â even charities that are very unlikely to be competitive with standard âtop choicesâ, and even if the estimates include a high degree of uncertainty (as long as this is communicated).
As a community, it seems good for EA to routinely âkeep in touchâ with a wide range of areas, for a few reasons:
Weâre less likely to miss a genuinely strong opportunity from outside our usual focus areas.
Weâre able to provide useful information to people interested in specific areas (even a highly uncertain analysis > having nothing but the charityâs claims to work from).
We get lots of practice in building, reading, and discussing models of the world, and are constantly exposed to many different methods of evaluation.
Thanks for this, and thanks Michael for the post.
This made me think we should perhaps have an overall evaluation of the cause area âHelping refugees migrateâ from different countries in crisis (e.g., South Sudan, Afghanistan, Haiti, NK etc.) and corresponding projects in receiving countriesâsuch as comparing LINK and GiveDirectlyâs cash transfers to refugess in Uganda.
I think that, for some countries, a useful proxy would be avg life expectancy, and maybe HDI differences (though HDI is not a cardinal measure, I think differences could help assess differences in life chancesâespecially if one can adjust for inequality). I made a personal rough evaluation about helping a specific Haitian family this way. However, I donât think this would extrapolate well for other countries (where HDI data is unreliable) or for people fleeing from persecution (where the counterfactual is not the average life, but just death); plus, in some cases (like NK and Afghanistan), it would be interesting to take into account political factors (point 4), but I have no idea about how to start to even begin to quantify this.