Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors
提出一种半参数估计方法，用于处理潜变量模型中回归元存在内生性或测量误差的问题，允许误差分布未知且与回归元相关，适用于经济学等领域的实证分析。
A simple root n. consistent, asymptotically normal semiparametric estimator of the coefficient vector ,B in the latent variable specification y = L(f,B'x + e) is constructed. The distribution of e is unknown and may be correlated with x or be conditionally heteroscedastic, e.g., x can contain measurement error. The function L can also be unknown. The identification assumption is that e is uncorrelated with instruments u and that the conditional distribution of e given x and u does not depend on one of the regressors, which has some special properties. Extensions to more general latent variable specifications are provided.