Within the effective altruism community, people often talk about “long-termist” vs “short-termist” worldviews. The official distinction between the two is that short-termists prioritize problems by how they affect people alive today, while long-termists prioritize problems by how they could affect humanity’s entire future trajectory. In practice, people usually treat this as synonymous with prioritizing either existential risk reduction (if long-termist), or scaling up proven global health interventions (if short-termist).
It’s a bit surprising that each worldview should have exactly one favorite cause area, though. Couldn’t you have short-termist work on existential risk, or long-termist work on global poverty? In reality, these supposedly discrete worldviews seem more like correlated clusters of various different beliefs:
- High time discount rate
- Prefers highly robust “outside view” type arguments
- Extrapolates existing effects or trends
- Skeptical of prima facie bizarre claims
- Focuses on fixing known, concrete problems
- Fast feedback loops are critical to making progress
- Low or no discount rate
- More open to “inside view” that this case might be different
- Reasons about the future from first principles
- Takes weird-sounding ideas more seriously
- Focuses on preventing hypothetical, nebulous risks
- Fast feedback is helpful, but not the most important thing
It’s understandable why some of these are correlated, but there must be a lot of people who fall through the cracks between the clusters. What if you share short-termists’ skepticism of weird claims and hypothetical risks, but you’re willing to focus on first-principles reasoning and work on a long time scale?
You’d still want to focus on something that’s a problem today, so you’d probably want to work on global poverty. But you’d dismiss GiveWell’s top charities as treating a symptom and not a cause. Why do these countries need charity in the first place? South Korea used to be just as poor as anywhere in Africa, but today it’s incredibly prosperous, while sub-Saharan Africa has made way less progress. If we could move the lowest-growth countries from their current trajectory onto South Korea’s, we’d have done much more than any single malaria-eradication campaign could.
If that were your worldview, you’d really enjoy Why Nations Fail, one of the best attempts I’ve seen at getting a first-principles understanding of what affects countries’ long-term economic growth.
First of all, what is economic growth? It’s when people produce more (or more valuable) stuff with the same effort. The first and least controversial point in Why Nations Fail is that for a nation to keep on doing more with less, its individual citizens need to be incentivized to become more productive. In particular, the state should not set up systems where, whenever someone gets more productive, other people come and take away the extra stuff they produced. Those systems are what the authors call extractive economic institutions, and they include things like slavery, serfdom, indentured servitude, roving bandits, guilds, collectivized agriculture, nationalization of private assets, officials requiring bribes, kangaroo courts, banana republics, and other [animal or vegetable] [civic institution].
You might think you could grow your economy under extractive institutions by forcing people to become more productive even if they won’t get to keep the surplus. This does often work in the short term (and the short term can last a surprisingly long time)–for instance, Soviet Russia grew at about 5% annually from 1930-1970, despite having extremely extractive institutions. But that only worked because the growth started from a low base. Soviet Russia’s economic institutions, while horrible, were arguably still less extractive than the serfdom that preceded them. Plus, the growth came mainly from “easy wins” like people switching from horrifically inefficient farming to horrifically inefficient industry.
In fact, growth under extractive institutions can only come from easy wins–easy enough that they’re obvious to whoever has the job of forcing other people to be more productive. (Nobody is going to generate their own productivity-boosting ideas, because they have no incentive to.) Any half-decent Soviet central planner could have told you that industry would be more productive than farming, so they were able to force peasants to make the switch. But nobody was good enough at central planning to fix all the ways their industry was inefficient–let alone come up with new inventions or technologies as fast as the US was. So once all the low-hanging fruit was plucked, circa 1980, the Soviet Union ran into a productivity wall and collapsed.
What’s more, even if an innovation is obvious to the extractive elite, they might actively try to crush it because it threatens their hold on power. For instance, in 19th-century Europe, it was obvious that factories and railroads could be a huge productivity improvement, but the extractive rulers of peripheral Europe wanted none of them. Here’s Austria:
When a plan to build a northern railway was put before [Emperor] Francis I, he replied, “No, no, I will have nothing to do with it, lest the revolution might come into the country.”
And here’s Russian Finance Minister (1823-44) Count Igor Kankrin:
[R]ailways do not always result from natural necessity, but are more an object of artificial need or luxury. They encourage unnecessary travel from place to place, which is entirely typical of our time.
