Monte Carlo studies on the effectiveness of the bootstrap bias reduction method on 2SLS estimates

DOI10.1016/0165-1765(86)90029-7zbMath1328.62619OpenAlexW2081858419MaRDI QIDQ899756

Hung-Gay Fung, Edwin F. Ulveling, Yu-Sheng Hsu, Kin-Nam Lau

Publication date: 1 January 2016

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0165-1765(86)90029-7

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Point estimation (62F10) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (5)

Approximating and reducing bias in 2SLS estimation of dynamic simultaneous equation models ⋮ Bootstrapping estimators for the seemingly unrelated regressions model ⋮ General linear hypotheses in a two-stage least squares estimation model ⋮ A Fast Iterated Bootstrap Procedure for Approximating the Small-Sample Bias ⋮ The asymptotic validity of the F-test in a two-stage least squares model

Cites Work

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• On bootstrapping two-stage least-squares estimates in stationary linear models
• Bootstrap methods: another look at the jackknife
• The Bias and Moment Matrix of the General k-Class Estimators of the Parameters in Simultaneous Equations
• The Existence of Moments of k-Class Estimators
• The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators

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