I am a Researcher at Rethink Priorities, working mostly on cross-cause prioritization and worldview investigations. I am passionate about farmed animal welfare, global development, and economic growth/progress studies. Previously, I worked in U.S. budget and tax policy as a policy analyst for the Progressive Policy Institute. I earned a B.S. in Statistics from the University of Chicago, where I volunteered as a co-facilitator for UChicago EA’s Introductory Fellowship.
Laura Duffy
I’ll also note that I think the counterfactual impact period was one of the model decisions I struggled the most with, which is why you can change it in the model here and see how the results change! https://my.causal.app/models/165404?token=6e8998626d0643db9c86482475aecc2c
Hi Michael, thanks for the comments!
I’ll take the second one first: thanks for bringing to my attention the two-envelopes problem. I’ll look more into this, and I’ll revise accordingly!
As for the years of counterfactual impact, I wanted this report to err on the side of being too conservative, because the impact still appears to be pretty large even under this conservative assumption.
A couple of reasons as to why I used four years include:
1. It’s still relatively consistent with other organizations’ assumptions of years of counterfactual impact. Šimčikas 2019 also gives an overview of other cost-effectiveness analyses’ counterfactual impact assumptions, which I quote below:“Bollard (2016) assumes that cage-free commitments accelerate changes by five years. He also adds: “In my view, the assumption that these campaigns only accelerated pledges by five years is very conservative. It seems equally likely that these companies would never have dropped battery cages, or would have merely transitioned to “enriched” cages. For instance, as recently as March 2015, a coalition backed by McDonald’s, General Mills, and other major food companies issued a report which largely endorsed “enriched” cages as an alternative to cage-free systems.
“ACE uses a subjective 90% confidence interval of 1.6 to 14 years (mean 5.6 years) for all corporate pledges. They explain that “This is the number of years for which we expect these commitments to have an effect for. It is primarily based on counterfactual reasoning—how long before another factor, such as a legislative change or a shift in consumer demand, leads to a similar result.”
“Capriati (2018) estimate does not have a direct equivalent to years of impact expected. Instead, it estimates the number of years THL moves the policy forward by. It assigns the value to this variable based on how important THL’s role was in bringing policies about. By analyzing six randomly selected campaigns, it concludes that on average, THL’s cage-free and broiler campaigns moved policies forward by one year. Note that this assumes that other organisations would have still done corporate campaigns.”
2. Given these estimates, four years seemed like an appropriate lower bound that also aligns with US political cycle.
3. I think, as you and zdgroff have pointed out, there are probably good reasons as to why the counterfactual impact period would be longer than that of corporate campaigns. I really look forward to reading this research! But I also wanted to maintain a degree of conservatism.
So perhaps one’s takeaway is: “this is a good lower bound on the cost-effectiveness of ballot initiatives and, if designed well, they can still look pretty competitive with corporate campaigns nonetheless.”
Again, thanks for the comment!
Hi Lizka! Thanks for the good summary of the ballot initiatives selection process.
Regarding the second question, I think you’re right it would be hard to estimate the probability of similar initiatives passing in other states, as well as the costs of doing so. Here are a few thoughts:
1. One reason we might be optimistic about the cost-effectiveness of pursuing ballot initiatives in more states is that the campaigns in California, Massachusetts, and Arizona may have done much of the heavy lifting in terms of proving to the public that these initiatives are feasible. Advocates also may have refined their techniques to be more effective, and the publicity they got (Prop 12 especially) may have made people in other states more willing to vote for enhanced welfare requirements.
2. But it also might be harder to pass these initiatives in states other than California and Massachusetts for various reasons (they’re very liberal, for example). Nevertheless, one study from 2014 models which states could pass initiatives similar to California Proposition 2 (which applied to domestic production only). Here’s a summary of their findings from my report (pg. 115):
“One study from 2014 used demographic data to model the vote share that a hypothetical initiative designed like California Proposition 2 would receive in all states. Amongst the states that allow ballot initiatives, Proposition 2 is predicted to gain above 50% of the votes in several of them. Depending on the model, these potential states could include Washington, Nevada, Michigan, Oregon, and Colorado, amongst others (Smithson et. al. 2014, pp. 120, 122). Though a few of these states have already passed legislation to implement some farmed animal welfare standards on the state level (Smithson et. al. 2014, pp. 122), and though the study only estimated the likelihood of passing initiatives that affect domestic animals, it seems plausible that initiatives impacting all goods sold in-state could pass in more states than just California and Massachusetts.
In the end, we really do not yet know if the cost-effectiveness of ballot initiatives–especially ones modeled after California Proposition 12 and Massachusetts Question 3–generalizes to states with political ideologies, wealth, and other demographics that differ from California and Massachusetts (which are themselves outliers).”
In all, I think this is a great question to be asking, and there are some reasons to be cautiously hopeful that ballot initiatives could be successful in states other than those studied, namely California and Massachusetts. In addition, I would suspect there is a lot of room for advocacy in these two states as well with regard to broiler chicken welfare.
A Cost-Effectiveness Analysis of Historical Farmed Animal Welfare Ballot Initiatives
To follow up on Bob’s point, the ranges presented here are from a mixture model which combines the results from several models individually. You can see the results for each model here: https://docs.google.com/spreadsheets/d/1SpbrcfmBoC50PTxlizF5HzBIq4p-17m3JduYXZCH2Og/edit?usp=sharing
For example, the 0.005 arises because we are including the neuron count model of welfare ranges in our overall estimates. If you don’t include this model (as there are good reasons not to, see https://forum.effectivealtruism.org/posts/Mfq7KxQRvkeLnJvoB/why-neuron-counts-shouldn-t-be-used-as-proxies-for-moral) then the 5th percentile welfare range for pigs of all models combined is 0.20.
The 1.031 comes from a model called the “Undiluted Experiences” model, which suggests that animals with lower cognitive abilities have greater welfare ranges because they are not as able to rationalize their feelings (eg. pets being anxious when you’re packing for a trip). A somewhat different model would be the “Higher-Lower Pleasures” model that is built on the idea that higher cognitive capacities means you can experience more welfare (akin to the JS Mill idea of higher-order pleasures). Under this model, we estimate that the range for pigs is 0.23 to 0.49--which is quite significant given how this model could be seen as having a pro-human bias!
In sum, the welfare ranges presented above reflect our high degree of uncertainty surrounding how to think about measuring welfare. As such, we invite you to take a closer look at each model (you’ll find most of them converge on the overall conclusion that vertebrates are within an order of magnitude of humans in terms of their welfare ranges).
Thanks for the comment, Ben!
And thanks so much to everyone doing direct work to improve animal welfare!