Nonlinear Models of Measurement Errors
综述了经济数据中测量误差导致的估计偏误问题，重点介绍了非线性模型下提供一致估计的最新方法，涵盖经典与非经典测量误差及离散变量误分类，适合关注计量方法的经济学者快速了解前沿进展。
Measurement errors in economic data are pervasive and nontrivial in size. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in economic analysis. While linear errors-in-variables models are usually handled with well-known instrumental variable methods, this article provides an overview of recent research papers that derive estimation methods that provide consistent estimates for nonlinear models with measurement errors. We review models with both classical and nonclassical measurement errors, and with misclassification of discrete variables. For each of the methods surveyed, we describe the key ideas for identification and estimation, and discuss its application whenever it is currently available.