1. When modifying a standard model to address a question, the modification continues to display the key facts that the standard model was capturing.
2. The introduction of additional features in the model is supported by other evidence for that particular additional features.
3. The model is essentially a measurement instrument. Thus, simply estimating the magnitude of that instrument rather than calibrating the model can influence the ability of the model to be used as a measuring instrument. In addition model’s selection (or in particular, parametric specification) has to depend on the specific question to be addressed, rather than the answer we would like to derive. For example, "if the question is of the type, how much of fact X can be accounted for by Y , then choosing the parameter values in such a way as to make the amount accounted for as large as possible according to some metric makes no sense."
4. Researchers can challenge existing results by introducing new quantitatively relevant features in the model, that alter the predictions of the model in key dimensions.