Estimation of nonlinear models with mismeasured regressors using marginal information
研究了当已知解释变量真实值的边际分布时，如何估计带有测量误差的非线性模型，提出了半参数极大似然估计法，并应用于AFDC福利持续时间模型。
Abstract We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi‐parametric MLE that is shown to be $\sqrt{n}$ consistent and asymptotically normally distributed. In a simulation experiment we find that the finite sample distribution of the estimator is close to the asymptotic approximation. The semi‐parametric MLE is applied to a duration model for AFDC welfare spells with misreported welfare benefits. The marginal distribution of the correctly measured welfare benefits is obtained from an administrative source. Copyright © 2010 John Wiley & Sons, Ltd.