Corporate campaigns affect 9 to 120 years of chicken life per dollar spent

First of all, great model and write-up.

One of my the biggest take aways from looking at your model was the importance of the *Mean Years of Impact *parameter. Looking at guesstimate's sensitivity analysis the r^2 value is about 0.75 [1], meaning approximately ~75% of the variance in the bottom line result is due to the variance estimating* Mean Years of Impact.*

Your choice of SCI is also significantly more optimistic than the figures that ACE or Lewis Bollard use. ACE seems to use a log-normal distribution with SCI 1.6 to 13 [2]. Using this in your mod... (read more)

72yTL;DR: Nobody seems to know what the value of mean years of impact should be,
and I don't see how this uncertainty could be reduced. I think that indirect
effects are more important and it would be better to research them.
Good points and I'm happy you brought it up.
Firstly, I know you know this, but Lewis wrote that in his view, "the assumption
that these campaigns only accelerated pledges by five years is very
conservative." It makes sense to use a conservative value when doing a point
estimate like he did. And I did use a similar value (4 years) in my conservative
estimate in Appendix 1. ACE did not really describe their choice for the value
so I didn't pay much attention to it. There's also Capriati (2018)
[https://founderspledge.com/research/Cause%20Area%20Report%20-%20Animal%20Welfare.pdf]
which assumed that THL's cage-free and broiler campaigns moved policies forward
by only one year (I just added the description. But this assumes that other
organizations would have still done everything they did. And even then, I don't
think it is reasonable.
To be honest, I think that nobody has a clue about what value to use here.
Hence, everybody uses random conservative values in order for the end result to
be more believable, because the estimated cost-effectiveness of campaigns is
unbelievably high even with a conservative values. I did that to a degree as
well. I asked some people who work on corporate campaigns what value would they
use for mean years of impact. They thought that my range was reasonable, but I
think they would have said that about many different ranges because it's
difficult to think about. Only one person was able to say what range for mean
years of impact would they use without looking at my range, and they said 40 to
100 years. If I weren't anchored by other estimates and didn't want to be a bit
conservative to be more convincing to skeptics, I think I would have chosen a
higher value as well, especially for the upper bound. In general, my im

In a literal information-theoretic sense, a percentage has log2(100)≈6.6 bits of information while a per-tenth has log2(10)≈3.3 bits. This might have been what was meant?

I agree that the half of the information that is preserved is the much more valuable half, however.