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Furslid comments on How much does consumption affect production? - Less Wrong
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Comments (60)
In the specific example, they could be cloned by expanding in the good locations.
More generally, if you're claiming that there's a limited supply of good locations from which to produce chickens, then that reduces to a "finite inputs" argument I discuss in the last section of the OP. (For further discussion see responses to this comment .)
In short, I agree that such effects can create a sloping long term supply curve in some cases, but I also believe that there are other effects that can lead it to slope the opposite direction, and it's not immediately obvious which wins out. My prior is that the long term supply curve for an arbitrary product is virtually flat.
Said another way, if you're going to argue that the long term cost-per-widget is higher when producing 2X widgets than X widgets, then you have to argue that the effect of finite inputs outweighs gains to scale and other factors. I haven't seen such an argument generally or in the case of chickens.
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.
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".
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.
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.
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.
Let X and Y have a causal relationship of the following form: if X is set to a given value x, Y takes on a value kx + z, where z is the value of a random variable Z which is independent of X.
What is the expected change in Y caused by a change in X of size dx?
It is k dx.
It does not matter how much the change in X is "swamped" by the variability of Z. It does not matter if it is so large that the change in Y consequent on that change in X cannot possibly be observed. The expected change is still k dx.
Of course, but you are assuming a linear relationship (y =kx + z) and I am unwilling to assume one.
Everything is linear, to first order. We are, after all, considering small changes in X. dx will only have no effect if the gradient of the actual function expressing the causal effect on Y is zero. It still has nothing to do with the magnitude of all the other effects on Y independent of X.
You are talking math and I'm talking empirics. You don't know the true function (or even whether it exists), all you can do is make approximations and build models (which, to quote George Box, are always wrong but sometimes useful).
A couple of posts up you said " It does not matter if it is so large that the change in Y consequent on that change in X cannot possibly be observed" -- and that's where we disagree. It doesn't matter in math, it does matter in reality because you don't have access to the underlying function.
OK, so I argue option A, you state option B, and the articles I link argue option C.
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.
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.
Let's be clear about distinguishing between the map and the territory. To what do your priors apply?
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.
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.
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"):
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.
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.
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)
Long term supply curves are different than supply curves. They are similarly named, but different concepts.
Supply curves measure supply at a price.
Long term supply curves measure market equilibrium supply as demand changes over time.
The elasticity measurement is the derivative of supply with respect to price. It cannot be applied to long term supply curves.
I agree with your definitions of the two curves, although I don't know what point you're making by the distinction.
In either case we can ask, "how much will changes in demand affect equilibrium quantity?" In a constant-cost industry, the answer will be 1:1 in the long-run (as indicated by a flat, or infinitely elastic long-run supply curve), but as you gradually shorten the scope over which you're looking at the market, making it a shorter- and shorter-run supply curve, it will steepen (elasticity decrease) such that the answer is "less than 1:1".