In response to EA Funds Beta Launch
Comment author: Peter_Hurford  (EA Profile) 28 February 2017 05:45:22AM 2 points [-]

On my browser (Chrome on a Macbook), the EA funds just spins forever, even when refreshing or reopening in a new tab. I notice, however, when I open in Incognito mode, it works fine. This could suggest that my uBlock, Privacy Badger, or other plugin is messing with the site?

Comment author: SamDeere 28 February 2017 07:39:13AM *  4 points [-]

Thanks for this

There was an issue with refreshing security tokens. I've just pushed a fix for this — if you refresh (or failing that, a hard refresh - e.g. Cmd+Shift+R) then the issue should resolve itself. I suspect that it works in incognito because you don't have any cookies set. If you're still having issues, try clearing cookies for the page*.

If that doesn't fix it, it'd be amazing if you could send the log from your Chrome console to tech[at]effectivealtruism[dot]org (open by pressing 'Cmd+Shift+J', save by right-clicking on the console background and selecting 'Save as...).

*Help on this if anyone needs it: https://support.google.com/chrome/answer/95647?co=GENIE.Platform%3DDesktop&hl=en

11

CEA Staff Donation Decisions 2016

In the lead-up to the December giving season, we asked some of the staff at The Centre for Effective Altruism where they're planning to donate this year. This is something  GiveWell  have done before, and we hope it's a useful resource for others thinking about donating. Read the whole post... Read More
Comment author: AndyMorgan 11 May 2016 09:34:19AM *  1 point [-]

\Hey everyone,

My recent accomplishment is that I've completed building an API to anonymously record donations made to charities, with the intention of allowing organisations like Giving What We Can and EAHub to automatically update the donation records of their members and to measure their impact (I figured there must be an easier way than individuals manually entering their donations).

At the moment I'm going to start working on integrating it with those organisations, and charities that are the most popular with effective altruists, but I'd also really be interested to hear any suggestions for possible applications for it that I could build?

Maybe something like a web application that exports all your donations to a CSV file?

Or maybe a Facebook plugin (is that what they're called?) that displays your donation total on your profile page?

I'm all ears.

It's currently set up to record a donor ID, a charity ID, the amount donated, a reference number, the date, and the time the database record was created.\

Comment author: SamDeere 11 May 2016 11:10:59AM 2 points [-]

Hey Andy, I'm currently working on something very similar as an upgrade to Giving What We Can's My Giving dashboard. Did you want to shoot me an email at sam.deere@givingwhatwecan.org to discuss — either as an opportunity to collaborate or to work out if there's significant overlap?

Sam

Comment author: kierangreig 09 December 2015 03:10:59AM *  10 points [-]

Hi Michelle,

Thank you so much for answering questions like this. I think it’s really worthwhile :). When you have a free moment it would be great if you could answer these questions. Unlike Peter I have only 6 questions:

1.) Should GWWC’s realistic impact estimate include the % of people each year who fulfill their pledge? For instance, the summary of the 2014 Giving Review states that 20-55% of people who pledged from 2009-2013 didn’t fulfill their pledge in 2014.

2.) On what information is the ratio of actual donations to pledged donations used in GWWC’s most recent realistic impact estimate based upon?

3.) Is the current technique that GWWC uses to calculate counterfactuals more likely to overestimate or underestimate GWWC’s impact given that the counterfactual percentage of all future donations is estimated when people initially take the pledge rather than when they make their donations in subsequent years?

4.) In Nick Beckstead’s 2013 quantitative performance review of GWWC he noted:

it is very unclear to what extent the new members are a result of the activities of GWWC’s staff, rather than organic growth.

What is your response to this?

5.) Around 6 months ago GWWC’s realistic impact estimate was a ratio of 60:1 and it’s now 104:1. Why has this number changed and do you expect it to change that much in another 6 months?

6.) It seems that GWWC’s comparative advantage is in generating and maintaining pledges for effective charities. Given that there is a large overlap between GWWC’s and GiveWell’s charity recommendations and GiveWell being in a better position to continue charity evaluations, why is it worth GWWC continuing charity evaluations?

Comment author: SamDeere 09 December 2015 01:51:07PM *  5 points [-]

Hi Kieran,

Michelle is in a better position to answer some of these, but I'll answer the ones I can. I'd also suggest having a look at the comments section of our last fundraising prospectus, which covered some similar ground and which may provide more detail to some of your questions.

