I'm a strategist at Affinity Impact, the impact initiative of a Taiwanese family.
Thanks for the clarification, Owen! I had mis-understood 'investment-like' as simply having return compounding characteristics. To truly preserve optionality though, these grants would need to remain flexible (can change cause areas if necessary; so grants to a specific cause area like AI safety wouldn’t necessarily count) and liquid (can be immediately called upon; so Founder's Pledge future pledges wouldn't necessarily count). So yes, your example of grants that result "in more (expected) dollars held in a future year (say a decade from now) by careful thinking people who will be roughly aligned with our values" certainly qualifies, but I suspect that's about it. Still, as long as such grants exist today, I now understand why you say that the optimal giving rate is implausibly (exactly) 0%.
Hi Owen, even if you're confident today about identifying investment-like giving opportunities with returns that beat financial markets, investing-to-give can still be desirable. That's because investing-to-give preserves optionality. Giving today locks in the expected impact of your grant, but waiting allows for funding of potentially higher impact opportunities in the future.
The secretary problem comes to mind (not a perfect analogy but I think the insight applies). The optimal solution is to reject the initial ~37% of all applicants and then accept the next applicant that's better than all the ones we've seen. Given that EA has only been around for about a decade, you would have to think that extinction is imminent for a decade to count for ~37% of our total future. Otherwise, we should continue rejecting opportunities. This allows us to better understand the extent of impact that's actually possible, including opportunities like movement building and global priorities research. Future ones could be even better!
I highly recommend the Founder's Pledge report on Investing to Give. It goes through and models the various factors in the giving-now vs giving-later decision, including the ones you describe. Interestingly, the case for giving-later is strongest for longtermist priorities, driven largely by the possibility that significantly more cost-effective grants may be available in the future. This suggests that the optimal giving rate today could very well be 0%.
Have you compared your analysis to this previous EA Forum post? Are there different takeaways? Have you done anything differently and if so, why?
Here’s the math on moral/financial fungibility:...You’re probably better off eating cow beef and donating the $6.03/kg to the Good Food Institute
Here’s the math on moral/financial fungibility:
You’re probably better off eating cow beef and donating the $6.03/kg to the Good Food Institute
Is refraining from killing really morally fungible to killing + offsetting? Would it be morally permissible for someone to engage in murder if they agreed to offset that life by donating $5,000 to Malaria Consortium? I don't mean to be offensive with this analogy, but if we are to take seriously the pain/suffering that factory farming inflicts on animals, we should morally regard it in a similar lens to inflicting pain/suffering on humans.
So, no, moral acts are not necessarily fungible. It is better to not eat meat in the first place than to eat meat and donate the savings to farm animal charities (even if you could save more animals). This is obvious from a rights moral framework but even consequentialists would consider financial offsetting dangerous and unpalatable. The consequences of allowing people to engage in immoral acts + offsetting would be a treacherous and ultimately inferior world.
So your calculations are not the cost of eating meat but rather, the cost of saving animals. You have not estimated the cost of chicken/cow suffering (which would require estimating utility functions and animal preferences), but rather, the cost of alleviating suffering. Your low-cost numbers don't imply that eating meat is inconsequential, but rather, that it's very cost-effective to help chickens and cows. GiveWell's $5,000 per human life doesn't make human life cheap, it means we have an extraordinary opportunity to help others at a very low cost to ourselves.
Thanks, Sanjay, I’m sharing a basic model I’ve written that highlights the trade-off for impact investments that seek both social impact and financial returns. This isn’t specifically about ESG but the key ideas still apply. The upshot: the investment must produce annually one percent of a same-sized grant’s social benefit for every one percent concession on its financial return. I construct impact investing’s version of the Security Market Line and quantitatively define what ‘impact alpha’ means.
This model was written a couple of years ago but since then, I actually haven’t applied it much. That’s because it’s hard to quantify impact, which is a key input that the model requires (and an input that any model will obviously require). There’s no established and easy way to monetize impact, especially given impact's tremendous heterogeneity. Comparing the value of a year's education versus a year's health is hard enough. What about quantifying the counterfactual impact that a business has? Or that of the investor investing into the business? So modeling is helpful but at this stage, I think data is what we actually need most.
I agree with Michael that a 70% allocation to US stocks is way too high. US stocks' outperformance against international developed stocks can almost entirely be explained by the increase in the US market's valuation (which shouldn't be assumed to continue and indeed, is more likely to reverse). See AQR's analysis on pg 6 here. Also, what about Emerging Market stocks? This should certainly get some allocation as well, especially if you're focused on the next 100 years. China and India will increasingly be key economic players and have capital markets that will outgrow the US in importance. In fact, 6 of the 7 largest economies in the world in 2050 are likely to be emerging economies. When it comes to investing, beware of simply extrapolating the past into the future! The US markets have done well because the US has been the dominant country in the 20th century. This is unlikely to continue during this century.
