So far, the effective altruist strategy for global poverty has followed a high-certainty, low-reward approach. GiveWell mostly looks at charities with a strong evidence base, such as bednets and cash transfers. But there's also a low-certainty, high-reward approach: promote catch-up economic growth. Poverty is strongly correlated with economic development (urbanization, industrialization, etc), so encouraging development would have large effects on poverty. Whereas cash transfers have a large probability of a small effect, promoting growth has a small probability of a large effect. (In general, we should diversify across high- and low-risk strategies.) In short, can we do “hits-based development”?[1]
How can we affect growth? Tractability is the main problem for hits-based development, since GDP growth rates are notoriously difficult to change. However, there are a few promising options. One specific mechanism is to train developing-country economists, who then work in government and influence policy in a pro-growth direction, ultimately increasing the probability of a growth episode. The key is that local experts have local knowledge of culture, politics, and law, which allows them to understand the impediments to growth in a way that foreign World Bank consultants cannot.[2] The goal is not to find the specific interventions that will boost growth in a specific country, but rather to find the experts who will be most capable of finding those interventions.
For example, Lant Pritchett mentions a think tank in India that influenced its liberalizing reforms, which preceded a large growth episode.[3] One way to think of the mechanism is having an economist "in the room" at a key moment to prevent the president from enacting a policy that would lead to hyperinflation (say). Since such an action is highly consequential, but also unlikely, it plausibly has high expected value.[4] A different angle is that local experts will improve the quality of solutions to important problems (urbanization, industrialization, health care, etc). This translates into a concrete goal: increase the number of local experts in developing countries, to increase the chance of a growth episode.
In terms of crowdedness, there are, for example, very few Africans doing economics PhDs in the US. Some developing countries (like China) already have many economists, and do not need to be targeted. One feature of this proposal is that, in principle, it has a clear stopping point: train developing-country economists until you reach N per country.
There are many ways that extra funding could relax budget constraints: GRE fees; PhD application fees; scholarships for undergrads, masters, and PhD students; research projects; thesis prizes; subsidizing RAships; TA buyouts; conference fees and travel; think tanks; translating textbooks; bootcamps/workshops/conferences; sabbaticals/research visits; and so on.
From initial conversations, it seems that the key constraint is the number of well-trained students who can get accepted into top PhD programs. Hence, funding should be targeted to training undergrads and Master's students, as the African School of Economics is doing.[5] Hence, one option is to fund ASE and its satellite campuses. Donations need not be restricted to scholarships, for two reasons. First, because of the fungibility problem, such restrictions are difficult to guarantee. Second, ASE's values are consistent with EA values. This matches GiveWell's advice to "find an organization whose existing priorities you are comfortable with – and give unrestricted."
Footnotes:
[1] See recent discussions on the forum here and here.
[2] Wantchekon says that his knowledge of culture and history led him to the research question of the effect of slavery on trust: "It was his data-mining skills that helped him find the answer. But it was his Beninese background that raised the question."
[3] See also: "I think you invest in people in those countries who are researching, acting, and investigating, and talking about precisely those questions [about property rights, corruption, democracy, transparency]. I think investing $15 million in a group in Nigeria who was asking in an evidence- and experience-based way how to reduce corruption in Nigeria—I think that seems like a pretty plausible way to get those questions answered."
[4] On this view, it's worth training a generation of economists, with only one becoming a presidential advisor, in order to prevent a single hyperinflation.
[5] Note that ASE is partly funded by Princeton and the World Bank.
Very interesting concepts! I have one comment and one contact offering which may be helpful in adding a new perspective to your core assumptions (primarily that systemic solutions, such as empowering the next generation of African economics students to help change legislation, would indeed be effective altruism):
I performed a broad and rather unrigorous quantitative overview of the strategic qualities of the top charities of GiveWell's top ten (OpenPhil, which is a major pioneer of bit-based giving, donates the most to GiveWell's suggestions), GiveWell's 'ineffective' charities (charities deemed not cost-effective or evidence-based enough) and Charity Entrepreneurship's incubated charities to determine what strategic qualities are most utilised by the highest-impact charities. What I found was that qualities relating to hit-based principles (primarily that of prioritising high reward, high risk interventions such as innovations and systemic solutions) didn't align with the high-impact charities and in fact the 'ineffective' charities aligned slightly more with the qualities of hit-based principles. The explanation I found most compelling was that the complexity necessary for high risk and high reward interventions (such as systemic wherein the results are fairly unclear) to success not only bumped up the costs considerably but also the resistance from donors to continue donating due to the complexity obscuring the direct effect of the charity ('how can we know it was helping the African economists which helped improve development? There's many other changes since then which could also have contributed'). And though there are a few statistical methods to try and tease out approximate benefit, systemic interventions may always be marred by unclear impacts, unforeseeable obstacles and undue resistance from donors and the system being changed. My documentation for this qualitative overview can be found here: https://6559c6fb-82b8-43c6-8296-70e9946338cc.filesusr.com/ugd/ed2a7c_e6005590c87341b1ac2e1d13d861d4d1.pdf with page 6 being the colour-coded summary spreadsheet.
The explanation above was mostly galvanised by the social innovator Andrew Benedict-Nelson (https://albnelson.com). Andrew's explanation was rooted in a history of successful systemic change from within the private sector such as Carnegie & Rockefella spending their private wealth to fund, among other creative means, medical conferences designed to increase the scientific approach within the medical industry. Andrew's suggestion was then to tie hit-based giving in with the private sector especially due to the private sector's openness to high risk, high reward investments. If you'd like me to connect you to pick his brain, I'd be happy to!