Modern economic growth has transformed global living standards, delivering vast improvements in health and well-being while helping to lift billions of people out of poverty.
Where does economic growth come from? Because new ideas — from treating infections with penicillin to designing jet engines — can be shared and productively applied by multiple people at once, mainstream economic theory holds that scientific and technological progress that creates ideas is the main driver of long-run growth. In a recent article, Stanford economist Chad Jones estimates that the growth in ideas can account for around 50% of per-capita GDP growth in the United States over the past half-century. This implies that the benefits of investing in innovation are large: Ben Jones and Larry Summers estimate that each $1 invested in R&D gives a social return of $14.40. Our Open Philanthropy colleagues Tom Davidson and Matt Clancy have done similar calculations that take into account global spillovers (where progress in one country also boosts others through the spread of ideas), and found even larger returns for R&D and scientific research.
But ideas don’t automatically raise living standards; economic growth requires turning them into technologies that can disseminate throughout society. Burdensome government regulations and institutional constraints are increasingly slowing the pace of this progress and creating artificial scarcity. Restrictive zoning and land use regulations have created housing shortages in many major cities, driving up rents and preventing people from making productive moves to centers of economic growth and innovation. Similar constraints hinder scientific and technological innovation — key institutional funders like the NSF or the National Institutes for Health (NIH) burden researchers with excessive paperwork and overly lengthy grant review processes, while preferring low-risk, incremental research over higher-risk but potentially transformative ideas. Meanwhile, environmental review laws slow a wide variety of infrastructure projects, including green energy.
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For Open Philanthropy as an institution, the timing is also right. Learning from the recent success of our Lead Exposure Action Fund (LEAF), which doubled the total amount of philanthropic funding toward lead exposure reduction in low-income countries, we are increasingly exploring pooled funding models. We talked with a number of like-minded donors who suggested potential appetite for a pooled fund like this, and ultimately received commitments for over $60 million so far from other funders. We’re grateful to Good Ventures, Patrick Collison, and our other donors in this fund for their support, and we’re always excited to hear from other funders who might be interested in collaboration opportunities.
Yes, I’ve read their entire post. $14.4 of “social return” per $1 in the US seems incredibly unlikely to be comparable to the best GiveWell interventions or even GiveDirectly.
Ozzie Gooen asked about this before, here’s (the relevant part of) what Alexander Berger replied:
Our innovation policy work is generally based on the assumption that long-run health and income gains are ultimately attributable to R&D. For example, Matt Clancy estimated in this report that general funding for scientific research ranged from 50-330x in our framework, depending on the model and assumptions about downside risks from scientific research. In practice we currently internally use a value of average scientific research funding of 70x when evaluating our innovation policy work. Of course, 70x is well below our bar (currently ~2,100x), and so the premise of the program is not to directly fund additional scientific research, but instead to make grants that we think are sufficiently likely to increase the effective size of R&D effort by raising its efficiency or productivity or level enough to clear the bar. Moreover, while most of our giving in this program flows to grantees in high-income countries operating on the research frontier, the ultimate case is based on global impact: we assume research like this eventually benefits everyone, though with multi-decade lags (which in practice lead us to discount the benefits substantially, as discussed in Matt’s paper above and this report by Tom Davidson).
Our innovation policy work so far has cleared our internal bar for impact, and one reason we are excited to expand into this space is because we’ve found more opportunities that we think are above the bar than Good Ventures’ previous budget covered.
We also think our housing policy work clears our internal bar for impact. Our current internal valuation on a marginal housing unit in a highly constrained metro area in the US is just over $400k (so a grant would be above the bar if we think it causes a new unit in expectation for $200). A relatively small part of the case here is again based on innovation—there is some research indicating that increasing the density of people in innovative cities increases the rate of innovation. But our internal valuation for new housing units also incorporates a few other paths to impact. For example, increasing the density of productive cities also raises the incomes of movers and other residents, and reduces the overall carbon footprint of the housing stock. Collectively, we think these benefits are large enough to make a lot of grants related to housing policy clear our bar, given the leverage that advocacy can sometimes bring.
Someone else asked him to clarify what he meant by the numbers on the housing policy work and also separately asked
Also I read the report you linked on R and D where it didn’t clear the funding bar. That said 45x, you were pushing that up to 76x
“In a highly stylized calculation, the social returns to marginal R&D are high, but typically not as high as the returns in some other areas we’re interested in (e.g. cash transfers to those in absolute poverty). Measured in our units of impact (where “1X” is giving cash to someone earning $50k/year) I estimate the cost effectiveness of funding R&D is 45X. This is 45% the ROI from giving cash to someone earning $500/year, and 4.5% the GHW bar for funding. More.”
I understand that you think you can raise efficiency of certain types of R@D, but getting from 70x to 2100x means you would have to 30x the efficiency. I struggle to understand how that would be likely again any pointers here?
to which he replied
On the housing piece: we have a long internal report on the valuation question that we didn’t think was particularly relevant to external folks so we haven’t published it, but will see about doing so later this year. Fn 7 and the text around it of this grant writeup explain the basic math of a previous version of that valuation calc, though our recent version is a lot more complex.
If you’re asking about the bar math, the general logic is explained here and the move to a 2,100x bar is mentioned here.
On R&D, the 70x number comes from Matt Clancy’s report (and I think we may have made some modest internal revisions but I don’t think they change the bottom line much). You’re right that that implies we need ~30x leverage to clear our bar. We sometimes think that is possible directly through strategic project selection—e.g., we fund direct R&D on neglected and important global health problems, and sometimes (in the case of this portfolio) through policy/advocacy. I agree 30x leverage presents a high bar and I think it’s totally reasonable to be skeptical about whether we can clear it, but we think we sometimes can.
(I don’t know anything else about this beyond the exchange above, if you’re interested in litigating this further you can try replying to his last comment maybe)
You’ve seen the blog post?
Yes, I’ve read their entire post. $14.4 of “social return” per $1 in the US seems incredibly unlikely to be comparable to the best GiveWell interventions or even GiveDirectly.
It isn’t 14.4x, it’s 2,000x they’re aiming for.
Ozzie Gooen asked about this before, here’s (the relevant part of) what Alexander Berger replied:
Someone else asked him to clarify what he meant by the numbers on the housing policy work and also separately asked
to which he replied
(I don’t know anything else about this beyond the exchange above, if you’re interested in litigating this further you can try replying to his last comment maybe)