Cross-posted to the Effective Altruism Forum.

Summary

• How we should spend our philanthropic resources over time depends on how much we discount the future. A higher discount rate means we should spend more now; a lower discount rate tells us to spend less now and more later.
• We (probably) should not assign less moral value to future beings, but we should still discount the future based on the possibility of extinction, expropriation, value drift, or changes in philanthropic opportunities.
• According to the Ramsey model, if we estimate the discount rate based on those four factors, that tells us how quickly we should consume our resources¹.
• We can decrease the discount rate, most notably by reducing existential risk and guarding against value drift. We still have a lot to learn about the best ways to do this.
• According to a simple model, improving our estimate of the discount rate might be the top effective altruist priority.

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Summary

Previously, we talked about how much leverage altruists should use. We looked at estimates of optimal leverage based on future projected returns, but this required making certain assumptions about how asset prices behave.

In many ways, theoretical asset pricing models do not reflect how investments behave in practice. These models may overestimate how much leverage to use. We can learn something about the extent of this overestimation by backtesting leveraged portfolios on historical price data.

In the backtests I performed, theoretically-optimal leverage according to the Samuelson share usually did not differ much from empirically optimal leverage according to backtests. However, the Samuelson share overestimated optimal leverage more often than it underestimated, and following the Samuelson share would have occasionally resulted in bankruptcy.

After performing this analysis, I am now somewhat more confident that it makes sense for altruists to apply substantial leverage to their altruistic portfolios, although probably less than the Samuelson share. However, investors should ensure they understand what that entails—in backtests, optimally-leveraged portfolios usually encountered >90% drawdowns at some points.

Disclaimer: This should not be taken as investment advice. Any given portfolio results are hypothetical and do not represent returns achieved by an actual investor.

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In an early draft of a paper, Philip Trammell points out two mistakes in my essay on giving now vs. later. And since writing it, I have identified a third mistake.

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Epistemic status: I don’t really understand Kantian deontology.

Summary: According to the rules of Kantian deontology, an action must be impermissible if it has any probability of resulting in an impermissible outcome. But all actions have some probability of resulting in such an outcome. Therefore, all actions are impermissible.

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Altruists often would like to get good predictions on questions that don’t necessarily have great market significance. For example:

• Will a replication of a study of cash transfers show similar results?
• How much money will GiveWell move in the next five years?
• If cultured meat were price-competitive, what percent of consumers would prefer to buy it over conventional meat?

If a donor would like to give money to help make better predictions, how can they do that?

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Update 2020-01-04: This essay contains a number of important mistakes. See Correction on Giving Now vs. Later.

Disclaimer: I am not an investment advisor and nothing in this essay serves as investment advice.

Introduction

Robin Hanson: If More Now, Less Later

The rate of return on investment historically has been higher than the growth rate–or, as they say, r > g. If you save your money to donate later, you can earn enough interest on it that you eventually have the funds to donate a greater amount. Because r > g, you should invest your money for as long as you can before donating¹–or so the argument goes.

Traditionally, we’d apply a discount rate of g to future donations, because that’s the rate at which people get richer and therefore the rate at which money becomes less valuable for them. But this ignores some important factors that affect how much we should discount future donations, and we can create a much more detailed estimate. This essay will explore that in detail. Exactly what factors determine the investment rate of return and the discount rate on poverty alleviation? Can we gain any information about which is likely greater?

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Some people have observed that small and large donors follow different giving patterns. Small donors who give out of their salary—that is, most people—tend to donate money more or less as soon as they earn it (usually within a year). Large donors—e.g., extremely wealthy people and foundations—tend to slowly distribute their money and hold on to most of it¹. For example, large foundations typically donate little more than the legally required 5% of assets each year. Why do they behave differently?

I don’t believe this difference is surprising, and actually it’s not really even a difference.

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Summary: The stock market can be modeled as Omega in Newcomb’s problem. On average, an asset will only outperform if the market predicts that you won’t buy it. So you cannot say “if I had bought that, I would have made a lot of money”, just as in Newcomb’s problem you can’t say “if I had taken both boxes, I would have gotten more money than if I only took one”.

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Summary: All expected value distributions must either (1) have a mean of infinity, or (2) have such thin tails that you cannot ever reasonably expect to see extreme values. When we’re estimating the utility distribution of an intervention, both of these options are bad.

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Summary: Large donors may create better incentives for both charities and small donors if, rather than providing fixed funding to a charity, they offer to match all donations to that charity over a relatively long time horizon.

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