I also think asking people questions about why they hold a view you think is wrong that suggestively indicate why you think it’s wrong can be a good approach (e.g. “But don’t you think...?”).
HStencil
Karma: 501
I don’t think my reasoning falls neatly into any one of the categories you listed, so I’ll post it as its own comment. I don’t give to “multiplier” charities mainly because I think a huge percentage of the good that they do probably comes from running great websites, but the fixed costs that were necessary to get these websites built and online have already been paid, basically, and while I believe that initial investment probably had a large multiplier, I’m far less convinced that subsequent expenditures by these organizations (other than maintaining their websites) will have such a large multiplier (and big donors would happily step in—or the multiplier charities would tell us—if maintenance costs could not be met).
Furthermore, in the exceptional cases when subsequent expenditures would likely have large multipliers, my sense is that usually, those expenditures require atypically substantial amounts of funding, without which the investments in question cannot happen. I am not a large donor, and it just isn’t clear to me that if I give a few thousand dollars to a multiplier charity instead of to, say, the GiveWell Maximum Impact Fund, that few thousand dollars will enable anything particularly high-impact to occur that otherwise wouldn’t have. By my mental model—which may be mistaken—for each additional dollar I give to GiveWell’s Maximum Impact Fund, my impact rises by some smooth function that probably isn’t far off linear. In contrast, I think that the value of additional dollars given to a multiplier charity probably follows some kind of a step function. I understand that my donations might increase the probability of the multiplier organization being able to “go up a step” sooner, but I suspect that if the step were truly likely to have an extraordinarily high charitable return, large donors, like foundations or ultra-high net worth individuals, would fund it no matter what, and the fact that I’d chipped in a few thousand on the margin wouldn’t change their calculus on that one bit. I’m just not the limiting factor here.
Finally, multiplier charities seem like sort of obvious breeding grounds for conflicts of interest in the community, and I’m quite wary about that because 1) I think the community has had a poor track record on managing conflicts of interest historically (though this has unquestionably improved), and 2) there is effectively no oversight of multiplier charities. They don’t have to go through anywhere close to the level of scrutiny or provide nearly as much transparency as GiveWell’s top charities, so I’m much more reluctant to take many of their claims to impact at face value.
Ultimately, I feel that my giving to multiplier charities would be troublingly analogous to the fact that around a quarter of foreign aid by OECD countries never leaves the donor country because it gets spent on consultants, auditors, and evaluators domestically. There is obviously a plausible case that the consulting, auditing, and evaluation in question increases the value of the foreign aid so much that it pays for itself, but doesn’t it seem more likely that these firms get retained for bad reasons (they lobby governments, have friends in high places, employ voters, tell unrepresentative horror stories about the misuse of aid, etc.) than for good reasons? I don’t mean to implicate multiplier charities in an unsavory comparison… but for the fact that the unsavory comparison is actually a meaningful reason why I don’t give to them. I just have no idea how I could tell with confidence that the way they would use my marginal dollars would actually beat other opportunities.
- What are the most common objections to “multiplier” organizations that raise funds for other effective charities? by (Dec 8, 2020, 2:10 PM; 33 points)
- 's comment on What are the most common objections to “multiplier” organizations that raise funds for other effective charities? by (Mar 9, 2021, 7:23 PM; 3 points)
This puts to words so many intuitions that have crept up on me—not necessarily so much about EA as about job-hunting as a young generalist with broadly altruistic goals—over the last few years. Like you, earlier this year, I transitioned from a research role I didn’t find fulfilling into a new position that I have greatly enjoyed after a multi-year search for a more impactful and rewarding job. During my search, I also made it fairly deep in the application process for research roles at GiveWell and Open Phil and got a lot of positive feedback but was ultimately unable to land either those positions or any others in EA (this is not a criticism of those hiring teams — they were absolutely wonderful every step of the way). Anyway, it’s great to hear from others who have had similar experiences, and it’s wonderful that you’re doing so well now. I think this post is fantastic, and I plan to send it to a number of undergrads I know who are about to start out their careers. Thank you so much for sharing it!
It’s not clear to me how one can believe 1) that there is nothing that ultimately explains what makes a person’s life go well for them, and 2) that we have an overriding moral reason to alleviate suffering. It would seem dangerously close to believing that we have an overriding moral reason to alleviate suffering in spite of the fact that it is not Bad for those who experience it. You might claim that suffering is instrumentally bad, that it makes it harder to achieve… whatever one wants to achieve, but presumably, if achieving whatever one wants to achieve is valuable, it is valuable because of the way in which it leads one’s life to “go well.” If that is the case, then you have a theory of well-being. If, on the other hand, achieving whatever one wants to achieve is not valuable in any absolute sense, then it is hard to say why it would be valuable at all, and you, again, would struggle to justify why suffering is a bad.