1) This is largely covered in the step Accounting for members donating a different amount than they pledged, which uses data from members who have reported their donations in My Giving, and comparing their actual donations with their pledges. The upper bound estimate in the Giving Review (80% of people keeping their pledge) uses the same dataset, but only takes into account a binary 'pledge met' vs. 'pledge not met'. The ratio of pledges to donations (117%) has more bearing our calculations because it captures both people who donate less than they pledge, and people who donate substantially more. Overall, due to people on average donating more than their pledge, the ratio is actually larger than 1:1 (so, even if only 80% of members hit their pledge amount, the number of people donating more than their pledge means the cohort as a whole donates more than it pledges).

The only quibble that you might have here is whether this cohort (people who report donations in My Giving) donates at a substantially different rate than people who don't report their donations (after we've factored out people who have both gone silent, and stopped donating, as per the earlier Accounting for membership attrition step). We have good reason to think this isn't the case (we know a lot of people personally who choose not to use My Giving, but who keep their pledges), but if you were more pessimistic about this, you could downweight the Ratio of Actual Donations to Pledged Donations in the spreadsheet (currently 1.17).


2) As above, this was calculated using data from members who have reported their donations in My Giving, and taking the ratio between their pledged amount and their reported donations, averaging over all members. See this section of the impact page for more info.


3) To clarify, are you talking about the impact of changes to members' income over time, or asking whether we're accounting for potential changes to donation patterns over time which affect the counterfactual ratio?

We're currently calculating our counterfactuals based on the amounts members say they would have donated without us — we haven't modelled behaviour changes into the future, and I'm not sure what we'd base such a model on. Whether it's conservative or optimistic is unclear, but I'd say that this is probably a wash — it's hard to know whether people's predictions of what they would have donated are overall optimistic or pessimistic. In our conversations with members, many people who say that they would have donated 10% without us also tell us that we're a useful commitment device (indicating that perhaps they wouldn't stick to their 10% without us, and that our counterfactual impact is actually greater than what we've accounted for in the model).

If you're just talking about the effect of members' income on the counterfactuals (because the calculations assume they will be static, when in reality income is likely to rise) then we think the calculation is fairly conservative. See the Donations Pledged By Members section of the impact page:

This methodology relies on the accuracy of members’ predictions about their future income. In general we have found that these predictions seem conservative, as most people underestimate their future earning potential[7] . If members do not estimate their future salary, we use the median salary for their country. We think that is a fairly pessimistic assumption, as our median member has an expected earning potential higher than the median wage[8] .

Footnotes 7 and 8 expand on this:

  1. For example, many members estimate their future income will be the same as their current income, even though they are at the beginning of their careers - in reality, income typically increases throughout a person’s career

  2. For example, many members attend prestigious universities and/or are pursuing careers that have an average salary much higher than the median wage

See also this comment made on the last prospectus for some discussion of the effect of modelling changing income over time. Using the same model with the updated figures yields a ratio of between 69:1 (using a fairly arbitrary starting pledged amount of $4,200,000 which produces donations over members' careers equivalent to the $344 million pledged amount, but accounts for income growth) and 157:1 (assuming that the current pledges correspond to current income levels, and that all members are at the beginning of their careers). You can play with this assumption by editing the figure in cell C2 on the 'Calculations' sheet of this spreadsheet, and the income growth rates at the bottom of the column.


5) We've taken into account an additional year (2014), where we had strong growth, but where our costs were not significantly higher. Our membership more than doubled (386 in 2009-13 vs 792 in 2009-14) but our costs only went up by around 40% (£238k in 2009-13 vs £332k in 2009-14). The assumptions have remained essentially the same, so the difference in those ratios accounts for most of the difference (with a less significant amount being due to small changes in membership attrition and counterfactual pledge ratios).

As we note in the caveats, we do expect this amount to go down in future as our staff costs increase, and we don't want people to fixate on it as a predictor of our impact. We see it more as a sanity check of whether we're a good bet, vs giving money to other effective causes.

The degree to which this will change significantly in future really depends on how strong our member growth vs. costs growth is. If the cost of creating a new member hits diminishing marginal returns soon (not at all unlikely), then it's likely to drop back fairly quickly. We don't see this as particularly troubling — so long as our absolute number of members keeps increasing and the ratio is positive, then we're still a good bet.

