HStencil

Karma: 501

HStencil Jun 29, 2020, 7:22 PM
1 point
0 ∶ 0
in reply to: Huwelium’s comment on: Million dollar donation: penny for your thoughts?
Thanks so much for looking into this and posting your read of the research! I’m glad I now have a clearer sense of how these two types of interventions compare to one another. The flaws you noted in TechnoServe’s internal evaluation are certainly quite concerning, and I’m glad someone brought them to my attention.

HStencil Jun 29, 2020, 6:46 PM
13 points
0 ∶ 0
on: HStencil’s Shortform
[UPDATED June 30, 10:00 pm EDT to reflect substantial improvements to the statistical approach and corresponding changes to the results]
I spent some time this weekend looking into the impact of COVID-19 on the 2020 U.S. presidential election, and I figured I might share some preliminary analysis here. I used data from The COVID Tracking Project and polling compiled by FiveThirtyEight to assemble a time series of Biden’s support head-to-head against Trump in 41 states (all those with adequate polling), along with corresponding COVID-19 data. I then implemented a collection of panel models in R evaluating the relationship between Biden’s performance against Trump in state polling and the severity of the pandemic in each state. My data, code, and regression output are on GitHub, and I’ve included some interpretive commentary below.
Interpretation of Results
When appropriately controlling for state-level fixed effects, time fixed effects, and heteroscedasticity, total COVID-19 cases and deaths are not significantly associated with support for Biden, nor are the number of ongoing COVID-19 hospitalizations (see Models A, B, and C in the 6.30 R script). However, controlling for state-level fixed effects, greater daily increases in cases and in deaths are significantly associated with higher support for Biden (see Models 2 and 3 in Table I above). Breusch-Pagan tests indicate that we must also control for heteroscedasticity in those models, and when we do so, the results remain significant (see Models 2 and 3 in Table II above), though only at a 90 percent confidence level.
These results do come with a caveat. While Lagrange FF multiplier tests indicate that there is no need to control for time fixed effects in Table I models 2 and 3, F-tests suggest the opposite conclusion. I lack the statistical acumen to know what to make of this, but it’s worth noting because when you control for both time fixed effects and heteroscedasticity, the results cease to be statistically significant, even at a 90 percent confidence level.
Interestingly, the state-level fixed effects identified by Table I models 2 and 3 are strikingly powerful predictors of support for Biden everwhere except for Arkansas, Florida, Georgia, North Carolina, Nevada, Ohio, and Texas, all of which (except for Arkansas) are currently considered general election toss-ups by RealClearPolitics. This makes sense — in a society as riven by political polarization as ours, you wouldn’t necessarily expect the impacts of the present pandemic to substantially shift political sympathies on the aggregate level in most states. The few exceptions where this seems more plausible would, of course, be swing states. In the case of Arkansas, the weak fixed effect identified by the models is likely attributable to the inadequacy of our data on the state.
A Hausman test indicates that when regressing the amount of COVID-19 tests performed in a state on the support for Biden there, a random effects model is more appropriate than a fixed effects model (because the state-level “fixed effects” identified are uncorrelated with the amount of tests performed in each state). Implementing this regression and controlling for heteroscedasticity yields the result featured under Model 1 in Table II above: statistically significant at a 99 percent confidence level.
This is striking, both for the significance of the relationship and for how counterintuitive the result of the Hausman test is. One would assume that the fixed effects identified by a model like this one would basically reflect a state’s preexisting, “fundamental” partisan bent, and my prior had been that the more liberal a state was, the more testing it was doing. If that were true, one would expect the Hausman test to favor a fixed effects model over a random effects model. However, it turns out that my prior wasn’t quite right. A simple OLS regression of states’ post-2016 Cook Partisan Voting Indexes on the amount of testing they had done as of June 26 (controlling for COVID-19 deaths as of that date and population) reveals no statistically significant relationship between leftist politics and tests performed (see Model 1 in Table III), and this result persists even when the controls for population and deaths are eliminated (see Model 2 in Table III).
