Super thank you - I especially liked the last line about saving the world...

If farmed chickens plausibly have overall net positive lives (per the discussion above), and if you're something like a total utilitarian, then you should want more of them to exist; hence eat more in order to at least weakly increase demand / production.

Alternately, if you think it's very difficult to know for sure whether chickens have net positive lives or not, and you enjoy the taste of chicken, then that's another case for eating more of them.

I attended an interesting (not just researchers!) Wellbeing Forum in London on Monday. Focus topics highlighted two unusual (for this topic) themes that might both be of interest to people here: 'Human wellbeing in the age of AI' and 'religion and spirituality' (using recent large global polling data from Gallup). Feel free to DM me if you want more info or have any questions.

Hi - thanks again for taking more time with this, but I don't think you do understand my model. It has nothing to do with capital assets, hiring/firing workers, or switching suppliers. All that it requires is that some decisions are made in bulk, i.e. at a level of granularity larger than the impact of any one individual consumer. I agree this is less likely for retail stores (possibly some of them order in units of 1? wouldn't it be nice if someone actually cared enough to look into this rather than us all arguing hypothetically...), but it will clearly happen somewhere back up the supply chain, which is all that my model requires.

Your mistake is when you write "Say they need to order in multiples of 10, and they order the minimum multiple of 10 that's at least 7 over what they predict." That's not what my model predicts (I think it's closer to M&H's first interpretation of buffers?), nor does it make economic sense, and it builds in linearity. What a profit-maximizing store will do is to balance the marginal benefit and marginal cost. Thus if they would ideally order 7 extra, but they have to order in multiples of 10 and x=4 mod10, they'll order x+6 not x+16 (small chance of one extra stock-out vs large chance of 10 wasted items). They may not always pick the multiple-of-10 closest to 7 extra, but they will balance the expected gains and losses rather than using a minimum. From there everything that I'm suggesting (namely the exponential decline in probability, which is the key point where this differs from all the others) follows.

And a quick reminder: I'm not claiming that my model is the right one or the best one, however it is literally the first one that I thought of and yet no one else in this literature seems to have considered it. Hence my conclusion that they're making far stronger claims than are possibly warranted.

I still haven't read Budolfson, so I'm not claiming that M&H misinterpret him. As I said, I did read their entire paper, and in the section specifically about him they describe two interpretations of "buffer", neither of which matches my model. So if his model is similar to mine, they got it wrong. If his model is different than mine, then they don't seem to have ever considered a model like mine. Either way a bad sign.

Everything you write about how you think they might respond to me (i.e. your three bullet points and the subsequent paragraph) is 100% consistent with my model and doesn't change any of its implications. In my model stores use predicted demand and can update it as often as they want. The point is that purchasing is in bulk (at least at some level in the supply chain); therefore there is a threshold; and the optimal threshold (every single time) will be chosen to be away from the mean prediction. This can still be extremely sensitive, and may well be. [Apologies if my brief descriptions were unclear, but please do take another look at it before responding if you don't see why all this is the case.]

To the final point, yes of course if someone decides to stop purchasing then the store [probabilistically] starts ordering fewer chickens [than otherwise]; I didn't disagree with that sentence of theirs, and it is also 100% consistent with my model. The question is the magnitude of that change and whether it is linear or not, crucial points to which they have nothing to contribute.

Yes all fair, and I'd say it goes beyond counterfactuals. I'm not sure people fully realize how sensitive many conclusions are to all sorts of assumptions, which are often implicit in standard models. I am on record disagreeing strongly with John Halstead about the likely cost-effectiveness of advocating for economic growth, and I feel similarly about much of the longtermist agenda, so this isn't specific to animals. My personal sense is that if you can save an existing human life for a few thousand dollars (for which the evidence is very clear, although point taken that the marginal impact isn't definitively pinned down - however I'd guess within a factor of two,), that's an extremely high bar to overcome.

Interesting - thanks for the extra info re Budolfson. I did in fact read all of M&H, and they give two interpretations of the buffer model, neither of which is related to my model, so that's what I was referring to. [That's also what I was referring to in my final paragraph: none of the sources you cited on that side of the causal efficacy argument seems to have considered anything like my model, which remains true given my current knowledge.]  In fact if Budolfson was saying something more like my model, which does seem to be the case, then that's an even worse sign for M&H because they must not have understood it.

The paragraph you quote from Budolfson is indeed more similar to my model, except that in my case the result follows from profit-maximizing behavior (in a competitive industry if you like!) rather than ad hoc and unusual assumptions. 

Suppose that I consider a threshold (for increasing or decreasing production next cycle) right at the mean of expected sales (15,000 in the example): half the time I'll stockout and have disappointed customers; half the time I'll have extra stock and have to sell it on a secondary market, or give it away, or waste it. Which is worse for business? Plausibly stocking out is worse. So my threshold will be higher than the mean, reducing the probability of stocking out and increasing the prob of excess. The optimal level will be set just so that at the margin, the badness of stocking out (larger) multiplied by the prob of stocking out (smaller) will exactly offset the badness of excess times the prob of excess. Because it is above the mean, which is in fact the true best-guess state of the world (ignoring any individual consumer), and because the distribution around the mean will plausibly be Gaussian (normal), which declines exponentially from the mean - not linearly! - every individual consumer should rationally believe that their decision is less than 1/n likely to be taking place at the threshold. QED.