We doubled staff numbers over 2015 (3 > 6) and we're hiring again now (6 > 8 or 9, depending on fundraising), so it's likely that this will push it back down. We think that maximising future membership growth will be contingent on broadening the skillset of our team (and just having more hands on deck to do outreach work would be a huge help!). Expanding the team, strengthening our organisation, and increasing our growth rate seems very important right now (and much more important than maintaining this ratio at the current level). My guess is that it will settle somewhere between 20:1 and 60:1 — not quite as impressive as 104:1, but still suggestive that we're making a big difference!

(This difference is similar to the reason that we don't think that using "overhead" is a good measure of a charity's effectiveness. In effect, this is our overheads increasing, but so long as this leads to greater (counterfactual) overall member growth and donations to top charities, then we should be happy for the ratio to drop.)


6) Hauke, our Director of Research answers this question here. The short version:

  • Supplement GiveWell research and find new charities within our comparative area of advantage (global poverty reduction)
  • Independently check GiveWell recommendations and provide resilience to the effective charity evaluation system
  • Provide supervision for students/early career researchers who want to focus on effectiveness
  • Ensure in-house credibility when talking about top charities and fact-checking all of our public-facing material

Hope that helps!

Comment author: SamDeere 08 December 2015 11:22:46PM 3 points [-]

I've updated our impact page to include a spreadsheet that you can use to test our Realistic impact calculation. Find it under the "Spreadsheet" header.

Also, preparing this spreadsheet for public use revealed a minor error in our workings (the original spreadsheet was using an out-of-date figure for Proportion of people who say we've affected their choice of charity) — this has been corrected, and the impact ratio has accordingly shifted slightly from 103:1 to 104:1.

Comment author: Denise_Melchin 01 July 2015 10:02:42AM 0 points [-]

Hi Sam,

I'd like to know how Rob Mather thinks AMF could increase their impact and if so, by how much, e.g. more specifically, what kind of person they'd need to work for them to achieve this.

Comment author: SamDeere 01 July 2015 10:46:06PM 0 points [-]

Thanks for this Denise — would you like to discuss this in person? If so, happy to add you to the Skype.

5

Opportunity to talk to Against Malaria Foundation founder Rob Mather

Rob Mather from the Against Malaria Foundation (one of Giving What We Can / GiveWell's top charities) has kindly offered to take some time to chat to supporters over Skype. The format will be a Skype conversation of around 1-2 hours, where participants will have the opportunity to ask Rob... Read More
Comment author: SamDeere 14 May 2015 06:36:26PM 3 points [-]

Thanks for the question Jon.

With regard to the pledged amount, this comes from members' predictions of their future annual salary, which we think are likely to be underestimates. We also use median wage as a stand-in if we're missing future salary data, which (given our members are in general likely to earn more than median wage) we also think is conservative. Accordingly, it's likely that the amount donated will be higher in reality.

We address this in more detail in our fundraising prospectus – see Appendix 2 for the full working.

From page 23 of the prospectus:

This methodology obviously relies on the accuracy of members’ predictions about their future income. In general we have found that these predictions seem conservative, as most people underestimate their future earning potential (1). If members do not estimate their future salary, we use the median salary for their country. We think that is a fairly pessimistic assumption, as our median member has an expected earning potential higher than the median wage (2).

And the footnotes to the above:

(1) For example, many members estimate their future income will be the same as their current income, even though they are at the beginning of their careers - in reality, income typically increases throughout a person’s career (2) For example, many members attend prestigious universities and/or are pursuing careers that have an average salary much higher than the median wage

The final $146m figure is arrived at by multiplying members' estimates of future salary by the number of years they have left in their careers. It therefore doesn't take into account any of this growth that you'd expect in reality. As such, it wouldn't make sense to go back and try to model growth based on the $146 million figure (say, $1.7 million in year one, growing to around $5.6 million/year by year 40, rather than a flat $3.7m per year)*.

Instead, you'd need to apply your model (say, fast wage growth in the first 10-20 years of a career, then slower growth until retirement) to the member estimates first to derive the final figure, and use the yearly amounts in your calculation. Given our assumption that member estimates of future salary err on the low side, this means that both the final pledged amount, and the per-year amounts are likely to be higher, and therefore our effectiveness would in fact be higher, notwithstanding that the discounting/attrition rate would affect the final number more aggressively.


