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On the polynomial structural relationship
Journal article   Peer reviewed

On the polynomial structural relationship

Y.H. Steve Huang and Longcheen Huwang
Canadian Journal of Statistics, Vol.29(3), pp.495-512
09/2001

Abstract

Mean squared error Measurement error Polynomial regression Weighted least squares
In estimating a linear measurement error model, extra information is generally needed to identify the model. Here the authors show that the polynomial structural model with errors in the endogenous and exogenous variables can be identified without any extra information if the degree is greater than one. They also show that a weighted least squares approach for the estimation of the parameters in the model leads to the same estimates as the solutions of a system of estimating equations.

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