LW survey: Effective Altruists and donations

By using a slightly different offset you get a slightly different nonlinear transformation, and one that may work even better.

There isn't a way to make this transformation without a choice. You've made a choice by adding $1 -- it looks kind of canonical but really it's based on the size of a dollar, which is pretty arbitrary.

For example say instead of denominating everything in dollars you'd denominated in cents (and added 1 cent before logging). Then everyone would move up the graph by pretty much log(100), except the people who gave nothing, who would be pulled further from the main part of the graph. I think this would make your fit worse.

In a similar way, perhaps you can make the fit better by denominating everyone's donations in hectodollars (h$1 = $100), or equivalently by changing the offset to $100.

We could try to pick the right offset by doing a sensitivity analysis and seeing what gives us the best fit, or by thinking about whether there's a reasonable meaning to attach to the figure. In this case we might think that people tend to give something back to society even when they don't do this explicitly as charity donations, so add on a figure to account for this. My feeling is that $1 is probably smaller than optimal under either interpretation. This would fit with the intuition that going from donating $1 to $9 is likely a smaller deal at a personal level than going from $199 to $999 (counted the same in the current system).

What do you mean by "dollar amounts become linear"? I haven't seen a random variable referred to as "linear" before (on its own, without reference to another variable as in "y is linear in x").

Here's why it matters:

If we add 100 to everything, that transformation will be sized differently after we take the log. 0s go from -infinity to +2, a jump of infinity (...plus 2, to the degree that makes any sense); 100s go from 2 to 2.3, a jump of .3. If we added 1 instead, 0s would go from infinity to 0, and 100s would go from 2 to 2.004. If we added .01, 0s would go to -2, and 100s would go to 2.00004.

But what does that do to our trendline? Suppose that 40% of EAs gave 0, and 60% of non-EAs gave 0. Then I when I calculate the mean difference in log-scale, the extra 20% of non-EAs whose score I can pick with my scaling factor is a third of the differing sample. The gulf between the groups (i.e. the difference between the trendlines) will be smaller if I choose 100 than if I choose 0.01. (I can't pick a factor that makes the groups switch which one donated more--that's the order preservation property--but if I add a trillion to all of donations, the difference between the groups will become invisible because both groups will look like a flat line, and if I add a trillionth to all of the donations, it'll look much more like a graph of percent donating.)

And so it seems to me that there are three potentially interesting comparisons: percent not donating by age for the two groups (it seems likely EA will have less non-donors than non-EA at each age / age group), per-person and per-donor amounts donated for each age group (not sure about per-donor because of the previous effect, but presumably per-person amounts are higher), and then the overall analysis you did where either an offset or a direct 0->something mapping is applied so that the two effects can be aggregated.

(I don't have R on this computer, or I would just generate the graphs I would have liked for you to make. Thanks for putting in that effort!)

As Caplan would say, social desirability bias seems like an issue here. One would not expect people to penalize themselves in such a self-report rather than nudge estimates upwards and make themselves look better in their own mind.

I don't think su3su2su1 made any claim involving donations split by EA-ness

Of course he did. It's literally the first line of my post:

the median charitable donation for an EA in the Less Wrong survey was 0.

on EA's own aggregative utilitarian premises, total dollars donated are what matter, not anything about the distribution of dollars over people.

This is a pretty narrow conception of EA. You can be an EA without earning to give. For example, you could carefully choose a career where you directly do good, you could work in advocacy, or you could be a student gaining career capital for later usage.

I'm with Lumifer on this: even though what EAists are supposed to care about is basically total money given (assuming it's given as effectively as possible), that doesn't mean that hypocrisy of EAists is a function of total money given.

Having said that, just eyeballing the data seems sufficient to demonstrate that EAists are (at least according to self-report) more generous than non-EAists in this population, and I bet any halfway reasonable analysis will yield the same conclusion.

total dollars donated are what matter, not anything about the distribution of dollars over people.

Really? Under this approach a hundred EAers where 99 donate zero and one donates $1m suffer from less hypocrisy than a hundred EAers each of which donates $100.

And if only total dollars matter, then there is no need for all that statistical machinery, just sum the dollars up. "Median donations", in particular, mean nothing.

I think you're mistaken about total dollars. If I were curious about the hypocrisy of EA people, I would look at the percentage which donates nothing, and for the rest I would look at the percentage of income they donate (possibly estimated conditional on various relevant factors like age) and see how it's different from a comparable non-EA group.