HaukeHillebrandt

Co-Founder of Lets-Fund.org

HaukeHillebrandt's Comments

Are there good EA projects for helping with COVID-19?

Found this paper: "Optimizing respiratory management in resource-limited settings"
"Mechanical ventilation is an expensive intervention associated with considerable mortality and a high rate of iatrogenic complications in many LMICs. Recent case series report crude mortality rates for ventilated patients of between 36 and 72%. Measures to avert the need for invasive mechanical ventilation in LMICs are showing promise: bubble continuous positive airway pressure has been demonstrated to decrease mortality in children with acute respiratory failure and trials suggest that noninvasive ventilation can be conducted safely in settings where resources are low." ... "One of the most significant developments in acute care research in LMICs in recent years has been the publication of three trials demonstrating that continuous positive airway pressure (CPAP) can reduce mortality in children under 5 years of age, compared with oxygen delivered via standard low-flow nasal cannula [35▪,36,37▪]. CPAP can also decrease the need for invasive mechanical ventilation [38▪▪]. There are three main ways to generate CPAP: first, by using a pressure driver or a ventilator; second, using high flow nasal-cannula oxygen therapy (HFNC); or third, by submerging the expiratory limb of a breathing circuit in water to create so-called bubble CPAP. Traditionally bubble CPAP circuits also contain a driver, although some newer iterations only use the oxygen/air flow from an oxygen concentrator to generate CPAP [39].

All three trials used bubble CPAP as the intervention and together showed a risk ratio of survival of 0.58 [95% confidence interval (CI) 0.41–0.82] [38▪▪]. One study had an additional intervention arm using HFNC, but no conclusions were drawn regarding its efficacy as the study was terminated early due to increased mortality in the control group.

Nasal cannulae, used as the patient interface in all three trials, are an attractive option for understaffed environments because they generally require lower levels of nursing supervision to use safely [39]. The basic circuits and simplified care protocols meant that the equipment required few adjustments, especially when compared with invasive mechanical ventilation.

There are elements of each of these studies that epitomize context-appropriate innovation and research. The bubble CPAP circuit deployed in the Bangladesh study was fashioned out of readily available, cheap equipment (standard nasal cannula, a shampoo bottle and intravenous fluid tubing) so the cost of the circuit was approximately $3 per patient [35▪]. They used an oxygen concentrator and no driver in the circuit with additional cost savings." https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319564/

here’s a build diagram for a bubble cpap

https://www.edjones.org/articles/bubble-cpap-in-resource-poor-settings/?fbclid=IwAR05oxQ2tPg1LDD6o73cBWOGKukaYBq8APcFpNmB1y900nPovTwV0yFBWBQ

are studies indicating it’s helpful for adults (despite its primary use in infants)

https://intjem.biomedcentral.com/articles/10.1186/s12245-019-0224-0

Growth and the case against randomista development

Yes, I list a couple more quotes from this article, but also many quotes from their Duflo and Banerjee's book in the Appendix. I think these quotes really get to the crux of the disagreement between growth and randomista development.

From their Foreign affairs article:

“There are many ways to improve allocation, from the moves away from collectivized agriculture that China made under Deng to the efforts India made in the 1990s to speed the resolution of debt disputes and thus make credit markets more efficient. But the flip side to this is that at a certain point, the gains start to diminish. Many developing economies are now reaching this point.”
“Quality of life means more than just consumption. Although better lives are indeed partly about being able to consume more, most human beings, even the very poor, care about more than that. They want to feel worthy and respected, keep their parents healthy, educate their children, have their voices heard, and follow their dreams. A higher GDP may help the poor achieve many of those things, but it is only one way of doing so, and it is not always the best one.”

Quotes from Duflo and Banerjee

From “Good Economics for Hard Times”