This is odd. Hausman tests on Models A, B, and C in the 6.30 R script favor fixed effects models over random effects models, indicating that state-level fixed effects (i.e. each state’s underlying politics) are correlated with COVID-19 cases, hospitalizations, and deaths, but those same fixed effects are not correlated with COVID-19 tests. Moreover, when applying appropriate controls (e.g. for heteroscedasticity, time fixed effects, etc.), we find that while cases, hospitalizations, and deaths are not associated with support for Biden, testing is associated with support for Biden (basically the opposite of what I would have expected, under the circumstances). We can run a Breusch-Pagan Lagrange multiplier test on Table I’s Model 1 just to confirm for sure that a random effects model is appropriate (as opposed to an OLS regression), and it is. At that point, we are left with the question of what those random effects are that are associated with support for Biden but not with COVID-19 testing, as well as it’s corollary: Why aren’t the fixed effects in Models A, B, and C associated with testing (given that they are associated with cases, hospitalizations, and deaths)? Without the answers to these questions, it’s hard to know what to make of the robust association between total COVID-19 testing and support for Biden revealed by Table I’s Model 1.
The puzzling nature of the Table I, Model 1 results might incline some to dismiss the regression as somehow erroneous. I think jumping to that conclusion would be ill-advised. Among other things that speak in its favor, the random effects identified by the model, however mysterious, are remarkably consistent with common intuitions about partisanship at the state level, even more so, in fact, than the fixed effects identified by Models 2 and 3 in Table I. Unlike those fixed effects models, Model 1′s state-level random effects explain a considerable amount of Biden’s support in Georgia and Texas. I consider this a virtue of the model because Georgia and Texas have not been considered swing states in any other recent U.S. presidential elections. They are typically quite safe for the Republican candidate. Furthermore, Model 1 identifies particularly weak random effects in a few swing states not picked up by Models 2 and 3 — notably, Wisconsin, Pennsylvania, and Arizona. Wisconsin and Pennsylvania are genuine swing states: They went blue in 2008 and 2012 before going red in 2016. Arizona has been more consistently red over the last 20 years, but the signs of changing tides there are clear and abundant. Most notably, the state elected Kyrsten Sinema, an openly bisexual, female Democrat, to the Senate in 2018 to fill the seat vacated by Jeff Flake, who is none of those things.
It’s worth noting that there is an extent to which the above is really an oversimplification of “swinginess.” As FiveThirtyEight explains, state-level opinion elasticity is not the same as being a swing state. While how close a state’s elections are is determined by the proportion of Democrat relative to Republican voters in the state (with states closer to ⁵⁰⁄₅₀ obviously being “swingier” in this sense), the extent to which events out in the world lead to shifts in polling in a given state is determined largely by how many people in the state are uncommitted to a particular partisan camp. A state being full of such voters without strong partisan commitments might well express itself in close elections, but it also might not, and by the same token, another way a state might end up with close elections is by being 50 percent composed of die-hard, party-line Republicans and 50 percent composed of die-hard, party-line Democrats. We would not expect new developments in current events to particularly shift voter sentiment in such a state. As a result, FiveThirtyEight proposes the metric of state-level opinion elasticity—measured using the extent to which shifts in national polling correspond to shifts in state-level polling in each state—as an alternative concept of “swinginess” that is potentially more appropriate for analyses such as this one. This is important because FiveThirtyEight has found that a number of states where there are frequently close elections actually exhibit extremely low elasticity. The paradigm case of this is Georgia, which has an elasticity of 0.84 (meaning a one-point shift in national polling corresponds to a 0.84-point shift in Georgia polling).
On this basis, a better way of comparing the fixed effects identified by Table I models 2 and 3 with the random effects identified by Model 1 would be to compare the average elasticities (calculated by FiveThirtyEight) of the “swing states” identified by each model. In the case of Models 2 and 3, the average is an uninspiring 0.994, or weakly un-swing-y. In the case of Model 1, however, the average is 1.025: pretty swing-y. That’s what happens when you swap out Georgia (0.84) for Arizona (1.07) and Wisconsin (1.06).
I have one outstanding technical question about Table I, Model 1. When controlling for heteroscedasticity in R’s plm package, I understand that the “arellano” covariance estimator is generally preferred for data exhibiting both heteroscedasticity and serial correlation but is generally not preferred for random effects models (as opposed to fixed effects models). The “white” covariance estimators, on the other hand, are preferred for random effects models, though “white1” should not be used to control for heteroscedasticity in data that also exhibit serial correlation. A Breusch-Godfrey test indicates that Model 1 requires an estimator compatible with serial correlation, but it is of course a random effects model, not a fixed effects model. Would it be better to control for heteroscedasticity here with “white2“ or with “arellano?” Ultimately, it doesn’t matter much because both approaches yield a result that is statistically signicant at at least a 95 percent confidence level, but only the “white2” estimator is statistically significant at a 99 percent confidence level.

