I often find the thing that is easier find the confidence interval for a result rather than the result that fits a confidence interval, so rather than targeting a particular confidence interval I find it more natural to say what I want to say and then specify the level of confidence in it.
Depends on your audience, but generally I see these distinct sources of uncertainty split out in papers - report the modeled confidence (output of the model based on data), AND be clear about the likelihood of model error.
TL;DR: How to choose the width of the confidence intervals one reports?
I am working on a paper on statistical technological forecasting.
Our model produces confidence intervals for the date when a particular milestone will be achieved. I am now thinking about how to report the results.
One line of reasoning is that you want the results to be as informative as you can, so we would report 90% confidence intervals.
Another one is that you dont want to overstate your results, specially on a domain such as the one I am working on where model error could be as high as 1/3 of the models. So your confidence interval should be commesurate with the expected base rate of model error (eg 70% confidence intervals in this case).
I think I am not framing this problem correctly, so any thoughts would be appreciated.