* I've tried this calculation, assuming a 4% growth rate for years 1-20 and a 2% growth rate in years 21-40. With a year one pledge of $1.7 million, this grows to $5.6 million by year 40, for a total of ~$147 million donated. This drops the effectiveness estimate down to 44-1 - a significant drop, but still excellent return for a donation to Giving What We Can. To reiterate, I think this would be a significant underestimate of peoples' future incomes.

Comment author: SamDeere 14 May 2015 07:30:37PM *  0 points [-]

Also, sorry if this reply doesn't exactly address your rephrased question – I wrote it in response to your first comment :)

Here's a copy of the spreadsheet with the calculations added in as above if you want to play around with it.

Thanks again for the question, let me know if there's anything else you want clarified.

Comment author: Jon_Behar 14 May 2015 05:52:45PM 1 point [-]

I think you could strengthen your model for calculating your multiplier quite a bit by adjusting for the fact that people will earn, and give, more over time. As you note in your writeup, assuming people will give an equal amount each year is an aggressive assumption, but I doubt people have good intuition for how much this matters (and its effects interact a great deal with assumptions about discount/attrition rates).

If you'd like, you can borrow the calcs to model this dynamic simplistically from the spreadsheet found in this blog post.

You'll probably find this cuts your realistic estimate by at least half, though of course that still leaves a substantial multiplier :)

Comment author: SamDeere 14 May 2015 06:36:26PM 3 points [-]

Thanks for the question Jon.

With regard to the pledged amount, this comes from members' predictions of their future annual salary, which we think are likely to be underestimates. We also use median wage as a stand-in if we're missing future salary data, which (given our members are in general likely to earn more than median wage) we also think is conservative. Accordingly, it's likely that the amount donated will be higher in reality.

We address this in more detail in our fundraising prospectus – see Appendix 2 for the full working.

From page 23 of the prospectus:

This methodology obviously relies on the accuracy of members’ predictions about their future income. In general we have found that these predictions seem conservative, as most people underestimate their future earning potential (1). If members do not estimate their future salary, we use the median salary for their country. We think that is a fairly pessimistic assumption, as our median member has an expected earning potential higher than the median wage (2).

And the footnotes to the above:

(1) For example, many members estimate their future income will be the same as their current income, even though they are at the beginning of their careers - in reality, income typically increases throughout a person’s career (2) For example, many members attend prestigious universities and/or are pursuing careers that have an average salary much higher than the median wage

The final $146m figure is arrived at by multiplying members' estimates of future salary by the number of years they have left in their careers. It therefore doesn't take into account any of this growth that you'd expect in reality. As such, it wouldn't make sense to go back and try to model growth based on the $146 million figure (say, $1.7 million in year one, growing to around $5.6 million/year by year 40, rather than a flat $3.7m per year)*.

Instead, you'd need to apply your model (say, fast wage growth in the first 10-20 years of a career, then slower growth until retirement) to the member estimates first to derive the final figure, and use the yearly amounts in your calculation. Given our assumption that member estimates of future salary err on the low side, this means that both the final pledged amount, and the per-year amounts are likely to be higher, and therefore our effectiveness would in fact be higher, notwithstanding that the discounting/attrition rate would affect the final number more aggressively.


* I've tried this calculation, assuming a 4% growth rate for years 1-20 and a 2% growth rate in years 21-40. With a year one pledge of $1.7 million, this grows to $5.6 million by year 40, for a total of ~$147 million donated. This drops the effectiveness estimate down to 44-1 - a significant drop, but still excellent return for a donation to Giving What We Can. To reiterate, I think this would be a significant underestimate of peoples' future incomes.

Comment author: Jon_Behar 14 May 2015 04:41:54PM 0 points [-]

Question about how you're doing the calcs… In your spreadsheet, it looks like you're taking the total amount pledged (146mm) and then assuming people will donate 1/40 of that amount (3.7mm) each year for 40 years. My impression is that many GWWC pledge takers are quite young (students or young professionals). Wouldn't you expect them to earn, and give, more over time? Adjusting for this dynamic will significantly increase the effects of both discounting and of people leaving. Am I missing something?

Comment author: SamDeere 14 May 2015 06:35:32PM *  0 points [-]

Deleted, responded to Jon's new comment above

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