When constructing a likelihood function, one often integrates over some distribution. When optimizing for its argmin, a crude approximation (e.g. insufficient nodes) in the numeric integral might exhibit systematic, proportional bias.
But that's okay in a likelihood function if the error is (proportionally) stable, since the argmin of the function will be the same, even when scaled by a constant.