I wasn't gesturing toward the relative competitiveness because it's important per se (you're right that it isn't) but rather as a way to gauge absolute competitiveness for those who don't already know that a net profit margin of 5.7% isn't bad at all. My intuition is that people realize that both defense and healthcare firms make decent profits (as they do) and hence that this fact would help convey that farmers (whether large or small; and if your point is that they can differentiate themselves and do some monopolistic competition then you're already on my side vs M&H) are not typically right on the edge of survival.

However I don't personally think the level of competition is crucial to anything here. M&H believe that it's necessary for their argument (in the abstract they say their case rests on it), so I was pointing out that (a) it's actually not that competitive; and (b) if they do think it's truly competitive (i.e. not differentiated) then that is indeed inconsistent with their own claim on p.23, which is a bad sign for their analysis.

My main point (which you don't seem to have responded to) remains that these are all conceptual arguments making various particular assumptions rather than actually trying to estimate an individual-level impact with a combination of a concrete well-defined model and empirics.

I had seen some of this, but not the specific paper (ungated) by McMullen & Halteman - thanks!

First of all note that the two sources you cite directly contradict one another: the first-hand anecdotal account says there is essentially no meat waste even in very small groceries, while M&H (p.12) say there is a modest constant unavoidable waste that is in fact higher in smaller / local stores than for big outfits. Indeed M&H are internally inconsistent: they say that the market is highly competitive (although they only give a very incomplete reference for this on p.14, which I couldn't find any trace of; my googling found this source suggesting a net profit margin for farming/agriculture of 5.7%, which is middling - better than aerospace/defense or healthcare), but then they also state (p.23) that larger firms have up to 60% lower costs than smaller ones -- so how do the latter survive if the industry is so competitive? All of these are bad signs right off the bat.

Second note that none of these sources actually do any data analysis or try to examine original data about the markets or supply chains; they are armchair papers. My whole point is that depending on which of several reasonable assumptions one makes, different conclusions will be drawn. The only way to adjudicate this is to actually figure out what's going on in the real world, and neither of these sources attempts to do that. Hint: neither of them gives an empirically-derived concrete estimate for individual-level elasticity.

Third (to finally answer your question!), no my hypothetical model is not the same as the way they are using the term "buffer" (which seems to be more about maintaining a minimum level of excess in the system; mine is simply about the optimal tradeoff between stockouts vs excess/waste). For instance M&H say (p.25) "if there is some probability (1/n) that any given purchase will occur on a threshold, then the threshold action will trigger a reduction in production of around n units, yielding an expected impact equal to 1" (and from the reducing suffering page: "The probability that any given chicken is the chicken that causes two cases instead of three to be purchased is 1/25"). Well yes - if it's linear then the expected effect is the same order of magnitude as the input. My model was precisely one where the probability is plausibly not linear: in any given cycle, total sales are much more likely to be near the mean than near the threshold, so every individual would correctly believe that their own actions are very unlikely to change anything, which is not inconsistent with the (obviously correct) claim that large changes in demand are roughly linear and do influence things according to whatever macro-level elasticity has been estimated for chickens.

Or my 30-second model might be wrong - I'm not claiming it's correct. I'm claiming that we don't know, and the fact that none of these sources seems to have even considered it (or any other ones), and don't even realize the nature of the assumptions they're making, and nevertheless draw such strong conclusions, is again a bad sign.

I'm a professor of economics, but thanks for the link explaining elasticity :) 

The answer is no, we can't just do that, since those approaches assume nontrivial changes (and/or they assume everything is continuous, which the real world isn't). One plausible simple model of supermarket (or restaurant) purchasing behavior is that when observed demand goes above/below a certain threshold relative to predicted demand, they buy more/less of the input next cycle. From an individual point of view, the expected aggregate demand of other agents in any time period will be a Gaussian distribution (by the law of large numbers), and the threshold will be away from the mean (doesn't make sense to update every time), which implies that one's probability of being the marginal buyer at the threshold declines exponentially (not linearly, as it would be for macro-level shifts and as you are implicitly assuming). From the ACE link: "we can approximate the supply and demand curves in this region by straight lines" - no, you can't do that (for individual behavior) without substantive additional assumptions or a lot of legwork into how these decisions actually get made.

In any case I have no idea if that's the right model, because I haven't studied supermarket supply chain management. As far as I can tell (but I'd love to see this somewhere), nobody in either the econ lit or animal welfare lit has tried to do this at the level required to make what I would consider an informed estimate; we're not just talking about a factor of 2 or 3 here. That knowledge gap doesn't seem to stop the latter group from making very strong claims; they mostly don't even seem to understand or acknowledge the high uncertainty and strong assumptions.