Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information
无辅助信息的经典测量误差模型：非参数识别与半参数估计
Virtually all methods aimed at correcting for covariate measurement error in regressions rely on some form of additional information (e.g., validation data, known error distributions, repeated measurements, or instruments). In contrast, we establish that the fully nonparametric classical errors-in-variables model is identifiable from data on the regressor and the dependent variable alone, unless the model takes a very specific parametric form. This parametric family includes…