Farmed fish slaughter commitments do not look cost-effective using an estimation method that prioritizes duration and does not assign a high moral value to averting intense suffering.
I do think your methodology greatly underestimates the value of averting extreme suffering. You say:
To calculate the direct $/âDALY range, I assumed that the stunning intervention leads to a welfare improvement between 10% and 50% of the entire fish welfare range (both positive and negative), that lasts for 50% to 90% of the duration of slaughter without stunning.
[...]
To convert this into DALYs averted, I assumed that an intervention that lasts for a year and generates an average welfare improvement of 50% of the entire human welfare range is equivalent to averting a DALY.
The assumptions in the 1st of the above paragraphs make sense to me if I interpret the welfare range as i) the difference between the welfare per unit time of the best and worst possible experience of 1 second, rather than ii) the difference between the welfare per unit time of the best and worst possible experience of 1 year (this can also be thought of as the difference between the welfare per unit time of the best and worst typical experience). However, for the 2nd paragraph to make sense, one has to interpret the welfare range as ii). So I think there is a contradiction:
Interpreting the welfare range as i), I would value 1 DALY as much less than a 50 % improvement in the welfare range, because being in extreme suffering is way worse than being in full health.
Interpreting the welfare range as ii), the improvement due to the stunning intervention would be way larger, because avoiding extreme suffering is way more important than extending full health.
I agree with this comment. Itâs worth nothing that the methodology used in this analysis isnât the same as the methodology used in the CURVE sequence. In the âHow Can Risk Aversion Affect Your Cause Prioritizationâ report, @Laura Duffy weighted 1 year of disabling pain at 2 to 10 DALYs and 1 year of excruciating pain at 60 to 150 DALYs. I expect that dying is at least disablingly painful and potentially excruciatingly painful, so these weights would imply a >5x improvement in cost-effectiveness (but even at the upper end, this probably wouldnât be cost-competitive with top EA interventions).
In general, I think itâs a good step to try and actually put interventions from different cause areas on the same scale, but I continue to think that because DALYs are a unit of health status and not a unit of utility, trying to use them as a unit of comparison is unlikely to be optimal (see here and here for more)
I would agree on that this intervention would look better (in $/âDALY space) if I were to have adopted the same assumptions as @Laura Duffy and come up with some plausible assumptions how much time in various pain intensities that would be averted through the intervention. I also think its very unlikely the intervention would look competitive the top AW and GHD interventions. Under the assumptions where this intervention were to look very competitive, Iâd suspect shrimp stunning interventions would look even better.
Thanks also for your very valid comments on using DALYs as a unit to compare interventions (and your general engagement on the research that @Rethink Priorities does!).
Thank @Vasco Grilo you for your thoughtful comments. Appreciate it!
I donât think youâve missed anything. I think youâve identified a very valid critique of the assumptions I used to express cost-effectiveness as a cost per DALY averted range. Expressing the welfare ranges in units of seconds or years is a great way of bringing this out â so thank you for doing that.
Some comments:
If I were to rebuild the cost-effectiveness model, with the benefit of hindsight (and more time), Iâd have probably used a probabilistic rather than deterministic variable for the assumption converting the % improvement in the human welfare range (for one year) that is equivalent to averting a DALY.
Iâm pretty sure assumption feeds through linearly into the $/âDALY results. So if you believed an assumption of 5% of human welfare range was more appropriate than 50%, you could divide the 5th and 95th percentiles of the cost per DALY averted range.
The formal sensitivity tests I did suggest the conclusions of how this intervention looks compared to the most promising GHD and animal welfare interventions wouldnât change with ârelatively smallâ adjustments to the assumptions needed to convert results into DALY space (e.g. doubling the fish welfare range relative to humans and assuming averting a DALY is equivalent to a human intervention that raises human welfare by 10% of the human welfare range for 1 year).
I think once you start making bigger adjustments to these assumptions, you can run into the risk of being criticised for placing too much moral value on short-duration but high intensity suffering. I donât think we have good empirical evidence to support any particular assumption here.
The moral value section of the results more formally illustrates how the fish stunning intervention compares to various $/âDALY benchmarks depending on the moral value you might assign to improving a year of fish life via the intervention relative to averting a DALY.
I donât think the narrative expressed in the executive summary would change even if I were to change the assumption on the moral value of averting intense suffering relative to extending healthy lifespan.
