This applies only if you are confident that your action is just one out of a large number of similar actions.
In any case, yes, I think we understand each other's positions and just disagree.
I believe that a small piece of rationalist community doctrine is incorrect, and I'd like your help correcting it (or me). Arguing the point by intuition has largely failed, so here I make the case by leaning heavily on the authority of conventional economic wisdom.
How does an industry's total output respond to decreases in a consumer's purchases; does it shrink by a similar amount, a lesser amount, or not at all?
The consensus answer in the few cases I've seen cited in the broader LW community appears to be that production is reduced by an amount that's smaller than the original decrease in consumption.
Animal Charity Evaluators (ACE):
Fewer people in the market for meat leads to a drop in prices, which causes some other people to buy more meat. The drop in prices does also reduce the amount of meat produced and ultimately consumed, but not by as much as was consumed by people who have left the market.
As is commonly known by economists, when you choose to not buy a product, you lower the demand ever so slightly, which lowers the price ever so slightly, which turns out to re-increase the demand ever so slightly. Therefore, forgoing one pound of meat means that less than one pound of meat actually gets prevented from being factory farmed.
The key points to note are that a permanent decision to reduce meat consumption (1) does ultimately reduce the number of animals on the farm and the amount of meat produced (2), but it has less than a 1-to-1 effect on the amount of meat produced.
These answers are all correct in the short-run (ie, when the “supply curve” doesn’t have time to shift). If there is less demand for a product, the price will fall, and some other consumers will consume more because of the better deal. One intuitive justification for this is that when producers don’t have time to fully react to a change in demand, the total amount of production and consumption is somewhat ‘anchored’ to prior expectations of demand, so any change in demand will have less than a 1:1 effect on production.
For example, a chicken producer who begins to have negative profits due to the drop in price isn't going to immediately yank their chickens from the shelves; they will sell what they've already produced, and maybe even finish raising the chickens they've already invested in (if the remaining marginal cost is less than the expected sale price), even if they plan to shut down soon.
In the long-run, however, the chicken producer has time to shrink or shut down the money-losing operation, which reduces the number of chickens on the market (shifts the "supply curve" to the left). The price rises again and the consumers that were only eating chicken because of the sale prices return to other food sources.
As a couple of online economics resources put it:
The long-run market equilibrium is conformed of successive short-run equilibrium points. The supply curve in the long run will be totally elastic as a result of the flexibility derived from the factors of production and the free entry and exit of firms.
AmosWEB*:
The increase in demand causes the equilibrium price of zucchinis [to] increase... and the equilibrium quantity [to] rise... The higher price and larger quantity is achieved as each existing firm in the industry responds to the demand shock.
However, the higher price leads to above-normal economic profit for existing firms. And with freedom of entry and exit, economic profit attracts kumquat, cucumber, and carrot producers into this zucchini industry. An increase in the number of firms in the zucchini industry then causes the market supply curve to shift. How far this curve shifts and where it intersects the new demand curve... determines if the zucchini market is an increasing-cost, decreasing-cost, [or] constant-cost industry.
Constant-Cost Industry: An industry with a horizontal long-run industry supply curve that results because expansion of the industry causes no change in production cost or resource prices. A constant-cost industry occurs because the entry of new firms, prompted by an increase in demand, does not affect the long-run average cost curve of individual firms, which means the minimum efficient scale of production does not change.
[I left out the similar explanations of the increasing- and decreasing-cost cases from the quote above.]
In other words, while certain market characteristics (increasing-cost industries) would lead us to expect that production will fall by less than consumption in the long-run, it could also fall by an equal amount, or even more.
Economists define the long-run as a scope of time in which producers and consumers have time to react to market dynamics. As such, a change in the market (e.g. reduction in demand) can have one effect in the short-run (reduced price), and a different effect in the long-run (reduced, constant, or increased price). In the real world, there will be many changes to the market in the short-run before the long-run has a chance to react to to any one of them; but we should still expect it to react to the net effect of all of them eventually.
Why do economists even bother measuring short-run dynamics (such as short-run elasticity estimates) on industries if they know that a longer view will render them obsolete? Probably because the demand for such research comes from producers who have to react to the short-run. Producers can't just wait for the long-run to come true; they actively realize it by reacting to short-run changes (otherwise the market would be 'stuck' in the short-run equilibrium).
So if we care about long-run effects, but we don't have any data to know whether the industries and increasing-cost, constant-cost, or decreasing-cost, what prior should we use for our estimates? Basic intuition suggests we should assume an industry is constant-cost in the absence of industry-specific evidence. The rationalist-cited pieces I quoted above are welcome to make an argument that animal industries in particular are increasing-cost, but they haven't done that yet, or even acknowledged that the opposite is also possible.
Have we really been messing up our cost-effectiveness estimates simply by confusing the short-run and long-run in economics data? If so, why haven't we noticed it before?
I'm not sure. But I wouldn't be surprised if one issue is, in the process of trying to create precise cost-effectiveness-style estimates it's tempting to use data simply because it's there.
