Hi Vasco, thanks for writing this! I’m glad to see more cross-cause research, and this seems like a useful starting point.
Some quick thoughts on why the deforestation rate assumptions might be too high:
Net change in forest area per capita in 2015[3] (m2/​person), in each of the countries analysed by GiveWell for its top charities here[4]. I calculated this from the ratio between:
Net change in forest area in 2015 by country (ha), based on these data from Our World in Data (OWID).
Population in 2015 by country, based on these data from OWID.
(...)
This is only accurate to the extent the annual impact on net forest area of the people saved by GiveWell’s top charities is similar to that of the mean citizens of their countries in 2015.
This assumption would not hold if some of the major causes of deforestation are limited by factors not very sensitive to population size. For example, some deforestation may be driven by international demand for products that are produced in those countries, so that the effects of more people willing to work on these products (by saving lives) should be tempered by elasticity effects. They could also be limited by capital, which GiveWell beneficiaries may be unlikely to provide, given their poverty and living situations.
Deforestation for agriculture for domestic consumption or for living area would be sensitive to the population size, but, again, GiveWell beneficiaries may be unrepresentative, a possibility you implicitly acknowledge by assuming is not the case.
Furthermore, with increasing deforestation, there will be less land left to deforest, and that land may be harder to deforest (because of practical or political challenges). Each of these point towards the marginal effect of population being smaller than the average effect.
I haven’t looked into any of this in detail or tried to verify any of these possibilities, though.
I agree I may well have overestimated the deforestation rate. That being said, even if the deforestation rate is only 1 % of what I assumed, the mean relative variation in cost-effectiveness would range from 3.86 k to 0.166 μ. We can narrow this down by focussing on the plausible moral weights, but without looking further it looks like the analysis could go either way.
Hi Vasco, thanks for writing this! I’m glad to see more cross-cause research, and this seems like a useful starting point.
Some quick thoughts on why the deforestation rate assumptions might be too high:
This assumption would not hold if some of the major causes of deforestation are limited by factors not very sensitive to population size. For example, some deforestation may be driven by international demand for products that are produced in those countries, so that the effects of more people willing to work on these products (by saving lives) should be tempered by elasticity effects. They could also be limited by capital, which GiveWell beneficiaries may be unlikely to provide, given their poverty and living situations.
Deforestation for agriculture for domestic consumption or for living area would be sensitive to the population size, but, again, GiveWell beneficiaries may be unrepresentative, a possibility you implicitly acknowledge by assuming is not the case.
Furthermore, with increasing deforestation, there will be less land left to deforest, and that land may be harder to deforest (because of practical or political challenges). Each of these point towards the marginal effect of population being smaller than the average effect.
I haven’t looked into any of this in detail or tried to verify any of these possibilities, though.
Hi Michael,
Thanks for the encouragement!
I agree I may well have overestimated the deforestation rate. That being said, even if the deforestation rate is only 1 % of what I assumed, the mean relative variation in cost-effectiveness would range from 3.86 k to 0.166 μ. We can narrow this down by focussing on the plausible moral weights, but without looking further it looks like the analysis could go either way.