“How would anyone know whether pre-1991 growth would have continued had there been no crisis and the trade barriers not been brought down in 1991? To complicate matters, trade was being liberalized gradually starting in the 1980s; 1991 just sped that up (a lot). Was the big bang necessary? We will never know unless we are allowed to rewind history and let it go down the other path. Unsurprisingly, however, economists find it very hard to let go of this sort of question.”
CHASING THE GROWTH MIRAGE
“Unfortunately, just as we don’t know much about how to make growth happen, we know very little about why some countries get stuck but others don’t—why South Korea kept growing but Mexico did not—or how one gets out."
“Perhaps the reason why some countries, like China, can grow so fast for so long is that they start with a lot of poorly used talent and resources that can then be harnessed”
“Solow’s was what economists call an exogenous growth model, where the word “exogenous,” meaning driven by outside effects or forces, acknowledges our inability to do anything about the long-run growth rate. Growth, in short, is beyond our control.”
“The growth tide does raise all boats, but it doesn’t lift all boats to the same level—many economists worry that there may be such a thing as the middle-income trap, an intermediate-level GDP where countries get stuck or nearly stuck. According to the World Bank, of 101 middle-income economies in 1960, only 13 had become high income by 2008.122 Malaysia, Thailand, Egypt, Mexico, and Peru all seem to have trouble moving up. “
“In Indian manufacturing there was a sharp acceleration in technology upgrading at the plant level, and some reallocation toward the best firms within each industry after 2002. This appears to be unrelated to any economic policy, and is described as “India’s mysterious manufacturing miracle.”121 But it is no miracle. At its root, it is a modest improvement from a dismal starting point, and one can imagine various reasons it happened. Perhaps a generational shift, as control passed from the parents to their children, often educated abroad, more ambitious, and savvier about technology and world markets. Or the effect of the accumulation of modest profits that eventually made it possible to pay for the shift to bigger and better plants.”
“One very real danger is that in trying to hold on to fast growth, India (and other countries facing sharply slowing growth) will veer toward policies that hurt the poor now in the name of future growth. The need to be “business friendly” to preserve growth may be interpreted, as it was in the US and UK in the Reagan-Thatcher era, as open season for all kinds of anti-poor, pro-rich policies (such as bailouts for over indebted corporations and wealthy individuals) that enrich the top earners at the cost of everyone else, and do nothing for growth. If the US and UK experience is any guide, asking the poor to tighten their belts, in the hope that giveaways to the rich will eventually trickle down, does nothing for growth and even less for the poor. If anything, the explosion of inequality in an economy no longer growing has the risk of being very bad news for growth, because the political backlash leads to the election of populist leaders touting miracle solutions that rarely work and often lead to Venezuela-style disasters. Interestingly, even the IMF, so long the bastion of growth-first orthodoxy, now recognizes that sacrificing the poor to promote growth was bad policy. It now requires its country teams to include inequality in factors to take into consideration when providing policy guidance to countries and outlining conditions under which they can receive IMF assistance.123
“The bottom line is that despite the best efforts of generations of economists, the deep mechanisms of persistent economic growth remain elusive. No one knows if growth will pick up again in rich countries, or what to do to make it more likely. The good news is that we do have things to do in the meantime; there is a lot that both poor and rich countries could do to get rid of the most egregious sources of waste in their economies. While these things may not propel countries to permanently faster growth, they could dramatically improve the welfare of their citizens. Moreover, while we do not know when the growth locomotive will start, if and when it does, the poor will be more likely to hop onto that train if they are in decent health, can read and write, and can think beyond their immediate circumstances. It may not be an accident that many of the winners of globalization were ex-communist countries that had invested heavily in the human capital of their populations in the communist years (China, Vietnam) or countries threatened with communism that had pursued similar policies for that reason (Taiwan, South Korea). The best bet, therefore, for a country like India is to attempt to do things that can make the quality of life better for its citizens with the resources it already has: improving education, health, and the functioning of the courts and the banks, and building better infrastructure (better roads and more livable cities, for example).”
On climate: “Mitigation through better technologies may not do the trick; people’s consumption will need to fall. We may have to be content not only with cleaner cars but also with smaller cars, or no cars at all.”
Growth and the case against randomista development

Excellent comment - strongly upvoted for engaging with the data.

how did you calculate the median figure for Vietnam that you reference in section 4 ($6,914 GDP per capita)?

The sheet where we calculated the median growth episode within the spreadsheet is here:

https://docs.google.com/spreadsheets/d/1VcQ2r5zuCztd1_2vRscK8UOEAiQqhvvhkJVfagCzpqQ/edit#gid=1331750623&range=D26

Source: Pritchett, Labor p23

Vietnam was just the median of these selected growth episodes- because Pritchett in his example uses quite a big growth episode. Pritchett calculates the NPV gain from growth acceleration per person from this median case as $6,914. This is for illustrative purposes, picking Vietnam has no special significance here. "To be affected by a think tank" also has no special significance, we didn't check whether this growth episode was likely affected by a think tank.

