(I work for Rethink Priorities in a different team. I had no input into the charter cities intervention report other than feedback in a very early version of the draft. All comments here truly my own. Due to time constraints I did not run it by anybody else at the org before commenting).
The Rethink Priorities report used a 2017 World Bank article on special economic zones as the reference point for potential growth rates for charter cities. The World Bank report concludes, “rather than catalyzing economic development, in the aggregate, most zones’ performance has resembled their national average.” The Rethink Priorities report ends up taking a similarly pessimistic conclusion on charter cities, in part driven by the findings of the World Bank report.
IIRC, I believe the model used a prior distribution informed by the SEZs.
I find the intuition of charter cities more useful than models which have arbitrary assumptions that have substantial implications on the outcome. However, even though David and Jason acknowledged the limitations of their model, it seems as though lots of folks are taking it as the primary implication of the paper! I think this is misguided.
I’m confused what “it” is referring to here.
On the pessimistic side, a 0% increase in the growth rate is certainly possible. Some charter cities will fail. David and Jason argue that it’s possible for charter cities to have a negative growth effect, though it’s hard to imagine how that’s possible under[...]
Are you saying that a negative growth rate relative to the host country is impossible? (or so vanishingly unlikely that it’s close to impossible?) If so, can you specify some betting odds? I get that you’re implicitly long charter cities because of your job, but I’m still happy to make some bets here.
Even Esther Duflo and Abhijit Bannerjee, economists known for their support of RCTs, positively reference charter cities in their recent book.
Pretty minor, but I don’t think it’s reasonable to expect people to buy a book and read through the entire book just to check a reference. At least include a page number!
Imagine a charter city is created on 200+ sq km, with good ocean access, and can attract initial infrastructure investment over $1b in a country that averages under 2% growth. Is it really outside the realm of possibility that the charter city could grow over 8% annually? This impact doesn’t even include the indirect effects of a charter city. [emphasis mine]
I don’t get why analyses from all sides keeps skipping over detailed analysis of indirect effects.* To me by far the strongest argument for charter cities is the experimentation value/”laboratories of governance”angle, such that even if individual charter cities are in expectation negative, we’d still see outsized returns from studying and partially generalizing from the outsized successful charter cities that can be replicated elsewhere, host country or otherwise (I mean that’s the whole selling point of the Shenzhen stylized example after all!).
At least, I think this is the best/strongest argument. Informally, I feel like this argument is practically received wisdom among EAs who think about growth. Yet it’s pretty suspicious that nobody (to the best of my knowledge) has made this argument concrete and formal in a numeric way and thus exposed it to stress-testing. I’ve heard that some people worry that making this argument publicly is bad PR or something, which, fair. These days, I try not to think about PR if I can get away with it and leave it to others. But to the best of my knowledge there’s no private models of this either, which seems like a large deficiency.
EA money is fairly expensive, the prima facie case for investing $millions or more in a charter town/city because of the putative benefits of several thousand or tens of thousands of potential residents ought to be fairly weak**, but much more plausibly good if the tradeoff is knowledge that can help many more people.
*I also flagged this complaint for the RP report. IIRC (and my memory can be quite faulty) the reasoning for not investigating this further was a) time constraints and b) CCI didn’t look into this and RP was trying to engage with CCI’s arguments directly.
**when the counterfactual money can be used to prevent children from dying at $1000-$10,000/child, so each million you invest in charter cities = 100-1000 more dead children. Such costs make sense when you aggregate benefits across millions or hundreds of millions of people (even in the US, gov agencies have a value of statistical life between 5 and 10 million), but the economic gains for several thousand people have to be truly massive if people are trading off between uncertain economic gain and percentage point probability of dying. ^
^ I find it helpful to use a veil of ignorance thought experiment for these interventions. Like what X% chance of dying would you trade off against Y income increase.
(I work for Rethink Priorities in a different team. I had no input into the charter cities intervention report other than feedback in a very early version of the draft. All comments here truly my own. Due to time constraints I did not run it by anybody else at the org before commenting).
IIRC, I believe the model used a prior distribution informed by the SEZs.
I’m confused what “it” is referring to here.
Are you saying that a negative growth rate relative to the host country is impossible? (or so vanishingly unlikely that it’s close to impossible?) If so, can you specify some betting odds? I get that you’re implicitly long charter cities because of your job, but I’m still happy to make some bets here.
Pretty minor, but I don’t think it’s reasonable to expect people to buy a book and read through the entire book just to check a reference. At least include a page number!
I don’t get why analyses from all sides keeps skipping over detailed analysis of indirect effects.* To me by far the strongest argument for charter cities is the experimentation value/”laboratories of governance”angle, such that even if individual charter cities are in expectation negative, we’d still see outsized returns from studying and partially generalizing from the outsized successful charter cities that can be replicated elsewhere, host country or otherwise (I mean that’s the whole selling point of the Shenzhen stylized example after all!).
At least, I think this is the best/strongest argument. Informally, I feel like this argument is practically received wisdom among EAs who think about growth. Yet it’s pretty suspicious that nobody (to the best of my knowledge) has made this argument concrete and formal in a numeric way and thus exposed it to stress-testing. I’ve heard that some people worry that making this argument publicly is bad PR or something, which, fair. These days, I try not to think about PR if I can get away with it and leave it to others. But to the best of my knowledge there’s no private models of this either, which seems like a large deficiency.
EA money is fairly expensive, the prima facie case for investing $millions or more in a charter town/city because of the putative benefits of several thousand or tens of thousands of potential residents ought to be fairly weak**, but much more plausibly good if the tradeoff is knowledge that can help many more people.
*I also flagged this complaint for the RP report. IIRC (and my memory can be quite faulty) the reasoning for not investigating this further was a) time constraints and b) CCI didn’t look into this and RP was trying to engage with CCI’s arguments directly.
**when the counterfactual money can be used to prevent children from dying at $1000-$10,000/child, so each million you invest in charter cities = 100-1000 more dead children. Such costs make sense when you aggregate benefits across millions or hundreds of millions of people (even in the US, gov agencies have a value of statistical life between 5 and 10 million), but the economic gains for several thousand people have to be truly massive if people are trading off between uncertain economic gain and percentage point probability of dying. ^
^ I find it helpful to use a veil of ignorance thought experiment for these interventions. Like what X% chance of dying would you trade off against Y income increase.