Thanks for your comment! I broadly agree with the point you’re making, and have amended the summary to capture it. Let me know if you think the updated wording addresses your concern.
I did ponder trying to quantify the potential impacts of catalyzing industry-wide change as a result of this pilot, and I just want to lay out a little bit of why I think that’s so hard. It’s very tempting to compute a massive EV for this by doing a calculation like (small chance that this brings industry-wide adoption forward n years) * (400 billion shrimp farmed/year) = giant number. But I think that’s probably a bad way to look at it. I think the better way to think of it is that industry-wide adoption would take a successful pilot plus other forms of activism like corporate campaigns, ballot initiatives, or legislative lobbying. So the pilot alone isn’t necessarily bringing forward broader adoption, but rather creating new potentially cost-effective opportunities for donations. The exact EV would therefore depend on questions like the relative cost-effectiveness of those new donation opportunities compared to the existing animal welfare portfolio, and on how funding constrained the animal welfare space is expected to be over the next several years.
None of this is to say that I disagree with your point, just that I’m quite uncertain about the indirect cost effectiveness and would struggle to find a way to easily model it.
I think the edits you made to the summary work very well in making it clear what the quantitative analysis does and doesn’t cover! Thank you for taking on board my comments so promptly.
Fully agree with your points on the difficulty of quantifying the indirect benefits, and also how/where those benefits should be attributed.
I think the challenge is that excluding indirect benefits from a quantitative analysis effectively assigns them a zero value. That is ok when indirect benefits are most likely only a small fraction of the direct benefits. But it becomes problematic when the indirect benefits could plausibly be several times (or orders of magnitude) larger than the direct ones and relevant to decision-making.
If judgements about the size of the indirect benefits might be important, think it is valuable to make the exclusions clear—as you’ve now done!
Thanks again for the time you put into the piece, and the clear write-up / reasoning transparency!
Thanks for your comment! I broadly agree with the point you’re making, and have amended the summary to capture it. Let me know if you think the updated wording addresses your concern.
I did ponder trying to quantify the potential impacts of catalyzing industry-wide change as a result of this pilot, and I just want to lay out a little bit of why I think that’s so hard. It’s very tempting to compute a massive EV for this by doing a calculation like (small chance that this brings industry-wide adoption forward n years) * (400 billion shrimp farmed/year) = giant number. But I think that’s probably a bad way to look at it. I think the better way to think of it is that industry-wide adoption would take a successful pilot plus other forms of activism like corporate campaigns, ballot initiatives, or legislative lobbying. So the pilot alone isn’t necessarily bringing forward broader adoption, but rather creating new potentially cost-effective opportunities for donations. The exact EV would therefore depend on questions like the relative cost-effectiveness of those new donation opportunities compared to the existing animal welfare portfolio, and on how funding constrained the animal welfare space is expected to be over the next several years.
None of this is to say that I disagree with your point, just that I’m quite uncertain about the indirect cost effectiveness and would struggle to find a way to easily model it.
I think the edits you made to the summary work very well in making it clear what the quantitative analysis does and doesn’t cover! Thank you for taking on board my comments so promptly.
Fully agree with your points on the difficulty of quantifying the indirect benefits, and also how/where those benefits should be attributed.
I think the challenge is that excluding indirect benefits from a quantitative analysis effectively assigns them a zero value. That is ok when indirect benefits are most likely only a small fraction of the direct benefits. But it becomes problematic when the indirect benefits could plausibly be several times (or orders of magnitude) larger than the direct ones and relevant to decision-making.
If judgements about the size of the indirect benefits might be important, think it is valuable to make the exclusions clear—as you’ve now done!
Thanks again for the time you put into the piece, and the clear write-up / reasoning transparency!