It might seem cartoonish for a ruler to ban technology out of fear of TEH REVOLUTIONZ–until you remember how many extractive states today, like Ethiopia and China, have resisted the Internet for similar reasons.
The next part of Why Nations Fail asks: if economic institutions explain long-term growth, what explains long-term economic institutions? The answer, maybe obviously, is politics.
Extractive economic institutions tend to persist more when social power is concentrated in a small elite (“extractive political institutions”) that can use this power to take the economic surplus for themselves–or just destroy it if it looks scary and potentially destabilizing. They persist less when social power is distributed widely in the population (“inclusive political institutions”) because in that case the people being extracted will often have enough political power to fight back against the extraction.
For instance, in the early 1900s in the United States, various industries (steel, oil, banking, chemicals, farming tools, etc.) ended up under the control of extractive monopolists who charged too much, paid too little, pocketed the difference, and spent the difference on gold-plated toilets. But even the world’s fanciest toilets couldn’t defeat the mass populist movement that rose up to oppose the monopolies (because the US was sufficiently pluralistic that mass populist movements were very powerful), and so they were eventually forcibly broken up and regulated.
In states with less pluralistic politics, the elites can get away with this kind of extraction. For instance, when the British colonized Sierra Leone, they set up monopoly cocoa and coffee purchasing boards that bought low from the farmers, sold high on international markets, and pocketed the margin. After independence, instead of dismantling the boards, Sierra Leone’s presidents turned them into a slush fund, driving the margin up to 90%.
Sierra Leone illustrates another sad fact about extractive economic institutions, which is that they persist surprisingly much across nominally different political regimes. What happened in Sierra Leone happened nearly everywhere in sub-Saharan Africa: the colonists were ousted by a revolutionary leader, who quickly realized that the colonists’ giant money-printing machine was still in place, and decided that maybe the entire colonial apparatus didn’t need to be smashed. And of course, in order to keep their hold on the economic surplus, the new “democratic” government quickly resorted to repression and violence. (Why Nations Fail is very clear that what matters is de facto, not de jure, democracy, and that confusing these two will lead to very wrong conclusions.)
Over long timescales, then, it seems like a mix of inclusive and extractive institutions is unstable. If institutions are inclusive enough, then any group that deviates and tries to institute extractive norms will get shut down by the rest of society. If institutions aren’t inclusive enough, one of those groups will eventually succeed, and then be incentivized to consolidate their power even further until the society is totally extractive.
The most glaring exception to this rule–which many reviewers have pointed out–is China since Deng Xiaoping, which has relatively inclusive economic institutions, but extremely authoritarian politics, for the last 40 years. Acemoglu and Robinson acknowledge this, but claim, basically, that China is not in a stable equilibrium:
All the same, [Chinese] growth will run out of steam unless extractive political institutions make way for inclusive institutions. As long as political institutions remain extractive, growth will be inherently limited, as it has been in all other similar cases.
This is a kind of weak explanation as written because they don’t even mention the mechanism by which it will be limited, but with some charity I think you can construct a decent argument. Concretely, it seems like the _Why Nations Fail_model predicts that China’s current, inclusive economic institutions are not sustainable without inclusive political institutions to support them. In the current regime, the Chinese political elite’s local incentives are to extract as much of the economy’s surplus as possible, because they can; it’s not sustainable to just hope they keep being altruistic enough to not do that. At some point, unless China’s political institutions give real power to a broad majority of people, the elites will give in to temptation and start taking all the economic surplus for themselves.
(Note by the way that China’s recent economic slowdown does not confirm this model’s predictions, unless you think the slowdown was caused by the political elite becoming more economically extractive, which doesn’t seem like the case.)
If you’re worried about having powerful authoritarian nations hanging around, this is a comforting model to have. On the other hand, China has been “out of equilibrium” for almost half a century, and Why Nations Fail doesn’t offer any framework for thinking about how long these disequilibria can last.
The strongest claim in Why Nations Fail, which is mostly left annoyingly implicit, is that institutions are the dominant factor in shaping economic growth, over long enough time horizons. Many of their reviewers disputed this.