While I think there is a lot of value in trying to place results into a âcommon currencyâ, I think this is also a good reason why cost per DALY averted numbers should always be treated with some caution (there is will always be moral value judgements there, some of which may be objectionable). I think itâs valuable important to look at a number of different metrics (number of animals affected, amount of time affected) to assess how promising an animal welfare intervention looks.
Thanks for sharing, Sagar!
I do think your methodology greatly underestimates the value of averting extreme suffering. You say:
The assumptions in the 1st of the above paragraphs make sense to me if I interpret the welfare range as i) the difference between the welfare per unit time of the best and worst possible experience of 1 second, rather than ii) the difference between the welfare per unit time of the best and worst possible experience of 1 year (this can also be thought of as the difference between the welfare per unit time of the best and worst typical experience). However, for the 2nd paragraph to make sense, one has to interpret the welfare range as ii). So I think there is a contradiction:
Interpreting the welfare range as i), I would value 1 DALY as much less than a 50 % improvement in the welfare range, because being in extreme suffering is way worse than being in full health.
Interpreting the welfare range as ii), the improvement due to the stunning intervention would be way larger, because avoiding extreme suffering is way more important than extending full health.
Am I missing something?
I agree with this comment. Itâs worth nothing that the methodology used in this analysis isnât the same as the methodology used in the CURVE sequence. In the âHow Can Risk Aversion Affect Your Cause Prioritizationâ report, @Laura Duffy weighted 1 year of disabling pain at 2 to 10 DALYs and 1 year of excruciating pain at 60 to 150 DALYs. I expect that dying is at least disablingly painful and potentially excruciatingly painful, so these weights would imply a >5x improvement in cost-effectiveness (but even at the upper end, this probably wouldnât be cost-competitive with top EA interventions).
In general, I think itâs a good step to try and actually put interventions from different cause areas on the same scale, but I continue to think that because DALYs are a unit of health status and not a unit of utility, trying to use them as a unit of comparison is unlikely to be optimal (see here and here for more)
Thank you for your comments, Matt!
I would agree on that this intervention would look better (in $/âDALY space) if I were to have adopted the same assumptions as @Laura Duffy and come up with some plausible assumptions how much time in various pain intensities that would be averted through the intervention. I also think its very unlikely the intervention would look competitive the top AW and GHD interventions. Under the assumptions where this intervention were to look very competitive, Iâd suspect shrimp stunning interventions would look even better.
Thanks also for your very valid comments on using DALYs as a unit to compare interventions (and your general engagement on the research that @Rethink Priorities does!).
Thank @Vasco Grilo you for your thoughtful comments. Appreciate it!
I donât think youâve missed anything. I think youâve identified a very valid critique of the assumptions I used to express cost-effectiveness as a cost per DALY averted range. Expressing the welfare ranges in units of seconds or years is a great way of bringing this out â so thank you for doing that.
Some comments:
If I were to rebuild the cost-effectiveness model, with the benefit of hindsight (and more time), Iâd have probably used a probabilistic rather than deterministic variable for the assumption converting the % improvement in the human welfare range (for one year) that is equivalent to averting a DALY.
Iâm pretty sure assumption feeds through linearly into the $/âDALY results. So if you believed an assumption of 5% of human welfare range was more appropriate than 50%, you could divide the 5th and 95th percentiles of the cost per DALY averted range.
The formal sensitivity tests I did suggest the conclusions of how this intervention looks compared to the most promising GHD and animal welfare interventions wouldnât change with ârelatively smallâ adjustments to the assumptions needed to convert results into DALY space (e.g. doubling the fish welfare range relative to humans and assuming averting a DALY is equivalent to a human intervention that raises human welfare by 10% of the human welfare range for 1 year).
I think once you start making bigger adjustments to these assumptions, you can run into the risk of being criticised for placing too much moral value on short-duration but high intensity suffering. I donât think we have good empirical evidence to support any particular assumption here.
The moral value section of the results more formally illustrates how the fish stunning intervention compares to various $/âDALY benchmarks depending on the moral value you might assign to improving a year of fish life via the intervention relative to averting a DALY.
I donât think the narrative expressed in the executive summary would change even if I were to change the assumption on the moral value of averting intense suffering relative to extending healthy lifespan.
While I think there is a lot of value in trying to place results into a âcommon currencyâ, I think this is also a good reason why cost per DALY averted numbers should always be treated with some caution (there is will always be moral value judgements there, some of which may be objectionable). I think itâs valuable important to look at a number of different metrics (number of animals affected, amount of time affected) to assess how promising an animal welfare intervention looks.