HStencil’s Quick takes

HStencilJun 29, 2020, 6:46 PM

3 points

7 comments EA link

HStencil Jun 27, 2020, 3:26 AM
9 points
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on: Dignity as alternative EA priority—request for feedback
I think the right kind of feedback here depends mainly on whether you mean to propose that EA underestimates the extent to which treating people with dignity improves their welfare or you mean to propose that EA fails to consider the importance of dignity as an intrinsically and independently valuable element of a life lived well. If dignity is only important on account of its instrumental role in improving welfare, I very much doubt that a thorough evaluation of that role would lead many EAs to conclude that they should redirect their charitable giving. Even if treating someone with dignity were associated with a truly striking increase in their welfare, it seems unlikely to me that, for instance, global health interventions with such an emphasis would outperform distributing insecticide-treated mosquito nets or deworming pills. Among other things, I imagine that most parents of young children would agree to an arbitrarily large amount of undignified treatment in exchange for preventing their child from dying of malaria (revealed preferences suggest this is true). This suggests that the AMF would outperform a hypothetical charity with a dignity focus even without accounting for the positive impact of saving children’s lives unless promoting dignity were extraordinarily cheap per person affected. Similarly, I doubt that integrating concern for the role dignity may play in determining welfare into longtermist perspectives would do much to shift people’s ideas about the best giving opportunities to safeguard the long-term future of humanity.
If on the other hand you take dignity to be valuable in itself (apart from any role it might have in bringing about another good, like improving welfare), I wonder whether the philosophical foundation for your view is really fully compatible with EA. From what I’ve read, it seems as if most of the philosophers who take treating people with respect to be a good in itself view dignity as the sort of thing that each of us has a reason to accord to others when we interact with them. They do not, however, by and large view dignity as the sort of thing that we have a reason to impartially maximize (i.e. while it’s very important for me to treat you with dignity, it’s nowhere near as important—and may not even be valuable at all—for me to counterfactually enable you to treat someone else with dignity). In their view, the obligation to treat others with dignity “spring[s] from an agent’s special relationship to his own actions” and “the claims of those with whom we interact to be treated by us in certain ways” (Korsgaard 1993, emphasis mine), not from the objective value of the world having more dignity in it (or anything like that). As a result, some (see, for example, Taurek 1977) go so far as to argue that it is not necessarily any better for more people to be treated well than for fewer. Following Korsgaard, we might think of the value of treating people with dignity as similar to the value of keeping promises — while I have reason to keep my own promises, I likely do not have reason to promote a world in which more promises are kept. Doing so would suggest that I misunderstood the way in which keeping promises is valuable. If dignity is the kind of moral good that most clearly has a place in non-consequentialist moral views that oppose interpersonal aggregation wholesale, I suspect that at least our present philosophical concept of it may be unsuited to sit among what we might conventionally refer to as “EA values.”
That said, I should note: Like surprisingly many EAs, I am not a utilitarian. I am, however, some kind of consequentialist, and I would love for EA folks to invest more effort in developing a thorough conception of human flourishing, of what it means for a person’s life to go well for them. Without such a theory, we cannot ensure that we are actually improving others’ lives to the greatest extent possible (because we lack a robust understanding of what it means for a life to be improved). For that reason, I personally welcome posts like this that seek to draw attention in those kinds of directions and propose some less conventional ideas about what flourishing might involve.

