I think I’m less concerned about an error in one of the parameters than you seem to be because of the different goals of the research.
Just to be clear, I wasn’t concerned about the error, I saw that deleting the cell and then making other appropriate changes increases the estimated probability by only 3%. I only commented about it because I thought that it is easy to fix. I agree that the approach you chose has its benefits.
Of course, I feel fully confident that the true outcome will be somewhere between 0% and 100%, but this result is not that informative when we need to make a call.
If your 90% CI is between 0% and 100%, it can be a little bit informative to put that in the model (preferably with a custom probability distribution), because it would help to distinguish between interventions that help 0-2 animals per dollar spent, and interventions that help 1 animal per dollar spent. You should of course prefer the latter to avoid the optimizer’s curse. If you end up not having actual 90% subjective confidence intervals because you want to make things simpler, I guess you should keep that in mind when filling the column for the strength of evidence in your Priority Asks table.
There is one part of the model that I disagree with:
When looking closely at the US cage-free campaigns, only one (Whole Foods) out ofthe 20 companies affecting the highest number of hens has switched to cage-free(though most deadlines are for planned for 2025). Those companies account for66% of hens that, in theory, would be affected by the campaign. Which means thatcompanies that met their deadline (average of 54% rate globally, across differentissues), had a smaller impact that the 20 that didn’t follow through. 5% of pledges isgoing to affect 66% of hens. That might suggest that enforcement will become moredifficult as reforms become more significant for the animals and more costly to theindustry.
You then use this in the model as a piece of evidence about the expected follow-through rate of all corporate commitments: All other top 20 companies (with a possible exception of Costco which seems to be close to being cage-free anyway) have their deadlines set in the future, as you say, mostly 2025. You can’t say that they did not follow-through, we just have to wait until 2025 and see if they will, nobody expected them to be 100% cage-free this early. If I were you, I would remove this cell from the model.
This is very interesting and useful, thank you!
I’m a little puzzled about how to interpret the results though, and it’s related with a maths problem that I’ve been confused about for a while. However, I have to warn that this is confusing and it might be counterproductive to think about it because of that.
Do you mean that if you start a new campaign for a new ask, then you expect 39% − 50% of companies that make commitments to follow through? If that is the case, the confidence interval seems to be very narrow. My 90% Subjective Confidence Interval (SCI) for that would be 0% − 100%. For example, there can be commitments like stopping chick culling which depend on the creation of new technologies. Scientists might fail to create such technologies in which case it’s 0%. Or they might make them very cheap and then everyone fulfils their commitments (100%).
Another way to interpret the result is that it is your subjective probability that a given company will follow through. But then I’m not sure it makes sense to have a 90% SCI of what your own subjective probability is. What would that even mean? How would you check that the true value is in the confidence interval?
But even if in your cost-effectiveness estimate you would use a point estimate (44%) instead of a SCI (39% − 50%) for the probability, I wouldn’t be sure about how to interpret the results. The result would still be a SCI because you will probably use SCIs in other parts of your calculations. But then that wouldn’t be a 90% SCI of the number of animal affected. It would be a 90% SCI of the expected value of the number of animals affected. But then again, I don’t know how to interpret a 90% SCI of an expected value.
I think that one way to model cost-effectiveness in a way that makes mathematical sense is to have a probability distribution of the percentage of companies that will follow through. The distribution would have some weight on 0%, some weight on 100% and some weight in between. Another way would be to use point estimates everywhere and say that it is an expected value. Of course, no one will die if you mix these two things, but the result might be difficult to interpret.
If anyone thinks that my reasoning here is wrong, I’d be very curious to hear because I encounter this problem quite often nowadays. And currently I am making a cost-effectiveness model of corporate campaigns myself, and I don’t quite know what to do with the uncertainty about following through...
More space per chicken is just one of the requirements. Probably the most important requirement is to use higher welfare breeds, which generally grow more slowly. But there are more requirements regarding lighting, enrichments, etc. You can see the full ask in the European Chicken Commitment. Asks for other regions are similar and can be seen here.
This will save me so much time, thank you!
When I say this, I mean the footnote thing. You are seeing an example of it right now. The bios thing is cool too though :) ↩︎
When I say this, I mean the footnote thing. The bios thing is cool too though :) ↩︎
This sentence has an inline footnote, which is probably the easiest kind to use while writing. 
