# MLR prediction intervals joint region

This thread offers some good information on the calculation of linear regression prediction intervals and includes a link to some practical notes. At the end of the link the author claims that, in case of multiple linear regression, we should consider the joint region of the predictor variables.

How should MLR prediction intervals be interpreted in light of their joint region limitations?

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For example, models of wage growth vs productivity growth and % employment developed using data from a period with more-or-less full employment may be very poor predictors of wage growth given a certain level productivity growth and % employment during a period with high unemployment. More simply, a linear approximation to $y = \sqrt{x}$ isn't bad when the range of $x$ is 1000 to 1001, but will produce very poor estimates when the input value of $x$ is, say, 500.