The second rule of software estimation

The more error there is in your estimates, the less precise you must be.

That's based on my past experience with being wrong a lot, and seeing other people be wrong a lot. If I tell you I can write a feature in a day, and sometimes I'm right, and sometimes it takes a month, then there's no reason to differentiate between 5-hour and 6-hour features when estimating.

I suspect that powers-of-n is a good model for many teams, where n depends on some combination of team familiarity with the code, technical debt, domain complexity, etc.

A statistician could certainly give some guidance here. Something about standard deviations.

A lot of teams like to use Fibbonaci numbers for their estimates, which seems weird to me. Why is this a good sequence? Why jump from 1 to 2 (a 100% increase) then to 3 (a 50% increase)? Can you really tell a 2 and a 3 apart, reliably enough to be useful?

In Fibonacci, the next number is "twice the average of the last two numbers", which is pretty close to "twice the last number". I doubt your estimates are reliable enough that the difference will matter. And powers of two are culturally familiar in software, easy to remember, and easy for programmers to add.

See also: the first rule.