Nonlinear Models of Measurement Errors
AbstractMeasurement 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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Bibliographic InfoArticle provided by American Economic Association in its journal Journal of Economic Literature.
Volume (Year): 49 (2011)
Issue (Month): 4 (December)
Find related papers by JEL classification:
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
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- Ryo Kambayashi & Daiji Kawaguchi & Ken Yamada, 2013.
"Minimum Wage in a Deflationary Economy: The Japanese Experience, 1994–2003,"
07-2013, Singapore Management University, School of Economics.
- Kambayashi, Ryo & Kawaguchi, Daiji & Yamada, Ken, 2013. "Minimum wage in a deflationary economy: The Japanese experience, 1994–2003," Labour Economics, Elsevier, vol. 24(C), pages 264-276.
- Kaspar Wüthrich, 2013. "Set Identification of Generalized Linear Predictors in the Presence of Non-Classical Measurement Errors," Diskussionsschriften dp1304, Universitaet Bern, Departement Volkswirtschaft.
- repec:siu:wpaper:35-2012 is not listed on IDEAS
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