To be fair, a lot of those reviewers seemed to have rounded off this claim to “institutions are always the dominant factor,” and then complained about the book not explaining China (despite the half-chapter explaining that China is out of equilibrium), or not sufficiently explaining Bolivia vs Vietnam over the last 30 years (if China can be out of equilibrium for 40 years, so can other countries), or similar. But even over long periods of time, it’s reasonable to ask whether institutions were really the most important possible thing.
The most obvious alternative candidate is geography (including natural resources). Why Nations Fail makes some attempt to argue that geography isn’t sufficiently explanatory, citing (a) the divergence between North and South Korea, and (b) that after European colonization of the Americas, the correlation between latitude and productivity went from negative (tropics more productive) to positive (temperate regions more productive):
As we saw in the last chapter, at the time of the conquest of the Americas by Columbus, the [tropical] areas… held the great Aztec and Inca civilizations.... In sharp contrast… the [modern] United States, Canada, Argentina, and Chile, were mostly inhabited by Stone Age civilizations lacking these technologies. The tropics in the Americas were thus much richer than the temperate zones, suggesting that the “obvious fact” of tropical poverty is neither obvious nor a fact. Instead, the greater riches in the United States and Canada represent a stark reversal of fortune relative to what was there when the Europeans arrived.
The reversal of fortune happened, they argue, because colonists were more likely to install extractive institutions in the densely populated (wealthiest) areas of the Americas, where they could rely on forced indigenous labor; and inclusive institutions in the sparsely populated areas where there was no forced labor supply and settlers needed to be incentivized to be productive. This difference in institutions eventually led to stagnation in the tropics and faster growth in the temperate regions.
This doesn’t seem like a very definitive refutation, though. The Koreas example only shows that institutions dominate when geography and culture are held constant (plus, it’s cherry-picked to be maximally extreme). The example of the Americas is stronger, but I can imagine alternative models. For instance, maybe being tropical was an advantage before the industrial revolution because it meant less lethal weather; but a disadvantage afterwards because it meant that your comparative advantage was farming, rather than industry, and farming-specialized economies grow less quickly because they don’t develop compounding technical knowledge.
The example of the Americas’ reversal of fortune also doesn’t address more complex geographical factors, like that iron, coal or navigable rivers are necessary for industrial growth. In the medium term, geography of this form seems obviously very important; it’s no coincidence that England was rich in all three. In the long term, it seems like they might become less important, because the types of resources that are important will change. (Today if you’re a developing country with no iron or coal deposits, you can trade with other countries to get them; if you don’t have navigable rivers, you can build railroads or highways.) But neither of those is a perfect substitute, so it seems like there’s still a strong case for geography mattering.
On the other hand, if you’re trying to encourage development, not just understand it, it’s not clear how actionable the pro-geography argument is. Even if geography is important, it’s not particularly tractable to change! The only implication I can think of is maybe that liberalizing immigration becomes more important, so that it’s easier for people to move from resource-poor to resource-rich areas.
If true, the claims in Why Nations Fail have huge implications for (global-poverty-focused) effective altruism. Global poverty EA currently focuses on scaling up development aid interventions that have a strong evidence base of randomized controlled trials. But if you buy Why Nations Fail‘s argument, you should probably prefer to take countries with extractive institutions and move them towards inclusivity, if that problem is tractable.
To me, it does seem tractable. For instance, in the recent election in Senegal, where I live, the incumbent president had a huge spending advantage, which was widely rumored to be because he diverted public funds to his campaign. (Not coincidentally, many prominent opposition politicians are currently in jail for misuse of public funds–the result of an investigation initiated by the same incumbent president.) The current Senegalese media is reluctant to investigate because the media in the capital are largely owned by people high up in government. Sponsoring the development of independent investigative media in Senegal seems like a (relatively) straightforward step towards improving Senegalese political institutions.
Of course, this take is only based on a couple hours of conversation with my Senegalese coworkers, so it’s definitely not optimal. Maybe it would even make things worse! But hopefully it illustrates the general point, which is that we know what inclusive institutions look like, so trying to move things in that direction is mostly a question of strategy and execution towards a known goal, not of solving some sort of mystery.
