Nonlinear Models of Measurement Errors
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.
Document Type: Research Article
Publication date: 2011-12-01
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- The Journal of Economic Literature (JEL) began publication in 1969 under the auspices of the American Economic Association with quarterly issues appearing in March, June, September, and December. JEL contains survey and review articles, book reviews, an annotated bibliography of newly published books, and a list of current dissertations in North American universities.
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