Asymptotic probability concentrations and finite sample properties of modified LIML estimators for equations with more than two endogeneous variables

DOI10.1016/S0304-4076(99)00082-2zbMath0968.62086OpenAlexW2102629354MaRDI QIDQ1584773

K. Rao Kadiyala, Dennis Oberhelman

Publication date: 17 September 2001

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

Full work available at URL: https://doi.org/10.1016/s0304-4076(99)00082-2

zbMATH Keywords

tablesMonte Carlosimultaneous equations modelsasymptotic mean-squared errorasymptotic probability concentrationmodified LIMLsmall sigma expansions

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20)

Related Items (1)

Estimation with weak instruments: Accuracy of higher‐order bias and MSE approximations

Cites Work

• Optimizing in the class of Fuller modified limited information maximum likelihood estimators
• Analytical Small-Sample Distribution Theory in Econometrics: The Simultaneous-Equations Case
• The Exact Distribution of Instrumental Variable Estimators in an Equation Containing n + 1 Endogenous Variables
• Evaluation of the Distribution Function of the Limited Information Maximum Likelihood Estimator
• Some Properties of a Modification of the Limited Information Estimator
• Evaluation of the Distribution Function of the Two-Stage Least Squares Estimate
• Comparison of k-Class Estimators When the Disturbances Are Small
• Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations

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