A 10% global bonds/90% global stocks portfolio is likely to be more robust and not suffer from a USD/US historical bias. Keep it simple and avoid picking bond/stock market winners.
This paper is relevant to your question.
Abstract: This article asks how sustainable investing (SI) contributes to societal goals, conducting a literature review on investor impact—that is, the change investors trigger in companies’ environmental and social impact. We distinguish three impact mechanisms: shareholder engagement, capital allocation, and indirect impacts, concluding that the impact of shareholder engagement is well supported in the literature, the impact of capital allocation only partially, and indirect impacts lack empirical support. Our results suggest that investors who seek impact should pursue shareholder engagement throughout their portfolio, allocate capital to sustainable companies whose growth is limited by external financing conditions, and screen out companies based on the absence of specific ESG practices that can be adopted at reasonable costs. For rating agencies, we outline steps to develop investor impact metrics. For policymakers, we highlight that SI helps to diffuse good business practices, but is unlikely to drive a deeper transformation without additional policy measures.
I don’t think it makes sense to compound the model distributions (e.g. from 1 year to 10 years). Doing so leads to non-intuitive results that are difficult to justify.
1) Compounded model results (e.g. 10x impact in 10 years) are highly sensitive to the arbitrarily assumed shape, range, and skewness parameters of the variable distributions. Also, these results will vary wildly from simulation to simulation depending on the sequence of random draws. This points to the model's fragility and leads to unnecessary confusion.
2) The parameter estimates may use annualized growth rates, but they need not correspond to an annual time frame. Indeed, it is more realistic to make estimates for longer horizons because short-term noise averages out (i.e. Law of Large Numbers). In other words, it is far easier to estimate a variable's expected mean than its underlying distribution. Estimates for the expected mean will already be highly uncertain. I don't think it's possible to reasonably defend distribution assumptions of the variables themselves.
The exercise is to compare giving-today vs. investing-to-give-later. The post usefully identifies key variables in this consideration. I think the most it can do is propose useful estimates of these variables’ expectations over the long run (i.e. their averages over time) and their key uncertainties (i.e. Knighting uncertainty and not quantifiable distribution parameters). If the expectations' net sum is above 1, it makes sense to give later. If it falls below 1, it makes sense to give now. Reasonable areas of uncertainty can be further discussed and debated. Already, there will be much irreconcilable (rational) disagreement. Compounding returns using arbitrary distribution parameters won’t (and shouldn’t) reconcile any differences and likely confuses the matter.
A 7% real investment return over the long-term is in my opinion, highly aggressive. World real GDP growth from 1960 through 2019 is 3.5%. Since the proposed fund expects to invest over “centuries or millennia,” any growth rate faster than GDP eventually takes over the world. Piketty’s r > g can’t work if wealth remains concentrated in a fund with no regular distributions.
Even in the shorter run, it’s unrealistic to expect the fund to implement a leveraged equity-only strategy (or analogous VC strategy):
1) A leveraged approach may not survive (e.g. will experience -100% returns). Even if the chance is small over a given year, this will be increasingly likely over a longer horizon. Dynamic leverage strategies can be implemented to reduce this risk but this likely reduce returns too.
2) A high-risk strategy will result in extremely painful drawdowns. In bad times, any fiduciary running the fund will face enormous pressure to shift to a more conservative strategy. During the Great Depression, US equities declined by nearly 90% during the course of just 3 years, even without leverage. Sticking to the same approach in the face of a potentially worse decline is nearly unimaginable.
3) A consistently leveraged portfolio approach has never been done before over long investment periods. Foundation/university endowments are probably in the most analogous position and few apply leverage. Harvard tried a modest 5% leverage during the 2000’s, and it blew up during the Financial Crisis.
4) Any successful strategy will be mimicked and thus face increasing competition and declining returns. If the fund grows to any significant size, it will start facing competition from itself. For example, Yale’s legendary endowment has seen declining returns from a ~9.5% real rate over the past 20 years to a ~5.5% one over the past decade. Similarly, given Berkshire Hathaway’s large size, it’s now increasingly difficult for Warren Buffet to beat the stock market.
Indeed, the proposed fund may actually have to be quite conservative for it to survive over time (through broad diversification even into low-return assets) and be accepted by the world (to avoid scrutiny or excess taxation). In my opinion, when investing over centuries with an unprecedented strategy, I would characterize a 2-4% real return (broad asset class diversification that keeps up with world GDP) as reasonable, and a 5%+ real return (all equity with or without leverage) as aggressive.