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Nonlinear Models of Measurement Errors
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DOI：10.1257/jel.49.4.901.png)
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摘要
En 中文
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.
Keyword:
IN-VARIABLES
SEMIPARAMETRIC ESTIMATION
NONPARAMETRIC REGRESSION
EFFICIENT ESTIMATION
OPTIMAL RATES
IDENTIFICATION
MISCLASSIFICATION
DECONVOLUTION
CONVERGENCE
ESTIMATOR
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期刊
IF:
10.6
论文数:
689
被引数:
1.3W
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引用论文
Instrumental variable treatment of nonclassical measurement error models非经典测量误差模型的工具变量处理.png)
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