They explain why they offer offset recommendations (even though, like Founders Pledge, they believe CATF is likely more cost-effective) at some length in their launch post: https://forum.effectivealtruism.org/posts/xfN7AwkjYBpEbbz6x/re-launching-giving-green-an-ea-run-organization-directing
A variety of different organizations have attempted projects like this in the past and have struggled to generate interest in participating among political candidates. For the most well-known, see: https://ballotpedia.org/Survey.
Looks like BlockPower is holding a hackathon tomorrow to help build out the platform they’re using for their GOTV efforts in the Georgia runoffs, if anyone’s interested!
When I was last on the job market, I spent a bunch of my free time trying to come up with well-justified cost-effectiveness estimates for a wide array of different interventions across several cause areas. I think something like this technically meets your three criteria, but I suspect it isn’t quite consistent with the spirit of what you’re looking for (i.e. projects that take longer than a week to do and will actually probably have some positive impact). Even though I don’t think my CEAs did anything at all to improve the world themselves, I’d still recommend this to early-career EAs, if only because I thought it was a huge help when applying for jobs at GiveWell and Open Phil (which, for the sake of full disclosure, I was not ultimately offered, though I made it fairly far in the process). Even for people who have no interest in working somewhere like GiveWell or Open Phil, I think doing this trains a lot of important skills: conducting literature reviews, thinking about counterfactuals and measuring counterfactual impact, thinking in terms of DALYs or QALYs, some math… etc., and it just isn’t that much of a commitment, either. I probably spent a few hours a day, most days, for up to week on each estimate, but you could spend more or less as you saw fit. It has an appealing kind of flexibility. Finally, it’s highly scalable — there’s no shortage of things to estimate the cost-effectiveness of, so there’s no reason why tons of people couldn’t all reap the human capital and intellectual benefits of doing this. In the aggregate, I think that itself could have a pretty positive impact, and if someone were to find strong evidence that some previously overlooked intervention was actually competitive with, say, the AMF, that would be a pretty great thing for the EA community to know!
Thanks so much—really appreciate your taking the time to look into this stuff!
I’m curious whether Landslide Coalition has given any thought to how one could most effectively make an impact on the Georgia Senate run-offs. Obviously, the stakes are much lower now that Trump has lost the presidency, but I think there’s still a reasonable case to be made that helping Democrats win Senate control at this moment in history is hugely important from an EA perspective. For those who think that’s a priority, I assume deep canvassing through People’s Action remains among the best volunteer opportunities available, but do you know whether they could productively use additional funding right now? Or could Working America, if they’re at all involved in the Georgia races? Are there any voter registration nonprofits that are running especially cost-effective programs? I’m sure someone must be focused on registering the ~23,000 teenagers who will become eligible to vote in Georgia between the 2020 general registration deadline and the Janury run-off registration deadline.… But I assume the campaigns themselves are (or will soon be) absolutely flush with cash and probably are not the most impactful groups to fund on the margin. Any thoughts?
I’d also add the International Consortium of Investigative Journalists. They do fantastic work in a similar vein.
The levers of corporate governance are pretty limited. The corporate form is designed to limit the extent to which minority owners of common stock can intervene in corporate operations. As a result, most proxy proposals of social concern pertain to public disclosures (e.g. of environmental impact, of lobbying expenditures, of pay equity data, etc.) or to the appointment of sympathetic board members/removal of unsympathetic board members. These are nowhere near a majority of total proxy proposals, but they’re a sizable percentage of total shareholder proposals (most of which do not pass). For more detail on this, see this comment.
Ah, sorry, I must have misread your original question. Here are my top-level takes on the question you did, in fact, ask:
1) I see some of these Calvert funds have done well over the past few years, but I’m sufficiently convinced by some form of the efficient markets hypothesis to be skeptical that their above-market returns will continue to exceed their fees over the medium-to-long-term.
2) While I do think that shareholder activism through the proxy process can occasionally yield important, positive changes in the corporate world, the levers of corporate governance are limited enough that I very seriously doubt that the money you’re spending on Calvert’s fees is doing more good maintaining your investments in those funds than it would do if it were donated to, say, Malaria Consortium’s SMC program.