Why Nations Fail provides a compelling theory, with clear implications, supported by many examples, a few of which (like the Koreas or Americas examples) even had some kind of “control group.” But as the book goes on, it becomes more and more glaring how much it relies on anecdotes, not studies. Unfortunately, that’s probably because the empirical situation is abysmal.
Acemoglu and Robinson might not agree with that claim, since they were publishing empirical studies of institutions in economics journals for a long time before they wrote Why Nations Fail. But they also chose not to cover most of that empirical research in the book, and I can see why: I couldn’t find a single study that seemed really defensible.
Some of the problems I saw were silly and avoidable, like treating Likert scales as continuous instead of leveled-categorical or obviously violating the assumptions of instrumental variables. But as far as I could tell, the bigger issues were core to any attempt to empirically study the causes of growth:
- The sample size is tiny. There are only 200 countries, many of which are too small or too weird to be informative. (We do have hundreds of years of growth data for some countries, but different years of growth for the same country aren’t independent data points.) The “effective” sample size is even lower because the “error term” is often spatially correlated, which most studies do not properly account for, causing widespread p-value inflation.
- When you’re analyzing countries’ growth, everything is endogenous. Your institutions in year 1 affect your growth in year 2, which affects who gets more power in year 3, which affects how your institutions change in year 4. If you measure a correlation between growth and institutions, it could just as easily be that fast growth causes better institutions, not the other way around.
- Institutions and growth have a really complicated causal structure–both of them have a huge number of causes and effects. In situations like that, and especially with a sample size of 200, correlational studies never work. Even if you try to control for all the confounders, there are just too many subtle things that can go wrong.
- Ordinarily you might try to get around that by using a fancier causal inference technique, like finding instrumental variables–random events that affect a state’s institutions, but aren’t correlated with them. For example, one famous paper tried to do this with European mortality rates in colonized countries (the theory being that colonists were less likely to install extractive institutions in countries where more Europeans had immigrated).
But a key assumption of instrumental variables is that the instrument only affects the outcome (growth) via its effect on other things you’ve measured (institutions or other covariates). In other words, to get a valid estimate, you’d need to measure every possible way that settler mortality could affect growth rates. Since measuring everything is impossible, and throwing it all into a model with only 200 data points is also impossible, that makes instrumental variables double-impossible. (Which didn’t prevent various economists from trying–apparently badly.)
These problems make me put almost zero weight on the empirical literature for institutions and growth, even before reading about the specific problems with specific papers. But they apply equally well to any attempt to find the causes of economic growth.
So where does that leave us?
Partly, it leaves us with a big methodological gap. The problems above make it relatively harder to get to a true understanding of what matters for development. But it doesn’t mean it’s hopeless to try and make intellectual progress on the question.
Indeed, I can imagine analyses that would make me more confident that the institutional hypothesis is correct–for instance, a systematic review with case studies of many different growth episodes, or many different institutional changes that you’d expect to affect growth. I’m not sure why Acemoglu and Robinson’s empirical work focused instead on what looks like badly-validated instrumental-variables models–maybe because they were easier to do (or easier to publish in top journals)? But given the amount of noise and the limited sample size, case studies seem much more likely to be informative than fancy models with questionable assumptions.
Nor is it unprecedented for lots of experts to agree on something even without airtight studies backing it up. A real-world role model could be something like the laws of supply and demand–which most economists believe in, even though they turn out to be tricky to verify in many real-world cases, like minimum wage laws or housing. Or even like the efficient-market hypothesis, which many effective altruists seem to endorse, far beyond our ability to empirically test it.
But on questions of poverty reduction, the effective altruism community doesn’t seem to be really looking for any methodology other than randomized controlled trials. In fact, this is a major (and not often addressed) criticism of global-poverty-focused effective altruism, including from Acemoglu himself in his_Boston Review_ critique of effective altruism:
[P]recise measurement of the social value of a donated dollar may be impossible. … If, as some economists and political scientists suggest, changes in political and economic institutions are critical for long-run economic growth, then watchdog organizations such as Amnesty may be essential for transforming dysfunctional regimes. Effective altruists don’t (yet?) see the importance of these more political organizations. If this narrow focus continues, it may divert public and media priorities from political factors underpinning economic development.
