Recently, I was browsing IMDb’s list of top-rated TV shows:

According to IMDb ratings, Planet Earth II is the second-best TV show of all time, with 9.5 stars out of 10. But if you look at the ratings of each individual episode, they range from 6.8 to 7.9¹:

In general, the rating of a TV show usually differs from the average rating of that show’s episodes. What does the list of top TV shows look like if we sort by average episode rating instead of show rating? Perhaps voters have different motivations when they’re rating shows than when they’re rating individual episodes, and it could be interesting to see how the ratings differ.

So I downloaded the IMDb public database to find out².

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Experiments are a critical part of science—perhaps even the central feature. But middle school and high school science experiments don’t teach students how experiments are supposed to work.

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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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This is a collection of writings on where people are donating. It only includes writings that I am aware exist (obviously) and that are written by effectiveness-minded people.

My descriptions are paraphrased from the linked writings as much as possible. The writing in this post includes combinations of my own and the linked writers’ words. My summaries often do not do the original writers justice, so I recommend reading all of the linked articles if you are interested.

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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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I have removed Disqus and replaced it with built-in static comments. Disqus comments are disabled, but still visible on any old posts¹. New posts going forward will only use the new static comment system.

I had been wanting to switch off Disqus for a while. It has a few disadvantages:

1. I have no control over comments except for the moderation tools Disqus provides.
2. I have no control over how comments are displayed.
3. I don’t know what Disqus is doing or might do with commenters’ personal information.

The new comment system does exactly what I want it to do and nothing more.

Edited to add: If anyone’s interested, I’m using the Jekyll Static Comments plugin by Matt Palmer, with a few personal modifications.

Notes

Posted on Sep 17, 2017

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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