My original question didn't generate the response I was looking for, so I'm going to ask a new but more specific question.
Let's say that we compute parameters for a multiple linear regression model for a data set, which includes at least one quadratic term.
If we were to collapse the first degree and second degree terms for a single variable and then compute the argmin (or argmax) for that variable, would there be any theoretical problems with this approach?