His concern was shared by Angus Deaton:
More broadly, the evidence for development effectiveness, for “what works,” mostly comes from the recent wave of randomized experiments. … How can those experiments be wrong? Because they consider only the immediate effects of the interventions, not the contexts in which they are set. Nor, most importantly, can they say anything about the wide-ranging unintended consequences.
However counterintuitive it may seem, … [d]evelopment is neither a financial nor a technical problem but a political problem, and the aid industry often makes the politics worse.
Peter Singer’s response (which, as I’ve argued before, misses the point):
[I]f large-scale reform offers some prospect of reducing poverty, then effective altruists will try to assess its chance of doing good, and if the expected value of such action is higher than the expected value of more limited interventions, they will advocate working for the large-scale reforms.
It’s been four years since Peter Singer wrote that, and I don’t see much sign of the prediction coming true. The leading EA global poverty charity evaluator, GiveWell, begged off because institution-focused interventions wouldn’t be transparent enough:
Root-causes-based approaches are, in our view, the kind of speculative and long-term undertakings that are best suited to highly engaged donors (as discussed above).
But the EA community doesn’t seem to have produced many such “highly engaged donors,” with the possible exception of Aceso Under Glass giving to Tostan. (GiveWell itself may be in the process of becoming one. I hope that changes this!) Instead, most global-poverty-focused effective altruists seem happy to follow GiveWell’s recommended charities. Maybe that’s because all the long-termists are working on mitigating existential risks. But for any who are still sympathetic to global poverty as a cause area, Why Nations Fail provides an interesting example of an alternate paradigm.
Thanks to Eve Bigaj, Drew Durbin, Milan Griffes, Alexey Guzey, Holden Karnofsky, Joyce Keeley, Jeff Kaufman, Dan Luu, Aaron T, and Yuri Vishnevsky for their comments on drafts of this post.
Technically economic growth also includes increasing the amount of effort–for instance, via population growth or via increasing hours worked–but those are much better-understood, so we’ll only think about productivity growth here. ↩︎
Source: the most conservative estimates on this chart. ↩︎
You might be aware of this, but Lant Pritchett largely agrees with your criticisms at the end of the piece - that the focus on RCTs isn't likely to be helpful in finding interventions that accelerate economic development.
I had one of his quotes on partial attribution bias (maybe even from that interview) in mind as I wrote this!
I wrote a similar post about this a few months ago, a few days before GiveWell announced they were looking into a wider range of interventions.
The EA fund for global development seems to be the easiest way to get funding towards this area. I suspect that most donors involved in EA would be happy to fund interventions with less hard evidence if given the choice.
One reason why there may be a lack of conversation in this area is that there are many organisations and 10,000+ experts in international development and ways to engage that don't involve EA. Whereas in factory farming and emerging technology risks there are fewer places for people to go to discuss these causes and so discussion happens in EA spaces (until causes get big enough to create their own networks).
In addition to the empirical problems, I was very underwhelmed by the theoretical mechanisms Acemoglu and Robinson outline. I wrote up my complaints in a couple of blog posts:
(These posts are still a bit drafty so apologies for typos, errors, etc.)
These theoretical claims seem quite weak/incomplete.
Yes, I agree they're very incomplete--as advertised. I also think the original claims they're responding to are pretty incomplete.
I agree that time horizons are finite. If you're taking that as meaning that the defect/defect equilibrium reigns due to backward induction on a fixed number of games, that seems much too strong to me. Both empirically and theoretically, cooperation becomes much more plausible in indefinitely iterated games.
Does the single shot game that Acemoglu and Robinson implicitly describe really seem like a better description of the situation to you? It seems very clear to me that it's not a good fit. If I had to choose between a single shot game and an iterated game as a model, I'd choose the iterated game every time (and maybe just set the discount rate more aggressively as needed--as the post points out, we can interpret the discount rate as having to do with the probability of deposition).
Maybe the crux here is the average tenure of autocrats and who we're thinking of when we use the term?
(I don't say "solve" anywhere in the post so I think the quote marks there are a bit misleading.)
I agree that to come up with something closer to a conclusion, you'd have to do something like analyze the weighted value of each of these structural factors. Even in the absence of such an analysis, I think getting a fuller list of the structural advantages and disadvantages gets us closer to the truth than a one-sided list.