How can we identify and prevent this bias in other estimates? Perhaps we should treat quantitative estimates as chains that are no stronger than their weakest link. If you're tempted to build a chain with a particularly weak link, consider if there's a way to build a similar chain without it (possibly gaining robustness at the cost of artificial precision or completeness) or whether chain-logic is even appropriate for the purpose.
For example, perhaps it should have raised flags that ACE's estimates for the above effect on broiler chicken production (which they call "cumulative elasticity factor" or CEF) ranged by more than a factor of 10x, adding almost as much uncertainty to the final calculation for broiler chickens as the 5 other factors combined. (To be fair, the CEF estimates of the other animal products were not as lopsided.)
This applies only if you are confident that your action is just one out of a large number of similar actions.
In any case, yes, I think we understand each other's positions and just disagree.
My "not buying a chicken" seems like it would look very similar to anyone else's "not buying a chicken".
I'm sorry, that is correct. You were describing a supply curve that doesn't behave normally. So I can't say anything about demand curves. I apologize for the cheap shot.
In the standard economic models, supply and demand curves have elasticity that is a positive, finite number. Infinitely elastic curves are not possible within the standard models.
The priors I start with, for any market, are that it behaves in a manner consistent with these economic models. The burden of proof is on any claim that some market is behaving in a different manner.
Thanks for acknowledging that.
I think standard economics agrees with your vision of "~always positively-sloping finite supply curves" in the short term, but not necessarily the long term. Here's a quote from AmosWEB (OK, never heard of them before, but they had the quote I wanted)
As a perfectly competitive industry reacts to changes in demand, it traces out positive, negative, or horizontal long-run supply curve due to increasing, decreasing, or constant cost.
Cumulative elasticity = Supply Elasticity/(Supply Elasticity - Demand Elasticity). A cumulative elasticity factor of one means a demand elasticity of 0.
I believe your math skipped a step; it seems like you're assuming that Supply Elasticity is 1. I actually claim in the original article that "the 'price elasticity of supply' in the arbitrarily long term becomes arbitrarily high". In other words, as "length of 'term'" goes to infinity, the Supply Elasticity also goes to infinity and the cumulative elasticity factor approaches 1 for any finite Demand Elasticity.
Thanks for the math demonstrating my point.
Stepping back, I worry from your sarcastic tone and the reactive nature of your suggestions that you assume that I am trying to 'beat you' in a debate, and that by sharing information that helps your argument more than it helps mine, I have made a mistake worthy of mockery.
Instead, I am trying to share an insight that I believe is being overlooked by the 'conventional wisdom' of this community and is affecting multiple public recommendations for rational behavior (of cost/benefit magnitude ~2x).
If I am wrong, I would like to be shown to be so, and if you are wrong, I hope you also want to be corrected. If instead you're just debating for the sake of victory, then I don't expect you to ever be convinced, and I don't want to waste my effort.
Oops, I meant to edit that rather than retract. Since I don't believe there's a way to un-retract I'll re-paste it here with my correction (Changing "Supply Elasticity is 1" to "Supply Elasticity is finite"):
Cumulative elasticity = Supply Elasticity/(Supply Elasticity - Demand Elasticity). A cumulative elasticity factor of one means a demand elasticity of 0.
I believe your math skipped a step; it seems like you're assuming that Supply Elasticity is finite. I actually claim in the original article that "the 'price elasticity of supply' in the arbitrarily long term becomes arbitrarily high". In other words, as "length of 'term'" goes to infinity, the Supply Elasticity also goes to infinity and the cumulative elasticity factor approaches 1 for any finite Demand Elasticity.
Thanks for the math demonstrating my point.
Stepping back, I worry from your sarcastic tone and the reactive nature of your suggestions that you assume that I am trying to 'beat you' in a debate, and that by sharing information that helps your argument more than it helps mine, I have made a mistake worthy of mockery.
Instead, I am trying to share an insight that I believe is being overlooked by the 'conventional wisdom' of this community and is affecting multiple public recommendations for rational behavior (of cost/benefit magnitude ~2x).
If I am wrong, I would like to be shown to be so, and if you are wrong, I hope you also want to be corrected. If instead you're just debating for the sake of victory, then I don't expect you to ever be convinced, and I don't want to waste my effort.
Cumulative elasticity = Supply Elasticity/(Supply Elasticity - Demand Elasticity).
A cumulative elasticity factor of one means a demand elasticity of 0.
A completely inelastic demand curve is not to be expected in standard economics, and as such it is an inappropriate prior. Thanks for the math demonstrating my point.
Cumulative elasticity = Supply Elasticity/(Supply Elasticity - Demand Elasticity). A cumulative elasticity factor of one means a demand elasticity of 0.
I believe your math skipped a step; it seems like you're assuming that Supply Elasticity is 1. I actually claim in the original article that "the 'price elasticity of supply' in the arbitrarily long term becomes arbitrarily high". In other words, as "length of 'term'" goes to infinity, the Supply Elasticity also goes to infinity and the cumulative elasticity factor approaches 1 for any finite Demand Elasticity.
