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Journal of Economic Literature: Vol. 49 No. 4 (December 2011)

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Nonlinear Models of Measurement Errors

Article Citation

Chen, Xiaohong, Han Hong, and Denis Nekipelov. 2011. "Nonlinear Models of Measurement Errors." Journal of Economic Literature, 49(4): 901-37.

DOI: 10.1257/jel.49.4.901

Abstract

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. (JEL C20, C26, C50)

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Authors

Chen, Xiaohong (Yale U)
Hong, Han (Stanford U)
Nekipelov, Denis (U CA, Berkeley)

JEL Classifications

C20: Single Equation Models; Single Variables: General
C26: Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
C50: Econometric Modeling: General


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