Nonlinear Models of Measurement Errors
Nonlinear Models of Measurement Errors
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DOI：
10.1257/jel.49.4.901
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发表时间：
2011-12-01
影响因子：
12.6
通讯作者：
Nekipelov, Denis
中科院分区：
文献类型：
--
作者：
Chen, Xiaohong;Hong, Han;Nekipelov, Denis
经济数据中的测量错误无处不在，规模不平凡。测量误差的存在导致偏见和不一致的参数估计，并导致经济分析中各种程度的错误结论。尽管通常使用众所周知的仪器变量方法来处理线性错误模型，但本文概述了最近的研究论文，这些研究论文得出了估计方法，这些方法提供了对具有测量错误的非线性模型的一致估计。我们审查具有经典和非经典测量误差的模型，以及离散变量的错误分类。对于所调查的每种方法，我们描述了识别和估计的关键思想，并在当前可用时讨论其应用程序。
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.