Specification Errors in Limited Dependent Variable Models

A preliminary investigation of two specification error problems in truncated dependent variable models is reported. It is shown that heteroscedasticity in a tobit model results in biased estimates when the model is misspecified. This differs from the OLS model where estimates are still consistent本文报道了针对截断因变量模型中两类设定误差问题的初步探究。研究表明，当托比特模型（Tobit model）设定错误时，其内部存在的异方差性会导致估计结果出现偏倚。这与普通最小二乘法（OLS）模型不同，后者的估计结果仍保持一致性。