Hi James, on the South Asian Air Quality portfolio, would be it be fair to say that OP's grants so far have been focused on research and diagnosing both the problem and potential solutions, rather than executing on interventions themselves? Is the current bottleneck a lack of cost-effective and feasible ideas - and if so, what looks most promising so far?

This is something Sjir's team and myself have discussed at length - we're definitely more pessimistic than GWWC on this point.

CEARCH's view is that the raw numbers look good, but if you regress dollar donated against year since pledging, while controlling for pledge batch (and hence the risk that earlier pledgers are systematically different/more altruistic), there is a positive but statistically insignificant relationship between average annual donations and years since pledging (n.b. increase in 35 dollars per annum at p=0.8). The experts we spoke to were split, with a weak lean towards it increasing over time - some were convinced by the income effects, while others were sceptical that you can beat attrition.

Ultimately, we chose to model a very marginal increase (<0.01% per annum); we're really not confident that you can reasonably expect an increase in giving over time for the 2025 and future pledge batches.

For how expected donations generated by a dollar evolves over time (ignoring discounts), available evidence suggests that it's flat (and so the graph is just a horizontal line terminating around 30 years later). There's a lot of uncertainty, not least on how long the giving lasts, given that we can only observe a little more than a decade of giving at this point.

Thanks Sjir! I'm grateful for the transparency and data sharing throughout - I don't see how we could have done the evaluation otherwise!

I don't have the estimates for how the multiplier changes over time, though you would expect a decline, driven by the future pledging pool being less EA/zealous than earlier batches.

For the value of a *pledge* - based on analysis of the available data, it doesn't appear that donations increase over time (for any given pledge batch), so after relevant temporal discounts (inflation etc), the value of a pledge is relatively front-loaded:
 

Hi Nuno,

We report a crude version of uncertainty intervals at the end of the report (pg 28) - taking the lower bound estimates of all the important variables, the multiplier would be 0x, while taking the upper bound estimates, it would be 100x. 

In terms of miscellaneous adjustments, we made an attempt to be comprehensive; for example, we adjust for (a) expected prioritization of pledges over donations by GWWC in the future, (b) company pledgers, (c) post-retirement donations, (d) spillover effects on non-pledge donations, (e) indirect impact on the EG ecosystem (EG incubation, EGsummit), (f) impact on the talent pipeline, (g) decline in the counterfactual due to the growth of EA (i.e. more people are likely to hear of effective giving regardless of GWWC), and (h) reduced political donations. The challenge is that a lot of these variables lack the necessary data for quantification, and of course, there may be additional important considerations we've not factored in.

That said, I'm not sure if we would get a meaningful negative effect from people being less able to do ambitious things because of fewer savings - partly for effect size reasons (10% isn't much), and also you would theoretically have people motivated by E2G to do very ambitious for-profit stuff when they otherwise would have done something less impactful but more subjectively fulfilling (e.g. traditional nonprofit roles). It does feel like a just-so story either way, so I'm not certain if the best model would include such an adjustment in the absence of good data.

https://docs.google.com/spreadsheets/d/1MF9bAdISMOMV_aOok9LMyKbxDEpOsvZ9VO8AfwsS6_o/

Probably majority AI, given the organizations being given to and the distribution of funding. This contrasts with the non-GWWC EG organizations in Europe, where I believe there is a much greater focus on climate, mainly to meet donors where they are at.

They're working on creating an option to make it easy for posters to add the diamond, but in the meantime you can DM the forum team (I did!) 

Hi Nicolaj,

Thanks for sharing! That's really interesting. Couple of thoughts:

(1) For us, CEARCH uses n=1 when modelling the value of income doublings, because we've tended to prioritize health interventions where the health benefits tend to swamp the economic benefits anyway (and we've tended to priortize health interventions because of the heuristic that the NCDs are a big and growing problem which policy can cheaply combat at scale, vs poverty which by the nature of economic growth is declining over time).

(2) The exception is when modelling the counterfactual value of government spending, which a successful policy advocacy intervention redirects, and has to be factored in, albeit at a discount to EA spending, and while taking into account country wealth (https://docs.google.com/spreadsheets/d/1io-4XboFR4BkrKXgfmZHQrlg8MA4Yo_WLZ7Hp6I9Av4/edit?gid=0#gid=0).

There, the modelling is more precise, and we use n=1.26 as a baseline estimate, per Layard, Mayraz and Nickell's review of a couple of SWB surveys (https://www.sciencedirect.com/science/article/abs/pii/S0047272708000248). Would be interested in hearing how your team arrived at n=1.87 - I presume this is a transformation of an initial n=1 based on your temporal discounts?

Cheers,
Joel