A MPEC Estimator for Misclassification Models

11 Pages Posted: 11 Nov 2013 Last revised: 8 Jun 2019

See all articles by Ruichang Lu

Ruichang Lu

Department of Finance, Guanghua School of Management, Peking University

Yao Luo

University of Toronto - Department of Economics

Ruli Xiao

Indiana University Bloomington - Department of Economics

Date Written: July 3, 2014

Abstract

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

Suggested Citation

Lu, Ruichang and Luo, Yao and Xiao, Ruli, A MPEC Estimator for Misclassification Models (July 3, 2014). Economics Letters, Volume 125, 2014, Available at SSRN: https://ssrn.com/abstract=2352935 or http://dx.doi.org/10.2139/ssrn.2352935

Ruichang Lu

Department of Finance, Guanghua School of Management, Peking University ( email )

Beijing
China

Yao Luo (Contact Author)

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S3G7
Canada

Ruli Xiao

Indiana University Bloomington - Department of Economics ( email )

Wylie Hall
Bloomington, IN 47405-6620
United States

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