Nonlinear Models of Measurement Errors
- 1 December 2011
- journal article
- research article
- Published by American Economic Association in Journal of Economic Literature
- Vol. 49 (4), 901-937
- https://doi.org/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)Keywords
This publication has 60 references indexed in Scilit:
- A simple estimator for nonlinear error in variable modelsJournal of Econometrics, 2003
- Robust and consistent estimation of nonlinear errors-in-variables modelsJournal of Econometrics, 2002
- Flexible Simulated Moment Estimation of Nonlinear Errors-in-Variables ModelsThe Review of Economics and Statistics, 2001
- Misclassification of the dependent variable in a discrete-response settingJournal of Econometrics, 1998
- Estimation of Linear and Nonlinear Errors-in-Variables Models Using Validation DataJournal of the American Statistical Association, 1995
- Nonlinear errors in variables Estimation of some Engel curvesJournal of Econometrics, 1995
- The Limiting Distribution of the Maximum Rank Correlation EstimatorEconometrica, 1993
- Approximate Quasi-likelihood Estimation in Models with Surrogate PredictorsJournal of the American Statistical Association, 1990
- Optimal Rates of Convergence for Deconvolving a DensityJournal of the American Statistical Association, 1988
- Identifiability of a Linear Relation between Variables Which Are Subject to ErrorEconometrica, 1950