Naccarato, Alessia and Zurlo, Davide and Pieraccini, Luciano (2012): Least Orthogonal Distance Estimator and Total Least Square.

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Abstract
Least Orthogonal Distance Estimator (LODE) of Simultaneous Equation Models’ structural parameters is based on minimizing the orthogonal distance between Reduced Form (RF) and the Structural Form (SF) parameters. In this work we propose a new version – with respect to Pieraccini and Naccarato (2008) – of Full Information (FI) LODE based on decomposition of a new structure of the variancecovariance matrix using Singular Value Decomposition (SVD) instead of Spectral Decomposition (SD). In this context Total Least Square is applied. A simulation experiment to compare the performances of the new version of FI LODE with respect to Three Stage Least Square (3SLS) and Full Information Maximum Likelihood (FIML) is presented. Finally a comparison between the FI LODE new and old version together with few words of conclusion conclude the paper.
Item Type:  MPRA Paper 

Original Title:  Least Orthogonal Distance Estimator and Total Least Square 
English Title:  Least Orthogonal Distance Estimator and Total Least Square 
Language:  English 
Keywords:  Least Orthogonal Distance Estimator, Simultaneous Equation Models, Total Least Square 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C51  Model Construction and Estimation 
Item ID:  42365 
Depositing User:  ALESSIA NACCARATO 
Date Deposited:  03 Nov 2012 15:16 
Last Modified:  05 Aug 2017 14:32 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/42365 