On the Use of Holdout Samples for Model Selection
从贝叶斯视角指出，使用留出样本进行模型验证并非最优，但可防止数据驱动的模型修改导致拟合度夸大，为研究者提供激励。
Researchers often hold out data from the estimation of econometric models to use for external validation. However, the use of holdout samples is suboptimal from a Bayesian perspective, which prescribes using the entire sample to form posterior model weights. This paper examines a possible rationale for the use of holdout samples: data-inspired modifications of structural models are likely to lead to an exaggeration of model fit. The use of holdout samples can, in principle, set an incentive for the modeler not to exaggerate model fit.