These are selected by Pritchett:

"These are a list selected the largest episodes of growth acceleration. Source: Selected episodes. Author’s estimates from estimates in Pritchett, Sen, Kar, and Raihan 2016"

so... re your question:

When I look at the those figures in Appendix A, though, it seems like the median growth episode calculated using PRM (without reference to dollar size) is somewhere around Ecuador's negative growth in 1978, which doesn't seem like it would line up even with the conversion to $PPP.

Yes, this is likely largely due to Vietnam having a roughly ~10x higher population and being 10x poorer back then.

I think it is okay to use, as Pritchett does, these selected growth episodes, because if one wants to maximize effectiveness using policy one can strategically only look at big poor countries. One could further look at only those countries where growth is sluggish and perhaps where economic policy is particularly bad.

I write about this in the appendix:

Because effective altruism often tries to focus on the poorest countries, where a dollar goes 100x further than in rich countries, there is perhaps most hope for growth diagnostics.
So perhaps Duflo is right in that “Growth is likely to slow, at least in China and India, and there may be very little that anyone can do about it.” And this is actually born out in China’s and India’s performance on the World Bank’s Doing Business indicators, where they score 63th and 31st out of 189 countries, though being relatively poor. Thus, there seem no low hanging fruit to improve their economic policy.
However, below I show a table where I multiply population size of every country by their poverty multiplier (i.e. $1 is worth x times more going to this country than to the richest country in the sample. See appendix 2 of this doc for more info). This can then be ordered by the utility created by increasing GDP per capita by $1. India comes out on top because of its large population (1.3bn) and relatively low GDP per capita ($6,574). China comes 3rd, because though it has a large population, it is already relatively rich ($15,531). Recall that the problem is that we might not know how to increase growth in India and China.
However, there are many smaller very poor countries in the top 10 sample such as DRC and Ethiopia - very poor countries with 100 million population. This can then also multiplied further by neglectedness/tractability criteria. For instance, in a country’s ranking on the WB Doing Business ranking divided by GDP. There one can see that, relative to its GDP per capita, China already does quite well on the Doing Business ranking. However, the DRC and Ethiopia do poorly on the doing business ranking, even relative to their GDP. These countries could be most cost-effective for economic policy assistance.
Growth and the case against randomista development

I think this view would probably be endorsed by many prominent development economists. But I concede that there are also development economists who believe that health and education is very important.

When I first read about Rodrik's theory of development, I updated in the direction that health and education are not that important for growth at least for very poor countries, even though it's quite unintuitive.

From the appendix doc:

Historically, almost all non-poor countries have grown their economies in three steps:
Rural to urban migration: Unskilled (subsistence) farmers migrate to cities and start working in factories. Over night, this increases their productivity many times over.
Manufacturing absorbs vast amounts of unskilled labor: These workers need very little human capital: they do not need to be educated because work in factories is very simple. Population health does not prevent growth either, because there are enough to replace sick workers.
Manufacturing exports niche products to the world market: The factories find their niche product (e.g. initially often garments) and export to the world market, which can absorb large amounts of the same good (e.g. billions of shoes)

Again quoting Weil's review of "Health and growth" (emphasis mine):

As is often the case in economics, the observation that income and health are correlated, is only the beginning of the discussion. Such a correlation can be induced by causation running in either direction, as well as by the effects of some third factor. A priori, there are good reasons to think that all of these are possibilities. People who are healthier can work harder and learn more in school; and where people live longer they will be incentivized to invest more in education.Thus, we would expect better health to cause economic growth. On the other hand, higher income allows individuals or governments to make investments that yield better health. Finally, differences in the quality of institutions (looking across countries), in human capital (looking across individuals), or in the level of technology (looking over time) can induce correlated movements in health and income."

re: Nunn: I'm not ruling out that invariant geographical factors influence economic development by way of health. But it's a different question on whether we can do anything about that by ramping up health spending and ameliorate these differences and whether that's important for growth.

Growth and the case against randomista development

In my opinion, randomistas do not focus on growth at all, be it level effects or growth effects.

Though to be fair there's this short passage in Duflo's new book on this:

while we do not know when the growth locomotive will start, if and when it does, the poor will be more likely to hop onto that train if they are in decent health, can read and write, and can think beyond their immediate circumstances. It may not be an accident that many of the winners of globalization were ex-communist countries that had invested heavily in the human capital of their populations in the communist years (China, Vietnam) or countries threatened with communism that had pursued similar policies for that reason (Taiwan, South Korea).

