I also found their neglect to mention to mention smokeless products strange. In Norway and Sweden, for example, snus has been replacing cigarettes.

There are not too many case studies to look at here, but in Bhutan, their 2010 ban on the importation and sale of all tobacco products (which was coupled with government counseling and treatment to facilitate cessation) proved controversial and difficult to enforce in the face of large-scale smuggling and was eventually scaled back in 2021. 

fair points! I should have been explicit here but I was invoking epistemological humility primarily in response to SMA's public statements about the tobacco industry which in my view do not seriously engage with the idea that tobacco use could be a free-but-harmful or free-and-beneficial choice for any consumers.

I would push back on the idea that the harm/benefit ratio to smoking is somehow 'medically settled'. The fact that cigarettes greatly increase risk of lung cancer, say, is settled but for the harm/benefit ratio to be settled it would require us to be able to put the harm and benefit in comparable units; the correct procedure for which is, in my view, a epistemological mystery (the problem here seems similar to trying to get an unambiguous answer with health economics whether to go on a fun-but-risky rafting trip or a safe-but-boring trip to the mall).

I do believe the freedom to choose self-destructive habits is an important principle worth defending though I don't think that claim is necessary for the more narrow point I was making in this post.

In what way do you find it unrepresentative? Just curious because I am unfamiliar with the dynamics here.

good points!

with respect to the utility function I originally chose log because it's what Open Philanthropy uses. However I now see that GiveWell sometimes uses an isoelastic utility function with $\eta =1.59$, which is faster diminishing returns than log-utility ($\eta =1$). 

Redoing the math with a general isoelastic utility function, for $\eta >1$ you get an optimal point at which to donate, with that point depending on the parameters of the model (income and investment growth rates, the rate of diminishing returns, etc.). This optimal donation time is also dependent on the size of the population you can donate too, so to get a more accurate model you would need to incorporate that (as well as a bunch of currently-unaccounted-for factors like the changing effectiveness of non-cash charities).

I think value drift (along with risk of losing control of your assets due to any number of scenarios) can just be modeled by discounting the expected growth rate for risk of loss. If you think you have a 1% chance of losing your money each year, you might treat your investment growth rate as 4.2% instead of 5.2%, for example.

yes, I definitely think this is a complication here. The toy model in this post assumes the only cause is something like direct cash transfers. I think this makes sense as a baseline (for the same reason GiveWell uses cash transfers as a baseline) but of course we can and do find global health interventions more promising than cash transfers and it is possible the effectiveness of these interventions diminishes over time faster than investment returns. However, I do not think this is what we have seen so for in practice. In 2015, GiveWell had 3 non-cash charities they estimated to be 5-10x more effective than cash transfers, but by 2018 they had 7 which they estimated to be 5-15x more effective than cash^[1]. 

1. ^{^}

   https://www.openphilanthropy.org/research/givewells-top-charities-are-increasingly-hard-to-beat/