HStencil Jun 16, 2020, 10:01 PM
1 point
0 ∶ 0
on: Million dollar donation: penny for your thoughts?
Because you’re recommending Village Enterprise, I’d also flag TechnoServe, which runs similar programs and is the top-rated poverty alleviation charity by ImpactMatters. It’s worth noting that ImpactMatters only evaluated (I believe) TechnoServe’s Impulsa Tu Empresa program, which operates exclusively in Latin America, but the organization runs analogous programs in Sub-Saharan Africa. Obviously, those might not be similarly cost-effective, but a prima facie basis for making that assumption (rather than the opposite, for instance) isn’t obvious to me.

HStencil May 23, 2020, 4:16 AM
4 points
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on: Influencing pivotal Individuals
The Center for Security and Emerging Technology (funded by Open Philanthropy) seems like it’s pretty clearly focused on influencing people in power.

HStencil May 23, 2020, 3:31 AM
1 point
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in reply to: IanDavidMoss’s comment on: Prioritizing COVID-19 interventions & individual donations
Thanks — that makes perfect sense!

HStencil May 22, 2020, 7:41 PM
1 point
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in reply to: IanDavidMoss’s comment on: Prioritizing COVID-19 interventions & individual donations
Great! Thanks so much for flagging that here! I assume this means that you consider Oxfam, PSI, DMI, and GiveDirectly to be more promising giving opportunities than the COVID-19 response programs of other TLYCS charities, like Living Goods, Project Healthy Children, etc. — is that right?

HStencil May 22, 2020, 7:36 PM
2 points
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in reply to: IanDavidMoss’s comment on: Prioritizing COVID-19 interventions & individual donations
Thanks so much! This resource has been extremely useful.

HStencil May 21, 2020, 5:05 AM
2 points
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on: Prioritizing COVID-19 interventions & individual donations
I’d also be curious about whether you’ve looked into the COVID-19 Early Treatment Fund’s work sponsoring outpatient trials of promising anti-virals as early treatments for COVID-19. Marc Lipsitch spoke favorably of its work in his recent interview on the 80,000 Hours podcast, and in a number of respects, it strikes me as similarly promising to Fast Grants.

HStencil May 13, 2020, 3:18 AM
11 points
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in reply to: AslanP’s comment on: Are we entering an experiment in Modern Monetary Theory (MMT)?
I’m happy to hear that what I wrote was helpful!
I actually don’t think it’s that surprising that we have so much difficulty modeling the macroeconomy with high fidelity. In part, this is because of large degrees of endogeneity and general equilibrium effects (the shocks you are trying to model may alter key parameters of the models themselves), and in part, it is because contemporary macroeconomic models (i.e. DSGE/New Keynesian models) must necessarily make assumptions about human psychology in establishing their “microfoundations.” For a long time, for the sake of simplicity, there was little focus among macroeconomists on ensuring that those assumptions about human psychology were accurate. More recently, significant focus has been dedicated to that question, and more sophisticated, hopefully more accurate New Keynesian models have emerged. That said, even if these models better reflect the expert consensus in psychology and behavioral economics, they are still reliant on empirical findings in those fields for their accuracy, and given the replication crisis in psychology, that reliance may be compromising. It seems that there is no easy way around the difficulty of modeling human behavior.
Regarding the reliability of macroeconomic predictions, I think it’s safe to say that macroeconomists have developed a poor reputation as predictors. Particularly, in the aftermath of the 2008 financial crisis, there was a lot of highly critical discussion about why “no one saw it coming,” where “no one,” more often than not, referred to macroeconomists. While this is not completely accurate (some macroeconomists, like Robert Shiller, did see it coming), macroeconomists, by and large, failed rather grandly to understand what was going on in markets. There are many reasons for this, but a large one, arguably, especially among experts at the U.S. Federal Reserve, was that they were looking at DSGE models based on implausible and largely discredited assumptions both about people (e.g. rational expectations, the permanent income hypothesis, etc.) and about markets (e.g. perfect competition, no asymmetric information, no price stickiness, no financial or labor market frictions, etc.). This inspired a substantial backlash against DSGE models in general (typified in work like chapter three of John Quiggin’s book Zombie Economics).
This criticism, I think, has proven misguided (and not only because the critics never seemed to be equipped with a superior alternative to DSGE). In the years since the crisis, as I mentioned earlier, DSGE models have been updated and improved, and many authoritative New Keynesian approaches today are (to the best of our knowledge) realistic in precisely the same areas in which their predecessors were unrealistic. The Federal Reserve Bank of New York actually now publishes its standard DSGE model on GitHub. If you’re curious about it, you can take a look here. Only time will tell whether the best models of today materially outperform the models of the early 2000s, but I will say that thus far, it looks like the Federal Reserve has done a vastly better job of responding to the COVID-19 economic crisis than it did in responding to the 2008 housing crisis, so I am optimistic about the progress the field has made in the last ten years.
Finally a minor clarification based on your comment: While the impact of monetary policy is mediated just about exclusively through the expectations channel when an economy is at the zero lower bound and nonetheless lacks full employment (like now, in most advanced economies), this is generally not the case when interest rates are well above zero, and monetary policy is reliant upon traditional rather than extraordinary tools (e.g. open market operations rather than quantitative easing).

