Optimal instruments when the disturbances are small

DOI10.1016/0304-4076(79)90079-4zbMath0404.62086OpenAlexW1966627573MaRDI QIDQ1256826

Roger W. Klein

Publication date: 1979

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(79)90079-4

zbMATH Keywords

Small DisturbancesEconometric ModelsNon-Iterative Principal Component EstimatorsOptimal Class Of EstimatorsOptimal InstrumentsSquared-Error Matrix Loss Function

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Statistical methods; economic indices and measures (91B82)

Cites Work

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• Asymptotic Theory and Large Models
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• Comparison of k-Class Estimators When the Disturbances Are Small
• A Simplified Structural Estimator for Large‐Scale Econometric Models¹
• Disturbance-Variance Estimation in Simultaneous Equations when Disturbances Are Small
• Finite-Sample Properties of the k-Class Estimators
• The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators
• K-Class Estimators: The Optimum Normalization for Finite Samples

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