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Title:

The Reduced Form of a Block Recursive Model

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Various estimators of the reduced form of a block recursive model are investigated and compared to each other. In particular it is shown that the structural reduced form estimator, which results from estimating separately each block of the block recursive model by some efficient method and then solving the system for the endogenous variables, is...

Various estimators of the reduced form of a block recursive model are investigated and compared to each other. In particular it is shown that the structural reduced form estimator, which results from estimating separately each block of the block recursive model by some efficient method and then solving the system for the endogenous variables, is more efficient than the OLS estimator of the reduced form. Other reduced form estimators derived from OLS or Two Stage LS estimators of a partially reduced form have intermediate efficiency properties. The paper has been published in Schneeweiss et al (2001), but without the appendices. Minimize

Year of Publication:

2003

Document Type:

doc-type:workingPaper

Language:

eng

Subjects:

ddc:330 ; Block recursive model ; reduced form ; simultaneous equations model ; Simultanes Gleichungssystem ; Schätztheorie ; Theorie

ddc:330 ; Block recursive model ; reduced form ; simultaneous equations model ; Simultanes Gleichungssystem ; Schätztheorie ; Theorie Minimize

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http://www.econstor.eu/dspace/Nutzungsbedingungen

http://www.econstor.eu/dspace/Nutzungsbedingungen Minimize

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Discussion papers / Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 307

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Title:

The Efficiency of Adjusted Least Squares in the Linear Functional Relationship

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A linear functional errors-in-variables model with unknown slope parameter and Gaussian errors is considered. The measurement error variance is supposed to be known, while the variance of errors in the equation is unknown. In this model a risk bound of asymptotic minimax type for arbitrary estimators is established. The bound lies above that one...

A linear functional errors-in-variables model with unknown slope parameter and Gaussian errors is considered. The measurement error variance is supposed to be known, while the variance of errors in the equation is unknown. In this model a risk bound of asymptotic minimax type for arbitrary estimators is established. The bound lies above that one which was found previously in the case of both variances known. The bound is attained by an adjusted least square estimator. Minimize

Year of Publication:

2000-01-01

Document Type:

doc-type:workingPaper ; Paper ; NonPeerReviewed

Language:

eng

Subjects:

Sonderforschungsbereich 386 ; Sonderforschungsbereich 386 ; ddc:510

Sonderforschungsbereich 386 ; Sonderforschungsbereich 386 ; ddc:510 Minimize

Relations:

http://epub.ub.uni-muenchen.de/1598/1/paper_208.pdf ; Kukush, Alexander und Maschke, Erich Otto (2000): The Efficiency of Adjusted Least Squares in the Linear Functional Relationship. Sonderforschungsbereich 386, Discussion Paper 208

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Title:

The efficiency of adjusted least squares in the linear functional relationship

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Description:

A linear functional errors-in-variables model with unknown slope parameter and Gaussian errors is considered. The measurement error variance is supposed to be known, while the variance of errors in the equation is unknown. In this model a risk bound of asymptotic minimax type for arbitrary estimators is established. The bound lies above that one...

A linear functional errors-in-variables model with unknown slope parameter and Gaussian errors is considered. The measurement error variance is supposed to be known, while the variance of errors in the equation is unknown. In this model a risk bound of asymptotic minimax type for arbitrary estimators is established. The bound lies above that one which was found previously in the case of both variances known. The bound is attained by an adjusted least-squares estimators. ; Adjusted least-squares estimator Asymptotic efficiency Gaussian errors Hajek bound Linear functional errors-in-variables model Minimize

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article

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Title:

The Reduced Form of a Block Recursive Model

Author:

Description:

Various estimators of the reduced form of a block recursive model are investigated and compared to each other. In particular it is shown that the structural reduced form estimator, which results from estimating separately each block of the block recursive model by some efficient method and then solving the system for the endogenous variables, is...

Various estimators of the reduced form of a block recursive model are investigated and compared to each other. In particular it is shown that the structural reduced form estimator, which results from estimating separately each block of the block recursive model by some efficient method and then solving the system for the endogenous variables, is more efficient than the OLS estimator of the reduced form. Other reduced form estimators derived from OLS or Two Stage LS estimators of a partially reduced form have intermediate efficiency properties. The paper has been published in Schneeweiss et al (2001), but without the appendices. Minimize

Year of Publication:

2003-01-01

Document Type:

doc-type:workingPaper ; Paper ; NonPeerReviewed

Language:

eng

Subjects:

Sonderforschungsbereich 386 ; Sonderforschungsbereich 386 ; ddc:510

Sonderforschungsbereich 386 ; Sonderforschungsbereich 386 ; ddc:510 Minimize

Relations:

http://epub.ub.uni-muenchen.de/1689/1/paper_307.pdf ; Schneeweiß, Hans und Maschke, Erich Otto und Pfannes, Manfred (2003): The Reduced Form of a Block Recursive Model. Sonderforschungsbereich 386, Discussion Paper 307

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