HStencil May 12, 2020, 9:19 PM
41 points
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on: Are we entering an experiment in Modern Monetary Theory (MMT)?
I pretty strongly disagree with the notion that any country on Earth right now is “trying out MMT” merely by running deficits without concern for their impact on public debt levels. After all, traditional Keynesian macroeconomics recommends the exact same course during a recession. Moreover, MMT itself is far more radical than this. It recommends basically switching the functions of the fiscal taxation authority and the central bank. In particular, it holds that instead of raising taxes to finance new government programs, the central bank should simply buy government debt (i.e. print money) to pay for them, and when this inevitably leads to significant inflation, the fiscal authority (e.g. the national legislature) should address it by raising taxes (thus reducing aggregate demand) rather than having the central bank address it by raising interest rates. With respect to the long-run trajectory of interest rates, MMT’s proponents believe they should be maintained at a low, stable level (zero, according to some).
I want to emphasize how different this would look from what we’re seeing right now in developed economies facing COVID-19-induced recessions. To do this, I’ll walk through a hypothetical based on the U.S. Here (in the U.S.), MMT would likely require the legislative abolition of central bank independence. Then, it would involve the Chair of the Federal Reserve, the Secretary of the Treasury, and the Speaker of the House of Representatives (presumably) jointly announcing that from this point forward the Fed would no longer be adjusting interest rates to maximize the objectives of full employment and stable prices specified in its (now former) dual mandate. Instead, it would be (permanently) buying as much government debt as necessary to pay for fiscal programs passed by Congress while maintaining some specified target interest rate (presumably around zero — it’s hard to get much below that) irrespective of the amount that this would expand the money supply. The Speaker of the House, for her part, would announce that when this new policy caused inflation to exceed some specified rate (the Fed’s current symmetrical 2% target?), Congress would pass a tax increase to wrangle aggregate demand back in check, thus reducing demand-pull inflation and (hopefully) ensuring continued stable prices.
MMT’s proponents often argue that we can trust that what they’re defending would not cause runaway inflation because even as advanced economies around the world have radically expanded their money supplies over the last few decades (some by nearly an order of magnitude), none of those economies have struggled with elevated inflation (ostensibly indicating a persistent gap between the money supplies and the productive capacities of these economies). This is a basically fair observation, but it misses the point. Today, we understand far better than we did 20 years ago that the inflationary consequences of extraordinary monetary policy (at the zero lower bound — i.e. like now) are caused primarily by the ways in which policy affects expectations regarding the future trajectory of interest rates and inflation rates. That is to say: Policy changes that radically reconfigure market participants’ expectations regarding the long-run monetary trajectory will almost certainly yield substantial changes in the inflation rate.
This is a policy that would radically reconfigure market participants’ expectations regarding the long-run monetary trajectory (pretty much by definition). It’s true that in MMT proponents’ perfect world, we would simply raise taxes to combat this rising inflation, and if market participants trusted that would occur as described when the transition to MMT policy were first announced, then perhaps the effects of the policy announcement on market expectations would be less pronounced. However, basically no one believes that (for example) the U.S. Congress could be trusted to pass (inevitably unpopular) tax hikes merely for the purpose of mitigating the risk of runaway inflation sometime down the road (remember, good monetary policy is proactive, not reactive!), given that it has proven unable to pass tax hikes to finance overwhelmingly popular government programs for the last decade. As a result, a government declaring an MMT policy approach would wildly shift market inflation expectations, thus causing significant inflation (a self-fulfilling prophecy), demanding, presumably, an increase in taxes shortly thereafter. When this increase fails to materialize, the market’s suspicions that the national legislature was not fully committed to the elements of MMT that require economic discipline would be confirmed, and inflation would increase even further, potentially surpassing the ability of any relevant government authorities to control it.
Even if you don’t buy any of that, though, I think there are some other pretty serious problems with the notion of using the tax code to control inflation. Intuitively, it’s an idea with significant distributive implications (though, of course, controlling inflation by raising interest rates also has distributive implications, and I can imagine how a person might reasonably conclude that those distributive implications are worse). More importantly, however, it could have a pretty substantial impact on labor market incentives. Bear in mind that if your intent in raising taxes is to reduce aggregate demand, you can’t just raise the corporate rate and call it a day (at least in the U.S., that would spur some tax inversions and some deduction-hunting but probably would not have much of an impact on demand). Rather, to have the desired effect, you would need to raise income taxes. That’s fine for a while, but eventually, inflation could get so high that the tax rate required to rein it in would meaningfully reduce people’s interest in working, thus diminishing the economy’s productive capacity (and GDP, etc.). Moreover, you better trust that your tax code is well-designed; otherwise, differentially disincentivizing work in this manner could produce some pretty odd labor market distortions. (Yes, many arguments similar to this one have been grossly mis-used by conservative economists to defend empirically indefensible conclusions. As Paul Krugman himself notes, this is not such a case.)
To close, I’d just note that MMT has substantial factual and theoretical faults entirely unrelated to anything I discussed here but nonetheless worthy of consideration. For a cogent run-through of just a few, I’d recommend these three columns by Krugman (one of which is also linked above).

