Our organization is not big enough to hire a statistician, although we will for sure get one when we are able to build a sufficiently large study / program. I’d be happy to refer you to the people that do have a ton of statisticians:
https://www.givedirectly.org/research-at-give-directly/
https://basicincome.stanford.edu/research/ubi-visualization/
https://www.penncgir.org/research
Let’s use a different analogy. Let’s say that you are in exactly the same situation you are in right now, and some random organization decided to start giving you $1,000 checks every month for one year. All they want, is periodic updates on how you’re doing, and they tell you that your answers are anonymized and will not affect the payments. Would you go out of your way to lie to them?
We are not trying to be anyone’s parents, and have no desire for the weird inter-personal shame dynamics that would be going on in your analogy.
We need to take a bit of a step back here. I am just as keen as you are to get good unbiased data that can be relied upon to know precisely how impactful cash transfers—and other interventions—are at helping people. And I’d like to acknowledge that you’re correct that we should not rely solely on unchecked survey data when trying to figure out impact results.
So I did a bit of a deep dive into meta-analyses and systematic reviews of cash transfer studies. It turns out that while surveys are generally one part of the data collected, researchers have been able to use objective measures and collect data that participants can’t lie about (such as government income reporting, and school attendance rates among others). So I figure you might find it useful to check out the systematic reviews, and the organizations with tons of statisticians that have likely accounted for the very real problems you’ve pointed out with surveys.
https://odi.org/en/publications/cash-transfers-what-does-the-evidence-say-a-rigorous-review-of-impacts-and-the-role-of-design-and-implementation-features/
We all know GiveWell, they do extremely rigorous analyses of studies, and came to this conclusion:
Their focus is primarily on cash transfers in developing nations, but I think their point about non-health interventions is especially interesting when considering how effective health interventions are much harder to come by in developed nations. There are several research institutions entirely dedicated to sussing out the effectiveness of cash transfers. They have tons of statisticians, and I’m sure they actively account for the issues with surveys versus other data types.
https://as.nyu.edu/departments/cash-transfer-lab/faq.html
https://basicincome.stanford.edu/research/ubi-visualization/
https://www.penncgir.org/research
I would like to see more research comparing cash directly to other interventions, I think there are a surprisingly large amount of current interventions going on that are either marginally helpful or actively harmful to beneficiaries. The most important thing in philanthropy is diverting as much funding as possible, at a global scale, to the interventions that we know are the most highly effective.
You’ve mentioned a few times that I need a statistician for what we’re doing, and I fully intend on going even further. When we have a large enough experiment to run we will not only hire a statistician but have unbiased external scientific institutions operate the research alongside our program (such as the research labs linked above). That way we cannot manipulate their results. I am very interested in falsifiable studies that can either indicate we’re going in the right direction or prevent us from wasting a lot of time on something that isn’t impactful.
Finally, I’m well aware that guaranteed income regarding homelessness is far smaller and much less rigorous than cash transfers in general or globally. However we’ve spoken to dozens of homeless aid workers as well as homeless people, and we’ve seen promising anecdotal results from all of the (imperfect) small to medium-scale studies done so far. As long as we’re conducting good large-scale research, and (good of you to point out) not relying entirely on surveys or other potentially biased metrics, I think doing larger-scale and higher-quality research is well worth EA dollars.
If the larger studies prove what we think we see happening on a small scale, we could solve the homelessness crisis with ~10% of the current amount we spend on the problem. If the large-scale studies show less impact, but are still in the same range as general cash transfer research, then guaranteed income would still be the most cost-effective way to help the homeless, just not 5-10X better than the other methods as it currently looks.
Overall, better research is needed, and we fully intend to produce highly consequential studies once we have the funding to launch a statistically relevant program. If we could get an EA statistician to look over the current homelessness research, they would be far more qualified than you or I to know just how much trust we should be putting in the research done so far. Do you know any?