It’s definitely true that all else equal, uncertainty inflates CEAs of funded grants, for the reasons you identify. (This is an example of the optimizer’s curse.) However:
This risk is lower when the variance in true CE is large, especially if its larger than the variance due to measurement error. To the extent we think this is true in the opportunities we evaluate, this reduces the quantitative contribution of measurement error to CE inflation. More elaboration in this comment.
Good CEAs are conservative in their choices of inputs for exactly this reason. The goal should be to establish the minimal conditions for a grant to be worth making, as opposed to providing precise point estimates of CE.
It’s definitely true that all else equal, uncertainty inflates CEAs of funded grants, for the reasons you identify. (This is an example of the optimizer’s curse.) However:
This risk is lower when the variance in true CE is large, especially if its larger than the variance due to measurement error. To the extent we think this is true in the opportunities we evaluate, this reduces the quantitative contribution of measurement error to CE inflation. More elaboration in this comment.
Good CEAs are conservative in their choices of inputs for exactly this reason. The goal should be to establish the minimal conditions for a grant to be worth making, as opposed to providing precise point estimates of CE.