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On the polynomial structural relationship
Author(s) -
Huang Y. H. Steve,
Huwang Longcheen
Publication year - 2001
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3316043
Subject(s) - polynomial , least squares function approximation , mathematics , degree (music) , estimation , polynomial and rational function modeling , degree of a polynomial , generalized least squares , statistics , mathematical analysis , engineering , physics , systems engineering , estimator , acoustics
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.