Okay, thank you. I aim to take a look at these evals and hopefully learn something and maybe give some useful feedback.
And one more point which maybe is obvious but just to get it out there.
Sure, but these are hard to account for. I agree it’s better to adjust the model when it’s possible, but you’ll still be left with a model that has a tonne of uncertainty.
I agree that a large amount of uncertainty will persist, but I suppose we should aim to do the modeling and adjustments is mean zero. E.g., we’d put in a large adjustment for ‘potential non-counterfactuality’ for things like “maybe the people who pledged would have pledged later on anyways and the fact that they pledged and donated now means that they’re likely to end their pledges earlier.”
I suspect that the impact evaluations indeed consider things like these, and I am looking forward to going over them when I have a moment. Thanks for engaging.
Okay, thank you. I aim to take a look at these evals and hopefully learn something and maybe give some useful feedback.
And one more point which maybe is obvious but just to get it out there.
I agree that a large amount of uncertainty will persist, but I suppose we should aim to do the modeling and adjustments is mean zero. E.g., we’d put in a large adjustment for ‘potential non-counterfactuality’ for things like “maybe the people who pledged would have pledged later on anyways and the fact that they pledged and donated now means that they’re likely to end their pledges earlier.”
I suspect that the impact evaluations indeed consider things like these, and I am looking forward to going over them when I have a moment. Thanks for engaging.