A MPEC Estimator for Misclassification Models
11 Pages Posted: 11 Nov 2013 Last revised: 8 Jun 2019
Date Written: July 3, 2014
In this paper, we propose a constrained maximum likelihood estimator for misclassification models, by formulating the estimation as an MPEC (Mathematical Programming with Equilibrium Constraints) problem. Our approach improves the numerical accuracy and avoids the singularity problem. Monte Carlo simulations confirm that the proposed estimator reduces bias and standard deviation of the estimator, especially when the sample is small/medium and/or the dimension of matrix is large.
Keywords: Mathematical Programming with Equilibrium Constraints (MPEC); Misclassification models; Nonparametric estimation
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