Is it a good idea to normalize the outputs of a Neural Network for Regression, when the different outputs vary in magnitude?
Yes, if proper weights were not introduced in cost function or target variables were not normalized, optimization process would be driven by the target variable which had the largest scale.

Therefore it's a good practice to normalize outputs if they have huge differences in terms of scale.