Two reduced-form approaches to the derivation of the maximum-likelihood estimators for simultaneous-equation systems

DOI10.1016/0304-4076(84)90057-5zbMath0564.62094OpenAlexW2083133624MaRDI QIDQ1058254

D. Stephen G. Pollock

Publication date: 1984

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

Full work available at URL: https://doi.org/10.1016/0304-4076(84)90057-5

zbMATH Keywords

likelihood functionestimating equationsmaximum-likelihood estimatorsreduced-form parameterssimultaneous-equation model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Estimation in multivariate analysis (62H12)

Related Items (2)

Twenty-five basic theorems in situation and world theory ⋮ Reasoning defeasibly about probabilities

Cites Work

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• A simple derivation of the limited information maximum likelihood estimator
• K-matrix-class estimators and the full-information maximum-likelihood estimator as a special case
• Sample Size Requirements in Full Information Maximum Likelihood Estimation
• The Elimination Matrix: Some Lemmas and Applications
• A General Procedure for Obtaining Maximum Likelihood Estimates in Generalized Regression Models
• Three Stage Least Squares and Some Extensions where the Structural Disturbance Covariance Matrix May Be Singular
• Asymptotic Theory and Large Models
• Two Methods of Computing Full-Information Maximum Likelihood Estimates in Simultaneous Stochastic Equations
• The Asymptotic Properties of Estimates of the Parameters of a Single Equation in a Complete System of Stochastic Equations

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