In preparation for this issue of The Journal of Risk Model Validation, we were assured by people whose opinion we value that model risk is, in principle, not quantifiable in a practical or consistent ...

Data analysts sometimes report (and more often produce) results from many alternative models with different explanatory variables, functional forms, observations, or exogeneity assumptions. Classical ...

The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.