Thanks for the math demonstrating my point.
Stepping back, I worry from your sarcastic tone and the reactive nature of your suggestions that you assume that I am trying to 'beat you' in a debate, and that by sharing information that helps your argument more than it helps mine, I have made a mistake worthy of mockery.
Instead, I am trying to share an insight that I believe is being overlooked by the 'conventional wisdom' of this community and is affecting multiple public recommendations for rational behavior (of cost/benefit magnitude ~2x).
If I am wrong, I would like to be shown to be so, and if you are wrong, I hope you also want to be corrected. If instead you're just debating for the sake of victory, then I don't expect you to ever be convinced, and I don't want to waste my effort.
That question seems to have a simple answer: your decision will not affect the long-term production of chicken.
Now I suspect that the real question is "If X million people decide to stop eating chicken, what would happen to the long-term production?" That is a much more complicated question which I don't think can be answered by moving or bending the supply and demand curves under the ceteris paribus assumption. One reason is that it's scale-dependent: different magnitude of X gives different answers. If X is small, its effect would be swamped by other factors (e.g. the growing prosperity in the developing world which generally leads to more people eating meat) and at the other end, obviously, if everyone stops eating chicken the production would drop to zero and chicken will become extinct.
That question seems to have a simple answer: your decision will not affect the long-term production of chicken.
OK, so I argue option A, you state option B, and the articles I link argue option C.
That is a much more complicated question
I agree it's a complicated question (in that it requires lots of information to answer precisely and accurately). If you had no empirical data to work with, what would be your best guess/expectation? Also if your answer is proportionally different than in the 'single chicken' case, I'd be curious to know why.
the better question is whether it's a good simplification
That is an excellent question, but it requires an additional piece: good for what purpose?
Right. In this case, to answer the question, "If I decide to reduce my lifetime consumption of chicken by one, should I expect the long term production of chicken to drop by ~1, ~0, or something in between?" Which is of demonstrated interest to the authors I am critiquing.
What you are effectively claiming is that there are no suboptimal producers of chickens. Unless every producer of chickens is ideally located, ideally managed, ideally staffed, and working with ideal capital there are differences in production costs.
There is a reason, that economics assumes that the amount of a good supplied changes as price changes, and I haven't seen any argument that exempts the case of chickens.
Also, how does the market create less chickens as demand falls? If there are differences in cost, the highest cost producers leave the market as price falls. Easy to answer with the standard assumptions, but almost impossible with your nonstandard prior.
What you are effectively claiming is that there are no suboptimal producers of chickens. Unless every producer of chickens is ideally located, ideally managed, ideally staffed, and working with ideal capital there are differences in production costs.
It's not that this will ever actually be the case, but the argument is that, in the long term, the market approaches what you would expect with such assumptions (and continues to have short term fluctuations away from that). But yes, even this assumption is clearly not actually true in all cases (as with all assumptions in neoclassical economics); the better question is whether it's a good simplification (enough to form a reasonable prior) or whether there is a better simplification we can consider (either simpler or more accurate).
The estimates I'm critiquing in the original post assume "short term elasticities are the best prior for long term elasticities" and I am advocating that "a better prior for the long term cumulative elasticity factor is 1".
There is a reason, that economics assumes that the amount of a good supplied changes as price changes, and I haven't seen any argument that exempts the case of chickens. Also, how does the market create less chickens as demand falls? If there are differences in cost, the highest cost producers leave the market as price falls. Easy to answer with the standard assumptions, but almost impossible with your nonstandard prior.
The explanation of both of these issues is the short term supply curve (which is not flat). In the short term, if people stop eating chicken, the price drops, and the producers that are (in the short term) able to improve their (expected long term) profits by scaling or shutting down do so.
I haven't looked at the empirical evidence because I didn't think it would be as convincing as the 2 theoretical arguments
Heh. It seems we have pronounced... methodological differences :-D
Empirical evidence is nice and often more convincing than theory, but I don't think it's necessary for an argument to be convincing (to believe otherwise would be quite... burdensome).
In this case, the original articles I am critiquing used purely theoretical arguments to claim that there will be long term price elasticity of supply, and I think that a theoretical critique is sufficient to show that the strength of their arguments is currently too weak to support the complexity of their theory.
I'm certainly open to any empirical evidence that may exist. Would you find a quick analysis of Big Macs moving (or if not, do you have a suggestion for a different empirical analysis)?
If I had no empirical data, I would not be making any guesses in this case.
The "single chicken" case is below the noise floor. Empirically speaking, the consequences are undetectable. And for "many chicken", how many matters -- I don't think there is a straightforward linear case here.
OK so you have no prior for large cases, you have no prior about the relationship between large cases and small cases, and your guess for small cases is "zero impact".
My prior for large cases is 1:1 impact, my prior is that the impact in large cases is proportionally similar to the impact in small cases, and therefore my prior for small cases is 1:1 impact.