3) It’s important to remember the actual comparative here. It’s not Calvert vs. an evil money manager; it’s probably Calvert vs. BlackRock, which has been loudly pushing its portfolio companies to be more conscientious about their impact on the climate. Of course, on account of its scale, BlackRock’s mutual fund and ETF offerings will be much, much cheaper than comparable funds offered by Calvert, and also on account of its scale, BlackRock controls a far larger number of shareholder votes than Calvert does. Ultimately, you have to ask yourself: How often do BlackRock and Calvert vote in different directions on issues that I think are genuinely high-impact (assuming Calvert always casts a socially optimal vote, which I also doubt)? And: How often are Calvert’s votes likely to decide those shareholder elections (when BlackRock is voting the other way)? And: How often are my Calvert fund shares likely to make the difference in whether Calvert decides those shareholder elections favorably? If you were to try to model that, I suspect you’d find that investing through Calvert isn’t much at all better for the world than investing through BlackRock, and to the extent that it has some extraordinarily modest advantage, it is likely inferior to the value of simply donating the fee money to a high-impact charity. Of course, if you think the Calvert funds will continue to beat the market over time, that would change the calculus, but like I said, I consider that unlikely.
I used to do some work in this space and may get around to writing a more in-depth response soon, but I’m pretty busy right now, so in case I don’t, two things:
1) Even if you think shareholder activist strategies have outperformed the market historically, the activism space has become substantially more competitive in the last 3-4 years or so, and it has begun to face growing regulatory pressures, so I generally expect that any activism-related arbitrage opportunity that may still exist will shrink over time until it is no larger than the cost of mounting an activism campaign.
2) See here for some pertinent background on the corporate governance ecosystem.
At least until quite recently, there was a fairly uniform consensus in mainstream Anglo-American economics that the convergence thesis was true. I think this was mainly because it was based on fundamental theoretical insights that were believed to be relatively unimpeachable, like the Solow Model and the Stolper-Samuelson Theorem.
The Solow Model uses a formal representation of the idea that capital can be put to better use (yielding a higher economic return) in places where it is more scarce to demonstrate that, all other things being equal, places further from a given steady-state output level will grow toward that level faster than places nearer to it. In other words, ceteris paribus, places where capital stock is lower will grow faster than places where capital stock is higher because adding a marginal unit of capital in a capital-poor economy will generate a greater return than adding a marginal unit of capital in a capital-rich economy, where all the high-yielding capital investment opportunities have already been funded. (Bear in mind, though, that “ceteris paribus” is doing a lot of work in that sentence. You might reasonably claim that the traditional Solow Model holds constant nearly everything we ought to care about in trying to explain development outcomes.) To the extent that it’s true, though, in a world with open cross-border capital flows, one would expect capital to flood from low-return investment opportunities in wealthier countries to high-return investment opportunities in poorer countries. Alas, the evidence that this is actually taking place on a large scale is mixed at best, and other factors excluded from the neoclassical theories of international trade and finance likely play a large role in determining the global allocation of capital.
The productivity term in the Solow Model also often comes up in discussions of convergence. This term, representing an economy’s efficiency at deploying its factors of production to make things, is frequently treated—for the purpose of simplification—as a representation of an economy’s level of technological advancement alone. Traditional growth economists tend to treat rates of technological advancement as largely exogenous (whether this assumption is realistic is the subject of considerable debate). However, separate models of global technological advancement are typically built around the idea that it’s cheaper to copy a technology that was developed in another country and put it to use in one’s domestic industries than it is to develop a wholly new technology from scratch, thereby advancing the technological frontier. As a result, economists often conclude that countries not yet at the technological frontier will enjoy faster productivity growth than counties that are at the technological frontier, in accordance with the convergence paradigm.
The Stolper-Samuelson Theorem shows that when a national economy specializes in the production of a good in which it has a comparative advantage and then the relative price of that good rises on global markets, the return on investment in the factor of production that most contributes to making that good will rise. For example, if a country has a comparative advantage in making blue jeans, and it specializes in making blue jeans, and labor is the most important factor of production in making blue jeans, if the relative price of blue jeans on globals markets rises, then the return on investment in labor in that country will rise. This is equivalent to saying that the marginal product of labor in that country will rise, and in a competitive labor market, the price of labor (the wage) should equal its marginal product, so producer wages should rise with, for instance, a relative increase in global demand for blue jeans (which would push up the price).