Here’s the note, which will appear at the bottom of the post once it’s published. ↩︎
I’m confused about what is happening here. I remember reading this article a year ago, and most of the comments are almost exactly one year old. But for some reason the date of the post is “8th May 2019” and the post is in the first page of the forum where it says that it was posted 8 days ago. I guess there is some kind of a bug in the forum that caused the date of the post to be wrong.
I don’t quite understand this comment. I don’t think there was any discussion here about vegetarianism vs. clean meat R&D. Maybe you should clarify if it’s important :)
According to the article The Impact of Food Prices on Consumption: A Systematic Review of Research on the Price Elasticity of Demand for Food, the elasticity for poultry in the U.S. is 0.68 (95% confidence interval is 0.44-0.92). This value is based on 23 estimates. Table 1 in the article contains elasticities of other animal products as well. But on a closer look this seems to not be the thing that you are looking for: “we sought to estimate the effects of price changes on consumer demand”.
In general, I would say that your friend is right that consuming less chicken might lead to less of a difference in supply than one would naively think, but it still leads to a difference. At least that’s my understanding. But I have a very shallow understanding of this topic.
I guess another thing to watch out for is whether the prize consistently creates controversies like the one in the thread above. If it does, then maybe the prize is more distracting than useful.
I didn’t think that far, I just expressed a concerned. But no one said it requires a significant time investment and Peter said the opposite, so maybe there is no problem :)
I wanted to write something similar. I saved up the money that I donated by buying cheaper food and living in cheaper places. It all felt a bit pointless when I saw that the orgs that I donated to spend some of that money on fancy offices in expensive areas. But if I remember correctly, it wasn’t a big deal as I continued donating to them. I thought that from an utilitarian POV it could be the right decision on their part.
I also want to say that I’m not sure that I now enjoy my job as a researcher at an EA org more than I enjoyed earning to give as a programmer. I thought that doing something directly meaningful would be much more enjoyable and make me more motivated day-to-day, but it’s not happening. I think that what matters more (at least for me) is the nature of the task and whether it’s easy to get into a flow.
As for social status, I always felt that even in EA circles (e.g. at EA Globals) it mostly depends on how charismatic/socially smooth you are and that what you do for a living has little impact on it. Maybe it’s different in places other than the UK, I don’t know. I guess I’m saying all these things because I want to show earning-to-givers that the other side might not be as glamorous as it can seem.
I’m interested in what you think about using subjective confidence intervals to estimate effectiveness of charities and then comparing them. To account for the optimizer’s curse, we can penalize charities that have wider confidence intervals. Not sure how it would be done in practice, but there probably is a mathematical method to calculate how much they should be penalized. Confidence intervals communicate both, value and uncertainty at the same time and therefore avoid some of the problems that you talk about.
Voters are important people whose time is valuable, and I’m a bit concerned about the time they spend to decide whom to vote for. For example, I don’t want them to read the very long post I’ve written just to decide whether to vote for it (provided it’s not relevant/interesting for them otherwise). I expect them to have more important things to do with their time. I understand that they are not obliged to read it. But being a voter probably puts some pressure on them to read the forum more than they would otherwise, and that might come at the expense of other work. Also, making voting decisions of this kind can be mentally tiring. And if voters don’t put much energy into it because they are busy with more important stuff, then wrong posts get selected.
In some cases, fish are released when they are small in size, and then recaptured when they are bigger (this is called sea ranching). This can be economically viable because it’s expensive to grow big fish in farms and their mortality rate in the wild is low compared to juveniles. In other cases, they try to augment or (re)create self-sustaining populations which increases the catch in the long term.
These fish are not slaughtered, they are released into natural waters. But I wouldn’t jump to conclusions that quickly :)
Icefish might weigh less than 10 grams, they really look tiny. Also, I see some wild-caught icefish in a fishcount table but it’s ten times less in weight than farmed icefish. It could be that these stats don’t include all the icefish though.
Fishcount also estimated that each year 0.45-1 trillion wild-caught fish are used to make fishmeal and fish oil, and that between 140 and 490 billion wild-caught fish are fed directly to farmed fish. But all of these fish seem to be wild-caught. This article also seems to assume that (although I only skimmed it). I haven’t seen evidence that fish are farmed to feed other farmed fish, I’m not sure if that could be economically viable.
I don’t quite understand this estimation. It seems you are comparing Albert Schweitzer Foundation’s work with an intervention that improves welfare for farmed food fish (rather than stocked fish)? It seems that the graph includes wild-caught fish. According to a fishcount estimate, in 2015 Germany slaughtered 8-66 million farmed fish. In general, my intuition is that those variables would not be similar to the ones in chicken campaigns.