I am far less convinced that life saving interventions are net population creating than I am that family planning decreases it. Written about 10 years ago, but still one of the better pieces on this IMO is David Roodman's report commissioned by GiveWell.

From the abstract of David Roodman's paper on The Impact of Life-Saving Interventions on Fertility (written in 2014):

In places where lifetime births/woman has been converging to 2 or lower, saving one child’s life should lead parents to avert a birth they would otherwise have. The impact of mortality drops on fertility will be nearly 1:1, so population growth will hardly change. In the increasingly exceptional locales where couples appear not to limit fertility much, such as Niger and Mali, the impact of saving a life on total births will be smaller, and may come about mainly through the biological channel of lactational amenorrhea. Here, mortality-drop-fertility-drop ratios of 1:0.5 and 1:0.33 appear more plausible.

So it looks like saving lives in low income countries decreases fertility, but still increases population size.

From the abstract of David Roodman's paper on The Impact of Life-Saving Interventions on Fertility:

In places where lifetime births/woman has been converging to 2 or lower, saving one child’s life should lead parents to avert a birth they would otherwise have. The impact of mortality drops on fertility will be nearly 1:1, so population growth will hardly change. In the increasingly exceptional locales where couples appear not to limit fertility much, such as Niger and Mali, the impact of saving a life on total births will be smaller, and may come about mainly through the biological channel of lactational amenorrhea. Here, mortality-drop-fertility-drop ratios of 1:0.5 and 1:0.33 appear more plausible.

So it looks like saving lives in low income countries decreases fertility, but still increases population size. Because of the decrease in fertility, it may be good to downgrade the cost-effectiveness. The above would suggest multiplying it by around 0.5 (= 1 - 0.5) to 0.7 (= 1 - 0.33).

For life-saving to reduce population, it would have to reduce total fertility by more than 1 per child saved, which is extremely implausible on its face.

Why? Each bednet costs 5 $, and Against Malararia Foundation (AMF) saves one life per 5.5 k$, so 1.1 k bednets (= 5.5*10^3/5) are distributed per life saved. I think each bednet covers 2 people (for a few years), and I assume half are girls/women, so 1.1 k girls/women (= 1.1*10^3*2*0.5) are affected per life saved. As a result, population will decrease if the number of births per girl/women covered decreases by 9.09*10^-4 (= 1/(1.1*10^3)). The number of births per women in low income countries in 2022 was 4.5, so that is a decrease of 0.0202 % (= 9.09*10^-4/4.5). Does this still seem implausible? Am I missing something?

Your authors' interpretation is that there is no overall effect on fertility rates: "In this case, women simply shifted the same number of births forward, leading to more births today and less in the future." (Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.) This implies increased population long term as the saved children later go on to reproduce.

That is one hypothesis advanced by the author, but not the only interpretation of the evidence? I think you omitted crucial context around what you quoted (emphasis mine):

However, the third interpretation is a tempo vs. quantum effect: perhaps the ITN distribution induced women to have more births now, but did not change the number of overall births they intended to have. In this case, women simply shifted the same number of births forward, leading to more births today and less in the future [this is the only sentence you quoted]. Therefore, it is important to view our positive fertility results as short run, one year effects, rather than the effect on completed fertility.

My interpretation is that the author thinks the effect on total fertility is unclear. I was not clear in my past comment. However, by "lifesaving interventions may decrease longterm population", I meant this is one possibility, not the only possibility. I agree lifesaving interventions may increase population too. One would need to track fertility for longer to figure out which is correct.

Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.

From Figure 6 below, there is a statistically significant increase in fertility in year 0 (relative to year -1), and a statistically significant decrease in year 3. Eyeballing the area under the black line, I agree it is unclear whether total fertility increased. However, it is also possible fertility would remain lower after year 3 such that total fertility decreases. Moreover, the magnitude of the decrease in fertility in year 3 is like 3 % or 4 %, which is much larger than the minimum decrease of 0.0202 % I estimated above for population decreasing. Am I missing something? Maybe the effect size is being expressed as a fraction of the standard deviation of fertility in year -1 (instead of the fertility in year -1), but I would expect the standard deviation to be at least 10 % of the mean, such that my point would hold.

Great work, Jérémy!

Thanks for the post, Henry.

Unfortunately these ranges have such wide confidence intervals that, putting aside the question of whether the methodology and ranges are even valid, it doesn't seem to get us any closer to doing the necessary cost-benefit analyses.

Large uncertainty also means a high cost-effectiveness of animal welfare research which tries to decrease the uncertainty, given the high value of information.

Nice points, Emre!

d. People seem to keep forgetting that uncertainty cuts both ways. If the moral worth of animals is too uncertain, that is also a reason against confidently dismissing them.

Uncertainty also means a higher cost-effectiveness of animal welfare research which tries to decrease the uncertainty, given the high value of information.

Hi Richard,

It is unclear to me whether the ripple effects (indirect longterm effects) of life saving interventions are beneficial or harmful. From Wilde et. al (2020), whose abstract is below (emphasis mine), bednets increase fertility 1 to 3 years after their distribution, but decrease it afterwards, so population initially increases^[1], but may decrease soon after the distribution.