There is vigorous debate over the extent to which the Stolper-Samuelson Theorem is applicable to world in which we live today. It requires making a number of assumptions in order for its conclusion to hold (constant returns to scale, perfect competition, an equal number of factors and products). One famous counterexample to Stolper-Samuelson was proposed Raúl Prebisch and Hans Singer and was embraced by the anti-trade left of the postwar years. Prebisch and Singer propose that because complex manufactured goods (like computers) exhibit greater income elasticity of demand than simple commodities (like wheat or coffee), if a country specializes in exporting wheat (consistent with its comparative advantage), and relies on imports from foreign manufacturers to get computers, as global incomes rise, it will suffer declining terms of trade (i.e. as time passes, each imported computer will cost more and more wheat). Today, the Prebisch-Singer Hypothesis, as it’s called, has received some degree of very qualified acceptance by mainstream economists. Its fundamental proposal that it doesn’t always make sense to treat comparative advantages as destiny is quite widely accepted, though more on the basis of Paul Krugman’s work in New Trade Theory (demonstrating, e.g., that comparative advantages can arise from economies of scale in addition to from initial actor endowments) than on the basis of Prebisch and Singer’s work. However, the specifics of the hypothesis are regarded as an extremely special case, an exception to what is generally true of developing countries. There are two main reasons for this. The first is that many developing countries specialize in the extraction of metals and minerals that are necessary inputs in making complex manufactured goods, like copper and silicon. These commodities likely violate Prebisch-Singer’s assumption that simple commodity goods necessarily exhibit lower income elasticity of demand than complex manufactured goods. The second reason is that many of the complex manufactured goods that the poorest countries import from wealthier countries actually probably increase those countries’ productivity in producing basic commodities (consider, for instance, the way organizations like Precision Agriculture for Development deliver scientific agricultural guidance to farmers throughout South Asia and Subsaharan Africa via their cell phones).
I’m not sure to what extent this theoretical background will be helpful to you as you think about convergence, but regarding the facts on the ground, with very few exceptions (like Botswana), almost all of the progress toward convergence in the last four decades has taken place in East Asia. While the “Asian Miracle” is very much real, it may itself prove to be a special case, specific to the region or the historical period in which it took place. As premature deindustrialization begins to take its toll on those countries that are not yet rich, there are, I think, a number of serious concerns about the continued viability of the export-led growth models that lifted countries like South Korea and Japan out of poverty. While the theoretical insights on which those models were based are robust, it remains to be seen to what extent they continue to apply in our 21st-century economy. Similarly, the traditional convergence thesis assumes increasing liberalization of international trade and capital flows, a premise that has grown increasingly untenable over the last five years.
Thanks! I booked a slot on your Calendly—looking forward to speaking Thursday (assuming that still works)!
Thank you so much for putting so much thought into this and writing up all of that advice! Your uncertainties and hesitations about the stats itself are essentially the same as my own. Last night, I passed this around to a few people who know marginally more about stats than I do, and they suggested some further robustness checks that they thought would be appropriate. I spent a bunch of time today implementing those suggestions, identifying problems with my previous work, and re-doing that work differently. In the process, I think I significantly improved my understanding of the right (or at least good) way to approach this analysis. I did, however, end up with a quite different (and less straightforward) set of conclusions than I had yesterday. I’ve updated the GitHub repository to reflect the current state of the project, and I will likely update the shortform post in a few minutes, too. Now that I think the analysis is in much better shape (and, frankly, that you’ve encouraged me), I am more seriously entertaining the idea of trying to get in touch with someone who might be able to explore it further. I think it would be fun chat about this, so I’ll probably book a time on your Calendly soon. Thanks again for all your help!
Thanks so much! I’m thrilled to hear you liked it. To be honest, my main reservation about doing anything non-anonymous with it is that I’m acutely aware of the difficulty of doing statistical analysis well and, more importantly, of being able to tell when you haven’t done statistical analysis well. I worry that my intro-y, undergrad coursework in stats didn’t give me the tools necessary to be able to pick up on the ways in which this might be wrong. That’s part of why I thought posting it here as a shortform would be a good first step. In that spirit, if anyone sees anything here that looks wrong to them, please do let me know!
As someone who first encountered EA through Slate Star Codex, this is also my sense.
I’m not sure, but it seemed to me that this was the view that you were defending in your original comment. Based on this comment, I take it that this is not, in fact, your view. Could clarify which premise you reject, 1) or 2)?