HStencil May 7, 2020, 8:19 PM
13 points
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on: Prioritizing COVID-19 interventions & individual donations
Thanks for this great post! I’m curious whether you’ve looked into any of the other developing world COVID-19 initiatives for which The Life You Can Save is currently raising money (beyond Development Media International and GiveDirectly). These include programs by TLYCS top charities D-Rev, Evidence Action, Living Goods, Population Services International, and Project Healthy Children, several of which are also, as you know, highly regarded by GiveWell.

HStencil May 4, 2020, 3:50 AM
4 points
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in reply to: Larks’s comment on: How to vote in Shareholder Meeting proxy votes
While it’s certainly true that in most instances, a retail shareholder’s participation will have no impact whatsoever on the outcome of a proxy vote, I think this breakdown of proxy proposals may obscure more than it clarifies. After all, the biggest reason why an individual shareholder’s votes typically make no difference is because the vast majority of ballot items each proxy season are uncontested. Presumably, thecommexokid is not wondering how they should vote on those. And with respect to meaningfully contested ballot items, I think it’s probably not quite right to say that the majority are proposed by cranks. Among other things, only about a quarter of shareholder proposals are proposed by retail shareholders of any variety. (It’s worth noting that in the U.S., companies regularly receive the SEC’s permission to exclude genuine crank proposals from their proxy statements on a variety of legal grounds.)
The vast majority of shareholder proposals in the U.S. fall into one of three categories: requests for certain kinds of disclosures (e.g. of environmental impact, of lobbying expenditures, of pay equity data, etc.), changes to technical governance rules (e.g. the requirements for proxy access or for calling a special meeting), and activist hedge funds seeking to replace members of a board of directors. In most cases, these are proposed in the context of some kind of organized campaign. This doesn’t guarantee that the vote will be close (obviously, many such campaigns are not meritorious), but it does mean that more often than not, the contested shareholder proposals that make it onto companies’ proxies have non-trivial support within the shareholder base. Consider, for instance, that around 37% of proposals submitted by public pension funds passed in 2017, as did 20% of proposals submitted by hedge funds. Moreover, sometimes, those votes do end up being quite close! And even if a vote fails (by a modest margin), it can send a powerful signal to the management and the board. Notably, whenever an executive pay package receives less than around 70% shareholder support in the U.S., there is a strong norm (supported by the major proxy advisors) for the company to propose a more modest package the following year.
Admittedly, the domains on which shareholders can exercise influence through the proxy process do not lend themselves to promoting the kinds of change that a socially concerned (or EA-focused) investor might like to see (in the U.S., the operations of the company are strictly off-limits). However, it isn’t difficult to imagine a story in which a particular shareholder’s vote mattered in bringing about a meaningfully positive outcome. If a person is already inclined to look into this stuff—perhaps because they find it interesting and have a bit of free time—I don’t think it’s unreasonable to try one’s best to use this resource, however modest, to bring about some good. After all, hedge fund activism in particular can be quite high-stakes. It’s plausible that it really does matter in some of those cases that the right side wins. And as far as disclosure campaigns go, making more information available to researchers, investors, employees, and consumers seems likely to, more often than not, improve the function of markets and maybe even advance the social good.