Also, if we accept the claim that Acemoglu and Robinson's empirical evidence is weak, then the fact that I haven't presented any evidence on the real-world importance of these theoretical mechanisms becomes a bit less troubling. It means there's something closer to symmetry in the absence of good evidence bearing on the relative importance of structural advantages and disadvantages in each type of society.
My intuition is that majoritarian tyrannies and collective action problems are huge, pervasive problems in the contemporary world, but I won't argue for that here. I can pretty quickly come up with several examples where it might be in an autocrat's self-interest to confront coordination problems and/or majoritarian tyrannies:
Obviously, each of these examples is only the briefest sketch and way more work would have to be done to make things conclusive.
Whoops, sorry about the quotes--I was writing quickly and intended them to denote that I was using "solve" in an imprecise way, not attributing the word to you, but that is obviously not how it reads. Edited.
I think China is basically in a similar situation to Prussia/Germany from 1848 to 1914. The revolutions of 1848 were unsuccessful in both Prussia and the independent South German states but they gave the aristocratic elites one hell of fright. The formal institutions of government didn't change very much, nor did who was running the show - in the Prussia then Germany the aristocratic-military Junker class. They still put people they didn't like in prison sometimes and still had kings with a large amount of formal power. However, they liberalised pretty spectacularly in lots of way - for instance trade unions were unbanned and the SPD (communist party at the time) grew to be the largest party in Germany, contract law was made equal between employers and workers and a market economy was allowed to flourish independently of the state and the old organisations of guilds and the vestiges of feudalism allowed to die.
To see how dramatic this change was one can look at the state of Prussian agriculture before and after 1848. Prior to 1848 agriculture was still in important ways governed by the Conservative mode of economic organisation - production, exchange and consumption were decided by what tradition dictated, was insulated from market forces by tariffs, and dominated by old aristocratic families. After 1848 Prussian agriculture was allowed to become a part of the market economy and become dominated by bourgeois men who ran their farms to make a profit and hired and fired workers as they pleased, and the market dictated the price of grain. It is hard to overstate how different this is from how agriculture was organised in, say, 1830.
I think China is doing something pretty similar now. 20 years ago individuals lives were controlled in lots of ways by their work units. Your factory unit provided you with your job, your house, your pension, your healthcare and it was controlled by the party. This is now not the case. People move freely between jobs (that's mostly but not entirely true) , regional newspapers report on government failures and people bring lawsuits against big powerful companies and sometimes they win.
Prussia/Germany was able to achieve growth at the frontier after 1848 and I think it's plausible China does the same. Basically, I think that both governments are acting something like monopolists would in a contestable market. From the outside it's looks uncompetitive and like the monopolist should be extracting big rents, but actually they're keeping prices low because they're shit scared that someone's going to come and take their place if they start trying to get monopoly profits.
Now, having said all that, the Chinese economy has some big structural problems that look like classic extractive institutions problems. The two biggest to me at least look like the urban-rural divide and the massive about of infrastructure spending fueled by local government spending based land value prices. The Hukou system increases the cost of individuals moving from one administrative district to another by making it extremely difficult to access public services. This has created an underclass of poorly educated, low productivity migrants in the big cities who've left their children back home who go to low quality schools and just have the poor life chances associated by being raised not by one's parents. China then also has the classic authoritarian problem of being really good at producing loads of infrastructure and then producing way too much of it relative. The political economy reason behind this is in the China case is that big infrastructure projects offer opportunities for graft and make regional GDP numbers look good.
I really like that you separated out a cluster of related beliefs in the 'long-term' and 'short-term' camps. I don't think the book 'Why Nations Fail' is that exciting, but I am happy to see someone trying to more concretely define the clusters of beliefs under 'long-term' and 'short-term'. It also explains why EAs who focus on climate change from a global poverty perspective are often called 'short-termist'.
For distinguishing short-termist from long-termist, I think risk aversion is a key factor. Long-termists are risk-neutral, and are happy to roll the dice in hits-based giving, whereas short-termists are risk-averse, and want a higher certainty of doing good. (And overall, individuals should not identify as one or the other, because the overall portfolio is going to have a mix of both.)