Also we do say that "we do not think that the things assessed by RD do not increase economic growth at all: indeed some RD health interventions increase earnings and consumption later in life, and thus do increase growth to an extent. However, evaluating whether the effect size is trivial or not should be a top priority for proponents of RD."

Growth and the case against randomista development

Yes, interesting take.

Aside from risk aversion, in the appendix, I list some more cognitive biases that might be at play for why people prefer RCTs.

Relatedly, perhaps people sympathetic to long-termism might believe that speeding up growth might speed up GCRs from emerging technologies. And while it is unclear when growth will speed up x-risk at all (see for instance), I think that when it comes to differential technological development, not all growth is equal.

What speeds up risks from emerging technologies is mostly growth in highly technical sectors in high-income countries. Growth in low-income countries will not increase world growth much and is less likely to cause risks from emerging technologies.

Put simply: Burundi’s catch-up growth won’t speed up global growth by much, is unlikely to speed up risks from AI or bio any time soon. Growth has been argued to lead to “Greater opportunity, tolerance of diversity, social mobility, commitment to fairness, and dedication to democracy.” Perhaps growth in poor countries will actually increase stability and thus be good from a differential technological development point.

Lower skilled labor also competes with AI R&D and so increasing trade and migration decrease AI R&D (see “Why Are [Silicon Valley] Geniuses Destroying Jobs in Uganda?”.

But even if growth in poor countries will slightly increase x-risks, then it might still be optimal to support it and offset the x-risk increase through targeted interventions to decrease x-risks. This is because multiobjective optimization for both x-risk reduction and global poverty is likely harder than single objective optimization for the most effective interventions in each category separately.

Growth and the case against randomista development

The paper we cited is a comprehensive recent meta-analysis on the topic of health and growth that synthesizes the literature on this topic.

The paper concludes:

“If improving health leads to growth, this would be a reason, beyond the welfare gain from better health itself, that governments might want to make such investments. However, the evidence for such an effect of health on growth is relatively weak. Cross-country empirical analyses that find large effects for this causal channel tend to have serious identification problems. The few studies that use better identification find small or even negative effects. Theoretical and empirical analyses of the individual causal channels by which health should raise growth find positive effects, but again these tend to be fairly small. Putting the different channels together into a simulation model shows that potential growth effects of better health are only modest, and arrive with a significant delay.”

We did however acknowledge that this claim is controversial:

Moreover, and more controversially, we do not believe that health interventions (whether directly funded or implemented by the state) are the best way to increase growth in the poorest countries.[15] Here, we want to start a discussion on what the most effective causes of growth are, given its huge importance.

This is a topic of ongoing debate in the literature - future research could look into this topic more and a starting point could be the citation trail from the study above.

Growth and the case against randomista development

Thanks (strongly upvoted for trying to falsify a central claim). All opinions are mine.

1. While the interesting paper you cite shows that policies bad for growth are at historic lows and argues that much progress has been made, 20% of all countries still have bad policies, and 25% of SSA countries. Given the potential very high effectiveness of growth policy, that we tried to demonstrate in the piece, the value of information of looking into this further is high.

2. I do cite Rodrik in the Appendix who argues that these days, “standard prescriptions” (i.e. Washington Consensus) might not work any longer and we should be skeptical of top-down, comprehensive, universal solutions (though perhaps there are some more generalizable policy prescriptions to be discovered with further research - Rodrik for instance expands the Washington consensus with an additional 10 policy prescriptions).

However, technical assistance by more specialized agencies (e.g. DFID, USAID, GIZ as well as the World Bank’s country offices), and also NGOs such as the International Growth Center, the Copenhagen Consensus, etc. might be able to do “growth diagnostics” to find out where growth is bottlenecked and then help with tailor-made policies on a country-by-country basis.

They might also help with implementation issues, and even indifference issues.

Growth and the case against randomista development
I'm not sure the 'extreme scepticism' (perhaps we could just call it scepticism?) argument is given a fair shake. Note that answering the question of what causes a country to grow is basically the big question of development economics, and as such it has received considerable attention from economists. In the Duflo and Banarjee piece, they argue that economists did find good low hanging fruit, notably misallocation of resources, but they argue this is reaching a point of diminishing returns. Economists are now struggling to find great opportunities in growth economics, and so there is a good case for looking at different approaches to development. This argument feels plausible to me, and it means you do not have to make the apparently crazy claim that economists never had significant influence on past effective growth policies.

