Using Higher Moments to Estimate the Simple Errors-in-Variables Model
提出利用样本矩（最高四阶）来检验和估计简单回归模型中变量测量误差的参数，通过最小卡方得到一致且渐近有效的估计，蒙特卡洛模拟表明该方法可行实用。
Using sample moments up to the fourth in the standard simple regression model with measurement errors allows testing whether the parameters are identified by having independent variables that are not normally distributed. These moments can be used to estimate the parameters, if identified, consistently and asymptotically efficiently by minimum chi-squared. Available instruments may be used to get more efficient, consistent estimates. A Monte Carlo study indicates that the approach offers a feasible, practical approach to handling errors in variables. Inference may sometimes be improved by using bootstrapped estimates.