Some points on China:
The way I think about the current slowdown is the same as the Soviet case: they got easy catch-up growth based on investment, but now they're hitting diminishing returns. To maintain growth, they have to switch to innovation, but that requires inclusive political institutions (to protect creative destruction). Also, China and Soviet Russia seem to be in the same boat re: counterexamples to AR's theory, because both achieved catch-up growth under extractive political institutions.
I wouldn't describe China's economic institutions as inclusive. They have a weird system of cronyism, where formal institutions are low quality, so firms use political connections to get stuff done (see this).
I'll note that OpenPhil is hiring researchers to "focus on causes in policy, scientific research, and global development". Hopefully their page on development won't be empty for much longer!
I really applaud this! Longtermism seems to me a compelling idea across cause areas. I've thought about what it means in the context of animal advocacy, and I think there too it would recommend a shift of focus. I'm glad to see someone bring this up in the context of poverty. I've seen many people over the years support development after hearing arguments for longtermism because of vague long-term flow-through effects, and actually researching long-term poverty alleviation is important if we want to actually support it.
What's the shift you think it would imply in animal advocacy?
As I've been doing research this summer, I've become a bit more tentative and wary of acting like we know much, but my general intuition is that (a) our focus should not be on saving animals now but on securing whatever changes save future animals, so ethical changes and institutional changes; (b) I think institutional changes are the most promising avenue for this, and the question is which institutional changes last longest; (c) we should look for path dependencies.
It's unclear to me what advocacy changes this means, but I think it makes the case for, e.g., the Nonhuman Rights Project or circus bans stronger than they are in the short term. I think this is a crucial area of research though.
For path dependencies, the biggest one right now I think is whether clean and plant-based meat succeed. The shift from longtermism here I think is that rather than trying to get products to market the fastest, we should ask what in general makes industries most likely to succeed or fail and just optimize for the probability of success. As an example, this makes me inclined to favor clean meat companies supporting regulations and transparency.
One way of thinking about this from a recent Open Phil blog post:
I agree with the thesis that EA focused on global poverty on average has neglected research and advocacy on pro-development institutions relative to their importance and cost.
Reminds me of how revolutionaries think they're really sticking it to the elites when they protest against free markets. But elites hate free markets, they try to insulate themselves from them as much as possible. Why would you want competition from up and coming new elites? That's why elites fund the useful idiots who think they are revolutionaries.
There's also a weird thing where newly minted elites don't think of themselves as elites and so don't engage with the possibility of moving major equilibria even though they are potentially large enough to do so, and doing so can be much more powerful than tuning efficiencies in existing equilibria. Probably fears related to consequentialist cluelessness as well.
"What if you share short-termists’ skepticism of weird claims and hypothetical risks, but you’re willing to focus on first-principles reasoning and work on a long time scale?" - then you'd probably focus on nuclear which isn't at all hypothetical
Just for fun: https://twitter.com/AgiaTheBun/status/1220664590859718656 (a)
This post was awarded an EA Forum Prize; see the prize announcement for more details.
My notes on what I liked about the post, from the announcement:
This is a great book explaining why England industrialized first and why institutions matter. However subsequent transitions from agricultural economies to industrial does not need to follow same paths. They can get the benefits by copying all the knowledge of industrialization and improve well being (without becoming rich)
I am not convinced that USSR collapse was inevitable or that China will collapse. China seems to have deeply studied USSR collapse and tries to its lessons. Will it succeed? Not sure.
Being productive in the industrial age means using energy and know how to churn out products for world or local markets.
Agricultural economies on the other hand were always extractive and poor, because they relied on dilute power from sun. And education was of not much help in those societies.
Not discussing energy or education is a problem of the book.
I can see how an extractive economy lowers the cost of labor. High labor costs and excess capital are the prerequisites for investing in labor saving technology.
It is not difficult for a bad government to copy existing technology that is more efficient. I believe the key difference between Africa and Asia is the green revolution of the 60s and 70s. The arguments are outlined here:
As China increased their yields they were able to move labor from subsistence farming into industrial production. Eventually the same revolution will happen in Africa. Inclusive economies are necessary for continued innovation. Applying several hundred years worth of productivity gains into a few decades may even given the illusion that fantastic economic growth is possible without inclusion. We will see if Africa becomes more inclusive as their productivity and growth begin to accelerate. I also feel personally attacked by the spot on long termist description.