Yes, I steelman this view in the Appendix (my view not necessarily John's):

"Growth is not as neglected as RD, its low-hanging fruit have been picked, and the marginal dollar is not as effective"
“The evidence that macroeconomic policies, price distortions, financial policies, and trade openness have predictable, robust, and systematic effects on national growth rates is quite weak—except possibly in the extremes. Humongous fiscal deficits or autarkic trade policies can stifle economic growth, but moderate amounts of each are associated with widely varying economic outcomes.”
For instance, take the debate over trade liberalization. Recall that there was exceptionally weak global trade growth over recent years. Relatedly to the previous point, some argue that the “low-hanging fruit” of economic liberalization has already been picked. For instance, Weyl argues that in “Radical markets”:
“There is a consensus that the economic gains from further opening international trade in goods is minimal. Studies by the World Bank and prominent trade economists find that eliminating all remaining barriers to international trade in goods would increase global output by only a small amount, 0.3–4.1%. For global investment, the most optimistic estimate in the literature finds a 1.7% increase in global income from the elimination of barriers to capital mobility. Many believe that liberalization of international capital markets has gone too far. Three top IMF economists recently argued that even liberalization that has already taken place has brought limited gains to economies while generating inequality and instability.”

However, there is a debate about this and counterarguments:

Others argue that trade policy is still very relevant. Complete rich-country liberalization would, after a 15- year adjustment, increase income in developing countries by $100 billion per year, which is approximately twice current aid flows.
Also, guarding against protectionism and not losing the growth from trade might be very important: one study suggest that an “increase in tariffs to average bound rates of 44.7 percent in highly protectionist countries such as India, Bangladesh, Pakistan and Sri Lanka would translate into a decline in real income in South Asia by 4.2 percent or welfare losses of close to US$125 billion relative to the baseline by 2020”.

Pritchett too seems much more optimistic about growth diagnostics and believes that while we might not know everything, we generally have a reasonable understanding of what causes growth and can even influence it.

Pritchett has edited a whole volume on growth diagnostics, including on the causes of growth in India.

Generally, my take is that growth diagnostics might get harder the richer a country becomes, by virtue of there being less and less data from other countries on how they developed. Thus, for the poorest countries, growth diagnostics might be easiest because we can draw lessons from all other countries on they developed.

Because effective altruism often tries to focus on the poorest countries, where a dollar goes 100x further than in rich countries, there is perhaps most hope for growth diagnostics.

So perhaps Duflo is right in that “Growth is likely to slow, at least in China and India, and there may be very little that anyone can do about it.” And this is actually born out in China’s and India’s performance on the World Bank’s Doing Business indicators, where they score 63th and 31st out of 189 countries, though being relatively poor. Thus, there seem no low hanging fruit to improve their economic policy.

But in the Appendix I have an analysis where I multiply population size of every country by their poverty multiplier (i.e. $1 is worth x times more going to this country than to the richest country in the sample. See appendix 2 of this doc for more info). This can then be ordered by the utility created by increasing GDP per capita by $1. India comes out on top because of its large population (1.3bn) and relatively low GDP per capita ($6,574). China comes 3rd, because though it has a large population, it is already relatively rich ($15,531). Recall that the problem is that we might not know how to increase growth in India and China.

However, there are many very poor countries in the top 10 sample such as DRC, Bangladesh and Ethiopia - very poor countries with +100 million population. This can then also multiplied further by neglectedness/tractability criteria. For instance, in a country’s ranking on the WB Doing Business ranking divided by GDP. There one can see that, relative to its GDP per capita, China already does quite well on the Doing Business ranking. However, the DRC and Ethiopia do poorly on the doing business ranking, even relative to their GDP. These countries could be most cost-effective for economic policy assistance.

The Copenhagen Consensus Center is actually doing something along the lines of assisting countries / highlighting the need to improve their economic policies. For instance they are helping Bangladesh to improve its economy and prioritize which policies would have the highest social, economic and environmental benefits for every dollar spent. On top of their list is e-procurement across government and land records digitization - related to criteria used to rank countries on the WB Doing Business index.

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