Focused information criterion for semiparametric models

模型选择的目标是以数据驱动的方式选择一个“最好”的模型。然而，最好的模型通常因模型的不同预期用途而不同。这项研究开发了一种基于经验似然的矩限制模型的模型选择方法，旨在获得感兴趣的特定参数的良好估计。本文还研究了矩约束模型的一种最小化估计量均方误差的模型平均方法。

The goal of model selection is to select a “best” model in a data-driven way. However, the best model generally differs for different intended use of the model. This study develops an empirical likelihood-based model selection method for moment restriction models that is designed to obtain a good estimate for a specific parameter of interest. This study also investigates a model averaging method for moment restriction models that minimizes the mean squared error of the estimator.