What links here?
- Is shareholder activism worth it? by sbowman (Sep 4, 2020, 11:49 PM; 21 points)

HStencil May 2, 2020, 11:21 PM
5 points
0 ∶ 0
on: How to vote in Shareholder Meeting proxy votes
I know a bit about the proxy advisory ecosystem, so I can provide something of a generic summary, though nothing specific to EA.
In the U.S., there are five different companies that advise institutional investors about how they should vote their shares: Institutional Shareholder Services, Glass Lewis, Egan-Jones, Segal Marco Advisors, and ProxyVote Plus. However, Institutional Shareholder Services (ISS) has around 61% market share, and Glass Lewis has another 36%, so the industry is quite concentrated. While ISS guarantees its clients 100% portfolio coverage (and as a result, produces research reports addressing pretty much every proxy ballot item on the planet each year), many of its smaller competitors offer narrower, more specialized services. For instance, Segal Marco advises primarily labor union pension funds, and there are a few other proxy advisors outside of the U.S. that specialize in companies listed in the country in which they are located.
ISS (like most of its competitors) offers its clients voting recommendations determined through the application of a defined voting policy selected by the client in question. While the plurality of its clients use its benchmark policy, which is focused on long-term shareholder value creation, ISS also offers a number of specialized policies targeted at investors concerned about corporate social responsibility, sustainability, labor interests, etc. For clients who feel that none of ISS’s preexisting policies fit their particular goals, ISS offers custom policies that clients can develop collaboratively with its advisors.
Assuming you are not an institutional investor, you will probably have a hard time accessing ISS’s proxy research (or that of any of its competitors) at a cost-effective price. In light of that, I’d refer you to two other organizations that work in the corporate governance space. The first is As You Sow. It runs shareholder campaigns at companies to promote largely environmentalist goals (though it does work in a few other areas, as well). If you own shares in any of the companies that it is targeting, you might be interested in taking a look at its campaign materials and considering them in the context of EA, your own values, etc.
The second organization is CtW Investment Group. It runs governance advising and shareholder campaigns on behalf of a coalition of U.S. labor unions on a broadly similar model to As You Sow, though it is more focused on worker interests and general good governance norms than on environmental concerns (by virtue of the stakeholders it represents). Like As You Sow, its campaign materials are publicly available online and might be worth reviewing if you’re voting a proxy at a targeted company. Both of these organizations are considered to be highly credible in the governance space, and while there’s room for disagreement about certain elements of their respective agendas, their research is considered to be of a reasonably high quality.

