So what you are saying is that IF the variance follows a normal distribution, then 2 is theoretically the best matching exponent. However, if the actual variance is not a normal curve, then it may not be.
However, since most "natural" things follow a normal variance, least-squred is used because for the normal assumption, it is the simplest known way to calculate the answer.
One would have to know more about the nature of the actual error distribution and know that it is not a normal distribution if they want to possibly do better than least-squares.
I can live with that.