MEASUREMENT ERRORS AND CENSORED STRUCTURAL LATENT VARIABLES MODELS
研究了外生变量存在加性测量误差的删失结构潜变量模型，利用过度识别条件为含误差变量提供工具变量，提出两阶段估计方法。
We consider censored structural latent variables models where some exogenous variables are subject to additive measurement errors. We demonstrate that overidentification conditions can be exploited to provide natural instruments for the variables measured with errors, and we propose a two-stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting reduced form parameters using consistent censored regression methods. The second stage obtains structural form parameters using the conventional linear simultaneous equations model estimators.