HStencil Apr 25, 2020, 4:51 PM
3 points
0 ∶ 0
in reply to: MaxDalton’s comment on: CEA’s Plans for 2020
Hey Max, thanks for all this explanation! One question: Has any thought been given to spinning off GWWC and EA Funds together (as a single organization), given that they share a similar focus, common users, and some degree of web integration?

[Question] What would “doing enough” to safeguard the long-term future look like?

HStencilApr 22, 2020, 9:47 PM

20 points

0 comments1 min readEA link

HStencil Feb 5, 2020, 3:39 AM
3 points
0 ∶ 0
in reply to: Jack Lewars’s comment on: Did Fortify Health receive $1 million from EA Funds?
Hi Jack, thank you so much for your thorough response to my concerns. I have seen the additions to your website, and I think they’re great. I should also note that I think One for the World is doing laudable and important work. I did not intend to suggest otherwise. As you say, I believe you “could be seen” as a publicity effort for GiveWell, but I certainly do not believe that characterization accurately captures the full scope of your activities or of your role in the broader EA ecosystem. On a similar note, I apologize for missing the acknowledgements of your financial relationship with GiveWell in the blog posts you mentioned and in your 2018 annual report. I admit I simply was not looking that hard for disclosures – I just browsed what I took to be the main pages of your website. I am thrilled to see that these pages now feature a similar (or greater) level of transparency. Finally, I am glad to hear that you are engaged in efforts to reduce your reliance on GiveWell for funding and that GiveWell is supporting you in those efforts. That strikes me as an excellent best practice. Thanks again for your response, for the changes, and for all of the great work you’re doing at One for the World.

HStencil Jan 15, 2020, 5:51 AM
3 points
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in reply to: SamDeere’s comment on: Did Fortify Health receive $1 million from EA Funds?
Hi Sam, thank you so much for explaining all of that — it’s all good to know. I certainly wouldn’t ask you to refund any of my donations (though I do appreciate the offer).
There’s just one more thing I’d like to flag. Recently, I noticed the “Scope and Limitations” page on the EA Funds website for the first time, which says it exists in part “to set clear expectations” for donors. The section dedicated to describing the scope of Global Development Fund reads, “The Global Health and Development Fund makes grants that aim to improve the health or economic empowerment of people around the world as effectively as possible,” giving the following as examples of “expected recipients”:
· [Projects that] directly provide healthcare, or preventive measures that will improve health, wellbeing, or life expectancy
· [Projects that] directly improve economic conditions or income
· [Projects that] build capacity in government or social systems such as healthcare systems, policymaking, or education, or conduct research that will be useful for building such capacity”
· [Projects that] conduct research that will assist practitioners in delivering such projects more effectively
It seems to me that the One for the World grant falls outside of the scope of those expected recipients. I understand that the expected recipients list is intended to be non-binding and that “if a Fund’s management team decides that a grant fulfils the Scope/Limitations, and the spirit of the Expected Recipients section, they may recommend the grant.” However, if it’s reasonably likely that the Global Development Fund will make more grants to movement-building organizations down the road, do you think that perhaps the expected recipients list should be updated to reflect that?
Finally, the webpage says, “Where a grant is determined to be ambiguous with respect to scope . . ., approval may require additional scrutiny.” If I understand correctly, you now agree that the One for the World grant was “ambiguous with respect to scope,” but on account of your prior understanding of the Fund’s prior scope, you did not feel that way at the time of the grant. Accordingly, I assume that the One for the World grant did not receive additional scrutiny. Is that correct?
Thanks again for engaging with me here. I’m grateful for the thought.

HStencil Jan 15, 2020, 5:04 AM
1 point
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in reply to: CatherineHollander’s comment on: Did Fortify Health receive $1 million from EA Funds?
Hi Catherine, thanks so much for clarifying that and for passing my feedback on to One for the World. I am thrilled to see that they have now added a new page to their website explaining the nature of their relationship with GiveWell in detail. To my eye, the page does a great job of providing donors with all of the information they might want to have and would be a good model for other organizations confronting similar issues.

HStencil

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