We examine the extent to which recent declines in child mortality and fertility in SubSaharan Africa can be attributed to insecticide-treated bed nets (ITNs). Exploiting the rapid increase in ITNs since the mid-2000s, we employ a difference-in-differences estimation strategy to identify the causal effect of ITNs on mortality and fertility. We show that the ITN distribution campaigns reduced all-cause child mortality, but surprisingly increased total fertility rates in the short run in spite of reduced desire for children and increased contraceptive use. We explain this paradox in two ways. First, we show evidence for an unexpected increase in fecundity and sexual activity due to the better health environment after the ITN distribution. Second, we show evidence that the effect on fertility is positive only temporarily – lasting only 1-3 years after the beginning of the ITN distribution programs – and then becomes negative. Taken together, these results suggest the ITN distribution campaigns may have caused fertility to increase unexpectedly and temporarily, or that these increases may just be a tempo effect – changes in fertility timing which do not lead to increased completed fertility.

So lifesaving interventions may decrease longterm population. Moreover, Eden and Kuruc (2024) suggest decreasing population decreases longterm income per capita, so lifesaving interventions may end decreasing the longterm size of the economy too. If so, the ripple effects would tend to be harmful.

1. ^{^}

   Because bednets also decrease nearterm mortality, which is why Against Malaria Foundation is one of GiveWell's top charities

Thanks, Joey!

I am far less convinced that life saving interventions are net population creating than I am that family planning decreases it. Written about 10 years ago, but still one of the better pieces on this IMO is David Roodman's report commissioned by GiveWell.

Fair! From Wilde et. al (2020), whose abstract is below (emphasis mine), bednets increase fertility 1 to 3 years after their distribution, but decrease it afterwards, so population initially increases (because bednets also decrease nearterm mortality), but may decrease soon after the distribution.

We examine the extent to which recent declines in child mortality and fertility in SubSaharan Africa can be attributed to insecticide-treated bed nets (ITNs). Exploiting the rapid increase in ITNs since the mid-2000s, we employ a difference-in-differences estimation strategy to identify the causal effect of ITNs on mortality and fertility. We show that the ITN distribution campaigns reduced all-cause child mortality, but surprisingly increased total fertility rates in the short run in spite of reduced desire for children and increased contraceptive use. We explain this paradox in two ways. First, we show evidence for an unexpected increase in fecundity and sexual activity due to the better health environment after the ITN distribution. Second, we show evidence that the effect on fertility is positive only temporarily – lasting only 1-3 years after the beginning of the ITN distribution programs – and then becomes negative. Taken together, these results suggest the ITN distribution campaigns may have caused fertility to increase unexpectedly and temporarily, or that these increases may just be a tempo effect – changes in fertility timing which do not lead to increased completed fertility.

I guess the above partly generalises to other interventions. If saving lives decreases population, it may well decrease welfare (if the increase in welfare per capita is not sufficiently large), thus being harmful under many moral views. Likewise for family planning interventions. CE's theories of change for the family planning interventions of the 3 reports I mentioned above have as outcome decreasing unwanted pregnancies. Are you assuming this is intrinsically valuable, or are you super confident that it leads to higher human welfare (because the increase in human welfare per capita exceeds the decrease in population)? I think the outcome should at least be increasing human welfare (and, ideally, increasing welfare accounting for both humans and animals).

I think for externalities you can get yourself pretty lost down a rabbit hole based on pretty speculative assumptions if you are not careful. We try to think of it a bit like the weight quantitative modeling described here and only include effects that we think are major (e.g. 10%+ effect after uncertainty adjustments on the total impact).

I agree, but I think it is at least worth mentioning the potential negative externalities on animals (without getting lost into rabbit holes). I also think it would be good to justify that the regression of the potential negative externalities is so large that they become negligible, especially if a direct interpretation leads one to conclude they overwhelm the direct effects (as in the report I discussed in the previous comment).

I'd still be worried about donations to these things generally growing the AW ecosystem as a side effect (e.g. due to fungibility of donations, training up people who then do work with more suffering-focused assumptions)

Without more information, I would guess that funding work on improving rather than decreasing animal lives will at the margin incentivises people to follow the funding, and therefore skill up to work on improving rather than decreasing animal lives.

I am sufficiently sceptical to put a low weight on the other 11 models (or at least withhold judgement until I've thought it through more). As I mentioned I'm writing a post I'm hoping to publish this week with at least one argument related to this.

I am looking forward to the post. Thanks for sharing the gist and some details. You may want to share a draft with people from Rethink Priorities.

To me neither of these lines of evidence ("brain structural similarity" and "behavioural similarity") seems obviously deserving of more weight.

I find it hard to come up with other proxies.

Right, I take this to be an implication of our best economic and demographic models (respectively).

Do you think we can trust the predictions of such models over more than a few decades? It looks like increasing population increases longterm income per capita, but not even this is clear (the conclusion relies on extrapolating historical trends, but it is unclear these will hold over long timeframes).

I don't know what you mean by "a decreasing effect size of fertility- and income-boosting interventions". Whether an intervention has a noticeable short-term effect on these targets? That would seem to address a different question.

Yes. I see it is a different question. No difference between the treatment and control group after a few decades could be explained by the benefits spilling over to people outside those groups. However, an increasing population or income gap between the treatment and control group would still be evidence for increasing effects, so a decreasing population or income gap is also evidence againt increasing effects.